economic impact study of business link local...

Economic Impact Study of Business Link Local Service

University of Warwick, Aston Business School and Kingston University

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URN 07/1169

Final Report

ASTON BUSINESS SCHOOL



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CONTENTS Page Acknowledgements 8 Glossary 9 Executive Summary 10 1. Evaluation Framework and Approach

1.1. The Evolution of Business Support in the UK 21 1.2. Business Link Implementation Issues 22

1.2.1. Brokerage Model in Action 24 1.3. Business Link Programme Objectives 25 1.4. Design of the Economic Impact Study 31

1.4.1. Analytical Approach to the Derivation of Value for Money (VfM) Estimate

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1.4.2. National VfM Estimates 32 1.4.3. Qualitative Views of Business Link Impact 33 1.4.4. Evaluation of Alternative Brokerage Models 34 1.4.5. Regional Benchmark Analysis 34

1.5. Structure of Report 34 2. Sample Characteristics

2.1. Introduction 36 2.2. Sample Confirmation and Contamination 36 2.3. Respondent Profile 37 2.4. Business Characteristics 40 2.5. Strategic Direction 45 2.6. Partners, Directors and the Background of the Business Leader 46 2.7. Main Partner/Managing Director 47

3. Nature Of Business Link Support and Business Performance

3.1. Profiling Business Link Support 50 3.2. Other External Business Assistance and Support 54 3.3. Firm Size and Performance 55 3.4. Summary 56

4. Assessing the Impact of Business Link

4.1. Introduction 58 4.2. Impact of Business Link Assistance 59 4.3. Perceived Impact of Business Link Assistance 70 4.4. Assessing the Economy-wide Impact of Business Link Assistance 73 4.5. Costs of Business Link 76 4.6. Displacement Issues 77 4.7. Summary 79



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5. The Effectiveness of Alternative BLO Delivery Models

5.1. Introduction 80 5.2. Previous Categorisations of BLOs 80 5.3. Bennett-Robson (B-R) Classification 81

5.3.1. Support Service Profile 82 5.3.2. Impact of BLO Services 84

5.4. Mole Classification 87 5.4.1. The Information, Diagnostics and Brokerage (IDB) Model 88 5.4.2. Four Models of BLOs 90 5.4.3. Operationalising the Models 91 5.4.4. Support Service Profile 98 5.4.5. Impact of BLO Services 100

5.5. Summary 103

6. Impact of Business Link Assistance: Evidence from the Face-to-Face Interviews

6.1. Introduction 106 6.2. Developing the Topic Guides 107 6.3. Case Study Selection 108 6.4. Intensively-Assisted Firms 111

6.4.1. Contact with Business Link 112 6.4.2. Nature and Delivery of Assistance 113 6.4.3. Impact on the Business 117

6.5. Other-Assisted Firms 120 6.6. Summary 122

7. Developing a Spatial Perspective on the Business Link Local Service

7.1. Introduction 124 7.2. Regional Baselines 124

7.2.1. The Age Characteristics of Respondent Firms 124 7.2.2. The Legal Status of Respondent Firms 128 7.2.3. Regional Differences in the Sectoral Composition of

Respondent Firms 130

7.2.4. Regional Differences in the Strategic Priorities of Respondent Firm

132

7.2.5. Regional Differences in Diversity, Director Numbers and Firm Size

135

7.3. A Rural Perspective 138 7.3.1. Firm Size and Performance 138 7.3.2. Perceived Impact of Business Link by Rural Area 142

7.4. Summary 146



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8. Conclusions and Discussion

8.1. Introduction 148 8.2. Value for Money 148 8.3. Comparisons with Previous Studies 149

8.3.1. PACEC (1998) 149 8.3.2. Business Link Tracker Study (2001) 150

8.4. Business Link Delivery Models 152 8.5. Sub-National Issues 154 8.6. Methodological Critique 157

References 158 Appendices 161 Appendix A Telephone Survey Questionnaire 162 Appendix B Weighting Protocols 201 Appendix C Face-to-Face Interview Topic Guide 203 Appendix D Additional Estimation Results Excluding Selection Effects 209 Appendix E Excerpt from Conference Paper on Correlates with Impact 215



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List of Figures Page

Figure ES.1 Business Link Operator Models and Impact 18 Figure 1.1 Programme Theory for Business Links 28 Figure 1.2 Study Overview and Structure 31 Figure 5.1 Models of Business Link Operators: Intensity of intensive assistance

and the proportion of firms intensively assisted. 91

Figure 7.1 Satisfaction with BL Service by Assisted Group and Rural Area 144

List of Tables Table 1.1 A Rationale for Business Link 23 Table 1.2 Business Link Outcomes and Impacts 27 Table 2.1 Respondents’ Position within the business – Selected Categories 39 Table 2.2 Age Distribution of Respondent Groups: All Firms 40 Table 2.2a Age Distribution of Respondent Groups: Rural Dispersed Settlements 41 Table 2.3 Legal Status of Respondent Firms: All Firms 42 Table 2.3a Legal Status of Respondent Firms: Rural Dispersed Settlements 42 Table 2.4 Sectoral Composition of Respondent Firms 44 Table 2.5 Strategic Priorities of Respondent Firms: All Firms 45 Table 2.5 Strategic Priorities of Respondent Firms: Rural Dispersed Settlements 45 Table 2.6 Partners and Directors, Ethnic and Gender Diversity 46 Table 2.7 Highest Qualification of Owner-Managers: All Firms 48 Table 2.7a Highest Qualification of Owner-Managers: Rural Dispersed

Settlements 48

Table 2.8 Age Distribution of Owner-Managers: All Firms 48 Table 2.8a Age Distribution of Owner-Managers: Rural Dispersed Settlements 49 Table 3.1 Frequency Distribution of Contacts between Intensively-assisted firms

and Other-assisted firms and Business Links 51

Table 3.2 Intensity of Assistance Received by Intensively-assisted firms and Other-assisted firms

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Table 3.3 Proportions of Intensively-Assisted Firms and Other-Assisted Firms Receiving Different Types of BL Services

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Table 3.4 Satisfaction with BL Services among Intensively-assisted firms and Other-assisted firms

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Table 3.5 Individual Sources of Business Advice and Assistance 54 Table 3.6 Firm Size Distributions: Sales and Employment 55 Table 3.7 Performance Indicators: Sales and Employment Growth, Sales per

Employee 56

Table 4.1 Probit Models of the Probability of Receiving Intensive Assistance 61



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Table 4.2 Probit Models of the Probability of Receiving Other Assistance 62 Table 4.3 Impact of Intensive Assistance: Full Model 66 Table 4.4 Impact of Other Assistance: Full Model 67 Table 4.5 Impact of Intensive Assistance: Restricted Models 68 Table 4.6 Impact of Other Assistance: Restricted Models 69 Table 4.7 Assisted Firms’ Perceptions of the Impact of Business Link Services 71 Table 4.8 Time Horizons for Experiencing the Benefits of BL Assistance 72 Table 4.9 Additionality of Business Link Assistance 73 Table 4.10 National Impact Estimates for Business Links 75 Table 4.11 Income of 43 Business Link Organisations: 2003 76 Table 5.1 Profiles of Intensive Assistance: by Bennett-Robson Typology 83 Table 5.2 Profiles of Other Assistance: by Bennett-Robson Typology 84 Table 5.3 Perceived Impact of BL Services: Intensively-Assisted Firms 85 Table 5.4 Perceived Impact of BL Services: Other-Assisted Firms 86 Table 5.5 Impact Coefficients in Regression Models of Employment, Sales &

Productivity Growth 87

Table 5.6 BLO Delivery Models and their Operating Environment 91 Table 5.7 Operationalising the BLO Models 92 Table 5.8 Number of Firms per Accountant in each Business Link Area 93 Table 5.9 Performance Monitoring Descriptive Statistics 94 Table 5.10 Intensity of Help - BLO clusters 95 Table 5.11 Proportionate Intensive Rate - Descriptive Statistics 96 Table 5.12 Proportionate Intensive Rate – Cluster Analysis 96 Table 5.13 Four Models of Business Link Assistance and BLOs Organisations 97 Table 5.14 Significant Correlations between Income and Intensity 98 Table 5.15 Profiles of Intensive Assistance: By Mole Typology 99 Table 5.16 Profiles of Other Assistance: By Mole Typology 100 Table 5.17 Perceived Impact of BL Services: Intensively-Assisted Firms 101 Table 5.18 Perceived Impact of BL Services: Other-Assisted Firms 102 Table 5.19 Impact Coefficients in Regression Models of Employment, Sales and

Productivity Growth: Mole Typology 103

Table 6.1 Sample Derivation from Telephone Survey 106 Table 6.2 Type of Assistance by BLO 110 Table 6.3 Business Link Model by Urban/Rural Area 110 Table 6.4 Industrial Sector by Employment Size 110 Table 7.1 Age of Firms by Region and Type 126 Table 7.2 Owner Age by Region and Type 127 Table 7.3 Legal Status of Firms by Region and Type 129 Table 7.4 Test Statistics: Sectoral Composition by Region and Type 130 Table 7.5 Sectoral Composition by Region and Type 131 Table 7.6 Proportion of Firms with a Given Strategic Priority: by Region and

Type 133



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Table 7.7 Test Statistics for Regional Differences in Strategic Priorities 134 Table 7.8 Average Firm Characteristics: By Region and Type 136 Table 7.9 Test Statistics for Regional Variation in Firm Characteristics 137 Table 7.10 Assisted Status by Urban/Rural Classification 138 Table 7.11 Urban-Rural Firm Size Contrasts 139 Table 7.12 Urban-Rural Performance Contrasts 141 Table 7.13 Proportions of Intensively-Assisted Firms receiving Different Types of

BL Services By Rural Area 143

Table 7.14 Time Horizons for Experiencing the Benefits of BL Assistance by Rural Area

145

Table 7.15 Additionality of BL Assistance by Rural Area 146



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Acknowledgements The research team would like to thank all the members of the Steering Group who provided invaluable inputs into the various stages of this evaluation study, and to those who commented on earlier drafts of this report and advised the project: Prof. Alan Hughes. Director, Centre for Business Research, University of Cambridge and Rod Spires. Director, Public and Corporate Economic Consultants (PACEC). A particular debt is owed to the CEOs and their staff in all the 43 Business Links for their support in the data extraction exercise from their client management systems which facilitated a robust sampling frame for the telephone survey. Many thanks to OMB Research for their patience as we designed the questionnaire for the main survey, their efficient execution of the survey of 3,448 businesses across the English regions, and their perseverance as we sought to collect GVA data for the sample. In particular, we would like to thank them for the delivery of the survey datafile in a ‘ready to go’ format. A number of consultations were undertaken as part of the design of the evaluation framework and we would like to record our appreciation to those representatives of the BLOs, Chambers of Commerce and the RDAs that provided time for our detailed discussions. To the owner-managers and senior management of the 34 case studies we would like to express out gratitude to them for allowing us access to their firms in order to understand more clearly the way in which individual Business Links interact with their business. To other members of the research team at the three universities: Dr Stuart Fraser (Warwick University) and Dr Li Ying Meng, Will Eadson and Richard Hyde (Kingston University). Finally, and by no means least, we would like to thank the SBS Evaluation Unit and in particular Phill Lacey (Project Manager, SBS) and George Bramley for their advice, support and patience throughout the project. The Research Team November 2006 Dr Kevin Mole (University of Warwick, Project Manager) Professor Stephen Roper (Aston Business School) Professor Mark Hart (Kingston University), Professor David Storey (University of Warwick) Dr David Saal (Aston Business School)



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Glossary Intensive assistance The assistance given to the SMEs by Business Link, which

involves the provision of some services on an on-going basis. There have been definitions of intensive assistance that has been brought in subsequent to this investigation.

Other assistance This assistance is less than intensive assistance, often one-off requests for information

Gross Value Added (GVA)A measure of additional value by the business consisting of output minus the cost of inputs. Operationally, the measure was profits plus the costs of wages and salaries and depreciation.

Additionality The extent to which the policy adds to what would have happened in the absence of policy. Additionality recognizes that firms sometimes would have done something anyway.

Displacement This refers to the impact of a policy on those who do not avail themselves of it. If those who avail themselves of a policy intervention then simply go on to gain at the expense of others in the same area then the policy simply displaces others.

Multiplier This also refers to the impact of the policy on those who do not receive it. In this case there is a positive impact as the additional gain of those who avail themselves of the policy go on to add to the demand of others who were not directly involved.



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Executive Summary Introduction The evaluation assessed the impact of Business Link Local Services on those businesses that received assistance in the 6 month period April to September 2003 and its impact over the subsequent period to May/June 2005. The original aims of the report were:

a) To understand and quantify improvements in the performance of the network since the last evaluation in 1988. The network was reorganised in 2001: How has performance in the network changed? To what extent can this be attributed to the re-organisation or to other factors that are driving the performance of Business Link operators and the network?

b) Identify examples of good practice and ways of working within the network; c) Update value for money estimates using gross value added (GVA) and other

measures; and, d) Provide a baseline for the new arrangements introduced in April 2005 when

the responsibility for delivery of Business Link services was transferred to Regional Development Agencies.

The study follows on from the previous value for money study conducted on Business Links in 1998 by PACEC and the Business link Tracker study conducted in 2001 (Roper et al., 2001). There are now a number of evaluations of Business Link and this study adds to that body of evidence. This value for money economic impact assessment was built around a methodology which included:

(a) An extensive telephone survey of approximately 3,500 firms covering BL intensively and other assisted businesses and a similarly sized control group. The assisted firms were drawn from the population of assisted firms in the target period. The survey was specifically designed to support an econometric approach designed to overcome any systematic bias in the type of assisted firms. Given the difficulties with the collection of GVA data, business growth (employment and sales) and sales per employee indicators were used as key performance measures in the models.

(b) A detailed face-to-face interview survey with 34 firms with a focus on those who

received intensive assistance. This provided more detailed information on the more organisational and strategic impact of BL support, particularly on those firms receiving intensive assistance.

(c) Interviews with 18 Business Link Organisations (BLOs) and the subsequent

development of a detailed typology of alternative brokerage models.



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Analytical Approach Based on the data obtained from the large-scale telephone survey of assisted and non-assisted firms four main quantitative analyses were undertaken in the evaluation:

1. A national estimate of the value for money (VFM) of the Business Links network. This will relate specifically to the VfM of BL network assistance provided in the period April to September 2003 and its impact on business performance until the time of the survey (mid-2005).

2. An analysis of firms’ views of the quality and impact of service received from

BL over the same period and their assessment of impact on strategy.

3. An analysis comparing the effectiveness of alternative brokerage models of assistance on business performance.

4. A spatial perspective which includes two components:

a. a regional baseline analysis (i.e. the 9 English regions) relating to the

type of businesses being assisted by BL in each region to provide an overview of the similarities and differences between intensively-assisted, other-assisted and non-assisted firms in the different Government Office Regions (GORs) across England. Our objective here is to provide a baseline against which future developments in the profile of assisted firms can be measured. In essence, this extends the analysis of Chapter 2, and highlights some substantial differences across GORs regions in the attributes and characteristics of assisted firms.

b. A rural perspective to provide headline data on the operation of Business

Link in rural areas in England. For the purposes of this analysis we adopt a typology of rurality which reflects both morphology and context. We use the following three-fold classification: urban, rural (less sparse) and rural (sparse).

Derivation of Value for Money (VfM) Estimate There is a significant positive effect of intensive Business Link assistance on employment growth, increasing employment growth rate of clients by 2.4 per cent. This estimate implicitly allows for additionality. Displacement effects have been tested through the use of cross-elasticity on the growth models. These were negative which indicated that competition was not on the basis of price. Moreover, the impact of displacement on the small firm clients may be to increase ‘productive churn’ which is seen as insignificant for increases in productivity. To estimate the economy-wide benefits of BL assistance on this basis requires three additional steps:



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1. Increments to employment growth based on the econometric models are converted into absolute employment gains (between 24,915 and 26,908 jobs).

2. These estimates are then grossed up to a national scale based on the number of

interventions with intensively-assisted firms (n=49,830)1.

3. These employment impact estimates are translated into value added using ratios of value added per employee derived from the ABI (i.e. £27,990 per employee).

Following these steps the overall impact on the economy of Business Link interventions is to generate £697 and £753m of additional value-added per annum, compared to a cost of Business Link interventions of approximately £150m for the period April to September 2003. If we then compare the cost to the value added at a midway point between the two estimates (which may in turn be underestimates) – that is, £725m, then the value-added for the 6 month period is £362.5m and so for every £1 spent by the public authorities through the Business Link network (including EU, SRB etc) would generated £2.26 of value2. In terms of cost per job if we take the average of the mid estimates of jobs created from the restricted and unrestricted models as 25,911 then the total cost excluding customer fees is £11,578 per job. We argue that these figures probably under-estimate the overall impact of BL due to:

• The exclusion from the calculation of any positive effects of other assistance. The effect of which on employment and turnover was positive but not significant.

• The de facto exclusion of any bottom line benefits to assisted firms which

occurred after the survey date.

• The exclusion of any positive multiplier effects which may stem from the additional demand generated by more rapidly growing employment.

Only 48 per cent of the assisted firms reported that they had realised all the benefits of assistance. Consequently, our estimates of the impact of Business Link intervention may be underestimates by half, if we take these responses at face value. In terms of a cost-per- job estimate, this can be arrived using the employment estimate derived from the econometric models and the costs of BL interventions. Overall, it is estimated that the cost-per-net-additional-job is £11,578 which is the cost of both

1 This figure is based on the broad definition of intensive assistance, which would have been in operation at the time of the BL interventions between April and September 2003 (it was defined as "significant" interventions and therefore easier to achieve than the current definition of intensive). The SBS monitoring statistics estimate the number of intensively-assisted firms to be 49,830 in the period April 2003 to March 2004. 2 This is discounted over two years at a rate of 3.5% (source: HM Treasury discount rate) excluding customer fees.



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intensive (and its effect) and the cost of non-intensive assistance. In our opinion this represents good value for money. Multipliers and Displacement The impacts of additionality on other firms can be either positive (multiplier effects) or negative (displacement). Adjustments were made for neither. Non-assisted firms, however, were generally operating in more price sensitive markets than those faced by assisted firms suggesting that the Business Link assisted group appeared less likely to suffer displacement than other firms. Moreover, the insignificance of own price elasticity in the employment growth model suggests that the firms were operating in less competitive markets where displacement was likely to be low. Overall, the extent of any displacement from BL assistance is unlikely to be significant either at local or national level. The small firm context is one where there is a great deal of churn. Business Link advisory services are inevitably involved in that churn. Nonetheless, Business Link firms are younger than average and more likely to be limited companies; the firms that Business link help are less likely to be competing solely with other local firms; the nature of competition is non-price; and the firms are too small to make any impact on local labour markets. Who gets assistance from Business Link? The type of firm receiving assistance from the BL network is important in the impact assessment. Our analysis shows that the characteristics of intensively-assisted firms, other-assisted firms and non-assisted firms differ substantially suggesting that unless these differences are controlled for in the estimation any assessment of the effect of assistance is likely to be misleading. Business Link assistance is more commonly used by younger firms with limited liability. In particular, intensively-assisted firms were more likely to be exporting and to have introduced new or improved products over the previous two years than other-assisted firms and non-assisted companies. There were significant differences in the strategic priorities of assisted and non-assisted firms. Notably, intensively-assisted firms placed less emphasis on maintaining their sales in current markets and more priority on increasing sales and product development for other new markets than either other assisted or non-assisted firms. In addition to their own partners directors, around 12.5 per cent of respondent firms also had non-executive directors, with significant differences evident in the proportion of firms in each of the intensively-assisted firms (13.6 per cent), other-assisted firms (14.1 per cent) and non-assisted firms (9.7 per cent) having non-executive directors. A similar pattern was evident in terms of the willingness to share equity in the business, a virtue attributed to 51.4 per cent of the directors of intensively-assisted firms, 35.5 per cent of directors of other-assisted firms and 28.1 per cent of those in non-assisted firms.



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Impact of Business Link Assistance Perceived Impact The standard additionality approach designed to investigate whether the additionality of the BL Local Service was ‘full’, or ‘partial’ (using self-assessment questions) revealed that:

• Two-fifths (40%) of intensively assisted firms and one-quarter (25%) of other-assisted firms reported business outcomes, which, without BL assistance, they would not have achieved.

• 25 per cent of intensively assisted firms and 20 per cent of other-assisted firms

said outcomes would have been the same without assistance but BL assistance helped to accelerate business development.

• 23 per cent of intensively assisted firms and 36 per cent of other-assisted firms

reported that the same business achievements would have been made without BL assistance – i.e. total or 100% deadweight.

Further, of those firms identifying changes in behaviour (i.e., softer indicators of additionality) as a result of BL assistance, around two-thirds of intensively-assisted firms and 55 per cent of other-assisted firms identified BL as the crucial factor in levering behavioural change within the firm. In each case BL assistance was identified as the crucial influence by a significantly higher proportion of firms in the intensively-assisted group. Finally, around half of firms (48% of intensively-assisted and 55% of other-assisted firms) reported already having experienced all of the benefits of BL assistance; the remainder expected the benefits to accrue over future years. Notably, 7.2 per cent of intensively-assisted firms expected the full benefit of BL assistance to take five years or more to be realised. Some recipients may use Business Links advice alongside other sources of support. Business Link has emphasised its brokerage aspect more and more over the period 2001 onwards. In the present study a high proportion of the assistance was provided directly by Business Link. Nevertheless, the use of external sources of advice was tested in the modelling of impact but was not significant and therefore is not part of the model presented in chapter 4. If clients did receive grants it did not seem to reveal itself in increased impact. Those Business Links that provided more advice on the sources of finance tended to perform less well - see pages 101 and 103 Modelling the Impact The econometric modelling – based on a two-stage Heckman approach which allows for selectivity – of the impact of assistance on performance produced the following results:



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• Intensive assistance is found to have a positive and significant impact on

employment growth increasing firms’ employment growth rate by 2.8 percentage points.

• Selection effects are generally weak and for intensively-assisted firms take varied

signs. For other-assisted firms signs are always positive suggesting the selection for assistance of better than average firms.

• In particular, our modelling suggests that while BL assistance has a range of

positive impacts on sales growth and productivity (sales per employee) these effects are generally statistically insignificant. More robust is the effect of intensive BL assistance on employment growth, which is statistically significant and positive.

Business Link Delivery Models

A network of Business Links was set up in England with some discretion to provide local solutions for business support. Each Business Link Organisation (BLO) can operate in different ways. Therefore, we have included the BLO models as part of the evaluation. Four models which may broadly reflect the range of ways in which BLOs operate were developed as part of this economic evaluation study. The four models can be described as follows:

Model 1 Light-touch brokerage

• The dominant model. Some BLOs suggest that they were ‘lean and mean’ with low levels of ‘touch’ with their clients and not too much follow-up.

• Philosophy is ‘Lets solve the business problem there and then’ • The pay off is in the high penetration rate • ‘Light touch’ BLOs are likely to be in areas that receive little non-core

funding such as EU supported funds. Model 2 Managed brokerage

• Many BLOs believe that to retain customers they need to manage the relationships between client, BL and consultant.

• The account manager who oversees the process with a project management role throughout the assistance and follow-up

• Almost all now have contracts between the consultant and client - an exception is Northumberland’s three way contract between consultant, client and BLO.

Model 3 Pipeline Forcing



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• ‘Trigger points’ to identify firms that may be ‘amenable’ to intensive

assistance. They are very keen to get a high proportion of firms through to the end of the funnel

• Not too many in; not many fall out • Generally have a close relationship with the LSC

Model 4 Managed Pipeline Forcing Brokerage

• A combination of both 2 and 3 • This option requires high levels of funding per assisted firm. • May be more prevalent in areas with low rates of business stock.

Using these four models, and allocating each of the 43 BLOs to one of the four models, we are able to make the following conclusions about service delivery and impact. Service Profile For intensively-assisted firms, significant differences were evident between the profiles of BLO assistance relating to business planning and action plan development, raising finance, help with e-commerce and help with IT issues. The key differences between the four models of BL assistance/BLOs were:

• Managed brokerage BLOs were most likely to be providing intensively-assisted firms with business planning assistance or action plan development;

• Help with raising finance was also most likely to be offered by managed

brokerage BLOs;

• Managed brokerage BLOs and BLOs operating both managed brokerage and Pipeline Forcing managed pipeline forcing brokerage were most likely to be providing assistance with e-commerce and IT.

More significant difference were evident in the service profiles being provided to other-assisted firms, with managed brokerage BLOs generally providing a higher proportion of client firms with each service than other types of BLO. Key points were:

• Managed brokerage BLOs were providing 42.3 per cent of their clients with help for raising finance compared to only 19.7 per cent of the clients of light touch brokerages;

• Managed brokerage BLOs were also providing more of their clients help with

exporting, e-commerce and IY than other types of BLOs;

• BLOs operating as managed pipeline forcing brokerage were most likely to be offering their clients help with training.



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Impact of the Delivery Model

We consider two indicators of impact – the impact perceived by firms and the econometrically modelled impact of BLO assistance on business growth. Reflecting the pattern of service provision for intensively-assisted firms, two significant differences were evident between the proportions of Business Link clients in each category in the Mole typology reporting that Business Link services has been an important catalyst for change within their business. Intensively-assisted businesses assisted by BLOs classified as Managed Brokerage BLOs were significantly more likely to cite the assistance as being an important source of change in financial sourcing than other types of BLO. They were also more likely to cite managed pipeline forcing brokerage BLOs as having had an important impact on training than other types of BLO. Only in terms of innovation capability were there significant differences in the proportion of intensively-assisted firms citing BLOs as the crucial factor in change in the firm. Here, light touch brokerages were said to have most commonly been the crucial factor. For other-assisted firms, significant differences between the proportions of firms reporting BLO assistance as important were evident only for financial sourcing and innovation capability. In both cases other-assisted firms were most likely to cite Managed Brokerage BLOs as being an important factor in stimulating change. The econometric estimates of the growth impact of the different types of BLO in the Mole typology reveal that:

• as in the aggregate results, we find no significant effect of Business Link assistance on other-assisted firms for sales or employment growth. Significant positive productivity growth effects are evident with the (positive) effect of light-touch brokerage of more absolute importance.

• no significant productivity effects were evident on intensively-assisted firms from any type of BLO, although the small group of managed pipeline forcing brokerage BLOs were having a positive sales growth effect. More notable perhaps are the

• employment growth effects where the managed brokerage and light-touch groups

of BLOs both had strongly positive and significant effects. Notably BLOs in the managed brokerage group had an employment impact (6.9 percentage points) almost three times that of those in the light-touch brokerage group.

• The figure below shows the four different models.



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Figure ES.1 Business Link Operators Models and Impact

Owner-Manager Views on the Impact of Business Link Support

The views of the 31 owner-managers of assisted firms (25 intensively-assisted and 6 other-assisted) revealed the following points:

• There is a general positive endorsement of the Business Link ‘brand’ which

confirms the aggregate assessment. The majority of businesses feel that their needs are being served by a Business Link network that has access to a wider pool of expertise (i.e. the ‘unique’ product) at a subsidised price. This would appear to be true for both intensively assisted and other-assisted firms.

• The time-scale is too short over which to measure the economic impact of

Business Link assistance received in the April to September 2003 period. Many of the benefits have still to be realised as much of the assistance relates to ‘changed behaviour’ in terms of, for example, strategic focus and staff training – the expectation is for enhanced business performance in the years ahead.

• The distinction between ‘intensive’ and ‘other’ assist is somewhat blurred in a

number of cases which has implications for the impact assessment.

Developing a Spatial Perspective

Regional Baselines

High

Proportion of Intensive

Assistance

Low

Low High Intensity of Assistance

Pipeline Forcing

Light-touch Brokerage

Managed Pipeline Forcing Brokerage

Managed Brokerage

Employment

Sales

Sales per employee



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The evaluation examined differences between the structural characteristics of intensively-assisted firms and other-assisted firms in each Government Office Region (GOR). The following main conclusions emerge:

• The implication is that BLOs in different GORs are targeting assistance at significantly different age cohorts of firms.

• BLOs in different GORs are targeting assistance at groups of firms with different

ownership profiles.

• This suggests that in general terms there is effectively some sectoral targeting of assistance by BLOs.

• Finally, it is worth noting that there are also robust differences between regions in

the size distribution of assisted firms. In London and the West Midlands intensively-assisted firms are, on average, larger than other-assisted firms, the opposite relationship is evident in the South West.

The differences identified between regions in the characteristics of assisted firms provide some support for the development of differentiated baseline statistics for each region. They also emphasise, however, that significant regional differences did exist during the reference period in the support strategies being adopted by BLOs. A Rural Perspective With respect to an urban – rural perspective on the operation of the business link local service we can conclude that there are differences in the headline performance data for intensively-assisted firms. Those located in less sparse rural areas perform better than in the more remote rural areas and urban areas. We have also seen that the ‘package’ of assistance received by intensively-assisted firms in the more remote rural areas differs significantly in a number of ways to similar firms in other locations. Satisfaction levels with the assistance received are similar across the three locations with marginally higher levels reported in rural areas. The assessment of the perceived impact of Business Link assistance revealed that there was very little difference in the time horizon over which benefits were anticipated to be realised. The proportion of firms reporting that they would have achieved similar business outcomes without BL assistance was similar in urban and the two rural locations. In general, this provides some evidence that the BL ‘brand’ is having broadly similar effects in both urban and rural areas across England.



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1. Evaluation Framework and Approach 1.1 The Evolution of Business Support in the UK There have been up to five distinct phases of business support policy in the UK in the past thirty years. Although the Bolton Committee’s reporting in 1971 provided a rationale for the Small Firms Service (Bennett and Robson, 2003a) policy towards small firms began, effectively, in the 1980s (Greene, et al., 2004). The most important single policy was the Enterprise Allowance Scheme (1982-1991), which enabled people to draw benefits whilst trying to establish a business. Over its lifetime 600,000 people participated in the scheme (Storey 1994). Other charitable schemes were targeted toward young people, the Prince’s Trust and Shell LiveWIRE (Greene, 2002). A second set of schemes towards the end of the 1980s was the Enterprise Initiative [(EI). The EI responded to a perceived failure in the market for business advice, in which SMEs were deemed to underestimate the benefits of external advice. The EI was a national scheme to encourage the use of external advice through approved consultants at a cost to the taxpayer (Bennett and Robson 2003a). One of the Enterprise Initiatives was the Marketing Initiative, which was a publicly supported ‘soft’ business support to subsidise up to 15 days of marketing consultancy in small and medium sized firms. It operated between 1988 and 1994. It was administered by four [then five] regional contractors. Firms eligible for the scheme were British-based firms with fewer than 500 employees. Wren and Storey (2002) evaluated the DTI’s Marketing Initiative and found that on average £1,000 in assistance created one extra job and generated about £30,000 of increased sales turnover. However, there may have been some displacement effects not included in this assessment. Nonetheless, this scheme at first sight would appear to be an outstanding success. The lessons learnt from the EI were that grants can enhance the amount of consultancy utilised by small and medium sized enterprise. The EI was a groundbreaker in many ways. It significantly increased the numbers of SMEs using advice from about 1 in every 10 to almost 1-in-3 (Bennett and Robson, 2003b). Scotland’s Expert Help Scheme also shows the consultancy market can be stimulated. This was introduced by the Scottish Office in 1995. It was designed to improve the performance of SMEs who failed to access external advice due to deficiencies on both the demand side (uncertainty of benefits) and the supply side. The take-up of advice was again increased through the provision of a subsidy (Turok and Raco, 2000). In the 1990s, policy shifted again, this time towards a more decentralised local business support system (Bennett and Robson, 2003a; Greene, et al., 2004). In Scotland, services were provided through Local Enterprise Companies (LECs). In England and Wales, local agents ran local ‘Business Links’ (‘Business Connect’ in Wales). The local agents had to



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demonstrate that they were a partnership of existing suppliers of business support. Partners were Training and Enterprise Councils (TECs) and often Chambers of Commerce, Local Authorities and Enterprise Agencies, with the TECs managing the contract between the DTI and the Business Link (Bennett and Robson, 2003a). Business Links were formed to encourage more collaboration amongst competing organisations. This was in response to the charge of business support being a ‘patchwork quilt’. Chambers of Commerce and Enterprise Agencies were able to take a full part in the delivery of the local Business Link. Contracts were held by the Training and Enterprise Councils (TECS). These complicated structures, with interlocking directorships, made for opaque decision-making. Moreover, the performance of the 89 Business Links varied considerably. Bennett and Robson (1999) suggested that in 1999, 21 per cent of the Business Link hubs accounted for 40 per cent of those clients dissatisfied with services. Intensive services, particularly those delivered by PBAs3, achieved the highest satisfaction ratings. Phase four, was when in 1999 the Business Links were reorganised. The number of Business Link Organisations (BLOs), as they were called, was reduced to 45. Each local franchise is now a distinct local body that contracts directly to the Small Business Service (SBS). However, the evidence from interlocking directorships suggests that only 58.1 per cent of BLOs are really independent; 25.6 per cent have strong interlocking directorships with Chambers of Commerce. The role of the business adviser changed to emphasise brokerage and referral rather than direct help. The raising of fees was also de-emphasised. In delivery terms, there was evidence that the changes to Business Links made some impact on their performance. By the 2002 Cambridge Business Research survey, Business Link was the foremost single source of public sector business support. The conclusions of the CBR are that the specific problem and the characteristics of the individual adviser decide client satisfaction (Bennett and Robson, 2003b). In the period 1997-2002, market penetration by BLOs has increased to 32.6 per cent of businesses. Bennett and Robson (1999) recommended that the SBS should focus on increasing the intensity of support for those clients that needed it. Phase five is the latest re-organisation. The government had already introduced a number of Regional Development Agency (RDA) business support pilots at the time of the 2004 budget. In the papers released at the same time, the government announced that ‘given the advantages in improved co-ordination shown by the RDA-led business support pilots, the Government has decided to extend the approach in the pilots to all of the English regions’ (HM. Treasury, 2004: 55). Devolving Business Link services was intended to offer a service more responsive to local needs and therefore RDAs were given the ability to tailor support to the key challenges of local areas (HM Treasury, 2004). 1.2 Business Link Implementation Issues

3 PBAs were personal business advisers who were encouraged to work as generalist facilitators to advice for small and medium-sized businesses. Arguably they were seen as the key to the policy (Bryson, 1997).



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The focus in the literature on small business policy tends to be towards policy–making rather than implementation issues. Hence the previous section focussed on changes to policy but policy only happens when it is implemented. For example, implementation has given rise to serious problems particularly around the issue of ‘targeting’ (Mole, 2002a). The Business Link pre-2001 organisations were to target some of the more expensive services to those SMEs with the ability to grow. In practice, the support for targeting amongst those delivering the service seemed lukewarm (Mole, 2002a) and the BL Tracker study (1996-2000) found that services were targeted, if anything, on larger firms that were facing increased pressure on profitability (Roper et al., 2001), rather than on those with growth potential, although that may be an effect of the urban sample in that study. In the post-2001, phase four, policy was conceived of as not too prescriptive to Business link Operators but to buy against 14 key delivery themes, rather than stick to the previous detailed manual. One of the difficulties with the public sector delivery was the perceived ‘one-size-fits-all’ nature of the products. In an attempt to overcome this, a brokerage model was developed Where the role of the, renamed, business adviser was to assess need and to direct the client to those best able to fulfil that need. The implementation of brokerage has spawned more than one model, including ‘internal’ brokerage where there is modest independence between the broker and client. This provides a clear and significant rationale for the investigation into the brokerage model in action.



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1.2.1 Brokerage Model in Action Brokerage is central to the new Business Link model but has been used in the context of many other public and private services, most notably in finance and housing. The brokerage model is not entirely new in the context of SME advice. As noted earlier, agents acting on behalf of the DTI brokered the relation between SMEs and consultants as part of the successful Marketing Initiative (Wren and Storey, 2002). Drawing partly on that experience, Turok and Raco (2000) suggest that the role of the broker and consultant needs to be carefully managed. Bryson (1997) argued that advisers would be more likely to work with consultants with whom they have worked previously leading to favouritism and a joint dependency. In turn, managers of brokering organisations need to lightly watch for favouritism outside the organisation. Turok and Raco (2000) argue that within the assessment of consultancy support there are a number of common issues and dilemmas:

a. Problems with the proliferation of supply. SME owners face difficulties in accessing knowledge in the marketplace – time pressure, lack of staff and restricted local networks (Bryson and Daniels, 1998). Turok and Raco say ‘Clear, simple and impartial access points are believed to be important to guide firms through the complex and fragmented range of business support to help them identify the most appropriate sources…’ (2000: 411). There is a role, therefore, for public agencies to act as a single point of contact which is likely to be publicly funded. The case is for an agent to make the market putting buyers and sellers in touch as independent brokers.

b. How much is customised? The public sector generally provides

discrete programmes whereas firms normally want unencumbered advice and expertise tailored to their specific circumstances. Improving the long-term competitiveness of an SME may require a more strategic approach needing ongoing dialogue and considerable time.

c. Are external advisors suitable? Public agencies may not be flexible

enough, whereas private sector sources may be distorted by commercial pressures. Consultants may provide pre-packaged solutions and so do little to transfer skills: ‘To maximise the value of consultancy, it may be helpful for development agencies to assist inexperienced SMEs to select consultants who suit their needs, manage their interventions to ensure that firms are closely involved in any plan of action that gets drawn up and that they learn as much as possible from the experience. It may also be necessary to follow through the support to facilitate implementation of the ideas.’ (2000:413).



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d. Targeting to avoid ‘deadweight’ losses is difficult in practice for local managers and often is at variance with the wishes of other parties such as advisers (Mole, 2002a).

It seems clear that the public sector’s SME clients tend to return to the public sector, although Turok and Raco (2000) showed that this was not confined to the public sector but also occurred in the private sector. Thus, the build up of trust in a relationship led to repeat business. There may be a role for brokerage here for two reasons. First because the broker will, in effect, have repeat business and therefore have ‘repeat business information’ and markets work better with repeat business (Storey, 2003). Second, because the broker may become the point of contact to which the business returns. In theory, therefore, brokerage may have some benefits for support agencies. Consequently the post-2001 Business Links were committed to brokerage. The first part of the evaluation examines how this has been implemented. The IDB model has changed the role of the business adviser within Business Links. In England, Business Links are to provide customers with information, diagnosis and brokerage (IDB). The information aspect describes Business Link as giving a non-competitive access to all information that is relevant to any business on the basis of need. Diagnosis examines customer needs as a precursor to broker external expertise to actually provide the services. Differences emerge particularly over the extent to which the brokered relationship is managed. As a client moves from the information to the brokerage they shift from being assisted to being intensively assisted. The Business Link University (BLU) has called for a map of the model of active brokerage used and the performance of a BLO but, in some cases BLOs use more than one model (Gee, 2004). The type of intervention is critical in understanding the ‘assistance parameter’ that will be used in the investigation of the impact of BL support on firm performance. Intensive assistance may differ from one BLO to another. Intensive assistance may involve diagnostics or it may not. We, therefore, need to understand the different models that are employed, perhaps using a checklist to categorise the assistance (Mole, 2004).

1.3 Business Link Programme Objectives Productivity is at the heart of the UK Government’s concerns about managing the economy. For example, the DTI’s public service agreement with HM Treasury for 2003-2006 commits to narrow the productivity gap (with the US, France and Germany) and PSA target 6 includes a target to improve the overall productivity of small firms4. Previous studies are suggestive of a contribution made by Business Link in this area (Roper et al., 2001).

4 PSA Target 6 Help to build an enterprise society in which small firms of all kinds thrive and achieve their potential, with (i) an increase in the number of people considering going into business, (ii) an improvement in the overall productivity of small firms, and (iii) more enterprise in disadvantaged communities (DTI, 2006).



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The government identified five key drivers of productivity: competition, enterprise, innovation, skills and investment (HM Treasury, 2000). In the 2004 report, HM Treasury (2004) recognised the link between skills and enterprise arguing that management skills raised entrepreneurship and business performance. The SBS aims to build the capability for small business growth (SBS, 2003) and the advice and support provided by Business Links are intended to improve the management skills and thereby improve business performance and entrepreneurship. In turn, this means that we need to be mindful to the way in which Business Link works to build the capability for growth. The task of theory driven evaluation is to understand the nature of a programme and thereby fully understand the purpose and context of an evaluation (Donaldson and Gooler, 2003). ‘Programme Theory’ sets out the assumptions and causal links that the programme is based on, the ‘theories of change’ and the realistic outcomes and indicators from the programme. Based on the programme theory the evaluation is designed to test the theory and the programme. Donaldson and Gooler (2003) suggest some practical considerations when developing a theory driven evaluation. The first of which is to start with the outcomes that are desired in the programme. In Table 1.1 the assumptions and rationale are set out. Table 1.1: A Rationale for Business Link Rationale Assumptions behind Rationale Market failure in terms of the demand for business advice

Small firms are unwilling to pay for business support services Small firms lack internal capabilities to analyse their problems and derive solutions Small firms focus on survival rather than development and therefore do not seek advice Small firms are uncertain about the quality of business advice so Business Link accreditation should increase the confidence in the use of business advice which will spill-over into increased demand for private sector services

Supply side institutional failure

Diversity in service provision leading to inconsistency Duplication of services Need for a one-stop-shop Lack of economies of scale and scope

Market failure in terms of the supply of business advice

Location of consultants Business services geared towards the major market in large firms

Source: SBS pre-2001 The units of advice traded are a combination of both demand and supply at the available prices. In order to increase the uptake of business advice there would need to be either an increase in supply or an increase in demand for business advice. The supply side institutional failure might by organising information provide a way to more effectively match latent supply and demand.



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Given that the rationale describes market failure this ultimate outcome for Business links must be to increase the market transactions in business advice in SMEs (see Table 1.2). In order to support a policy to increase the use of business advice, one must have some reason to believe that the result of this interaction would be beneficial to society. This appears implicit in the outcome above. Evidence from the earlier Business Link Tracker study suggested that the ultimate impact was to increase firms’ productivity (Roper et al., 2001) and this is consistent with the performance of the firm.



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Table 1.2: Business Link Outcomes and Impacts Programme Intermediate Outcomes End Outcome Impact Business Links • Small firms are more

certain about the quality of business advice;

Increased use of business advice by SMEs

Increased performance of SMEs

• Small firms develop more internal capabilities to analyse their problems and derive solutions;


• That Business Link legitimation increases the confidence in the business advice;

Increased use of (public sector sponsored) business advice by SMEs


• SMEs know where to go to get business support services;

Increased use of (private sector?) business advice by SMEs


• Business Link has high visibility

Increased use of (public sector sponsored) business advice by SMEs


• There are more consultants dealing with SMEs.

Increased use of (private sector) business advice by SMEs


Source: derived from SBS



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The programme theory for Business Links is set out in Figure 1.1 and is meant to be read from left to right. The arrows indicate the direction of causality. Business Links is the national brand for business support in England and this evaluation focuses on the local service delivery – that is the operator. Figure 1.1: Programme Theory for Business Links

Starting from Business Link on the left hand side and moving towards the right the figure suggests a number of causal links between Business Link and the increased use of business advice. First, that the consultant works for Business Link may confer some legitimacy for business advice, which increases certainty that should lead to increased use of business advice. Here, then, is the first testable hypothesis:

• Hypothesis 1: That legitimation by Business Link leads to a reduction in the uncertainty for SME managers surrounding the performance of the ‘hired’ consultant.

The Federation of Small Businesses (FSB) survey of members in 2003 found that only 5.3 per cent of members cited unqualified advisers as a factor in not taking up business support. The small number citing this factor was attributed to the brokerage role of Business Links (Rigby, 2004). A second element is that learning from their involvement with Business Links enables firms to develop internal capabilities to analyse their problems and derive solutions. This seems to commit the Business Links towards a role where they are facilitating learning by owner-managers it is hoped that, ultimately, the firm will become self-sufficient and have developed their internal capabilities. The resource-based view (RBV) of the firm stresses the development of capability as a key to competitive success. Differences in the capability of the management are part of the explanation of productivity differences between firms (Mole, 2002c) yet, to be able to measure management capability is not trivial. Nonetheless, a second hypothesis is:

Increased use of business advice by SMEs

Small firms more certain of quality business advice

More consultants dealing with SMEs

SMEs know where to get business support services

Business Link accreditation

Small firms develop internal capabilities to analyse their problems and derive solutions

High visibility

Business Link

Increased Management skills



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• Hypothesis 2: That working with Business Link will increase the capacity of

SME managers to analyse their problems and derive solutions This second hypothesis has strong implications for Business Link business support services. Effectively, this is asking Business Link advisers to transfer knowledge. Transferring knowledge takes place in an atmosphere of trust. Nevertheless, a programme theory that stresses learning does imply that Business Link work with companies on a long-term basis to develop stronger relationships (Bryson and Daniels, 1998). The tension between the length of time needed to develop strong ties and the performance monitoring of Business Link has been explored previously by academics regarding about the impact on the time taken with each firm on the measurement against target of the number of firms advised (see Sear and Agar, 1996; Mole 2002b). The third hypothesis examines the SME managers’ knowledge of where to go for advice. This part of the programme theory suggests that the high visibility of Business Link leads to SME knowing where to go for business advice. In the SBS (2004b) evidence base for its action plan the high visibility of Business Link, its brand awareness, is a key dimension to the evaluation of the network.

• Hypothesis 3: That the high visibility of Business Link enables SME owner-managers to know where to go to find business advice

The 2004 FSB survey of its members, a large but biased sample, found that lack of awareness of the services offered was the major reason that firms did not use government-funded business services (Rigby, 2004) - another 15.3 per cent cited confusion over services. This suggests that lack of awareness still hampers the take up of business advice. The SBS’s annual survey of business suggested that: ‘Overall, 68 per cent of all small businesses were aware of Business Link either prompted or unprompted. Just over a fifth (21%) of all SMEs were aware of a national advisory service and could name it as Business Link unprompted. A further 47 per cent of all small businesses were aware of Business Link when prompted but did not initially identify the existence of a national service.’ (SBS, 2006: 153). In addition the SBS’s annual survey suggested that the reason businesses did not use advice was because they did not have any pressing need, which is consistent with models of management consultancy (Keogh and Mole, 2005)

• Hypothesis 4: That the number of consultants dealing with SMEs has increased.

The fourth hypothesis is that the number of consultants for SMEs will increase. The demand for consultancy by SMEs induces greater numbers of consultants to offer services to smaller companies, rather than large. One might expect that this may create a virtuous circle. If demand induces supply then the extra supply through competition might improve the quality of business services which induces demand for consultancy and so on. Accordingly the line between supply and the outcome of more SMEs taking



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advice is double arrowed indicating that causality runs both ways. Nonetheless, there is a clear hypothesis suggested here: The evaluation of business links itself does not test this factor. Alternative sources for this data may be suggestive. VAT statistics show that the end of year stock of VAT registered businesses in SIC 741 which includes legal, accounting and marketing consultancy services grew from 75,620 in the end of year 1994 to 133,035 in the end of year 2003 – one of the highest growth of any three digit sector in the UK over this period. Whilst this does not prove the case it is indicative of a potential increase in the supply of business consultancy. Finally, the SBS rationale for intervention states that there is an assumption that once the subsidy ends businesses go on to seek more external advice from either the private or the public sector at full market cost. Therefore, a final hypothesis that can be tested is:

• Hypothesis 5: That once subsidy ends former Business Link clients are more likely to seek further external advice

Typically, a summative evaluation suggests that a programme adds to the economic welfare if it benefits the participants over and above the costs of the programme and that these benefits would not have happened anyway (additionality) or is not simply captured by one group at the expense of another (displacement). The programme theory outlined here, however, is one where the benefits may accrue over a long period of time and might not be immediately apparent. Whereas a programme like the Enterprise Initiative attempted to solve a perceived problem of, say, a lack of sales in an SME, Business Links have a less specific set of programmes designed over time to improve the quality of the business that takes up its services. Essentially, if a programme sets out to stimulate a market and can show that the programme does indeed increase the number of transactions and actors within that market, then the programme has achieved its aims. Summary Following a ‘Programme Theory’ framework for the evaluation of the Business Link programme has resulted in the identification of five hypotheses that may be tested:

• Hypothesis 1: That legitimation by Business Link leads to a reduction in the uncertainty for SME managers surrounding the performance of the ‘hired’ consultant.

• Hypothesis 2: That working with Business Link will increase the capacity of

SME managers to analyse their problems and derive solutions

• Hypothesis 3: That the high visibility of Business Link enables SME owner-managers to know where to go to find business advice



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• Hypothesis 4: That the number of consultants dealing with SMEs has increased.

• Hypothesis 5: That once subsidy ends former Business Link clients are more

likely to seek further external advice The next stage might be to examine these hypotheses in the evaluations of business support. In turn the results may have implications for the way that Business Link is delivered.

1.4 Design of the Economic Impact Study

The study consisted of two main stages which broadly corresponded to the methodology set out in the SBS Evaluation Plan for the New Business Link Network. These are set out in Figure 1.2. Stage 1 enabled the research team to develop a clear understanding of the various forms of BLO models in operation and to seek to build a more appropriate ‘assistance’ parameter in the quantitative analysis and econometric modelling. Stage 2 is the economic impact component of the evaluation and involved econometric treatment modelling, structural equation modelling and selected qualitative intensive interviews with assisted firms. In terms of research activities the study had three opportunities to gather data. In the first, the researchers interviewed a number of representatives of Business Link Organisations in order that we might better understand the BLO model. In the second, the study conducted a telephone survey of over 3,000 businesses to support the main econometric modelling. In the third, the study conducted case studies of programme recipients to understand and better interpret the econometric findings. The major thrust of the evaluation is the econometric evidence but the researchers were anxious to provide some interpretation to the evidence that may help to develop the programme theory.

Figure 1.2: Study Overview and Structure

Stage 1: Operation of BLO Model

• Mapping of BLOs • Taxonomy of BLO Model • Testing of Taxonomy

Stage 2: Economic Impact

• Sampling • Design of Questionnaire • Survey of intensively assisted and

matched comparison group • Coding and Database construction • Econometric Modelling • Case Studies

Assistance Parameter

Project Outcomes

• Estimates of Net Benefits and VfM measures • Models of Good Practice Business Support

• Regional Baselines



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1.4.1 Analytical Approach to the Derivation of Value for Money (VfM) Estimate Based on the data obtained from the large-scale telephone survey it is proposed to do four main quantitative analyses, which will provide:

1. A national estimate of the value for money of the Business Links network. This will relate specifically to the VfM of BL network assistance provided in the period April to September 2003 and its impact on business performance until the time of the survey (mid-2005).

2. An analysis of firms’ views of the quality and impact of service received

from BL over the same period and their assessment of impact on strategy.

3. An analysis comparing the effectiveness of alternative brokerage models of assistance on business performance.

4. A regional baseline analysis relating to the type of businesses being assisted

by BL in each region and the perceived impact of BL support. In addition, two other derivative analyses will be undertaken focussing first on improvements in the BL service between the last VfM survey (see PACEC, 1998) and the current study, and second a ‘path analysis’ focussing on identifying the possible ways in which BL assistance impacts on company performance. The latter analysis will use a structural equation modelling approach and its application is regarded as experimental in the context of the current study. 1.4.2 National VfM Estimates The starting point for these estimates are the responses from the telephone survey. In particular, given the difficulties with the GVA data collection, business growth and sales per employee indicators will be used as key performance measures. The output from this element of the study will be a value for money estimate of BL assistance provided between April and September 2003 based on its impact over a period of 12-18 months. The calculation will involve a number of different steps:

a. Weighting and descriptives – as the telephone survey was structured weighting is necessary to ensure a representative response. Weights have been constructed to ensure the sample results are representative of the whole BL assisted group. Non-assisted responses have been weighted to match the assisted group. This allows the non-assisted group to be used as a control-group for the assisted firms in the descriptive analysis. Bivariate, descriptive analysis relating intensively-assisted firms, other-assisted firms and non-assisted firms will be conducted.



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b. Impact modelling – the impact of BL assistance on firm performance was

modelled econometrically using a 2-stage Heckman approach. This allowed for selectivity bias in the estimate of the impact of assistance, while a multivariate approach allowed for differences in the other characteristics of the assisted and non-assisted groups. The key output from this stage of the process will be estimates of the contribution of BL assistance to firms’ employment growth, sales growth and sales per employee over the 2004-05 period. These implicitly allow for additionality and include variables to test extent to which displacement is likely to occur.

c. GVA estimates and grossing up – at this stage the individual sales and

employment impacts derived at (b) will be scaled to the whole of the assisted population. These can then be translated into GVA using industry and size band ratios derived from the Annual Business Inquiry. This provides the ‘benefit’ element of the VfM cost-benefit analysis.

d. Attributable Costs – derived from BL accounting data this will reflect the costs of

providing the BL service during the period April to September 2005. For comparative reasons the methodology used here should reflect that used in the earlier VfM study.

VfM estimates will then be derived as the difference between (c) and (d). We would want to stress, however, the conditionality which will apply to our estimates of VfM and the likelihood that our estimates are likely to under-estimate the true longer-term effect of BL assistance. This is because only one year’s performance data is going to be available. 1.4.3 Qualitative Views of Business Link Impact As indicated earlier the VfM estimate for BL will provide a quantitative indicator of BL assistance over the 12-18 months after the assistance is provided. This is only part of the picture, however, due to the potential longer-term capability benefits of BL assistance. Indeed, only around half of the respondents to the survey indicated that the full effect of assistance would be realised within 12 months. The qualitative element of the analysis will reflect:

a. Firms’ assessment of the time horizon over which BL assistance will influence performance.

b. The areas of their operations on which BL assistance had some influence and

those on which it had a ‘crucial’ impact.

c. Firms’ overall satisfaction with the BL assistance they received.



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1.4.4 Evaluation of Alternative Brokerage Models The aim of this exercise is to evaluate the impact of alternative brokerage models being used by BL during 2003 in terms of their impact on business performance. The analysis will be based on variants of the same impact model as the VfM analysis. The key stages in the modelling will be:

a. Classification of BLOs – using quantitative management data the first step will be to develop a grouping of BLOs according to the extent and type of brokerage model they are using. The impact of each different type of brokerage model on business performance will then be evaluated separately.

b. Estimation of business performance effect – using similar models to the VfM

analysis we propose to estimate impact models for each different brokerage model. This will allow us to estimate the ‘assistance’ effect of each type of brokerage model and develop some comparisons.

Again, however, we would want to stress the strong conditionality which would apply to this procedure. In particular, the fact that only one year’s performance data is going to be available is likely to mean that we underestimate the effect of BL assistance. Moreover, if the time profile of performance effects of the alternative models of assistance is different – as it might be if they emphasise different forms of company support – the inter-model comparisons may also be somewhat misleading. 1.4.5 Developing a Spatial Perspective: Regional Baselines and a Rural Perspective The final element of our analysis relates to the derivation of a set of regional baselines for the RDAs moving forward with the Business Link network. These will again be cross-tabulations by region which can be used to provide an indication of the structure and character of BL assisted firms. This chapter focuses on differences between intensively-assisted, other-assisted and non-assisted firms in the different Government Office regions to provide a baseline against which future developments in the profile of assisted firms can be measured. In essence, this highlights some substantial differences across Government Office regions in the attributes and characteristics of assisted firms. A final element will be to present headline performance data on the assisted groups of firms disaggregated by urban and rural areas with the latter defined in terms of morphology and context following DEFRA’s classification of rural areas (i.e., less sparse and more sparse).

1.5 The Structure of the Report The initial analysis concentrates on the descriptive analysis of the telephone survey and examines the characteristics of what type of businesses use Business Link (Chapter 2) and the impact of that use (Chapter 3). Chapter 4 sets out the impact analysis and value



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for money estimates using the econometric models. Respectively Chapters 5 and 6 discuss the variety of Business Link models in operation throughout the network and the qualitative analysis from the face-to-face interviews with the owner-managers of assisted and non-assisted businesses. Chapter 7 has the regional baselines and a brief rural perspective on the headline impact analysis. The report concludes with a summary discussion of the findings.



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2. Sample Characteristics and the Nature of Business Link Support 2.1 Introduction This chapter presents a brief overview of the descriptive results from the telephone survey of 3,448 small businesses: 1,130 intensively-assisted; 1,166 other-assisted and 1,152 non-assisted small businesses. These businesses were surveyed between May and July 2005. The chapter is organised around the main structure of the telephone survey questionnaire (see Appendix A). The key sub-sections are:

� Sample Confirmation and Contamination � Respondent Profile � Business Characteristics � Strategic Direction � Partners, Directors and the Background of the Business Leader � Main Partner/Managing Director

Weighting has been applied to the responses to take into account sample structuring (see Appendix B). Appendix B reports the numbers of firms receiving intensive assistance and other assistance from Business Link in the period April – September 2003. The weighting means that the sample population and survey population have the same characteristics for firm size (less than 10, 10-49, 50-250) and for broad sector (primary, production, construction and services). For a number of Tables we compare the findings for all firms with the pattern for sparse rural settlements to ascertain whether there are different patterns that emerge in those areas. Sparse rural settlements are based on DEFRA definitions and derived from the postcodes. There are tables 2.2a, 2.3a, 2.5a, 2.7a, and 2.8a

2.2 Sample Confirmation and Contamination In the sampling, respondent firms were classified as either intensively-assisted or assisted based on data provided directly by the BLOs. Firms’ use of Business Link’s services was confirmed in the telephone survey, however, using a simple question asking whether firms had actually used BL services during the reference period (April to September 2003). The vast majority (96.5 per cent) of firms classified as ‘intensively assisted’ confirmed their use of BL services between April and September 2003, with only 3.5 per cent reporting no BL use over this period. Similarly, the vast majority (96.2 per cent) of other assisted firms also confirmed their use of BL services over the reference period. In



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this group 3.8 per cent recalled no BL contact during this period (April to September 2003)5. A more general question relating to BL use over the last two years largely confirmed this pattern of response with 58 intensively assisted firms reporting BL use compared to 57 other assisted firms. Larger proportions of firms reported using BL prior to April 2003 – 63.8 per cent of intensively assisted firms and 60.3 per cent of other assisted firms. Similarly high proportions of assisted firms were either engaged with BL at the time of the survey or were planning to use BL services at some time in the future - 73.9 per cent of intensively assisted firms and 64.0 per cent of other assisted firms. Notably the proportion of intensively assisted firms continuing to use or planning to use BL services was statistically significantly higher than the proportion of other assisted companies in this category (t=-4.79, ρ<0.001). In terms of the assisted group, this initial analysis suggests the overall validity of the sample. Key points are:

• It is reassuring that assisted firms’ recall of BL usage during the reference period largely reflects the original sampling data provided by the BLOs.

• It is also reassuring that levels of contamination due to continued BL use between

the reference period and the survey date were relatively low.

• The high proportion of assisted firms which were intending to make use of BL services in the future provides a positive initial indicator. Particularly interesting is the higher proportion of intensively assisted firms intending to make future use of BL services.

Similar initial questions to the non-assisted sample were intended to confirm that they had not received assistance from BL and to estimate any contamination. Of the non-assisted respondents, 13.8 per cent reported using BL as a source of advice or assistance at some point in the past, with the majority of these (92.4 per cent) confirming that this BL assistance had been provided prior to the start of the reference period (i.e. before April 2003). The remaining 7.6 per cent were unable to be certain about the timing of the BL assistance they had received. The suggestion is, however, that the extent of any contamination of the non-assisted sample is low, and that they will therefore provide a valid control group. In the non-assisted group 43.1 per cent responded negatively when asked whether ‘they had ever heard of Business Links before this interview today’.

2.3 Respondent Profile

5 Note these are weighted responses, derived using the relative weights. The actual number of respondents identified as intensively-assisted and other-assisted by BL but reporting no BL use during the reference period were: 36 intensively-assisted firms and 44 other-assisted firms.



38

As part of the survey the gender and position of respondents within the company was identified. Overall around two-thirds of survey respondents were male, with no significant difference in the proportion of male respondents between the intensively assisted (69.8 per cent), other assisted (67.0 per cent) and non-assisted (68.1 per cent) firms (χ2 (2)=2.161, ρ=0.339). More significant were differences in the position of respondents within the business with a wide range of job titles being reported (Table 2.1). Managing directors accounted for a larger proportion of respondents in intensively-assisted firms, while owner-managers were more common in the other-assisted and non-assisted groups. This distribution is likely to reflect the greater number of limited liability companies in the intensively assisted group, and conversely the higher proportion of sole traders in the groups of other-assisted and non-assisted firms.



39

Table 2.1: Respondents’ Position within the business – Selected Categories

Intensively-assisted firms

Other-assisted firms

Non-assisted firms

All Surveyed

Firms % % % % Owner/proprietor 22.0 32.2 34.2 29.5 Managing Director 35.6 23.5 20.5 26.4 Partner 7.6 10.0 11.3 9.6 Director 10.7 11.7 7.7 10.0 Senior Manager 3.6 3.6 4.3 3.9 Company Secretary 2.3 2.9 5.1 3.5 General Manager 4.0 2.8 4.3 3.7 Chief Executive (CEO) 1.1 .6 .4 .7 Chairman .4 .7 .4 .5 Office Manager 1.4 2.2 3.4 2.3 Accounts/Account Manager

.7 .9 1.2 .9

Admin Manager/Officer .7 .5 .7 .6 Business Development Manager

.4 .2 .2 .2

HR Manager/Director .7 .4 .3 .5 Commercial Manager/Director

.2 .2 .2 .2

Operations Manager/Director

.9 .9 .4 .8

Design Engineer/Manager

.2 .1 .1 .1

Engineer .1 .1 .1 Executive Officer .3 .1 Finance Director/Manager

1.3 .6 1.2 1.0

PA/Secretary .4 .7 .4 .5 IT Manager .1 .1 .1 Marketing Manager/Director

.9 .2 .3 .4

Production Manager .2 .2 .3 .2 Project Manager .1 .2 .1 .1 Sales .4 .3 .2 Sales Manager/Director .5 .6 .3 .5 Training Manager .1 .1 .1 Transport Manager .1 .1 .1 Other Manager 1.7 2.0 .6 1.4 Other Director .4 .1 .2 .2 Other .8 1.3 1.6 1.2 Consultant .4 .4 .3

Source: BL Telephone Survey (2005)



40

2.4 Business Characteristics Previous studies of small business growth have emphasised the role of firm characteristics – such as age, sector, legal status etc. – as determinants of business growth. Identifying the impact of BL assistance requires us to ‘control’ for the influence of these factors. Importantly, these factors may also differ between assisted and non-assisted respondents shaping their patterns of differential growth. In this section we therefore focus on a brief comparison of the characteristics of the businesses in the three groups of respondents (i.e. intensively-assisted, other-assisted and non-assisted). Company age has in previous studies been linked negatively to business growth rates, i.e. younger firms tend to grow faster. Table 2.2 summarises sample data on the age of respondent firms and suggests that the groups of assisted firms – both intensively and other – are significantly younger than the non-assisted group (χ2 (10) =78.42, ρ<0.001). For example, only 8.7 per cent of non-assisted firms were established in the last 2-3 years compared to 13.0 per cent of intensively assisted and 11.3 per cent of other-assisted firms. Similarly, nearly two-fifths of non-assisted firms had been established for more than 20 years compared to less than a third of assisted firms. Two implications follow. First, it seems clear that BL assistance is more commonly used by younger firms, or perhaps that BL assistance is being targeted at younger firms. Secondly, if our expectation that younger firms tend to grow faster is realised, we would expect, all other things unchanged, the assisted groups to be growing faster than the non-assisted group. Table 2.2: Age Distribution of Respondent Groups: All Firms Intensively

-assisted firms


Non-assisted firms

All Firms

When did your business start?

% % % %

2-3 years ago 13.0 11.3 8.7 11.0 3-4 years ago 6.9 7.4 4.1 6.1 4-5 years ago 8.3 6.7 5.5 6.8 5-10 years ago 20.0 18.8 15.3 18.0 10-20 years ago 24.6 27.8 25.6 26.0 More than 20 years ago

27.3 28.0 40.7 32.0

Source: BL Telephone Survey (2005) Note: Reponses are weighted to give representative results. Table 2.2a provides a comparison for the rural dispersed settlements. This produces a more pronounced pattern with the younger firms being more likely to be assisted (χ2 (10) =2068.60, ρ<0.000).



41

Table 2.2a: Age Distribution of Respondent Groups in Rural Dispersed Settlements Intensively

-assisted firms


Non-assisted firms

When did your business start?

% % %

2-3 years ago 12.3 6.2 8.4 3-4 years ago 5.0 6.1 0.4 4-5 years ago 6.6 7.1 4.5 5-10 years ago 18.0 22.5 13.0 10-20 years ago 27.0 22.2 16.2 More than 20 years ago

31.0 35.9 57.5

Source: BL Telephone Survey (2005) Note: Reponses are weighted to give representative results. Another factor which has been linked to business performance in previous studies is legal form. Again among respondents significant differences were evident between the legal form of the assisted and non-assisted groups (χ

2 (18)=137.44, ρ<0.001), with some differences also evident here between intensively assisted and other-assisted respondents (Table 2.3):

• Intensively-assisted firms were less likely to be sole traders than either other-assisted or non-assisted firms. Sole traders accounted for nearly a quarter of other-assisted and non-assisted firms but only 1:7 intensively-assisted businesses.

• Limited liability companies comprised around 70 per cent of intensively-assisted

firm, 60 per cent of other-assisted firms and 40 per cent of non-assisted businesses.

• Social enterprises accounted for 2.0 per cent of the whole group of respondents

but were less likely to be in either of the assisted groups.



42

Table 2.3: Legal Status of Respondent Firms: All Firms Intensively

-assisted firms


Non-assisted firms All Firms

% % % % Sole trader 14.1 24.3 28.3 22.3 Partnership 12.0 14.0 17.8 14.6 Private Limited Company (Ltd)

68.7 55.1 47.7 57.1

Public Limited Company (plc) 2.0 2.9 1.4 2.1

Limited Liability Partnership .8 .7 1.2 .9

Social Enterprise 1.5 2.1 2.4 2.0

Branch/Subsidiary or larger company .2 .4 .2

Private (Unlimited) Company .2 .3 .2

Company Limited by Guarantee .2 .1 .1

Other .4 .7 .3 .5 Source: BL Telephone Survey (2005) Table 2.3a: Legal Status of Respondent Firms in Rural Dispersed Settlements Intensively

-assisted firms


Non-assisted firms All Firms

% % % % Sole trader 22.8 25.1 29.8 27.2 Partnership 21.0 21.1 29.0 24.8 Private Limited Company (Ltd)

52.5 49.8 37.0 43.9

Public Limited Company (plc) 2.0 .5 .0 .4

Limited Liability Partnership .0 .0 .6 .3

Social Enterprise 1.8 2.7 3.6 3.1

Other .0 .8 .0 .4 Source: BL Telephone Survey (2005) In the rural dispersed settlements the similar pattern of differences was evident (χ2

(12)=951.29, ρ<0.000) (Table 2.3a).



43

• The overall proportion of sole traders was higher and sole traders were more likely to gain assistance in the rural dispersed settlement than in the overall sample.

• Social enterprises accounted for 3.6 per cent of the whole group of respondents

but were less likely to be in either of the assisted groups. Our expectation – based on the results of previous studies – would be that firms with some form of limited liability would grow faster than those without such legal protection. In this case, and ceteris paribus, the larger proportion of intensively and other-assisted firms would suggest that these groups would again tend to grow faster than the non-assisted group. Another characteristic which might be important in determining growth is whether or not firms were part of multi-site organisations. In fact, broadly similar proportions of firms in each category were part single and multi-site businesses, with around four-fifths single site organisations (81.8 per cent of intensively-assisted plants; 82.9 per cent of other-assisted plants and 86.5 per cent of non-assisted firms) (χ2(2)=9.58, ρ=0.008). Sectoral composition of assisted and non-assisted groups also differed significantly (χ2(26)=155.41, ρ<0.000) with a concentration of intensive and other assistance on manufacturing companies and a relatively small proportion of assisted companies in the retail, wholesale and repair categories (Table 2.4).



44

Table 2.4: Sectoral Composition of Respondent Firms Sample Group



Non-assisted firms

All Firms

% % % %

A - Agriculture, hunting & forestry 5.8 4.2 4.9 4.9

B - Fishing .0 .1 .3 .1 C - Mining & quarrying .0 .1 .0 D - Manufacturing 23.4 19.0 18.8 20.3 E - Electricity, gas and water supply .3 .3 .2

F - Construction 5.5 6.5 5.6 5.9 G - Retail, wholesale and repair of motor vehicles

14.7 17.9 28.1 20.3

H - Hotels and catering 4.3 5.6 8.3 6.1 I - Transport, storage and communication

3.1 2.5 3.0 2.8

J - Financial intermediation (Finance) 1.0 .8 1.8 1.2

K - Real estate, renting and business activities

27.6 30.9 16.6 25.0

M - Education 2.0 1.6 1.0 1.6 N - Health and social work 6.6 5.5 5.8 6.0

O – Other community, social and personal service activities 5.8 5.4 5.5 5.5

Source: BL Telephone Survey (2005) Intensively-assisted firms (28.8 per cent) were also more likely to be exporting than other assisted firms (20.2 per cent) and non-assisted companies (14.7 per cent) (χ2 (2)=69.10, ρ<0.000). Intensively-assisted firms were also more likely to have introduced new or improved products over the previous two years (64.6 per cent) than either other-assisted (55.2 per cent) or non-assisted (39.8 per cent) firms. Similarly intensively-assisted firms were also more likely to have introduced new or improved processes (49.8 per cent) compared to other assisted (38.4 per cent) and non-assisted firms (26.0 per cent). In each case there were statistically significant differences between the propensity of firms in each respondent group to introduce new products (χ

2 (2)=142.66, ρ<0.000) and processes (χ2

(2)=133.49, ρ<0.000).



45

In terms of the markets in which assisted and non-assisted groups were operating, a high proportion of each group reported intense competition. Non-assisted firms, however, were generally operating in more price sensitive markets than those faced by assisted firms. There are two implications: first that the assisted firms had ‘better strategies’ in terms of having non-price factors that they were able to compete on. Second, the higher levels of price elasticity may indicate that firms were in a zero sum game where one firms gain was at the expense of another. In a zero sum game, displacement effects are more likely; consequently the Business Link assisted group appeared less likely to suffer displacement. Two-thirds (64.3 per cent) of intensively assisted firms identified competition in their main market as ‘very intense’ or ‘intense’, a larger proportion than other assisted (58.9 per cent) or non-assisted firms (60.7 per cent) (χ2(2)=7.107, ρ=0.029). High own price elasticities (i.e. >2) were more common among non assisted firms (9.3 per cent) compared to intensively assisted (7.6 per cent) or other assisted (5.0 per cent) firms. These differences were significant at the 1 per cent level (χ2 (2)=14.84, ρ=0.001). High competitors price elasticity (i.e. >2) were also more common among non-assisted firms (9.7 per cent) than among either intensively assisted (8.1 per cent) or other assisted (4.4 per cent) firms. As before these differences were significant at the 1 per cent level (χ2 (2)=22.98, ρ<0.000).

2.5 Strategic Direction In addition to the differences in firm characteristics noted earlier, significant differences in the strategic priorities of assisted and non-assisted firms were also evident. Notably, intensively assisted firms placed less emphasis on maintaining their sales in current markets and more priority on increasing sales and product development for other new markets than either other assisted or non-assisted firms (Table 2.5). The strategic priority of each group of firms, however, was to increase their sales in the markets they currently served. Moves into new market areas within existing or new products had a lower priority. Table 2.5: Strategic Priorities of Respondent Firms:All Firms Intensively-

assisted firms


Non-assisted firms

% % % Significance χ

2(2) (ρ) Maintain sales in present markets 22.7 30.9 36.2 50.56 (<0.000) Increase sales in current markets 55.5 52.7 49.9 7.109 (0.029) Increase sales in new markets 19.3 14.2 10.3 36.95 (0.000) New products for existing markets 9.0 7.4 5.8 8.58 (0.14) New products for new markets 4.4 2.4 1.6 17.165 (0.000) Source: BL Telephone Survey (2005) Table 2.5a: Strategic Priorities of Respondent Firms: Rural Dispersed Settlements Intensively-

assisted firms


Non-assisted firms

% % % Significance χ

2(2) (ρ)



46

Maintain sales in present markets 28.9 33.1 39.4 154.68 (<0.000) Increase sales in current markets 49.8 51.9 43.9 164.66 (0.000) Increase sales in new markets 15.6 17.2 9.0 379.31 (0.000) New products for existing markets 10.2 8.6 8.4 6.844 (0.33) New products for new markets 2.2 2.7 0 354.117 (0.000) Source: BL Telephone Survey (2005) Again the sparse rural settlements display a similar pattern of significant differences between strategic priorities of those who receive assistance. In sparse rural settlements more firms in all three groups emphasised maintaining sales in present markets although intensively assisted firms placed less emphasis on maintaining their sales in current markets and more priority on increasing sales and product development for other new markets than either other assisted or non-assisted firms (Table 2.5a). The survey reported greater proportions of firms introducing new products for existing markets in sparse rural settlements. Further evidence of the difference in strategic approaches of the three groups of respondents relates to their use of formal business planning. 63.4 per cent of intensively-assisted firms had a formal business plan compared to 52.9 per cent of other assisted firms and 29.9 per cent of non-assisted enterprises (χ2 (2) = 263.3, ρ<0.000). Firms’ business plans had also been updated more recently by intensively assisted firms (88.3 per cent within the last 2 years) compared to other assisted (86.1 per cent) or non-assisted (83.4 per cent) firms (χ2 (2)=17.07, ρ=0.002). No significant difference was evident between groups of firms, however, in the objectives of the business plan: in each case 28-30 per cent of firms had developed the plan primarily for use by an outside agency to justify funding or finance (χ2(2)=1.686, ρ=0.430)

2.6 Partners, Directors and the Background of the Business Leader In this section we focus on a series of questions relating to the ethnic and gender mix of the group of partners/directors in respondent firms, and the characteristics and background of the main business leader, i.e. the owner manager or managing director. Four key measures are examined: the number of partner/directors, the percentage of those partners/directors that are female, the proportion drawn from ethnic minorities, and whether or not the firms have non-executive directors (Table 2.6): Table 2.6: Partners and Directors, Ethnic and Gender Diversity



Non-assisted firms

% % %

Directors and partners (number)

2.3 2.3 2.1

Gender diversity -% female 28.8 28.8 27.2 Ethnic diversity - % ethnic 3.5 4.8 3.3




47

• No significant differences were evident between intensively-assisted firms and other-assisted firms in terms of either the mean number of directors (t=0.306, ρ = 0.760), gender diversity (t=0.010, ρ = 0.992), or ethnic diversity in their group of partners/directors (t=-1.473, ρ = 0.141).

• More significant differences were evident between intensively-assisted firms and

non-assisted firms in terms of the number of directors and partners in the business (t=2.589, ρ = 0.010), although the two groups of firms had similar levels of gender (t=1.086, ρ = 0.278) and ethnic diversity (t=0.363, ρ = 0.716).

• Significant differences were also evident between other-assisted firms and non-

assisted firms in terms of the number of directors/partners (t=2.398, ρ = 0.017) and ethnic diversity (t=1.770, ρ = 0.077).

In addition to their own partners directors, around 12.5 per cent of respondent firms also had non-executive directors, with significant differences evident in the proportion of firms in each of the intensively-assisted firms (13.6 per cent), other-assisted firms (14.1 per cent) and non-assisted firms (9.7 per cent) having non-executive directors ((χ2(2)=12.104, ρ=0.002).

2.7 Main Partner/Managing Director The final set of questions related to the characteristics of the main partner or owner-manager of the firm. These questions were included as the characteristics of the owner-manager have been shown to be a key determinant of small business growth in a range of previous studies. Key contrasts were:

• Around 86 per cent of main partners/managing directors were equity holders (>20 per cent) in respondent firms, with no significant differences evident between groups (χ2(2)=0.116, ρ=0.944).

• 72-76 per cent of main partners/directors were also involved in other businesses.

Again there was no significant difference between respondent groups ((χ2(2)=2.153, ρ=0.341).

• More important differences were evident in the proportion of main

partners/directors who had been involved in founding other businesses. Percentages were significantly different between respondent groups ((χ2(2)=32.43, ρ<0.000), and highest among intensively-assisted firms (40.1 per cent) and other-assisted firms (36.0 per cent) than among non-assisted firms (28.4 per cent).

• A similar pattern was evident in terms of the willingness to share equity in the

business (χ2(2)=97.55, ρ<0.000), a virtue attributed to 51.4 per cent of the



48

directors of intensively-assisted firms, 35.5 per cent of directors of other-assisted firms and 28.1 per cent of those in non-assisted firms.

Educational attainment has also been shown to be a key factor in shaping the growth potential of smaller firms. Grouping the educational qualifications of owner-managers into four categories suggests significant differences between respondent groups (χ2(6)=54.8, ρ<0.000) , with owner-managers in intensively-assisted firms more likely to have degree level qualifications, while those in non-assisted firms are more likely to have no post-school qualifications (Table 2.7). Table 2.7: Highest Qualification of Owner- Managers: All Firms Intensively

assisted firms

Other assisted firms

Non-assisted firms

All Firms

% % % %

Degree or equivalent qualification 64.3 62.4 49.6 59.3 NVQ3 or apprenticeship qualification 18.1 17.5 20.5 18.6 Other post-school qualifications 2.1 1.7 1.3 1.7 No post-school qualifications 15.5 18.4 28.6 20.4

Source: BL Telephone Survey (2005) In rural sparse rural settlements the pattern was repeated with slightly fewer qualified at degree level and slightly more at NVQ3 level, and slightly more with no post-school qualifications (Table 2.7a). Table 2.7a: Highest Qualification of Owner- Managers: Rural Dispersed Settlements Intensively

assisted firms


Non-assisted firms

All Firms

% % % %

Degree or equivalent qualification 64.5 60.8 40.2 52.8 NVQ3 or apprenticeship qualification 16.9 23.1 19.1 20.9 Other post-school qualifications 4.0 0.5 2.7 1.7 No post-school qualifications 14.6 15.6 38.1 24.7

Source: BL Telephone Survey (2005) Age has also been shown to be an important factor in shaping the success of owner-manager’s firms. Here again significant differences were evident between intensively-assisted firms, other-assisted firms and non-assisted firms (χ2 (10)=31.648, ρ<0.000), although these tended to be concentrated at the extremes of the age range. More specifically, a relatively high proportion of the owner-managers of non-assisted firms were in the 65 plus age group compared to the groups of assisted firms (Table 2.8). Table 2.8: Age Distribution of Owner-Managers: All Firms Intensively Other Non- All



49

assisted firms

assisted firms

assisted firms

Firms

Age % % % % Under 25 .2 .5 .9 .5 25-34 8.8 9.8 7.0 8.5 35-44 29.3 28.2 28.9 28.8 45-54 37.0 35.1 32.4 34.8 55-64 22.1 21.1 23.9 22.4 Over 65 2.7 5.3 6.9 5.0

Source: BL Telephone Survey (2005) There were some differences between the sparse rural settlements and the age distribution, although once again the pattern was similar. Unsurprisingly, the owner-managers in the rural areas were older than the managers in the urban areas with 11.2% who were over 65 yet there were fewer receiving intensive assistance (Table 2.8a).

Table 2.8a: Age Distribution of Owner-Managers: Sparse Rural Settlements Intensively

assisted firms


Non-assisted firms

All Firms

Age % % % % Under 25 .0 1.1 .4 .7 25-34 7.9 6.2 7.2 6.8 35-44 19.3 28.2 20.3 28.8 45-54 38.2 35.7 35.8 34.8 55-64 33.8 28.1 23.3 22.4 Over 65 .9 10.8 13.0 11.2




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3. Business Performance and Assisted Status

3.1 Profiling Business Link Support

Our main objective in this section is to profile – at national level - the support received from BL by each group of assisted firms. The profiles reflect both the form and frequency/intensity of firms’ contacts with BL and the focus of the assistance they received (i.e. for marketing, innovation, ITC etc). This is important because it defines the packages of assistance received by firms from BL, and it is the impact of these packages of assistance on performance which form the basis of the overall impact assessment6.

Three main groups of firms are considered here – intensively-assisted firms are defined here – as in the rest of the report - as those classified by the BLOs themselves as having received intensive-assistance during the reference period. Other-assisted firms are all other companies which received assistance over this period. Non-assisted firms are the control group of firms which received no assistance from BL either during the reference period or subsequently. What is clear, however, from our analysis of different delivery models (Chapter 5) and our regional analysis (Chapter 7) is that what constituted ‘intensive-assistance’ or ‘other-assistance’ did differ between BLOs and regions. In the next Chapter, where we focus on national effects, we abstract from these differences which are considered in more detail in later sections. It is also worth bearing in mind that the context for the impact assessment is the 2003-2005 period. This was a period of rapidly changing GDP growth which rose from around 2.2 per cent per annum in 2003Q1 to 3.6 per cent per annum in 2004Q2, before falling again to 2.0 per cent per annum in 2005Q1. These movements in GDP growth – and more general economic prospects – influenced both the assisted and non-assisted firms, however, effectively controlling for changes in the economic climate. Before looking at the intensity and type of assistance received by intensively-assisted firms and other-assisted firms, however, it is probably worth considering briefly the different routes by which firms actually got in touch with BL. Here, some marked differences were evident between different respondent groups:

• While 90.7 per cent of intensively-assisted and 90.1 per cent of other-assisted firms reported receiving mail shots from BL, this was true of only 16.8 per cent of non-assisted firms (χ2(2)=1847.12, ρ<0.000).

• Similarly, 67.3 per cent of intensively-assisted firms reported using BL websites

compared to 63.5 per cent of other-assisted firms and only 4.6 per cent of non-assisted firms (χ2(2)=1146.3, ρ<0.000).

6 More specific differences between BL operators in the way services are delivered, and the effectiveness of different brokerage models are considered in Chapter 5.



51

• A lower proportion of firms in each category had received direct approaches from

BL staff but the proportions of firms contacted were still notably higher among intensively-assisted firms (54.0 per cent) and other-assisted firms (41.9 per cent) than among non-assisted firms (4.9 per cent) (χ

2(2)=671.36, ρ<0.000).

• Around a third of intensively-assisted firms were referred to BL by friends (31.6 per cent), a larger proportion than that of either other-assisted firms (21.7 per cent) or non-assisted firms (4.1 per cent) (χ

2(2)=287.94, ρ<0.000).

• Smaller proportions of firms were referred by external advisors: intensively-assisted firms (15.0 per cent), other-assisted firms (9.4 per cent) and non-assisted firms (1.1 per cent) (χ2(2)=144.05, ρ<0.000).

Once in contact with BL, it is clear that the frequency of contacts between intensively-assisted firms and BL was, on average, greater than that for other-assisted firms (Table 3.1) (χ2(7)=76.12, ρ<0.000).

Table 3.1: Frequency Distribution of Contacts between Intensively-assisted firms

and Other-assisted firms and Business Links Intensively-

assisted firms


All Assisted

firms % % % Every week 2.6 2.1 2.3 Every fortnight 3.6 2.7 3.2 Every month 17.9 12.6 15.2 Every 3 months 28.3 19.1 23.6 Every 6 months 21.7 21.7 21.7 Once a year 12.0 21.0 16.6 Less often 11.7 17.6 14.7 (Don t know) 2.2 3.2 2.7

Source: BL Telephone Survey (2005) Differences in the type of advice received by different groups of respondents reflected these differences in contact frequency. Factual advice and basic advice were received by similar proportions of intensively-assisted firms and other-assisted firms (Table 3.2), while in-depth assistance and ‘long-term or intensive-assistance’ was received by significantly more firms in the intensively-assisted group (25-28 per cent) than by other-assisted firms (14-21 per cent).



52

Table 3.2: Intensity of Assistance Received by Intensively-assisted firms and Other-assisted firms



% % χ2(2) ρ

Factual information 40.6 42 0.467 0.494 Basic advice 47.5 48.4 0.165 0.684 In-depth advice 25.4 20.8 6.714 0.010 Long term or intensive assistance 28 14.4 63.392 0.000 Something else 10 6.9 7.344 0.007

Source: BL Telephone Survey (2005) More thematically, it is clear that during the reference period (i.e. April to September 2003) intensively-assisted firms consistently received more different types of support than other-assisted firms in the group of respondents (Table 3.3). In all cases these differences were statistically significant. For example, around 14 per cent of intensively-assisted firms reported receiving help with business benchmarking or diagnosis compared to only 7.0 per cent of other-assisted firms. Table 3.3: Proportions of Intensively-Assisted Firms and Other-Assisted Firms

Receiving Different Types of BL Services



% % t ρ General business information 57.3 56.5 0.43 0.67 Business benchmarking or diagnosis 13.6 7.0 5.17 0.00 Business planning, action plan development 39.7 23.9 8.18 0.00 Information on regulation and compliance 34.9 24.1 5.63 0.00 Help with finding external consultants 22.9 11.5 7.21 0.00 Help with raising finance 35.5 22.9 6.61 0.00 Help with making cost/quality improvements 15.4 7.8 5.63 0.00 Help with marketing 35.4 20.7 7.88 0.00 Help with R&D or NPD 12.3 9.8 1.89 0.06 Help with exporting 13.5 7.6 4.58 0.00 Help with training 41.0 30.5 5.20 0.00 Help with e-commerce 16.2 9.4 4.85 0.00 Help with IT issues 21.0 13.9 4.42 0.00 Anything else 7.0 7.3 -0.25 0.80

Source: BL Telephone Survey (2005) It might have been expected that a similar proportion of BL assistance to intensively-assisted firms and other-assisted firms would have been provided by BL staff. In fact, however, 65.2 per cent of intensively-assisted firms (79.6 per cent of other-assisted firms) reported that all of this support was provided by BL staff, with 34.8 per cent of intensively-assisted firms and 20.4 per cent of other-assisted firms reporting that some services were referred to an external party (χ

2(1)=57.99, ρ<0.000). The suggestion is that



53

external brokerage was more common in the provision of services to intensively-assisted firms. The process of brokerage may have been only worthwhile for intensive assistance or the BLO may have been capable of providing routine services. Another potentially important indicator in terms of the nature of the brokerage process is whether or not firms paid for the services being provided. Among survey respondents, around a quarter of intensively-assisted firms (27.5 per cent) and a sixth (15.5 per cent) of other-assisted firms reported paying for BL services (χ2(1)=47.2, ρ<0.000). In other words, it would appear that internal brokerage – to a fee-paying service within BL – was operating for around a quarter of intensively-assisted firms and a sixth of other-assisted firms. More surprising perhaps is that only 51.7 per cent of intensively-assisted firms and 30.6 per cent of other-assisted firms reported paying for externally referred services (χ2(1)=24.5, ρ<0.000). Therefore, considerable external brokering by BL staff was to non-fee paying services rather than market based services. Over the whole sample of BL assisted respondents, 75.6 per cent reported either being satisfied or very satisfied with the services they had received, although there was generally a higher level of satisfaction among intensively-assisted firms (χ2(4)=39.7, ρ<0.000) (Table 3.4). Satisfaction tends to decay over time so these figures are high, although repeat assistance would tend to increase the satisfaction rate by reducing the time for the decay.

Table 3.4: Satisfaction with BL Services among Intensively-assisted firms and




All Firms

% % %

1 - Very dissatisfied 5.7 5.8 5.7

2 4.6 5.1 4.8

3 10.3 17.4 13.8

4 44.1 46.4 45.3

5 - Very satisfied 35.3 25.3 30.3




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3.2 Other External Business Assistance and Support Aside from BL, around one in five respondents (20.5 per cent) reported using other external sources of information, advice or support to develop their business over the previous two years – that is in the period 2003 to 2005. This proportion was significantly different between groups of respondents (χ

2 (2) = 42.4, ρ<0.000), being highest (26.6%) among intensively-assisted firms, and lower among other-assisted (20.1%) and non-assisted firms (15.2 per cent). Table 3.5 summarises the most common forms of other business information and support, although survey respondents reported a wide variety of sources of ‘other’ advice and help.

Table 3.5: Individual Sources of Business Advice and Assistance



Non-assisted firms

All Firm

s % % % % χ2(2) ρ

An Accountant 3.4 3.3 3.2 3.3 0.043 0.979 Consultants (excl. management) 5.2 2.7 2 3.3 20.295 0.000 A Trade Association 2.7 2.5 2 2.4 1.155 0.561 A Bank 1.9 1.2 2.7 1.9 6.883 0.032 A Management Consultant 1.2 2.1 1.3 1.5 3.679 0.159 Another business owner 1.5 1.0 0.7 1.1 3.557 0.169 Chamber of Commerce 2.4 0.7 0.3 1.1 24.400 0.000 Friends or relatives 0.9 0.9 1.4 1.0 1.995 0.369 A Solicitor 1.2 0.9 0.9 1.0 1.101 0.577 Dept of Trade and Industry 1.1 0.9 1.0 1.0 0.300 0.861 Customer or Supplier 1.0 0.5 1.3 0.9 3.946 0.139 Regulatory body (e.g. HSE) 1.2 0.5 1.1 0.9 3.279 0.194 Employers federation 0.8 0.6 0.7 0.7 0.319 0.852 Enterprise Agency 0.8 1.2 0.2 0.7 8.611 0.130 Inland Revenue 0.3 0.2 0.3 0.3 0.688 0.709 Other 7.7 6.2 3.4 5.7 20.220 0.000

Source: BL Telephone Survey (2005) The key points to note are that:

• Accountants were the most common form of business advice and information for the whole group of respondents, used by 3.2-3.4 per cent of firms in all respondent groups.

• Other consultants – excluding management consultants – were also used by 3.3

per cent of the sample; their use was significantly more common, however, among intensively-assisted firms.



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• Trade associations, management consultants, banks and other business owners were the other most common sources of advice and information. Chambers of Commerce may have an organisational connection to Business Link.

Some recipients may use Business Links advice alongside other sources of support. Business Link has emphasised its brokerage aspect more and more over the period 2001 onwards. In the present study a high proportion of the assistance was provided directly by Business Link. Nevertheless, the use of external sources of advice was tested in the modelling of impact but was not significant and therefore is not part of the model presented in chapter 4. If clients did receive grants it did not seem to reveal itself in increased impact. Those Business Links that tended to provide more advice on sources of finance performed less well see pages 101 and 103.

3.3 Firm Size and Performance Sales and employment provide a basic indication of firm size and are the primary indicators reviewed here. Average employment for all respondents was 23 persons in 2004 and 24 persons in 2005 with other-assisted firms slightly larger than the mean (Table 3.6). In each group of firms median employment is below 10, suggesting that more than half of the firms in each category fall into the ‘micro’ category, i.e. those with 1-10 employees. The suggestion is of a very skewed distribution with a strong concentration among smaller companies. This table contains all the firms in the sample who provided employment and sales data and it is not recommended that the population be compared because this would be misleading. For a comparison of like-for-like see table 3.7. Table 3.6: Firm Size Distributions: Sales and Employment

Intensively assisted firms


Non-assisted firms

All Firms

Employment 2004 Mean 22.7 27.2 18.8 22.9 Median 8.0 6.0 5.0 6.0 Std

Deviation 67.892 308.739 71.542 188.673

Valid N N=1096 N=1126 N=1092 N=3314 Employment 2005 Mean 24.3 28.6 18.7 23.9 Median 9.0 6.0 5.0 7.0 Std

Deviation 69.085 332.619 71.471 201.772

Valid N N=1106 N=1128 N=1098 N=3331 Sales 2004 (000s) Mean 2,093.8 2,843.5 2,630.7 2,464.8 Median 570.0 298.0 318.3 430.6 Std

Deviation 7,528.5 18,244.3 14,116.7 13,221.9

Valid N N=507 N=318 N=410 N=1235



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Sales 2005 (000s) Mean 2,432.5 3,604.4 3,000.4 2,911.1 Median 600.0 353.4 380.8 500.0 Std

Deviation 7,967.8 20,250.1 14840.8 14,183.7

Valid N N=599 N=353 N=474 N=1425 Source: BL Telephone Survey (2005) Sales data suggests a similar picture with average sales among sample companies in the financial year 2004-5 being £2.91m. Again median sales in each group is significantly smaller (£350-600,000) suggesting a preponderance of smaller firms. Intensive-assisted firms have a median sales figure in 2004-05 of £600,000 compared to between £350-380,000 for the other groups. Mean employment growth for the sample as a whole is positive (10.4 per cent) over the 2004-2005 period with larger increases in employment in the intensively-assisted and other-assisted firms compared to non-assisted firms. Intensively-assisted firms grew more rapidly than other-assisted firms in between 2004 and 2005. Similarly, mean sales growth was strongly positive for each group with notably higher average growth for intensively-assisted firms and other-assisted firms compared to the non-assisted group. Turnover per employee – an indication of productivity – was, however, slightly lower among intensively-assisted and other-assisted firms compared to the control group of non-assisted firms (Table 3.7).

Table 3.7: Performance Indicators: Sales and Employment Growth, Sales per Employee

Intensively assisted firms


Non-assisted firms

All Firms

Employment Growth Mean 16.6 9.9 4.7 10.4 Median 0.0 0.0 0.0 0.0 Std

Deviation 69.4 43.6 26.8 50.0

Valid N N=1093 N=1122 N=1088 N=3302 Sales Growth Mean 27.2 50.9 11.2 27.7 Median 8.3 11.1 0.2 7.1 Std

Deviation 96.8 184.3 29.5 113.1

Valid N N=496 N=284 N=382 N=1161 Sales per employee Mean 106,894.9 99,388.7 123,749.9 110,635.7 Median 54,035.0 50,000.0 60,000.0 54,545.5 Std

Deviation 254,105.2 216,975.6 229,230.9 237,352.8

Valid N N=592 N=341 N=461 N=1394




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3.4 Summary The analysis of BL assistance confirmed, as expected, that the nature and extent of assistance differed markedly for the intensively-assisted and other-assisted groups. More importantly, in the context of the evolving nature of the BL local service since 2001 was the finding that external brokerage was more common in the provision of services to intensively-assisted firms. More surprising perhaps is that only 51.7 per cent of intensively-assisted firms and 30.6 per cent of other-assisted firms reported paying for externally referred services. Therefore, a considerable external brokering by BL staff was to non-fee paying services rather than market based services.

In terms of external business advice accountants were the most common form of business advice and information for the whole group of respondents, used by just over 3 per cent of firms in all respondent groups. Intensively-assisted firms were more likely to use ‘other consultants’ (excluding management consultants).

The observed differences in the performance of the assisted groups of firms and the non-assisted group were marked but must be treated with some care. There is an obvious temptation to read into these differences the effect of BL assistance but that would be methodologically flawed and misleading in terms of the implications for policy. As we have set out in Chapter 1, the evaluation methodology designed to isolate the effects of assistance are based upon an econometric approach which includes two important dimensions – a test for selection bias and the inclusion of a set of control variables (e.g., size, sector, owner-manager characteristics, strategy, innovativeness, market orientation) which may also have an impact on firm performance. The next Chapter presents the results of this approach.



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4. Assessing the Impact of Business Link

4.1 Introduction In this Chapter we provide evidence on the impact of Business Link support on both intensively-assisted firms and other-assisted firms. Section 4.2 sets out an econometric approach to the impact evaluation of BL assistance, while Section 4.3 then profiles firms’ qualitative assessment of the timing and extent of BL assistance on their business as well as the extent of additionality. Section 4.4 develops our value for money assessment. This is developed in four main stages7:

1. First, we use an econometric approach to estimate the impact and significance of BL assistance on the performance of individual intensively-assisted firms and other-assisted firms. As it turns out, BL assistance does have a significant and positive effect (2.2-2.4 per cent) on the employment growth of intensively-assisted firms.

2. Second, we scale up these impacts on individual firms to reflect the number of

firms which received intensive assistance during the reference period. This gives us the aggregate employment effect of BL assistance over the year.

3. Third, we translate this employment effect into a national value added estimate

using data from the ABI on value added per employee. This gives us the total addition to national value added due to BL support.

4. Fourth, this is then compared to the cost of the BL network to give a value for

money estimate. In assessing the results of the value for money calculation it is important to acknowledge, however, that the earlier discussion of the timing of the impact of BL support on firm performance suggests that in the majority of cases benefits are spread over some years. This has implications for the interpretation of our econometric analysis which measures the impact of BL support over an 18-24 month period. In particular, it means that our econometric analysis is likely to under-estimate the true impact of BL assistance on firm performance, a factor which is also reflected in some contrasts between our qualitative

7 Our original approach to the estimation of BL value added was slightly different, although it followed the same general pattern. In particular, we aimed initially to estimate econometrically the impact of BL on the value added created by individual firms, which would then have been grossed up to provide a national value added estimate. In the company survey, however, we only obtained complete value added information for a small number of firms (around 7% of the sample). This provided too few observations for the econometric analysis and a potentially atypical response. Our preference was therefore to use the more indirect approach of estimating employment and turnover impacts using an econometric approach, and then to use ABI data on value added per employee to allow us to calculate aggregate value added.



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and quantitative impact assessments. These issues are discussed in more detail in Section 4.4.

4.2 Impact of Business Link Assistance Two main issues arise in estimating the impact of BL assistance on an individual firm. First, as indicated in Chapter 2 the characteristics of intensively-assisted firms, other-assisted firms and non-assisted firms differ substantially suggesting that unless these differences are controlled for in the estimation any assessment of the effect of assistance is likely to be misleading. This emphasises the importance of a strongly multi-variate approach which explicitly allows for differences in the characteristics of assisted and non-assisted companies, their strategic orientations and the strengths of their owner-managers and managerial teams. Second, previous studies have also emphasised the importance of clearly identifying any selection effect to avoid any potential bias due to the selection by BL of either better or worse than average firms to assist. Addressing this latter point can be done through a two step procedure that involves the estimation of two related statistical models – a model for the probability that a firm will receive assistance and a second model relating to the effect of selection and assistance on business growth or performance. This two step approach allows an identification of the ‘selection’ and ‘assistance’ effects as well as explicitly allowing for differences between the characteristics of assisted and non-assisted firms. In setting up the modelling in this manner the significance, or otherwise, of the selection parameter allows a ‘test for selection’. The first stage is therefore the development of a series of Probit models of the probability of receiving assistance. These are reported in Tables 4.1 for intensively-assisted firms and Table 4.2 for other-assisted firms8. In each case three models are reported with slightly different specifications to give an indication of robustness, with Model 3 in each case providing the preferred model specification. Models both for the probability of receiving intensive and other assistance performed well, with high proportions of correct predictions and a number of significant variables. Key findings were:

• Limited liability firms were 28 to 36 per cent more likely to be intensively-assisted firms but other-assisted firms were no more likely to have limited liability than non-assisted firms. Legal partnerships, however, were 16 to 25 per cent less likely to be in the other assisted group than remain unassisted.

• There was no evidence that firm size was important as a determinant of the

probability of receiving either intensive or other assistance.

8 In each case sample sizes are dictated by the combined number of sample respondents of intensively-assisted firms and non assisted firms (Table 4.1) and of other-assisted firms and non-assisted firms (Table 4.2). In both tables a number of specifications are reported, some exclude insignificant variables.



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• Firms established for five years or more had a significantly lower probability of receiving intensive assistance than younger firms. Other assistance was equally common among firms less than 20 years old. Firms that were more than 20 years old were less likely to receive other assistance.

• Information sources play an important role in determining the probability that

firms fell into the groups of intensively-assisted firms or other-assisted firms. Receipt of BL mail shots, use of the BL website, direct contacts with BL, and receiving an introduction from an advisor all led to statistically significant increases in the probability of receiving both intensive and other assistance. In contrast, while receiving a referral from a friend resulted in a statistically significant increase in the probability of receiving intensive assistance, this was not the case for other assistance.

• Ethnic diversity in firms’ teams of directors had no impact on the probability of

assistance but firms with higher gender diversity among their directors were more likely to be receiving both intensive and other assistance.

• Clear patterns between industry and the probability of receiving assistance can be

identified, particularly in Model 3, which excludes insignificant industry dummies. Firms in the Agriculture, Hunting, and Forestry; Manufacturing; Construction; Transport; Real Estate; Health and Social Services; and Other Services industries all have a statistically significantly greater probability of receiving intensive assistance than other firms. In contrast, while firms in the Construction and Real Estate Industries have statistically higher probability of receiving other assistance, firms in the Retail, Wholesale; Financial Services; and Hotels and Catering industries have statistically lower probability of receiving other assistance.

In other words, younger, limited firms with boards of directors exhibiting higher gender diversity were more likely to take up intensive assistance. Other assistance was also being targeted at younger firms with statistically weaker evidence of a similar gender effect. Also, clear evidence exists that firms in different industries have different probabilities of receiving assistance. However, a clear distinction also exists between which industries are likely to receive intensive or other assistance. Finally, in both cases direct action by BL to recruit contacts seems to have substantially increased the probability of using BL services.



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Table 4.1: Probit Models of the Probability of Receiving Intensive Assistance

Coef. t-stat Coef. t-stat Coef. t-statConstant -1.770 -7.57 -1.867 -9.51 -1.850 -13.57Firm CharacteristicsLegal Partnership -0.045 -0.32Ltd Liability Company 0.282 2.39 0.361 3.95 0.358 3.95Other type of company -0.346 -0.98Multi-plant firm 0.143 1.08Firm Size (employment) -0.0002 -0.17Firm age: 3-4 years -0.347 -1.51Firm age: 4-5 years -0.146 -0.66Firm age: 5-10 years -0.477 -2.81 -0.326 -2.35 -0.330 -2.39Firm age: 10-20 years -0.323 -2.02 -0.188 -1.49 -0.196 -1.58Firm age: 20 plus years -0.753 -4.81 -0.573 -4.83 -0.582 -4.97Information Variables BL mailshots 1.573 16.70 1.566 17.02 1.562 17.01BL website 1.227 11.50 1.232 11.75 1.230 11.76BL direct contacts 0.910 8.51 0.916 8.68 0.917 8.76BL referred by friend 0.363 2.75 0.346 2.67 0.347 2.68BL referred by advisor 1.093 5.36 1.166 5.82 1.162 5.81Management TeamNumber of directors 0.045 1.55Gender diversity (%) 0.003 1.93 0.002 1.92 0.002 1.91Ethnic Diversity (%) -0.001 -0.42Industry DummiesAgriculture, hunting & forestry 0.861 3.62 0.841 3.63 0.835 4.76Fishing and related 0.609 0.70 0.603 0.70Mining and quarrying -7.941 0.00 -8.023 0.00Manufacturing 0.228 1.13 0.220 1.12 0.215 1.81Electricity and Water 0.394 0.42 0.344 0.37Construction 0.360 1.39 0.335 1.33 0.329 1.67Retail, wholesale 0.009 0.04 -0.003 -0.02Transport, storage etc. 0.499 1.66 0.506 1.72 0.499 1.98Financial Services -0.003 -0.01 -0.033 -0.08Real Estate etc. 0.320 1.59 0.330 1.68 0.324 2.64Education 0.255 0.45 0.305 0.56Health and Soc Service 0.495 1.98 0.451 1.87 0.446 2.37Other Services 0.426 1.64 0.419 1.67 0.412 2.03

N 2067 2139 2139Log Likelihood -539.67 -555.97 -556.99Chi-Squared 1786.13 1852.96 1850.92Estrella 0.710 0.711 0.709Veall/Zim 0.775 0.776 0.774% Correct 88.97 88.59 88.50

Model 1 Model 2 Model 3

Notes: Hotels and Catering is the excluded Industry Dummy in Models 1 and 2; Chi-Squared Statistic Indicates that ρ<0.000 in all models; Coefficients values reported are marginal values computed at variable means; Marginals for Dummy Variables relate to the impact of a change from 0 to 1.



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Table 4.2: Probit Models of the Probability of Receiving Other Assistance

Coef. t-stat Coef. t-stat Coef. t-statConstant -1.463 -6.82 -1.590 -9.42 -1.327 -14.84Firm CharacteristicsLegal Partnership -0.255 -2.01 -0.174 -1.66 -0.161 -1.56Ltd Liability Company -0.099 -0.99Other type of company -0.192 -0.62Multi-plant firm 0.038 0.31Firm Size (employment) 0.000 -0.10Firm age: 3-4 years 0.015 0.07Firm age: 4-5 years -0.146 -0.66Firm age: 5-10 years -0.089 -0.55Firm age: 10-20 years -0.099 -0.64Firm age: 20 plus years -0.464 -3.09 -0.377 -4.55 -0.376 -4.58Information Variables BL mailshots 1.730 19.93 1.720 20.31 1.719 20.38BL website 1.186 11.91 1.185 12.15 1.176 12.14BL direct contacts 0.601 5.66 0.610 5.83 0.603 5.78BL referred by friend 0.153 1.13 0.211 1.59 0.211 1.59BL referred by advisor 0.583 2.67 0.591 2.73 0.612 2.85Management TeamNumber of directors 0.026 0.94Gender diversity (%) 0.001 1.05 0.002 1.54 0.002 1.68Ethnic Diversity (%) 0.000 0.07Industry DummiesAgriculture, hunting & forestry 0.393 1.71 0.402 1.79Fishing and related -0.059 -0.06 -0.008 -0.01Mining and quarrying -0.426 -0.31 -0.416 -0.31Manufacturing 0.172 0.94 0.198 1.12Electricity and Water -5.688 0.00 -5.684 0.00Construction 0.575 2.60 0.574 2.66 0.311 1.93Retail, wholesale -0.043 -0.24 -0.015 -0.09 -0.281 -2.82Transport, storage etc. 0.345 1.24 0.381 1.38Financial Services -0.457 -1.02 -0.488 -1.12 -0.753 -1.83Real Estate etc. 0.416 2.31 0.454 2.61 0.189 1.80Education 0.524 1.19 0.553 1.28Health and Soc Service 0.259 1.08 0.226 0.99Other Services 0.326 1.38 0.345 1.49Hotels, catering -0.268 -1.64

N 2086 2167 2167Log Likihood -633.75 -656.72 -658.24Chi-Squrared 1624.23 1690.66 1687.61Estrella 0.662 0.662 0.661Veall/Zim 0.739 0.739 0.738% Correct 87.87 87.72 87.82

Model 1 Model 2 Model 3

Notes: Hotels and Catering is the excluded Industry Dummy in Models 1 and 2; Chi-Squared Statistic indicates that ρ<0.000 in all models; Coefficients values reported are marginal values computed at variable means; Marginals for Dummy Variables relate to the impact of a change from 0 to 1.



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The impact of this assistance is then reflected in OLS models for employment, sales and labour productivity growth (i.e. growth in sales less growth in employees). These models take a semi-log form to correct for the highly skewed distribution of growth rates, a form which also allows a ready interpretation of the coefficients. For continuous variables a unit increase in the variable leads to a percentage point increase in the growth rate which is 100 time the coefficient. That is, a coefficient of 0.03 implies an increase in the growth rate of 3 per cent for a unit increase in the explanatory variable. For dummy variables (which take the value 1 if a firm has a specific characteristic or zero otherwise), 100 times the coefficient reflects the percentage point increase in the growth rate due to moving from a value 0 to value 19. Selection effects are generally weak and for intensively-assisted firms take varied signs. For other-assisted firms signs are always positive suggesting the selection for assistance of better than average firms. The lack of significance of the selection variables suggests that the models could be run without selection. Accordingly the selection models are in the appendix D and the reported models are using OLS with no selection. Models compare the impact of either intensive assistance versus no assistance or other assistance versus no assistance. Tables 4.3 and Tables 4.4 respectively report models for intensively-assisted and other-assisted firms that include a wide array of potential determinants of employment, sales, and labour productivity growth. In contrast, Tables 4.5 and 4.6 report preferred specifications after the removal of extraneous variables with little to no explanatory power. The models report the determinants of performance in intensively-assisted firms and non-assisted firms (Tables 4.3 and 4.5) and other-assisted firms and non-assisted firms (Tables 4.4 and 4.6) in both cases against the no assistance category. The key variables of interest are the assistance parameters which give the ‘assistance’ effect. The key results from the estimations are as follows:

• Intensive assistance is found to have a positive and significant impact on employment growth increasing firms’ employment growth rate by 2.4 percentage points.

• Intensive assistance has a positive but insignificant effect on firms’ sales growth,

increasing sales growth by 2.8 percentage points.

• Intensive assistance has a negative but statistically insignificant effect on firms’ labour productivity, decreasing productivity growth by 1.2 percentage points.

• Other assistance is found to have a positive but statistically insignificant effect on

employment growth, increasing employment growth by 0.8 percentage points..

9 See Barkham et al,. (1996), pp. 32-40 for a detailed discussion of this form of model in the context of small business growth.



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• Other assistance is found to have a positive but statistically insignificant effect on sales growth, increasing sales growth by 4.2 percentage points.

• Other assistance has a positive but statistically insignificant effect on firms’

labour productivity, increasing productivity growth by 5.0 percentage points.

Other factors also prove important, however, in the determination of employment, sales and productivity growth. :

• Firm age has statistically significant impact on growth. Firms aged more than 10 years are found to have significantly lower employment, sales, and productivity growth, and these effects are particularly significant in the intensively-assisted models. While not as strongly evident as in the intensively-assisted models, the other-assisted models suggests that firms aged 3-4 years have significantly higher sales growth (Table 4.5 and Table 4.6). Since Business Links are working with younger firms then that suggests that Business links are working with firms that are more likely to grow.

• That firm size is not significant may in part be due to the sampling strategy that

matched firms on size.

• Firms with limited liability are found to have more rapid employment growth in the other-assisted firms model but this growth is restricted by statistically significant market factors related to high numbers of competitors and less significantly in markets where firms’ own price elasticity is high (Table 4.6). The level of price competition is an indicator that growth is ‘harder to come by’ and is more likely to give rise to displacement effects.

• Own Price elasticity has a negative and statistically significant effect on both the

sales and productivity growth in the other assisted firms model. (Table 4.6) This effect is also evident for productivity growth in the intensively-assisted firms’ model, but is statistically insignificant (Table 4.5)10.

• Multi-plant firms are found to have significantly higher employment growth in

the other-assisted models (Table 4.6). Although this effect is evident for intensively-assisted firms in the full model reported in Table 4.3, it becomes statistically insignificant and is not included in the preferred specification reported in Table 4.5.

• Several strategy focus variables proved to be important and statistically

significant. Both models suggest that employment growth is faster in firms that

10 No significant effects were evident in any of the growth models from a variable reflecting cross-price elasticities. This variable was, therefore, dropped from the models reported.



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focus on developing sales growth in their current markets. However, this strategy has a negative impact in the other-assisted model. (Tables 4.5 and 4.6).

• In contrast, a strategy focused on sales in new markets was found to have a

consistent positive statistically significant impact on sales and productivity growth in both models. (Tables 4.5 and 4.6). This suggested that the promotion of sales in new markets both increased the productivity of firms and sales growth as such this strategy may increase labour productivity significantly. At the same time the own-price elasticity suggests that competing on price is ‘bad’.

• Business planning has a positive statistically significant effect on employment

growth for intensively-assisted firms (Table 4.5).

• Firms with owner managers aged 55 or older are found to have significantly lower employment growth but (insignificant) faster productivity growth (Table 4.5)

• In the other-assisted models, evidence is found to support a positive relationship

between sales and productivity growth and Owner Managers who have founded multiple companies. (Table 4.6).



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Table 4.3: Impact of Intensive Assistance versus No Assistance: Full Model Excluding Selection Effects

Employment

Growth Sales

Growth Productivity

Growth Coeff t-stat Coeff t-stat Coeff t-stat

Constant 0.009 0.351 -0.034 -0.482 -0.027 -0.347 Firm Characteristics Firm Size 0.000 -0.544 0.000 -0.202 0.000 0.769 Size squared 0.000 0.273 0.002 0.844 0.000 -0.008 Firm age: 3-4 years -0.023 -1.265 0.039 0.821 0.009 0.165 Firm age: 4-5 years -0.013 -0.766 0.022 0.488 0.010 0.200 Firm age: 5-10 years -0.009 -0.647 -0.011 -0.314 -0.051 -1.237 Firm age: 10-20 years -0.015 -1.114 -0.049 -1.397 -0.068 -1.694 Firm age: 20 plus years -0.023 -1.698 -0.052 -1.464 -0.057 -1.400 Legal Partnership 0.009 0.742 0.024 0.772 0.021 0.614 Ltd Liability Company 0.013 1.328 0.029 1.107 0.012 0.436 Other type of company 0.003 0.088 -0.013 -0.155 -0.001 -0.015 Multi-plant firm 0.029 2.572 -0.019 -0.697 -0.025 -0.813 Exporter 0.000 -0.022 0.004 0.182 0.018 0.801 Market Characteristics No. of competitors -0.009 -1.128 -0.008 -0.415 0.027 1.367 Own Price Elasticity -0.006 -0.488 -0.020 -0.670 -0.048 -1.505 Business Strategy Focus: Sales in current markets 0.024 3.129 -0.006 -0.339 -0.013 -0.636 Focus: Sales in new markets 0.017 1.592 0.077 3.403 0.048 1.963 Focus: New products, new markets 0.012 0.864 -0.010 -0.319 -0.019 -0.534 Formal Business Plan 0.026 3.212 0.007 0.377 -0.031 -1.472 Non-executive Directors -0.004 -0.356 0.030 1.046 0.017 0.528 Owner Manager O-M has equity 0.001 0.120 0.033 1.196 0.019 0.642 O-M age 25-34 0.020 0.970 0.044 0.822 0.015 0.260 O-M age 35-44 0.003 0.183 0.017 0.399 0.018 0.413 O-M age 45-54 -0.006 -0.336 0.044 1.094 0.057 1.345 O-M age 55 plus -0.016 -0.907 0.021 0.513 0.045 1.060 Serial Founder -0.003 -0.341 0.013 0.734 0.013 0.656 Intensively-Assisted Firms 0.022 2.831 0.028 1.432 -0.012 -0.577

Note: Models Also Include a Full Set of Industry Dummies to Control for Industry Specific Differences in employment, turnover, and productivity growth. Models with selection effects are included in Table 4.3.



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Table 4.4: Impact of Other Assistance versus No Assistance: Full Model Excluding Selection Effects

Employment

Growth Sales

Growth Productivity


Constant 0.030 1.338 0.106 1.247 0.020 0.222 Firm Characteristics Firm Size 0.000 -0.666 0.000 -1.479 0.000 -0.281 Size squared 0.000 0.732 0.000 1.219 0.000 0.012 Firm age: 3-4 years -0.003 -0.169 0.101 1.668 0.117 1.687 Firm age: 4-5 years 0.000 0.020 0.008 0.128 0.058 0.855 Firm age: 5-10 years -0.008 -0.592 -0.030 -0.588 0.047 0.803 Firm age: 10-20 years -0.013 -1.048 -0.051 -1.032 0.028 0.495 Firm age: 20 plus years -0.022 -1.831 -0.076 -1.495 -0.001 -0.022 Legal Partnership 0.006 0.602 -0.007 -0.195 0.004 0.106 Ltd Liability Company 0.019 2.334 0.036 1.236 0.005 0.157 Other type of company -0.025 -1.023 -0.090 -0.943 -0.070 -0.679 Multi-plant firm 0.027 2.650 0.058 1.573 0.028 0.708 Exporter 0.003 0.382 -0.021 -0.729 -0.026 -0.854 Market Characteristics No. of competitors -0.013 -1.996 -0.006 -0.277 0.024 0.951 Own Price Elasticity -0.023 -1.854 -0.102 -2.410 -0.084 -1.919 Business Strategy Focus: Sales in current markets 0.017 2.524 -0.045 -1.918 -0.063 -2.542 Focus: Sales in new markets -0.008 -0.710 0.057 1.878 0.077 2.345 Focus: New products, new markets 0.030 2.266 -0.072 -1.604 -0.065 -1.315 Formal Business Plan 0.001 0.126 0.035 1.382 -0.005 -0.175 Non-executive Directors 0.004 0.342 -0.012 -0.347 -0.001 -0.018 Owner Manager O-M has equity -0.021 -2.014 0.019 0.553 0.030 0.810 O-M age 25-34 0.011 0.649 -0.005 -0.080 0.007 0.110 O-M age 35-44 0.017 1.190 -0.005 -0.109 -0.012 -0.249 O-M age 45-54 0.013 0.967 0.019 0.411 -0.009 -0.188 O-M age 55 plus 0.000 0.013 0.010 0.213 0.021 0.434 Serial Founder 0.009 1.256 0.028 1.187 0.044 1.747 Other-Assisted Firms 0.008 1.177 0.042 1.705 0.050 1.902

Note: Models Also Include a Full Set of Industry Dummies to Control for Industry Specific Differences in employment, turnover, and productivity growth. Models with selection effects are included in Table 4.4.



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Table 4.5: Impact of Intensive Assistance versus No Assistance: Restricted Models Excluding Section Effects

Employment

Growth Sales

Growth Productivity


Constant 0.009 1.111 0.040 0.904 0.020 0.443 Firm Characteristics Firm age: 5-10 years -0.055 -1.955 Firm age: 10-20 years -0.014 -1.683 -0.061 -3.275 -0.068 -2.581 Firm age: 20 plus years -0.021 -2.777 -0.070 -3.777 -0.060 -2.294 Market Characteristics No. of competitors -0.019 -1.251 0.027 1.472 Own Price Elasticity -0.041 -1.435 Business Strategy Focus: Sales in current markets 0.022 3.360 Focus: Sales in new markets 0.072 3.771 0.042 1.868 Formal Business Plan 0.031 4.558 Non-executive Directors 0.037 1.551 Owner Manager O-M has equity 0.032 1.436 O-M age 45-54 -0.014 -1.928 0.038 1.922 O-M age 55 plus -0.019 -2.332 0.030 1.320 Intensively-Assisted Firms 0.024 3.543 0.029 1.849 -0.020 -1.139

Note: Models Also Include a Full Set of Industry Dummies to Control for Industry Specific Differences in employment, turnover, and productivity growth. Models with selection effects are included in appendix D.



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Table 4.6: Impact of Other Assistance versus No Assistance: Restricted Models Excluding Section Effects

Employment

Growth Sales

Growth Productivity


Constant 0.040 2.530 0.090 1.906 0.072 1.497 Firm Characteristics Firm age: 3-4 years 0.101 2.471 0.075 1.720 Firm age: 10-20 years -0.013 -1.717 -0.038 -1.501 Firm age: 20 plus years -0.022 -2.852 -0.048 -1.975 Ltd Liability Company 0.016 2.458 Multi-plant firm 0.025 2.616 Market Characteristics No. of competitors -0.014 -2.144 Own Price Elasticity -0.021 -1.777 -0.115 -3.174 -0.094 -2.502 Business Strategy Focus: Sales in current markets 0.020 3.045 -0.048 -2.277 Focus: Sales in new markets 0.073 2.776 0.079 2.788 Formal Business Plan 0.031 1.484 Owner Manager O-M has equity -0.013 -1.359 O-M age 55 plus -0.013 -1.670 Serial Founder 0.041 1.982 0.056 2.510 Other-Assisted Firms 0.008 1.295 0.037 1.746 0.040 1.855

Note: Models also include a full set of Industry Dummies to Control for Industry Specific Differences in employment, turnover, and productivity growth. Models with selection effects are included in Table 4.6

One interesting question here is why BL assistance was having a larger short-term effect on employment growth than it was on sales. One possibility – found in both the innovation (e.g. Love and Roper, 2005) and small business research literatures (e.g. Roper and Hewitt-Dundas, 2001) - is a type of restructuring effect in which assistance encourages the firm to explore new opportunities which require new employees, but which take some time to have a sales or productivity benefit11. If this was the case, the initial effect observed would be employment growth with subsequent productivity growth as the opportunity developed. If BL assistance – particularly intensive assistance – was encouraging firms to adopt this type of development path the observed effects would be anticipated. Of course, this also means that our estimates based on the impact of assistance over an 18-24 month period are also likely to underestimate the longer-term benefits of each project.

11 See Roper, S and Hewitt-Dundas, N (2001) ‘Grant Assistance and Small Firm Development in Northern Ireland and the Republic of Ireland’, Scottish Journal of Political Economy, 48, 1, 99-117. Love, J H and Roper, S (2005) ‘Innovation, Productivity and Growth: An Analysis of Irish Data’, Presented at the EARIE Annual Congress, Porto.



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4.3 Perceived Impact of Business Link Assistance Three factors are considered here. First, we are interested in behavioural additionality, i.e. the extent to which BL assistance was significant or crucial in changing the way in which the firm does business. This is important because it is these changes in behaviour or capability which, in the longer term, will lead to improvements in growth and performance. Secondly, we are interested in firms’ view of the time-horizon over which the benefits of BL assistance will impact on firm performance. As suggested earlier this is important in terms of our understanding of our modelling of the impact of BL assistance. Finally we consider additionality and firms’ qualitative assessment of the performance impact of BL support. As part of the survey firms were asked about two levels of behavioural impact12. First, firms were asked whether as a direct result of receiving BL services certain changes in capability or operations had been made. In this case BL support may have been one factor among many causing the change to take place. Second, firms were asked whether BL was the critical factor in leading to change. Table 4.7 summarises firms’ responses, giving the proportion of firms in the intensively-assisted firms and other-assisted firms groups experiencing each type of change, and the proportion of those firms suggesting that BL support was the crucial factor in levering behavioural change.

12 This analysis is based on questions C11a and C11b (see Appendix A) with firms allowed to select one or more effects as appropriate.



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Table 4.7: Assisted Firms’ Perceptions of the Impact of Business Link Services



% % t ρ Part A: BL Services Important for Change (% of all respondents) More inclined to use external support services 28.69 16.59 6.84 0.000 More inclined to use specialist consultants 29.69 15.66 7.95 0.000 Image of business has improved 39.61 25.45 7.16 0.000 Technical capability has improved 17.98 12.98 3.23 0.001 Financial management has improved 28.51 19.12 5.20 0.000 Better at planning 39.93 27.08 6.44 0.000 Export capacity has improved 13.65 7.60 4.64 0.000 Financial sourcing has improved 32.20 16.98 8.39 0.000 Regulation and compliance capability has improved 33.09 19.67 7.20 0.000 Invested more in training 30.43 19.13 6.18 0.000 Increased innovation capability 21.02 11.95 5.74 0.000 Improved product or service quality 25.10 14.77 6.11 0.000 Part B: BL Assistance Critical to Change (% of those experiencing change) More inclined to use external support services 65.53 51.63 3.03 0.003 More inclined to use specialist consultants 67.36 54.80 2.72 0.007 Image of business has improved 75.99 60.43 4.28 0.000 Technical capability has improved 71.43 49.57 4.02 0.000 Financial management has improved 71.37 59.14 2.81 0.005 Better at planning 71.70 57.44 3.92 0.000 Export capacity has improved 74.29 67.69 1.06 0.292 Financial sourcing has improved 68.05 60.06 1.79 0.074 Regulation and compliance capability has improved 69.67 62.18 1.79 0.073 Invested more in training 76.23 59.73 3.91 0.000 Increased innovation capability 63.73 49.87 2.55 0.011 Improved product or service quality 67.30 56.23 2.28 0.023

Source: BL Telephone Survey (2005) In each category, a higher proportion of intensively-assisted firms identify changes in behaviour influenced by BL than other-assisted firms. Given the profile of assistance discussed earlier this is not perhaps surprising. Importantly, however, nearly a third of intensively-assisted firms – and nearly a fifth of other-assisted firms – reported that they were more inclined to use external support services as a result of their support from BL. The most commonly reported impacts of BL assistance were on company image (40 per cent of intensively-assisted firms, 25 per cent of other-assisted firms), planning capability (40 per cent and 27 per cent) and firms’ ability to deal with regulation and compliance (33 per cent and 20 per cent). Least common were effects on export capability (13 per cent and 7 per cent) and technical capability (17 per cent and 13 per cent). Of those firms identifying changes as a result of BL assistance, around two-thirds of intensively-assisted firms and 55 per cent of other-assisted firms identified BL as the



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crucial factor in levering behavioural change within the firm. In each case BL assistance was identified as the crucial influence by a significantly higher proportion of firms in the intensively-assisted group (Table 4.7, part B). This type of behavioural change is important but will take some time to impact on firm performance. To help to gauge these time-lags firms were asked about the time horizon over which they expected their performance to reflect the benefits from BL assistance received during the previous two years. These profiles differed significantly between intensively-assisted firms and other-assisted firms (χ2(7)=70.93, ρ<0.000). Around half of firms, a slightly larger proportion of other-assisted firms, reported already having experienced all of the benefits; the remainder expected the benefits to accrue over future years. Notably, 7.2 per cent of intensively-assisted firms expected the full benefit of BL assistance to take five years or more to be realised (Table 4.8) Table 4.8: Time Horizons for Experiencing the Benefits of BL Assistance



All Firms

% % %

You have already realised all the benefits 48.1 51.7 49.9

You expect to realise all the benefits in the next year 13.3 14.1 13.7

You expect to realise them in the next 2 years 13.2 7.2 10.2

In the next 3 years 3.0 2.0 2.5 In the next 4 years 1.0 .5 .8 In the next 5 years 1.5 1.1 1.3 Or it will take more than 5 years to fully realise all the benefits of BL support 7.2 2.6 4.9

(No benefits experienced from Business Link support) 12.7 20.8 16.8

Source: BL Telephone Survey (2005) An additional approach to assessing the perceived impact of BL assistance is the standard additionality approach, designed to investigate whether additionality was ‘full’, or ‘partial’ (Table 4.9)13. Responses were again significantly different between intensively-assisted firms and other-assisted firms (χ

2(5)=101.8, ρ<0.000):

• 23 per cent of intensively-assisted firms and 36 per cent of other-assisted firms reported that the same business achievements would have been made without BL assistance – i.e. total deadweight.

13 This is based on the responses to survey question C20, See Appendix A.



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• 25 per cent of intensively-assisted firms and 20 per cent of other-assisted firms

said outcomes would have been the same without assistance but BL assistance helped to accelerate business development.

• Remaining firms (40 per cent of intensively-assisted firms and 25 per cent of

other-assisted firms) reported business outcomes which, without BL assistance, they would not have achieved.

• A relatively high proportion of firms (16 per cent) provided no response to this

question (or responded ‘none of these’). This may reflect the lack of any short-term impact on performance in some cases as suggested by Table 4.8.

Table 4.9: Additionality of Business Link Assistance Additionality Question Response Intensively-

assisted firms


All Firms

% % %

Deadweight We would have achieved similar business outcomes anyway 23.2 36.3 29.8

Partial Additionality

We would have achieved similar business outcomes, but not as quickly 25.1 19.6 22.3

We would have achieved some but not all of the business outcomes 27.3 17.0 22.0

Full Additionality

We probably would not have achieved similar business outcome 9.6 5.2 7.4

We definitely would not have achieved similar business outcomes 2.6 2.4 2.5

No Response (None of these) 12.3 19.6 16.0 Source: BL Telephone Survey (2005)

4.4 Assessing the Economy-wide Impact of Business Link Assistance As indicated earlier, our preferred approach to estimating the economy-wide effects of BL was to estimate the impact of BL assistance on value added at company level and then to scale this to reflect the number of BL interventions in the given period. The weakness of the survey response to the GVA questions, however, rendered this approach infeasible and potentially misleading. The econometric analysis of the previous section, however, does suggest that BL intensive assistance had a statistically significant and



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positive effect employment growth. More specifically, the models suggest that employment growth in intensively-assisted firms is 2.2 – 2.4 percentage points higher than that in the absence of assistance. Other effects reflected in the equations were also positive but were statistically insignificant – i.e. we cannot be confident that these effects were statistically different from zero. In particular, the point estimate of the impact on sales was insignificant suggesting a positive but heterogeneous impact of Business Link on sales. We therefore base our estimates of BL impact on the positive and significant employment growth effects identified. As suggested by the econometric models, these positive and significant effects relate solely to the group of intensively assisted firms. In taking this approach to the value for money estimate, we make an assumption that firms do not create jobs without the real prospect of future sales implicitly accepting that there is a type of restructuring effect in which assistance encourages the firm to explore new opportunities which require new employees, but which take some time to have a sales or productivity benefit14 see page 69. To estimate the economy-wide benefits of BL assistance on this basis requires three additional steps:

• Increments to employment growth based on the models in Tables 4.5 and 4.6 are converted into absolute employment gains. These are positive and statistically robust only for intensively-assisted firms.

• These estimates are then grossed up to national scale based on the number of

interventions with intensively-assisted firms.

• These employment impact estimates are translated into value added using ratios of value added per employee derived from the ABI.

These steps are reported in Table 4.10 which also gives the standard 95 per cent confidence interval attaching to each estimate.

14 See Roper, S and Hewitt-Dundas, N (2001) ‘Grant Assistance and Small Firm Development in Northern Ireland and the Republic of Ireland’, Scottish Journal of Political Economy, 48, 1, 99-117. Love, J H and Roper, S (2005) ‘Innovation, Productivity and Growth: An Analysis of Irish Data’, Presented at the EARIE Annual Congress, Porto.



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Table 4.10: National Impact Estimates for Business Links Unrestricted Model Restricted Model Notes Lower Mid Upper Lower Mid Upper Average level of employment 1 22.7 22.7 22.7 22.7 22.7 22.7 Average growth increment 2 0.7 2.2 3.7 1.0 2.4 3.8 Implied additional employment per firm 3 0.15 0.50 0.84 0.23 0.54 0.86 Number of assisted firms 4 4983015 49830 49830 49830 49830 49830 Total Employment Effect 5 7475 24915 41857 11461 26908 42854 GVA per employee (£000pa) 6 27990 27990 27990 27990 27990 27990 Total value added (£m) 7 209 697 1172 321 753 1199 Total Cost of BL p.a. 300 300 300 300 300 300 Net value added -91 397 872 21 473 899

Notes and Sources:

1. Mean employment in intensively-assisted firms (2003-04 business year. Source: Table 3.6). 2. Average employment growth increment implied by employment growth models and upper

and lower confidence interval limits (pp). Sources: Tables 4.5 and 4.6. 3. Average increment to employment per enterprise. Product of (1) and (2). 4. Number of intensively assisted firms per year. Source: BLOs. 5. Total employment effect. Product of (3) and (4). 6. GVA per employee in 2003 (£000pa), UK mean. Source: ABI. 7. GVA effect (£m pa). Product of (5) and (6).

This suggests that over the 2004-05 business year intensive BL assistance nationally increased employment by between 24,915 and 26,908. This additional employment generated value added of between £697 and £753m. Two factors have to be borne in mind in considering these estimates, however. First, they are subject to relatively wide confidence intervals, reflecting the coefficient standard errors in the equations. These are detailed in Table 4.10. Second, these figures probably under-estimate the overall impact of BL due to:

15 This figure is based on the broad definition of intensive assistance which would have been in operation at the time of the BL interventions between April and September 2003 (it was defined as "significant" interventions and therefore easier to achieve than the current definition of intensive). The SBS monitoring statistics estimate the number of intensively-assisted firms to be 49,830 in the period April 2003 to March 2004. The number of intensively-assisted firms obtained from the 43 BLOs as part of this evaluation study totaled 22,154 for the 6 month period April to September extraction exercise for the research team. The SBS Management Information figure for the year 2004-2005 is around 39,000 when the new definition is in common usage across the BLO network.



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• The exclusion of any positive multiplier effects which may stem from the additional demand generated by more rapidly growing employment. On the other hand the figures are not subject to displacement, either in part because the absence of own price elasticity suggests that the firms were operating in less competitive markets where displacement was likely to be low.

To provide an indication of the robustness of these estimates it is possible to derive a ‘break-even’ scenario given the value added per employee figures in Table 4.10. Given these figures, and the costs of the BL service, suggests that the level of job creation for break-even (i.e. the gains from BL assistance equalling the cost) would be job creation of around 10,700 or 39-43 per cent of the central point estimates for job creation. The implication is that even if the models over-estimated the average level of job creation by a significant margin BL assistance would still generate positive value added. In fact, as suggested earlier, our approach is actually likely to underestimate the job creation benefits of BL assistance due to gains occurring after the sample period. 4.5 Costs of Business Link Using the quarterly financial returns for the Business Link Organisations (BLO) the total cost of Business link can be calculated. The quarterly returns report the income from seven different sources which are listed down the left-hand side of table 4.11. Table 4.11 shows the actual income for the BLOs for the 6 month period of the study April – September 2003. Table 4.11: Income of 43 Business Link Organisations: 2003 Source Income for 43 BLOs

£s SBS

68,409,792.20

British Trade International

4,886,623.20

European Union and Single Regeneration Budget

26,816,479.15

Learning and Skills Councils

19,809,924.99

Regional Development Agencies

18,607,939.97



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Others 9,033,691.98 Total 147,564,451.49 Using the quarterly financial returns for the BLOs (all except Humberside) the total income for the 43 BLOs (from SBS, British trade international, EU & SRB, LSC, RDA and others) for the six months April - September 2003 can be derived see Table 4.11. In addition, since Humberside is not included estimates for Humberside may be derived on two different assumptions: either

1. Humberside is estimated as an average of BLOs (but remember London skews the average)

2. Humberside is estimated by the proportion of the average contact rate that they

have (74.79%)

• under 1 the total figure comes to £150,996,182.90 • under 2 the total figure comes to £150,131,043.40

(Note: 1 is probably an overestimate because of the London effect)

Consequently the cost of the BLO network for six months is approximately £150m. The value added was calculated on an annual basis so the six month value added would be halved. If we then compare the cost to the value added at a midway point between the two estimates (which may in turn be underestimates) – that is, £725m, then the value-added for the 6 month period is £362.5m and so for every £1 spent by the public authorities through the BLO network (including EU, SRB etc) would generate £2.26 of value. In terms of cost per job, if we take the average of the mid-estimates of jobs created from the restricted and unrestricted models as 25,911 then the total cost excluding customer fees is £11,578. 4.6 Displacement Issues Our micro-econometric approach to estimating the effects of Business Links assistance concentrates on the direct impact on recipients; however, given that we find a significant impact on the recipients of Business Link assistance, to what extent does this impact on those firms that do not or cannot avail themselves of Business Link services? This is reflected in the notion of Displacement which is the potentially negative impact on non-recipients of Business Link services as the competitiveness of Business Link recipients increases16. Displacement is not reflected directly in our econometric analysis which focuses instead on the impact on individual recipients, but there are good grounds for thinking that the displacement effects of BL assistance are likely to be relatively minor. The critical

16 The positive impact on non-recipients, through increased demand in the supply chain, for example, is called the multiplier and we do not estimate multipliers in the econometrics either.



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element of any discussion concerning displacement of Business Link assistance relates to our understanding the competitive environment of those small firms helped by this scheme. Three factors are important here: the general dynamics of the small business sector (‘churn’) which suggests that any displacement effect from Business Links is likely to be relatively small compared to the overall level of market dynamics and may indeed be positive; the location of firms’ competitors; and the nature of price competition in the SME markets. First, within the small firm sector there is a great deal of churn. Typically one-in-ten firms enters or exits a market in any one year, although the smallest, newest companies are most at risk (Disney et al., 2003a). Moreover, the same research shows that much of the growth in productivity comes from the opening and closing of plants (Disney et al., 2003b) Accordingly policymakers have recognised ‘productive churn’ where more productive firms displace the less productive leading to an increase in industry productivity. Insofar as Business Link helps predominantly new firms then it may contribute to productive churn (see Table 2.2). Where Business Link helps predominantly high productivity firms to grow then it contributes to productivity; however, our evidence suggest that Business Link was not helping the most productive firms, (Table 3.7). Two points are important here. First, any displacement resulting from the positive effects of Business Link support is likely to be relatively minor compared to that in the small business sector as a whole. And, secondly, any such effects may be positive for productivity as more productive Business Link assists displace less efficient competitors. Second, we would expect that any displacement effects from BL assistance would be greater where a firm’s competitors were local. Data from our survey, however, in response to a question asking ‘if your business were to cease trading tomorrow, who do you think would take up sales? Would it mainly be competitors based locally?’, suggests that just under half of those surveyed thought that local competitors would take up their customers if they were to cease trading. This is likely to mean that any displacement effects from BL assistance are likely to be geographically dispersed minimising any local impact. More generally, almost 90 per cent of assisted firms highlighted UK based competitors who would take up their market in a situation of closure. At this level therefore there is more evidence that displacement may be an issue. The positive aspects of this type of potential churn have already been highlighted however. Notwithstanding this descriptive data, the most important piece of evidence on displacement comes from the impact of price changes. In this respect we would expect small firms to create relatively little displacement. First, small firms are unlikely to make any impact on the local labour market in the form of increases in wages within the region. Further, in the firm growth models the ‘own price elasticity’ co-efficient was not significant suggesting that the influence of small firms’ price changes in the markets was muted. Combining the conceptual argument and the empirical data it is unlikely that the subsidised support from Business Link can aid a firm to reduce prices and ‘hurt’ their competitors, unfairly.



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Overall, therefore, our view is that the extent of any displacement from BL assistance is unlikely to be significant either at local or national level. The small firm context is one where there is a great deal of churn. Business Link advisory services are inevitably involved in that churn. Nonetheless, Business Link firms are younger than average and more likely to be limited companies; the firms that Business link help are less likely to be competing solely with other local firms; the nature of competition is non-price, and the firms are too small to make any impact on local labour markets.

4.7 Summary In this chapter we estimate the value for money of BL using data on interventions during the 6 month period from April to September 2003 and its impact over the subsequent business year. We differentiate in the analysis between the impact on intensively-assisted firms and other-assisted firms, something which proves important in our econometric modelling of the impact of BL assistance on individual firms. In particular, our modelling – based on a two-stage Heckman approach which allows for selectivity – suggests that while BL assistance has a range of positive impacts on sales growth and productivity (sales per employee) these effects are generally statistically insignificant. More robust is the effect of intensive BL assistance on employment growth, which is statistically significant and positive. This effect provides the basis for our subsequent value for money calculations. Our central estimates are that this BL assistance generated £697-£753m of additional value added on an annualised basis although these estimates are subject to fairly wide confidence intervals (see Table 4.10). Value for money reflects both the value added generated net of the cost of operating the BL network. We estimate the overall cost of operating the network for six months at around £150m based on the income of BLOs from different sources. Comparing this cost to the mid-point of our two value added estimates suggests that over a six-month period additional value-added is £362.5m, and so every £1 spent by the public authorities (including EU, SRB etc) would generate £2.26 of value17 discounted over two years.

17 The benefits have been discounted using the Treasury discount rate of (1.035)2 over two years



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5. The Effectiveness of Alternative BLO Delivery Models

5.1 Introduction The organisation of BLOs is a critical factor in understanding the way they operate. Rather than having a hierarchical approach where a central authority has local branches (like Scottish Enterprise) SBS created a franchise structure to enable local partnerships to use their local knowledge. The model was always an unusual franchise because rather than adopt a tried and tested business model the franchisees were individual local partnerships that created best practice (Mole, 2002). This was a deliberate and considered choice to enable ‘local solutions for local needs’. Thus, rather than being able to be controlled, the franchise structure means that the BLOs are facilitated. Whereas branches of Scottish Enterprise are headed by a manager, the BLOs are headed by a CEO. The CEO has more ‘room for manoeuvre’ to find new sources of income and strands of business. To this end BLO CEOs are relatively free in comparison with a local branch of an executive agency (c.f. Scottish Enterprise). This enables them to pursue partnerships and build relationships within their local areas including in sub-regional partnerships. 5.2 Previous Categorisations of BLOs There have been a number of different categorizations of BLOs. These categorizations tend to focus on one particular aspect: geography, income and governance . These three foci are not independent of each other. Thus governance and geography have an effect on income and vice versa.

Geography The environment is the structure within which each BLO find themselves so that clusters have been undertaken on the basis of geography including: income per head; manufacturing/services, urban/rural, size of firm (Dale, SBS). Bennett et al., (2001) suggest that rural services have most impact. There has been a long tradition of using this classification from the TEC clusters to Business Links. The Business Link Tracker study (Roper, et al., 2001) used the TEC clusters and the Business link clusters are used in monitoring information. Income sources Many of these sub-regional relationships are motivated by the search for income. Accordingly, BLOs have also been classified on the basis of their income sources, particularly on the major sources of their income from SBS, EU, LSC, RDAs and clients (SBS). Since funds tend to come ‘with strings attached’ then the source of funds may interact with the behaviour of the Business Link to produce differences in the way the programmes are delivered. This classification was done for SBS.



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The Role of Governance In previous categorisations of Business Links the role of governance has been one aspect that has been isolated and compared with performance. In the pre-SBS days: they were classified by their contractual relationship towards the TECs where those with arms-length contracts appeared to perform well (Hutchinson, Foley and Oztel, 1996). This way of categorising Business Link Organisations (BLOs) continues. Recently, they have been classified by the relationship with Chambers of Commerce (Bennett and Robson, 2003) or other partnerships (Bennett and Robson, 2004) where broadly those that were Chamber of commerce associated improved average performance, although there were some poor performing chamber-linked BLOs. In this chapter we focus on an assessment of the differential impacts of different delivery models which have been adopted by BLOs. The analysis has two key stages. First, the delivery models of individual BLOs are compared and individual BLOs are grouped into four categories. Two different categorisations are explored; one – developed by Bennett and Robson (2003) is based on corporate status; another – developed by Mole - takes into account governance, funding and delivery mode. The second stage of the analysis compares the type of services received by intensively-assisted firms and other-assisted firms from each type of BLO and the perceived and actual impact on firm performance. The final impact assessment is based on variants of the econometric impact models presented in Chapter 4.

5.3 Bennett-Robson (B-R) Classification Bennett and Robson (2003) develop a four-way classification of BL operators based on an analysis of corporate status and interlocking and overlapping directorships between BLOs and other related organisations. This suggested that:

• 26 BLOs were truly independent having no interlocking or overlapping directorships with other local service providers;

• 4 BLOs were subsidiaries or ‘arms length’ operations of some other body;

• 11 BLOs were de facto subsidiaries of local Chambers of Commerce, or operated

as ‘arms length’ operations of Chambers of commerce; and

• 2 BLOs were private, commercial, for profit companies. Based on an analysis of data from the Cambridge Centre for Business Research they concluded that:



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• Market penetration of subsidiaries is higher than that of independent BLOs and is highest of all among subsidiaries of Chambers of Commerce;

• Subsidiaries of Chambers of Commerce also have the highest levels of use of

individual services between different types of BLO, particularly for advice and grants;

• Subsidiaries of Chambers of Commerce also have the largest impact of all types

of sources of business support;

• Subsidiary organisations in general achieve higher levels of satisfaction than independent franchises, while subsidiaries of Chambers also generate strong satisfaction levels apart from their provision of sales and marketing services.

Data from our survey provides an opportunity to validate these observations as well as providing an opportunity to assess the impact of intensive and other assistance provided by each type of BLO on firm performance. One issue, which arises with this classification, however, is the predominance of BLOs in the ‘independent’ category. This limits the size of other groups of BLOs and the likely statistical significance of differences between groups. Having said this, section 5.2.1 focuses on the profile of support offered by the different types of BLO in the Bennett-Robson classification and section 5.2.2 summarises their differential impacts on performance.

5.3.1 Support Service Profile By and large the profiles of intensive assistance offered by different types of BLOs in the B-R typology seem broadly similar (Table 5.1) Two statistically significant differences do emerge, however, with Chamber subsidiaries more likely to be providing business planning services and action plan development to intensively-assisted firms, while private BLOs were notably more likely to be providing intensively-assisted firms with IT assistance.



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Table 5.1: Profiles of Intensive Assistance: by Bennett-Robson Typology (% of firms receiving each service) Bennett-Robson Typology of BLOs

Independents Other

Subsid. Chamber Subsid. Private

All Firms Χ

2 ρ General business information 57.4 66.8 55.7 45.0 57.4 2.830 0.419 Business benchmarking or diagnosis 14.0 7.8 14.0 9.2 13.6 2.007 0.571 Business planning, action plan development 38.4 54.9 43.4 25.5 39.6 7.705 0.053 Information on regulation and compliance 33.9 43.7 39.5 19.3 34.9 5.400 0.145 Help with finding external consultants 22.9 27.7 23.7 3.6 22.9 4.129 0.248 Help with raising finance 34.6 29.7 40.2 47.8 35.4 3.710 0.295 Help with making cost/quality improvements 15.0 16.0 17.1 19.0 15.4 1.017 0.797 Help with marketing 34.9 39.0 39.6 14.5 35.4 4.701 0.195 Help with R&D or NPD 12.0 11.7 15.0 5.6 12.3 2.208 0.530 Help with exporting 13.0 15.5 16.9 6.4 13.5 3.006 0.391 Help with training 40.4 50.8 40.1 52.0 41.0 3.229 0.358 Help with e-commerce 15.4 15.1 18.8 23.9 16.0 1.708 0.635 Help with IT issues 20.0 22.2 23.2 49.6 21.0 10.135 0.017 Anything else 6.8 9.7 8.5 0.0 7.0 2.464 0.482

Source: BL Telephone Survey (2005) Services provided to other-assisted firms are also broadly similar across BLO types with more variation evident here than between the services being provided to intensively-assisted firms. Here (Table 5.2):

• Private BLOs were notably more likely to provide other-assisted firms with assistance with IT as well as with R&D and new product development;

• Private BLOs and other subsidiaries were significantly more likely to provide

assistance to other-assisted firms with obtaining finance than either Chamber subsidiaries or independents.



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Table 5.2: Profiles of Other Assistance: by Bennett-Robson Typology (% of firms receiving each service)

Bennett-Robson Typology of BLOs

Independents Other

Subsid. Chamber Subsid. Private

All Firms Χ

2 ρ General business information 57.3 54.7 57.5 38.5 56.6 4.529 0.210 Business benchmarking or diagnosis 6.5 5.6 10.5 11.5 7.0 3.740 0.291 Business planning, action plan development 23.4 26.6 27.0 17.4 23.9 1.930 0.587 Information on regulation and compliance 24.0 25.2 22.8 30.5 24.1 0.680 0.878 Help with finding external consultants 11.9 10.7 11.8 3.2 11.5 2.183 0.535 Help with raising finance 21.0 19.3 35.9 40.2 22.9 19.220 0.000 Help with making cost/quality improvements 8.2 3.5 9.1 8.2 7.8 2.778 0.427 Help with marketing 21.5 16.4 19.4 19.2 20.8 1.724 0.632 Help with R&D or NPD 9.0 9.3 13.7 21.4 9.8 0.699 0.072 Help with exporting 7.5 4.8 11.0 3.2 7.5 3.848 0.278 Help with training 30.2 31.0 31.0 32.4 30.5 0.191 0.979 Help with e-commerce 9.3 6.0 10.7 19.2 9.4 5.872 0.118 Help with IT issues 13.3 11.1 17.5 28.5 14.0 6.343 0.096 Anything else 7.6 8.0 4.0 8.9 7.3 2.325 0.508


5.3.2 Impact of BLO Services We consider two measures of impact here. First, firms own subjective assessment of the impact of BLO services on their development. As in Chapter 4 we consider two levels of perceived impact; first, whether BL assistance was ‘important’ for changes in the business and, secondly, whether BL assistance was the ‘crucial’ factor. Secondly, we consider econometric evidence of the impact of BLO services provided by each type of BLO in the Bennett-Robson typology. This analysis is based on the models developed in Chapter 4 for employment, sales and productivity growth. The broad similarity in services being provided by the different types of BLO in the Bennett-Robson classification is also suggested by similarity between the perceived impacts of services. Table 5.3 profiles this for intensively-assisted firms and Table 5.4 for other-assisted firms. In terms of the perceived impact of BL assistance by intensively-assisted firms, we find two significant differences. First, BL assistance is commonly said to be have been important in improving business planning by other subsidiaries, and second, independents were less commonly cited by firms as having had a crucial effect on the technical capability of the business than other types of BLO (Table 5.3). No statistically significant differences were evident in terms of the perceived impact of BL assistance to other-assisted firms (Table 5.4).



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Table 5.3: Perceived Impact of BL Services: Intensively-Assisted Firms Bennett-Robson Typology of BLOs

Independents Other

Subsid. Chamber

Subsid Private

All Firms Χ

2 ρ Part A: BL Services Important for Change (% of all respondents) More inclined to use external support services 27.9 40.4 30.6 21.9 28.7 4.630 0.201 More inclined to use specialist consultants 28.8 33.9 33.7 22.1 29.6 2.654 0.448 Image of business has improved 39.6 42.7 39.5 33.2 39.6 0.584 0.900 Technical capability has improved 17.5 9.9 21.6 29.5 18.0 5.456 0.141 Financial management has improved 27.5 34.6 32.2 30.5 28.5 2.271 0.518 Better at planning 40.6 50.9 32.3 39.4 39.8 6.380 0.095 Export capacity has improved 13.2 13.2 17.6 5.6 13.7 3.093 0.377 Financial sourcing has improved 31.6 26.3 37.4 29.6 32.2 2.894 0.408 Regulation and compliance capability has improved 32.8 32.6 36.6 20.6 33.1 1.875 0.599 Invested more in training 29.3 42.0 31.5 45.3 30.5 5.496 0.139 Increased innovation capability 21.1 11.2 22.9 25.7 21.0 3.546 0.315 Improved product or service quality 25.4 19.7 23.1 40.5 25.1 4.256 0.235 More inclined to use external support services 66.5 53.8 67.4 37.1 65.5 2.952 0.399 Part B: BL Assistance Critical to Change (% of those experiencing change) More inclined to use specialist consultants 67.8 62.8 65.2 71.2 67.2 0.383 0.944 Image of business has improved 75.9 77.6 76.6 66.6 75.9 0.357 0.949 Technical capability has improved 76.5 48.9 56.1 44.1 71.4 9.095 0.028 Financial management has improved 71.2 83.5 68.1 71.5 71.3 1.166 0.761 Better at planning 71.9 74.8 71.6 49.4 71.6 1.845 0.605 Export capacity has improved 75.3 100.0 65.5 100.0 74.3 2.595 0.460 Financial sourcing has improved 69.2 65.5 64.2 53.2 68.0 1.364 0.714 Regulation and compliance capability has improved 69.6 77.0 65.8 100.0 69.7 2.297 0.513 Invested more in training 75.8 62.5 85.8 67.1 76.2 4.305 0.230 Increased innovation capability 63.1 63.1 72.9 21.9 63.7 5.608 0.132 Improved product or service quality 66.9 72.1 74.6 35.9 67.2 4.037 0.258




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Table 5.4: Perceived Impact of BL Services: Other-Assisted Firms Bennett-Robson Typology of BLOs

Independents Other

Subsid. Chamber

Subsid Private

All Firms Χ

2 ρ Part A: BL Services Important for Change (% of all respondents) More inclined to use external support services 17.2 13.9 16.1 10.4 16.6 1.548 0.671 More inclined to use specialist consultants 16.0 14.0 16.4 11.4 15.7 0.907 0.824 Image of business has improved 25.0 27.2 28.9 20.7 25.5 1.395 0.707 Technical capability has improved 13.6 7.0 14.3 11.1 13.0 3.732 0.292 Financial management has improved 19.8 15.3 19.1 14.0 19.2 1.886 0.596 Better at planning 26.8 32.3 29.4 11.4 27.2 6.020 0.111 Export capacity has improved 7.5 6.0 9.5 9.5 7.6 1.185 0.757 Financial sourcing has improved 17.2 13.4 18.3 19.5 17.0 1.442 0.696 Regulation and compliance capability has improved 20.7 15.6 16.7 17.4 19.7 2.564 0.464 Invested more in training 19.8 17.3 16.4 13.7 19.1 1.611 0.657 Increased innovation capability 11.4 14.4 14.9 9.8 12.0 2.025 0.567 Improved product or service quality 14.8 17.3 15.6 5.0 14.8 3.390 0.335 Part B: BL Assistance Critical to Change (% of those experiencing change) More inclined to use external support services 49.2 58.4 58.4 100.0 51.6 3.595 0.309 More inclined to use specialist consultants 54.2 55.0 55.9 71.5 54.8 0.194 0.978 Image of business has improved 57.6 67.1 71.5 66.1 60.4 2.653 0.399 Technical capability has improved 50.0 16.9 56.7 100.0 49.6 5.619 0.132 Financial management has improved 59.0 41.1 69.5 67.8 59.1 2.918 0.404 Better at planning 55.3 58.6 67.3 100.0 57.4 4.005 0.261 Export capacity has improved 71.1 43.8 52.8 100.0 67.7 3.461 0.326 Financial sourcing has improved 57.7 54.1 68.1 100.0 60.1 5.243 0.155 Regulation and compliance capability has improved 60.5 65.7 70.6 83.6 62.2 0.948 0.814 Invested more in training 58.8 61.2 63.3 76.0 59.7 0.475 0.924 Increased innovation capability 49.0 62.3 43.6 52.7 49.9 1.706 0.636 Improved product or service quality 53.7 50.9 75.0 100.0 56.2 3.555 0.314

Source: BL Telephone Survey (2005) Turning then to the regression model results which are based on variants of the models included in Table 4.5 and 4.6. Table 5.5 reports the coefficients and t-statistics of the assistance terms for each type of BLO within the Bennett-Robson typology. In essence, the aggregate effects reported in Table 4.5 and 4.6 are a weighted sum of these more disaggregated results. As in the aggregate models covering all BLOs (Tables 4.5 and 4.6) we find no significant evidence of any impact on sales growth – in this respect the different models of BLO



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identified in the Bennett-Robson typology behave similarly. In terms of employment growth we also find confirmation of the aggregate results with none of the different types of BLO having any impact on the employment growth of other-assisted firms. Effects on intensively-assisted firms are stronger, however, with significantly positive effects concentrated in independents, other subsidiaries, and chamber subsidiaries. Notably there are significant differences between the size of these coefficients, with other subsidiaries having an employment effect which is nearly twice as large as that of independents and chamber subsidiaries. Table 5.5: Impact Coefficients in Regression Models of Employment, Sales and

Productivity Growth

Employment

Growth Sales

Growth Productivity

Growth Coeff t-stat Coeff t-stat Coeff t-stat A. Intensively-assisted firms Independents 0.028 3.107 0.026 1.384 -0.020 -0.910 Other Subsidiaries 0.054 2.419 -0.014 -0.256 -0.056 -0.915 Chamber Subsidiaries 0.028 1.927 -0.030 -0.960 -0.071 -1.924 Private BLOs -0.004 -0.118 0.050 0.422 -0.049 -0.368 B. Other-assisted firms Independents 0.003 0.305 0.047 1.677 0.064 2.222 Other Subsidiaries 0.014 0.865 -0.022 -0.379 -0.032 -0.544 Chamber Subsidiaries 0.001 0.094 0.009 0.170 0.050 0.979 Private BLOs 0.044 1.486 -0.078 -1.015 -0.222 -2.363

Source: BL Telephone Survey (2005) In terms of productivity growth the results also tend to confirm the aggregate picture with generally weak BLO assistance impacts on productivity growth among intensively-assisted firms. For other-assisted firms a slightly different picture emerges, however, with independent BLOs having a small positive effect and private BLOs a larger negative effect. The absolute importance of this last (negative) result, however, is reduced by the relatively small number of firms covered by private BLOs.

5.4 Mole Classification

The Business Link network contains 43 separate organisations (BLOs), which, whilst all are working their way toward brokerage models, are doing so from different positions. Their economic context also differs with some BLOs covering prosperous areas whereas others cover disadvantaged areas. Our purpose is to categorise BLOs on the basis of their business models. This shows that there are different ways of approaching the Information, Diagnostics and Brokerage (IDB) model. It may also provide initial insights into the types of business models with the greatest impact.



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This report re-states the previous categorization of BLOs. It then reports soundings from a series of interviews conducted with Business Link’s senior management. It then introduces four models of BLOs and discusses how these might be identified and used in the economic impact modelling. The remainder of this chapter reflects outcomes from a series of interviews conducted by the author(s) with BLOs at the Chief Executive or Director of Operations levels – sometimes both. These interviews were conducted between June 2005 and September 2005 with representatives of 15 BLOs and two RDA operatives.

5.4.1 The Information, Diagnostics and Brokerage (IDB) model

BLOs differ in:

– their institutional environment – how intensive their assistance is – the way in which intensive clients are found – the proportionate number of intensive clients – where they get their money from – the sort of relationships they aim to foster

a. Their institutional environment BLOs find themselves having to deal with a number of different partnerships, particularly with local authorities, with other support agencies and with the private sector. For some BLOs these relationships are relatively stable and easy to manage; for others they are complicated. BLOs argue that they can be either helped or hindered by their relationships with other partners in business support. Other organisations can help by working with Business Link, for example Business Link CEOs talk about the brand as ‘a route to market’ for other public sector provision, such as Learning and Skills Councils. However, the more organisations that are involved in business support, both private and public, the more this confuses the consumer. CEOs are, therefore, keen to play a co-ordinating role in their area. Of course, the numbers of private sector suppliers of advice, most notably accountants, differ markedly and systematically across the country, which means that in some areas private sector advice is plentiful and in other it is limited. It does appear that fewer private sector advisers are located in rural areas which, in part, may explain the success of BLOs in rural areas (Bennett et al., 2001).

b. How intensive BLOs assistance is Some BLOs are keen to be more intensive in their assistance than others. Some aim to work very intensively with clients variously described as a ‘high cost per intervention’ (Birmingham) ‘very, very intensive assistance (Sheffield). Both cases depended on obtaining funding to supplement ‘SBS core funding’, most frequently from the EU. c. How BLOs find their intensively assisted clients



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There are essentially two options. The first is to use the ‘gateway’ to screen clients. The second is to use special events and direct marketing. Again the options are contingent upon the type of clients that are seen as important. When clients are selected by some clear criteria such as sector or disadvantage it is easier to use the ‘gateway’ to screen potential clients. When the criteria requires a judgement of the potential to grow, and the ability of the business adviser to help, the gateway becomes less useful, at least as a direct conduit for more intensive assistance. d. The proportionate number of intensive clients to less intensive clients Some BLOs regard intensive assistance as that part of the business that had the most impact on the local economy. Delivering high rates of intensive assistance is contingent on funding, in this case normally from the LSC. e. Where they get their money from BLO models reflect both the total funds available and their sources. In turn, this depends upon the geography of the BLO. Given the CEOs are ‘on the lookout’ for funds then the obvious sources are EU funds and the Learning and Skills Councils. European money is more likely to come to a BLO in a deprived area.

f. The sort of relationships they aim to foster If the BLO aims to foster long-term relationships then it is more likely to attempt to have a more managed brokerage model..



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5.4.2 Four models of BLOs Using the above six questions we now can formulate four models which may broadly reflect the range of ways in which BLOs operate. The four models are referred to as:

– ‘Light touch’ brokerage – ‘Managed’ brokerage – ‘Pipeline forcing’ – ‘Managed Pipeline Forcing’ brokerage


• The dominant model. Some BLOs suggest that they were ‘lean and mean’ with low levels of ‘touch with their clients and not too much follow-up.

• Philosophy is ‘Lets solve the business problem there and then’ • The payoff is in the high penetration rate • ‘Light touch’ BLOs are likely to be in areas that receive little non-core funding

such as EU supported funds. Model 2 Managed brokerage

• Many BLOs believe that to retain customers they needed to manage the relationships between client, BL and consultant.

• The account manager oversees the process with a project management role throughout the assistance and follow-up

• Almost all have contracts between the consultant and client - an exception is Northumberland’s three way contract between consultant, client and BLO.


• ‘Trigger points’ to identify firms that may be ‘amenable’ to intensive assistance. They are very keen to get a high proportion of firms through to the end of the funnel




.



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Figure 5.1 Models of Business Link Operators: Intensity of intensive assistance and the proportion of firms intensively assisted. Proportion of Firms Intensively Assisted

High Low Intensity of Intensive assistance

Highly intensive Model 4 Managed Pipeline Forcing Brokerage

Model 2 Managed brokerage

Low intensity Model 3 Pipeline Forcing


In order that we may map the models to the differences in their operating environment the following matrix was constructed (Table 5.6). Table 5.6: BLO Delivery Models and their Operating Environment Models BLOs differ in…. 1 Light-touch

brokerage 2 Managed brokerage

3 Pipeline Forcing

4 Managed Pipeline Forcing

Brokerage their institutional environment

Clear/Complex Complex Complex Complex

how intensive their assistance is

Not very Very Very Very

the way in which intensive clients are found

Gateway Gateway Sector

Gateway Triggers

Gateway Sector, Triggers

the proportionate number of intensive clients

Low Mid High High

where they get their money from

SBS EU LSC/EU EU

the sort of relationships they aim to foster

One-off Ongoing Ongoing Ongoing

5.4.3 Operationalising the Models To model the BLOs we use data as shown in Table 5.7. In this way most of the classification is covered. There are differences that remain: the relationships that the BLOs aim to foster and the way in which intensive clients are found. On the relationships we have some evidence that BLOs are training their advisers to foster ‘process consulting’ but the variation in this relationship may be at the individual business adviser



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level. On the way in which intensive clients are found we have the data at the firm level already collected in the main questionnaire. Table 5.7: Operationalising the BLO Models

Factor Measure Source 1. Complexity of

institutional environment

Number of intermediaries such as accountants

ICAEW direct

2. Intensively of assistance

BLO turnover BLO accounts

3. Where they get their money from

SBS vs LSC vs EU incomes

BLO accounts

4. The proportionate number of intensive clients

Intensive clients as a proportion of businesses ‘touched’

SBS data

One of the issues is whether the appropriate modelling is to cluster the BLOs into three groups or to use dummy variables to account for the complexity of the environment or rural area. In practice, we might expect to do both since the cluster is intended to capture the business models of the BLOs. Complexity of institutional environment - the Private Competition In order to ascertain the private competition we used the business location of members of the Institute of Chartered Accountants of England and Wales (ICAEW) as a proxy for the number of private sector advisers (Table 5.8). Accountants are the most mentioned business advisers by SMEs (Mole, 2002). What we find is not particularly surprising. There are fewer firms (on the VAT stock of firms) per chartered accountant in prosperous areas such as Surrey and Cheshire and in big city locations like Birmingham and Near Manchester (East Lancs. and North Manchester are now part of Manchester). We expected fewer accountants to be registered in Cumbria, Durham and Northumberland. One surprise is the high number of firms per accountant in Somerset and West (Bristol).



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Table 5.8: Number of Firms per Accountant in each Business Link Area Business Link No. of Firms per Accountant West 226.52 Somerset 226.52 Humberside 201.25 Manchester 193.63 North Manchester 193.63 Stafford 166.53 Northumberland 156.23 Derbyshire 151.59 Tees Valley 145.86 Cumbria 143.25 Northampton 142.13 Norfolk 142.13 Suffolk 139.39 County Durham 137.53 Lincolns 134.59 Shropshire 134.13 N.Yorkshire 133.63 Black Country 129.65 S.Yorkshire 127.28 Leicester 126.03 Gloucestershire 125.84 Coventry 125.50 Cambridge 119.46 Bedfordshire 117.21 Hereford 115.70 Hampshire 113.58 Nottingham 112.97 Devon & Cornwall 109.96 London 109.10 Tyne & Wear 106.05 Sussex 105.02 W.Yorkshire 102.84 Berks & 102.12 Dorset (Wessex) 101.68 M.Keynes 100.50 Merseyside 95.93 N&W Lancs. 90.04 East Lancs. 90.04 Essex 89.02 Kent 75.73 Hertford 66.72 Birmingham 62.49 Cheshire 58.94 Surrey 47.36 Source: ICAEW Performance Monitoring Data Using the SBS performance monitoring data for April 2003-September 2003 we can use proxies for, at least some of, the models. The major starting point for this analysis is to



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use the reported results from the monitoring statistics and the financial results from the BLOs. As has been said before the way in which income is gathered can have an important impact on the sort of business models that the BLOs operates.18 To measure the extent to which a BLO attempts to have a light or heavy touch we use a number of proxies: the cost per customer, the proportion of funds provided by SBS, the proportion of funds provided by the EU, and the amount of EU funds per customer (Table 5.9). The reason that we choose this grouping is because they all appear to measure something similar which is the underlying intensity of the help that the BLO provides. Table 5.9: Performance Monitoring Descriptive Statistics

N Minimum Maximum Mean Std.

Deviation Cost per customer 42 £209.68 £1364.24 £527.63 £227.13 EU and SRB proportion

43 0.0 63.0 14.5 15.2

SBS as a proportion of total

43 18.0 78.0 45.4 15.2

Source: SBS A Hierarchical Cluster analysis on this basis produces five clusters, on the basis of their intensity. As can be seen in Table 5.10 the cluster analysis groups together BLOs that are similar. The Tyne and Wear and South Yorkshire are both very intensive with their assistance; where they differ is on the amount of EU and SRB funding that they produce. Cluster 4 manage to generate high levels of costs per customer although they do not fund their activity from the EU, both of these BLOs received more funds from the RDA than from the SBS in this period. All of these four clusters use significantly more intense assistance than the average BLOs. The group of BLOs that are characterised as having more intense assistance includes all four of the delineated clusters.

18 Of course the actual direction of causality is debateable. Obviously in South Yorkshire there are large amounts of EU money available that would tend to suggest a very intensive assistance model but other areas might deliberately garner funds to support an avowed very intensive assistance aim.



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Table 5.10: Intensity of Help - BLO clusters Cluster BLOs

Cost per customer

£

SBS funded

%

EU and SRB

funded %

1 Tyne and Wear 1198.20

24 29

2 South Yorkshire 1364.24

18 63

3 Durham 920.77

26 21

North Manchester19 792.52

30 33

Merseyside

738.29 45 35

Northumberland 640.27

30 38

East Lancs.20 637.17

29 39

Hertfordshire 634.38

35 29

4 Birmingham 750.19

19 9

Shropshire

735.76 34 0

5 All bar the above 429.65 52 10 Consequently, there is a group of BLOs offering more intensive assistance comprising Tyne and Wear, South Yorkshire, Durham, North Manchester, Merseyside, Northumberland, East Lancashire, Hertfordshire, Birmingham and Shropshire. The average cost per customer of those who were spending more per customer was £841 which was 1.95 times that of the light-touch group. Next, we can compare the intensive assistance rate to the penetration rate. This may enable us to evaluate the membership of Cluster 3 – that is, those that attempt to intensively-assist a high proportion (Table 5.11). At this time the intensively-assisted rate was not a monitoring target (which means it didn’t suffer from Goodhart’s law) but the definition was probably not as tight as it was subsequently. The ratio of intensive assistance to the penetration rate varies from between 3 per cent to over 37 per cent (Northumberland). 19 North Manchester has been subsumed into Greater Manchester Chamberlink 20 East Lancs. has been subsumed into Greater Manchester Chamberlink



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Table 5.11: Proportionate Intensive Rate - Descriptive Statistics

N Minimum Maximum Mean Std.

Deviation Intensive per penetration rate (%)

43 3.0 37.0 9.6 6.8

A Hierarchical Cluster analysis suggests that there were essentially three clusters of BLOs using this criterion (Table 5.12). The first cluster is Northumberland all on its own. The second comprises a number of rural and North Eastern BLOs. This is a smaller group. Finally a further group is the rest of the Business Link Organisations. In this group, therefore, are all the BLOs that have a high level of assistance. However, this group also comprises two BLOs that are in group 2 the heavy intervention group. Table 5.12: Proportionate Intensive Rate – Cluster Analysis

Cluster

BLOs

Intensive rate per penetration rate (%)

1 Northumberland 37 2 Tees Valley 24 Cumbria 23 Durham 22 Humberside 20 Suffolk, 18 3 All bar the above 7

Reviewing the range of criteria available to assist the definition of a typology of BLOs, and mindful of the constraints surrounding the data gathering, it is possible to allocate individual BLOs to the four different models of Business Link service delivery (Table 5.13). Those BLOs who do not make it into any other category are in the light touch brokerage catch all category (Model 1). Managed brokerage includes those more intensive BLOs (Model 2). Model 3 includes those BLOs that have a high level of intensive assistance compared to non-intensive and finally Model 4 captures the two BLOs who have both a high level of intensity and a high level of intensive assistance.



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Table 5.13: Four Models of Business Link Assistance and BLOs Organisations Model 1 Model 2 Model 3 Model 4

Light Touch Brokerage

Managed Brokerage

Pipeline Forcing Managed Pipeline Forcing Brokerage

Bedfordshire Tyne and Wear Cumbria Durham Berks & Wiltshire South Yorkshire Humberside Northumberland Black County North Manchester21 Suffolk Cambridge Merseyside Tees Valley Cheshire East Lancashire22 Coventry Hertfordshire Derbyshire Birmingham Devon & Cornwall Shropshire Dorset (Wessex) Essex Gloucester Hampshire (Wessex)

Hereford Kent Leicester Lincolnshire London M.Keynes Oxford Manchester N&W Lancs. N.Yorkshire Norfolk Northampton Nottingham Somerset Stafford Suffolk Surrey Sussex W.Yorkshire West

21 North Manchester has been subsumed into Greater Manchester Chamberlink 22East Lancs. has been subsumed into Greater Manchester Chamberlink



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Table 5.14: Significant Correlations between Income and Intensity

Total income

SBS as a proportion

of total Cost per customer

EU and SRB proportion

EU funds per Customer

Total income SBS as a proportion of total Cost per customer EU and SRB proportion EU funds per customer

1 -.177 .312* .220 .289 -.177 1 -.684** -.604** -.575** .312* -.684** 1 .637** .825** .220 -.604** .637** 1 .886** .289 -.575** .825** .886** 1

* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). Table 5.14 shows that focussing on the intensity aspects of the Business Link organisation is inevitably associated with the sources of funds. What the table does not show is that the funds from Learning and Skills Council are not significant. Therefore, the simple use of sources of funds does not capture the significant variations in Business Link Organisations. Data for these four models of Business Link assistance/BLOs is compared below. Section 5.4.4 focuses on the services provided by each group of BLOs in Mole’s classification, while Section 5.4.5 focuses on the impact of BLO services on business growth and development. As with the Bennett-Robson categorisation examined earlier, however, the Mole categorisation produces groups of BLOs of very different sizes, limiting the power of any statistical test to discriminate between groups.

5.4.4 Support Service Profile For intensively-assisted firms, significant differences were evident between the profiles of BLO assistance relating to business planning and action plan development, raising finance, help with e-commerce and help with IT issues. The key differences between the four models of BL assistance/BLOs were (see Table 5.15):

• Managed brokerage BLOs were most likely to be providing intensively-assisted firms with business planning assistance or action plan development.


brokerage BLOs;

• Managed brokerage BLOs and BLOs operating both managed brokerage and Pipeline Forcing managed pipeline forcing brokerage were most likely to be providing assistance with e-commerce and IT.



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Table 5.15: Profiles of Intensive Assistance: By Mole Typology (% of firms receiving each service)

Mole Typology

Light-touch

Managed Brokerage

Pipeline Forcing

Managed Pipeline Forcing

Brokerage All

Firms Χ2 ρ

General business information 58.7 58.4 51.1 55.4 57.4 3.201 0.362 Business benchmarking or diagnosis 14.3 12.6 11.8 11.6 13.6 1.077 0.783 Business planning, action plan development 37.7 51.9 39.6 41.5 39.6 8.671 0.034 Information on regulation and compliance 34.9 42.5 29.6 35.8 34.9 4.700 0.195 Help with finding external consultants 24.5 21.7 15.9 23.4 22.9 6.059 0.109 Help with raising finance 32.9 51.8 33.5 42.6 35.4 16.863 0.001 Help with making cost/quality improvements 15.5 12.6 15.1 19.1 15.4 1.667 0.644 Help with marketing 36.4 39.8 28.9 32.9 35.4 4.399 0.221 Help with R&D or NPD 12.1 16.5 10.3 13.6 12.3 2.549 0.459 Help with exporting 13.2 17.1 13.3 11.9 13.5 1.554 0.670 Help with training 42.3 42.8 33.6 40.6 41.0 4.305 0.230 Help with e-commerce 14.0 21.4 16.1 30.9 16.0 16.037 0.001 Help with IT issues 19.1 30.4 15.9 40.1 21.0 24.883 0.000 Anything else 7.2 9.4 6.8 1.8 7.0 3.917 0.271


More significant difference were evident in the service profiles being provided to other-assisted firms (Table 5.16), with managed brokerage BLOs generally providing a higher proportion of client firms with each service than other types of BLO. Key points were:

• Managed brokerage BLOs were providing 42.3 per cent of their clients with help for raising finance compared to only 19.7 per cent of the clients of light touch brokerages;

• Managed brokerage BLOs were also providing more of their clients help with

exporting, e-commerce and IY than other types of BLOs (Table 5.16);

• BLOs operating as managed pipeline forcing brokerage were most likely to be offering their clients help with training (Table 5.16).



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Table 5.16: Profiles of Other Assistance: by Mole Typology (% of firms receiving each service)

Mole Typology

Light-touch

Managed Brokerage

Pipeline Forcing


Brokerage All

Firms Χ2 ρ

General business information 56.8 62.6 54.6 45.4 56.6 4.269 0.234 Business benchmarking or diagnosis 7.2 4.6 6.5 8.0 7.0 0.968 0.809 Business planning, action plan development 24.0 22.0 27.8 19.7 23.9 1.513 0.679 Information on regulation and compliance 23.0 30.2 27.8 28.0 24.1 3.177 0.365 Help with finding external consultants 11.3 16.1 8.7 12.5 11.5 2.084 0.555 Help with raising finance 19.7 42.3 26.7 40.5 22.9 34.758 0.000 Help with making cost/quality improvements 7.5 7.9 11.8 7.7 7.8 1.668 0.644 Help with marketing 20.0 23.2 26.5 19.9 20.8 2.223 0.527 Help with R&D or NPD 9.5 12.3 7.7 15.3 9.8 3.054 0.383 Help with exporting 7.1 15.2 5.4 4.8 7.5 10.084 0.018 Help with training 31.3 31.6 17.4 34.9 30.5 8.424 0.038 Help with e-commerce 8.9 16.7 4.2 14.1 9.4 9.387 0.025 Help with IT issues 13.1 23.2 10.5 19.5 14.0 9.217 0.027 Anything else 7.3 6.8 7.5 7.8 7.3 0.161 0.984


5.4.5 Impact of BLO Services As in the case of the Bennett-Robson typology we consider two indicators of impact – the impact perceived by firms and the econometrically modelled impact of BLO assistance on business growth. Reflecting the pattern of service provision for intensively-assisted firms, two significant differences were evident between the proportions of BL clients in each category in the Mole typology reporting that BL services has been an important catalyst for change within their business. Firms that received support from Business Links that used the Managed Brokerage model were significantly more likely to report them as having been an important source of change in financial sourcing than other types of BLO. Firms that received support from Business Links that used the Managed Pipeline Forcing Brokerage model were significantly more likely to report them as having had an important impact on training than other types of BLO (Table 5.17). Only in terms of innovation capability were there significant differences in the proportion of intensively-assisted firms citing BLOs as the crucial factor in change in the firm (Table 5.17). Here, light touch brokerages were said to have most commonly been the crucial factor.



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Table 5.17: Perceived Impact of BL Services: Intensively Assisted Firms

Mole Typology

Light-touch

Managed Brokerage

Pipeline Forcing


Brokerage All

Firms Χ2 ρ

Part A: BL Services Important for Change (% of all respondents) More inclined to use external support services 29.0 32.9 24.4 28.4 28.7 2.395 0.495 More inclined to use specialist consultants 28.8 37.4 25.2 36.4 29.6 5.991 0.112 Image of business has improved 38.5 48.5 40.3 35.6 39.6 4.493 0.213 Technical capability has improved 17.4 23.9 16.0 19.8 18.0 3.797 0.284 Financial management has improved 28.0 35.4 25.0 31.4 28.5 3.558 0.313 Better at planning 40.9 34.9 38.4 39.4 39.8 1.495 0.683 Export capacity has improved 13.6 19.9 9.7 14.2 13.7 5.136 0.162 Financial sourcing has improved 30.8 46.2 24.7 44.4 32.2 18.861 0.000 Regulation and compliance capability has improved 33.0 37.9 27.8 40.1 33.1 4.375 0.224 Invested more in training 31.3 34.1 22.4 35.2 30.5 6.882 0.076 Increased innovation capability 20.5 24.1 21.9 20.0 21.0 0.596 0.897 Improved product or service quality 24.7 25.0 25.0 30.6 25.1 0.939 0.816

Part B: BL Assistance Critical to Change (% of those experiencing change) More inclined to use external support services 65.9 67.8 64.9 56.7 65.5 0.952 0.813 More inclined to use specialist consultants 66.8 71.2 60.0 75.9 67.2 1.844 0.605 Image of business has improved 77.0 72.1 73.3 79.2 75.9 1.046 0.790 Technical capability has improved 73.2 57.9 78.6 66.2 71.4 3.670 0.299 Financial management has improved 71.5 74.4 63.6 79.2 71.3 1.649 0.648 Better at planning 71.8 80.4 68.0 64.6 71.6 2.674 0.445 Export capacity has improved 76.8 57.9 72.4 87.1 74.3 4.481 0.214 Financial sourcing has improved 70.0 58.1 63.9 73.6 68.0 3.500 0.321 Regulation and compliance capability has improved 69.8 78.3 60.8 70.4 69.7 2.795 0.424 Invested more in training 77.0 81.5 78.6 56.1 76.2 4.880 0.181 Increased innovation capability 69.9 55.8 52.2 36.3 63.7 8.667 0.034 Improved product or service quality 69.4 53.4 71.5 56.3 67.2 3.632 0.304


For other-assisted firms, significant differences between the proportions of firms reporting BLO assistance as important were evident only for financial sourcing and innovation capability (Table 5.18). In both cases other-assisted firms were most likely to cite Managed Brokerage BLOs as being an important factor in stimulating change.



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Table 5.18: Perceived Impact of BL Services: Other-Assisted Firms

Mole Typology

Light-touch

Managed Brokerage

Pipeline Forcing


Brokerage All

Firms Χ2 ρ

Part A: BL Services Important for Change (% of all respondents) More inclined to use external support services 15.9 24.2 17.2 15.2 16.6 4.111 0.250 More inclined to use specialist consultants 14.9 18.7 17.3 22.6 15.7 2.990 0.393 Image of business has improved 24.6 32.9 26.3 26.3 25.5 3.064 0.382 Technical capability has improved 12.4 19.1 14.4 10.5 13.0 3.785 0.286 Financial management has improved 18.8 22.2 23.2 13.8 19.2 2.489 0.477 Better at planning 27.5 26.5 28.9 19.1 27.2 1.697 0.638 Export capacity has improved 7.4 10.0 6.9 8.4 7.6 0.818 0.845 Financial sourcing has improved 15.2 24.6 23.8 22.6 17.0 10.216 0.017 Regulation and compliance capability has improved 19.0 21.2 21.8 26.2 19.7 1.704 0.636 Invested more in training 19.3 19.2 17.8 16.9 19.1 0.312 0.958 Increased innovation capability 10.9 21.8 12.5 11.6 12.0 9.802 0.020 Improved product or service quality 14.8 20.4 15.4 4.1 14.8 6.964 0.073

Part B: BL Assistance Critical to Change (% of those experiencing change) More inclined to use external support services 47.2 66.4 68.1 59.0 51.6 5.276 0.153 More inclined to use specialist consultants 51.9 52.9 67.9 73.5 54.8 2.741 0.433 Image of business has improved 57.3 77.3 64.1 63.5 60.4 4.294 0.231 Technical capability has improved 47.7 56.9 57.7 47.0 49.6 0.490 0.921 Financial management has improved 56.2 86.2 54.6 61.7 59.1 6.255 0.100 Better at planning 55.5 74.0 57.0 65.3 57.4 3.290 0.349 Export capacity has improved 65.4 64.3 74.5 100.0 67.7 2.075 0.557 Financial sourcing has improved 58.1 56.9 74.7 61.7 60.1 2.201 0.532 Regulation and compliance capability has improved 60.8 53.7 74.5 78.2 62.2 3.002 0.391 Invested more in training 62.4 49.8 55.9 36.8 59.7 3.328 0.344 Increased innovation capability 48.0 50.3 64.8 51.3 49.9 0.981 0.806 Improved product or service quality 52.2 66.9 76.9 72.6 56.2 3.862 0.277

Source: BL Telephone Survey (2005) Econometric estimates of the growth impact of the different types of BLO in the Mole typology are given in Table 5.19, based on models such as those in Table 4.5 and 4.6. As in the aggregate results we find no significant effect of BLO assistance on other-assisted firms for sales or employment growth. Significant positive productivity growth effects are evident with the (positive) effect of light-touch brokerage of more absolute importance.



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Table 5.19: Impact Coefficients in Regression Models of Employment, Sales and Productivity Growth: Mole Typology

Employment

Growth Sales

Growth Productivity

Growth Coeff t-stat Coeff t-stat Coeff t-stat A. Intensively-assisted firms Light-touch 0.025 2.757 0.016 0.833 -0.020 -0.888 Managed Brokerage 0.069 4.117 0.046 1.303 -0.038 -0.917 Pipeline Forcing 0.018 1.275 -0.014 -0.475 -0.035 -1.035 Managed pipeline forcing brokerage 0.035 1.754 0.094 2.030 -0.086 -1.492 B. Other-assisted firms Light-touch 0.005 0.585 0.055 1.999 0.072 2.509 Managed Brokerage 0.005 0.295 -0.030 -0.590 -0.025 -0.492 Pipeline Forcing -0.011 -0.621 -0.086 -1.270 -0.031 -0.431 Managed pipeline forcing brokerage 0.027 1.175 -0.092 -1.455 -0.136 -1.927

Source: BL Telephone Survey (2005) No significant productivity effects were evident on intensively-assisted firms from any type of BLO (Table 5.18), although the small group of managed pipeline forcing brokerage BLOs were having a positive sales growth effect. More notable perhaps are the employment growth effects where the managed brokerage and light-touch groups of BLOs both had strongly positive and significant effects. Notably BLOs in the managed brokerage group had an employment impact (6.9 percentage points) almost three times that of those in the light-touch brokerage group. For the managed brokerage group the cost per customer was almost double that of the light-touch group, if the employment impact was the be all and end all of the programme then the managed brokerage group would appear to be greater value for money; however, the light-touch group showed impacts on sales and productivity from other assistance.

5.5 Summary The chapter concentrated on discovering any significant differences between types of Business Link Organisations with respect to the impacts on employment growth, sales growth and productivity growth. Two classifications of Business Links were tested: the Bennett and Robson classification on the basis of governance and the Mole typology on the basis of delivery methods. In the Bennett and Robson classification independents, other subsidiaries, and chamber subsidiaries were found to have significantly positive employment growth effects on intensively-assisted firms. The chapter found significant differences between the type of BLOs and their performance. We found that our broad aggregate models were confirmed with much of the differences being between the effects on employment growth for intensively assisted firms. In terms of productivity growth the results also tend to confirm the aggregate picture with generally weak BLO assistance impacts on productivity growth among intensively-assisted firms. For other-assisted firms a slightly different picture emerges, however, with independent BLOs having a small positive effect and private



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BLOs a larger negative effect. The absolute importance of this last (negative) result, however, is reduced by the relatively small number of firms covered by independent BLOs. The Mole typology also shows the impact of employment growth. In this case it is the light-touch and managed brokerage firms that have greater impact on intensively assisted firms. Going back to Table 5.16 suggested that both types improve the sourcing of finance for firms. In terms of productivity growth on the other assisted firms light-touch brokerage BLOs have a positive effect which is rather difficult to trace in the differences in the type of services shown in Table 5.17. Light touch other assisted clients tend to have an increase in sales growth too. One interpretation is that there are poor returns from pipeline forcing. This may indicate that the targets for intensive assistance may be unhelpful as regards impact. Thus, if the onus is on the client to opt-in to more intensive assistance then this suggests that both advisers and clients are making a dispassionate assessment of the benefits of advice rather than being forced into a ‘relationship’. Given the economic rationale of Business Link is to encourage productivity within the small firm sector, how do our results shed light on the ways in which it might do this? Recall from section 1.3 that the SBS aim to build the capacity for small business growth through improvements to the management skills within the target group of small and medium sized enterprises. The evidence suggests that intensive assistance in all of the models make some perceived impact on the management from the BL services. A significant difference was that the pipeline forcing model resulted in a lower perceived impact of the sourcing of finance (table 5.17), and their clients invested less in training, although they received less assistance in this aspect. A similar impact is also evident in the Bennett-Robson model which suggests that those firms that have financial problems may not show the impact within the two years that we expect impacts to develop, even on employment. This would tend to suggest that the firms that are using Business Link for this purpose are not growing strongly. Nonetheless, nearly 40% believe that they are better at planning and the image of the business has improved; around a third of businesses have improved their ability to raise finance and deal with regulation, and one-quarter have improved their product quality. The implications of the Mole typology is that the models that perform well are the light touch particularly in the other assistance aspect, and the managed brokerage particularly in generating employment. For the Business Link faced with a choice of spending priorities between gaining more intensive customers or spending more on each one the implication is that they should choose spending more on each. The model that appeared to work well was the light touch model which produced impacts on all three of the measured impacts under certain circumstances. The light-touch model was found to have employment growth impact from intensive assistance, sales growth impact from non-intensive assistance (weakly) and productivity growth impact from non-intensive assistance. If the employment growth was the only consideration then the managed brokerage model was expensive but produced greater benefits than the light-touch model.



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Another implication of the modelling is in the original equations that demonstrate that the key to increasing the productivity and sales growth of the firms is to encourage them to seek to exploit new markets. Those firms that are seeking new markets are consistently more likely to grow in sales and productivity (see tables 4.5 to 4.6).



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6. Impact of Business Link Assistance: Evidence from the Face-to-Face Interviews

6.1 Introduction In this Chapter we provide evidence on the impact of Business Link support on both intensively-assisted firms and other-assisted firms from 34 in-depth face-to-face interviews (‘case studies’) with the owner-managers of businesses who responded to the telephone survey and who were willing to participate in further research on the project23. Overall, 57 per cent (1,964 firms) of the surveyed firms agreed to be contacted in the future: evenly spread over the three categories of assistance in the analysis (see Table 6.1). Table 6.1: Sample Derivation from Telephone Survey

All Intensively-

Assisted Other-Assisted Non-assisted Overall Population 3,448 1,130 1,166 1,152 Agreed to be contacted 1,974 702 635 351 Agreed & held strong view on the impact of BL assistance and support 474 193 281 N/A Number of case studies interviewed 34 25 6 3

Source: BL Telephone Survey (2005) The overall objective of the case studies was to provide important insights into how the assistance provided by the BLO network can be connected to performance and indeed to other softer (i.e., behavioural) benefits of that assistance. Also the additionality of that assistance can be probed in more detail. The results from this qualitative stage of the project will add to an understanding of the results presented in previous chapters and, in particular, aid an assessment of the effectiveness of public policy business support models.

6.2 Developing the Topic Guides

23 It was agreed at the outset of the project that we would aim to achieve 45 face-to-face interviews. However, within the allotted time-scale for this stage of the project it was only possible to arrange and undertake 34 face-to-face interviews. These case studies were undertaken in October and November 2005. On average each interview lasted around 45-60 minutes with the owner-manager/CEO or ‘business leader’ of the business. All interviews were taped and full transcriptions made.



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The intention was to select a small number of issues that require further elaboration through this qualitative approach. Reviewing the results from the telephone survey revealed a number of issues that could usefully be pursued:

• the profile of assistance and how delivered/brokered; • perceived impact of that assistance • additionality – ‘hard’ and ‘soft’.

The broad structure to the topic guides for the face-to-face interviews with each of the two groups of assisted businesses was as follows (see Appendix C):

• identifying the performance ‘story’ and seeking to capture the major events

associated with that at the outset of the face-to-face interview. This was an important initial area of discussion with the assisted business as we sought to ‘lock down’ a performance trend and some key explanatory factors at the outset of the interview before embarking upon a discussion of the nature of the relationship with Business Link and its perceived impact.

• Confirmation of the ‘package’ of assistance received from BLO network and

an assessment of its relative importance – probing on additionality - self-assessment’ of the counterfactual position – in the absence of assistance how would the business have performed.

• The impact of the assistance on the subsequent performance and behaviour of

the firm. The importance here was to engage in a discussion of the ‘hard’ and soft’ aspects of the impact of assistance.

• Expectations of the business prior to the engagement with the BLO network –

what were they looking for and why approach Business Link? • Experiences of the nature and delivery of the support provided through the

BLO network – internal/external brokerage issues were explored here to understand more clearly from the point of view of the business the role of the variety of models of delivering business support.

• Alternative sources of business support. This was included to ascertain the

nature of the Business Link ‘fit’ in the wider market place of business support services.

The agenda for the non-assisted businesses was a rather narrower and focused again on explaining recent performance trends as well as seeking to understand the extent to which they used external business support services and their awareness of the Business Link ‘brand’. 6.3 Case Study Selection The 34 face-to-face interviews were drawn from those firms who had agreed (via a question on the telephone survey) to be involved in further research associated with the project. Face-to-face interviews were carried out with owner/managers and senior



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management who had confirmed at the time of securing the interview that they were involved in the ‘package’ of assistance received in the April to September 2003 period. There were a number of principles used to select the case studies. These can be summarised as follows:

• range of BLO models • range of locations (region and urban/rural) • variety of sectors (e.g., manufacturing, financial and business services) • range of business size • focus on intensively-assisted businesses but other-assisted and non-assisted

included In addition, the individual businesses who had been assisted by Business Link were further pre-selected in terms of their responses questions on additionality and the impact of assistance particular aspects of their business in the telephone questionnaire (i.e., questions 11 and 26 – see Appendix A). In brief, an attempt was made to include businesses from across the spectrum of responses to the self-assessment additionality question: that is, from ‘zero’ to ‘100%’ additionality. Similarly, we wished to interview only those business owners that had expressed strong opinions, either positively or negatively, in answering questions that asked respondents to rate on a scale of 1 to 5 the extent to which Business Link assistance had helped improve certain aspects of their business and selecting only those that had answered a ‘1’ or ‘5’ to one of the questions. In all, 25 intensively-assisted, 6 other-assisted and 3 non-assisted businesses were interviewed24. In doing so, a broad geographical spread was obtained (Table 6.2). The aim was also to achieve an even spread between the different Business Link operational ‘models’ and to ensure that targeted businesses were not just in urban areas, but also in rural areas – particularly deprived rural areas (Table 6.3). In total, there were 7 rural businesses included in the sample, of which 5 were in deprived rural wards.

With respect to size and sector of the interviewed businesses Table 6.4 provides a summary of their characteristics. Over half (56%) could be classified as micro-enterprises (currently less than 10 employees) while a small number employed more than 50 employees. This reflects the characteristics of the respondents of the telephone survey (see Section 3.2). Service sector businesses predominate although 13 of the 34 interviews were with businesses in the production sector. However, representativeness was not the prime concern here as the objective was to include a variety of ‘cases’ of assistance.

24 The purpose of the 3 non-assisted interviews was to understand the key factors related to the performance of the business and to ascertain the role of external assistance, including Business Link.



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Table 6.2: Type of Assistance by BLO

Government Office Region BLO

Intensively-assisted

Other-assisted

Non-assisted

South East Berks & Wilts 1 West Midlands Birmingham 1 East of England Cambridge 1 West Midlands Coventry 2 East Midlands Derbyshire 3 East of England Essex 2 South East Kent 3 Greater London London 3 1 2 East of England Milton Keynes 2 East Midlands Northants 1 North East Northumberland 2 East Midlands Nottingham 2 East of England Suffolk 2 South East Surrey 2 South East Sussex 1 1 North East Tyne & Wear 2 Total 25 6 3

Table 6.3: Business Link Model by Urban/Rural Area

BLO Delivery Model (Mole Classification)

Area 1 2 3 4 Rural (of which deprived)

1 (1) -

2 (2)

4 (2)

Urban 8 3 9 4 Total 9 3 11 8

Table 6.4: Industrial Sector by Employment Size Current Employment Size Sector 1-9 10-49 50+ Total Construction 2 3 1 6 Primary 0 1 0 1 Manufacturing 4 1 2 7 Services 13 6 1 20 Total 19 11 4 34



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6.4 Intensively-Assisted Businesses The majority of the face-to-face interviews were conducted with intensively-assisted businesses (n=25) and the aim of this section is to add to the analysis set out in the previous chapters. In particular, a number of issues have already been identified that might be further explored through the qualitative data. For example,

• There is some evidence that the type of delivery model matters in terms of the impact upon business performance for intensively-assisted businesses (see Chapter 5, Table 5.19) – but, from the perspective of the business, it is important to investigate the particular ways in which this may or may not be important.

• External brokerage was more common in the provision of services to

intensively-assisted firms. A considerable external brokering by BL staff was to non-fee paying services rather than market based services. Further, it would appear that internal brokerage – to a fee-paying service within BL – was operating for around a quarter of intensively-assisted firms. Can the interviews provide further insights into the nature of this ‘internal’ BL assistance and the way it compares with or indeed connects to other ‘external’ forms of brokered support?

• Nearly a third of intensively-assisted firms reported that they were more

inclined to use external support services as a result of their support from BL. The most commonly reported impacts of BL assistance were on company image, planning capability and firms’ ability to deal with regulation and compliance. Least common were effects on export capability and technical capability.

• In each area of influence on the business BL was identified as the crucial

influence levering change within the firm by a significantly higher proportion of firms in the intensively-assisted group. What exactly were the types of changes being implemented and what impact did they have on business performance?

• Additionality was self-reported by intensively-assisted businesses as follows:

o A quarter (23%) of intensively-assisted firms reported that the same business achievements would have been made without BL assistance – i.e. total deadweight.

o A further quarter (25%) of intensively-assisted firms said outcomes would have been the same without assistance but BL assistance helped to accelerate business development.

o Two-fifths (40 per cent) of intensively-assisted firms reported business outcomes which, without BL assistance, they would not have achieved.



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• Finally, the econometric models showed that for the intensively-assisted group of firms there were some ‘assistance’ effects (see Chapter 4) which can be explored through the qualitative data:

o Intensive assistance is found to have a positive and significant impact

on employment growth increasing firms’ employment growth rate by 2.8 percentage points.

o Intensive assistance has a positive but insignificant effect on firms’ sales growth, increasing sales growth by 1.9 percentage points.

o Intensive assistance has a negative but statistically insignificant effect on firms’ labour productivity, decreasing productivity growth by 2.8 percentage points.

The remainder of this section is organised as follows. The discussion commences with perspectives on the nature and delivery of ‘intensive’ assistance and concludes with a qualitative assessment of the impact of that assistance upon business performance. 6.4.1 Contact with Business Link For the majority of this group of intensively-assisted businesses it is clear that, in general, the relationship with Business Link pre-dated April 2003. There was a range of previous assistance dating mostly from 2000-01, although in a small minority of cases the business had been a client of Business Link for over 10 years. The type of support previously received from Business Link included:

• help with start-up support (e.g., financial planning, marketing, premises); • participation in seminars and/or networking events related to specific business

issues (e.g., staff training, funding, exporting, ICT issues) organised by Business Link alone or in partnership with the local Chamber of Commerce;

• specific support on exporting and/or technical matters. Therefore, the assistance received by these businesses from Business Link in the April-September 2003 period was, with one or two exceptions, within the context of an existing relationship (though not necessarily an ‘intensive’ one) with the local BLO. One obvious implication of this prior relationship is the ability of the business to accurately separate out the impact on the business of previous support from Business Link from that received in the period under consideration in this study. Nevertheless, having established the existence and nature of a previous relationship at the outset of the interview it was possible to ensure that the subsequent discussion of the impact of the ‘2003’ tranche of support was handled more carefully to reduce this ‘contamination’ effect. Further reassurance about the influence of prior assistance was obtained when all but of the interviewees were able to recall (some after a little prompting) the specific reason for their involvement with Business Link in the target period and the details of the assistance received.



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Across the 25 intensively-assisted businesses there was a mixture in the ‘direction of initiation’ of the contact with Business Link. The majority of interviewees reported that they had been the ones to initiate the contact for assistance in the April-September 2003 period, although some of the respondents acknowledged that it was in response to a specific mailing from the Business Link (e.g. concerning the Passport to Export scheme) or as a result of discussions with their Business Advisor. It became clear that those businesses assisted following discussions with the Business Advisor were among the first group classified as ‘intensively-assisted’, whereas the remainder of businesses interviewed were categorised as such subsequent to their approach to Business Link in the target period. It should be noted that there were a small number of firms who were unaware that they were classified by Business Link as ‘intensively-assisted’ and these were mostly micro-enterprises in the service sector. Those that had made the initial contact were generally motivated by the desire to obtain funding for specific actions in areas that they themselves had identified within the business – primarily marketing, ICT and technical support. From their previous experience of Business Link support they were seeking support and assistance on the basis of a combination of the ‘unique service and a subsidised price’ provided by Business Link - a phrase that was volunteered by respondents on a number of occasions. A number of businesses were able to discuss in detail the price they had paid for assistance previously received and the reduction in outlay/costs they had achieved as a result of using Business Link. What alternative services were available in the market place? A number of respondents reported that they were aware of, and indeed had used, alternative providers of support and advice. A common observation was that it was very difficult to ‘find the right person’ and in general they ‘were expensive for the return obtained’. 6.4.2 Nature and Delivery of Assistance The nature of the assistance received by this group of intensively-assisted businesses was wide-ranging and included the following:

• Strategic Action Plan – leading in all cases to further actions in generic areas (see below)

• Human Resources – Investors in People (IiP); STEP Programme; Go for

Growth Programme (managerial competencies); staff development/employee training

• Technical Capability – SMART Award; ICT development; website design &

development; ISO 9000 Quality Assurance Award • Marketing - Passport to Export Scheme; advertising; market intelligence on

new market areas (geographic and sectoral); marketing plan



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• General Business Advice and Support – liabilities insurance, business

planning; financial management & payroll; Health & Safety; employment law Seeking accreditation with IiP was the most common form of support service provided by Business Link to this group of businesses in the period under review and the experience was a very positive one in that it had wider benefits than simply staff training and appraisal. Many of the respondents were able to integrate the systems and procedures introduced as a result of the IiP award into the wider process of business planning and financial management of the business. A frequent comment of the IiP accreditation process was that it represented excellent value for money ‘for an outlay of £1,500 to Business Link it allowed the business to grow by around £50,000’. The role of the Business Adviser in the delivery of support services has been an integral part of any assessment of the overall impact of the Business Link network (see for example, Bennett and Robson, 1999; 2003b; Roper et al., 2001). In this qualitative assessment of the impact of Business Link support services we sought to assess the value of the PBA within the context of a group of intensively-assisted businesses. Interestingly, not all the intensively-assisted businesses reported (unprompted) that they had been assisted by Business Link in developing a Strategic Action Plan (SAP) following a process of ‘diagnosis’. Instead, they tended to focus on the specific forms of assistance (e.g., grants or accreditation) that they received without acknowledging that it was set it in the context of a wider review of the business25. This was especially the case for some of those businesses who were pursuing the IiP award. However, when prompted, all the respondents recalled some process of ‘diagnosis’ taking place with the business advisor from Business Link which led to some form of ‘action’. The views on the value of the SAP, and the role of the Business Adviser, were mixed. Some respondents felt that it was too general (‘just a collection of ideas really without much direction’ – ‘not enough expert knowledge of the business to be helpful’) which perhaps explains why it was not mentioned when questioned about the nature of assistance received. However, there were others (the majority of this group) who valued not only the final outcome but the actual process of sitting down with an external business advisor and reviewing the strategic direction of the business. The following comments illustrate the value placed on the development of the SAP by this group of intensively-assisted businesses:

25 Interestingly, the results from Wave 5 of the DTI Business Support Product Survey (2005) provide some corollary evidence on this point. Business Performance Diagnostic (BPD) recorded a lower score across a number of output measures than in the previous surveys. This would appear to be a result of the decline in overall satisfaction with the ‘product’. One possible interpretation is that the respondent is more inclined to value the ‘end result’ (e.g., a grant application) of the diagnostic process rather than the process itself. The qualitative evidence presented here from the face-to-face interviews with intensively-assisted Business Link clients, albeit regarding assistance received in the April to September 2003 period and therefore a slightly different ‘product’, lends some supportive evidence for this interpretation.



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“The advisor was like a ‘critical friend’ at the initial meeting. They talked through different ways in which to develop the business and the advisor gave some advice on things the advisor thought might not be a good idea to do based on the advisor’s experience and some things that the advisor thought it might be a good idea to do……, and then when the advisor had finished the advisor wrote a letter summarising the advice that he’d given. It was then up to me to turn this into a strategic document for the business – I feel it was unrealistic to expect the business advisor to write a SAP for the business. The most important aspects of the services have been helping to evaluate options for taking business forward” (Business Service Firm - to technology-based businesses).

“The advisor visited the company. In the beginning they just went through

what the company was doing at the moment and where did the company think it wanted to expand, which we didn’t really know. After couple of months, the advisor focused the company on what the best plan was for the company to expand. The most important aspect of the services and support is that it opened our eyes to the opportunities and highlighted markets which we thought were impossible”.

“In addition, the Business Link advisor carried out a financial audit, which highlighted areas for improvement that we have tried to implement, such as tightening up credit controls”.

As the SAP was being taken forward in these businesses there was a range of internal/external brokering taking place depending on the nature of the assistance and support being sought. Again there were a range of views expressed which demonstrated the importance of the signposting process to sources of advice and support external to the Business Link. For example;

“Business Link is more useful for ‘general’ businesses matters, or for signposting. For specialised services, such as finance or marketing, other providers are more useful – e.g. EnTrust, who we have used on various occasions without going through Business Link. As a result, Business Link can’t be said to be better or worse than other business advice services – more a case of ‘horses for courses” (Publishing Company; 7 employees).

“Business Link signposted the business to a number of subcontractors who could help design a website, from which I was able to choose one. This subcontractor also helped out with marketing – creating brochures and a corporate profile – as well as some in-house training which has given the business the impetus to take on a full-time in-house IT technician.” (Mail Order Battery Specialist; 10 employees).

“…and just talking to somebody objective who understood businesses …

It wasn’t that he told me the actions to take as part of the plan for the business….. He just asked me the right questions and gave me the questions I should ask myself and then pointed in the right direction to find the people that gave me the answers. He put me in touch with someone for



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premises, put me in touch with someone for training in business management. He showed me how to get some funding discount on the training.”(Business Services – Construction Site management: 7 employees).

A number of the intensively-assisted businesses included in the face-to-face interviews were located in rural areas (5 of the 7 were in deprived rural wards). Unprompted the value of regular visits by the Business Link Business Advisor and rurality were connected by one or two of the respondents:

“Businesses, particularly us in rural areas that are isolated, need that critical friend to be there even if it’s just for a chat and say ‘Well, everything seems fine - carry on what you’re doing’.. and that’s lost recently …. due to the introduction of targets….they may have, you know, a target that each Business Link advisor has to see 10 people a day. Well, they can’t see 10 people a day in a rural area. It’s simply impossible. So what happens is, you know, Business Link will concentrate on the town and cities because they can get round 10 people a day in that area. I see my advisor less and less now”. (Publishing Business: 1 employee).

We have already reported from the telephone survey that there is a general degree of satisfaction with the support and advice provide by Business Link (Table 3.5). Almost 8 out of 10 intensively-assisted businesses in the telephone survey were either satisfied or very satisfied with the support provided. The evidence gathered from these face-to-face interviews clearly supports that aggregate assessment and provides a greater sense of why the Business Link ‘brand’ received that high level of endorsement. In brief, it reflects the way in which the majority of businesses feel that their needs are being served by a Business Link network which has access to a wider pool of expertise (i.e. the ‘unique’ product) at a subsidised price. The previous Chapter has highlighted the complexity of the Business Link ‘brand’ throughout the network and how, in fact it does seem to matter in terms of the modelling of business performance (see Table 5.18). However, for the perspective of the individual assisted businesses it is clear that the distinction between ‘light-touch’ and ‘managed’ brokerage is impossible to discern in the narrative of the nature and style of delivery of the assistance received.



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6.4.3 Impact on the Business

The primary focus in this study is to identify the scale of the economic impact of business support services provided by Business Link. Having discussed the nature of the support received by this group of intensively-assisted businesses and ascertained their views on their experience of working with the Business Advisor we now turn our attention to the qualitative assessment of the impact of Business Link assistance.

We have seen in Chapter 4 that for the intensively-assisted group of businesses:

• There were positive and significant employment growth effects attributable to Business Link assistance in the econometric models of business performance – and sales growth effects for one of the four BLO Delivery Models (Model 4);

• In response to the self-assessment additionality questions (see Table 4.9) 40 per cent of intensively-assisted firms reported business outcomes which, without BL assistance, they would not have achieved. A further 25 per cent of intensively-assisted firms said outcomes would have been the same without assistance but that Business Link assistance helped to accelerate business development.

The following points from the group of intensively-assisted businesses help explain both the positive ‘hard’ and ‘soft’ outcomes reported in the aggregate analysis. In terms of enhanced performance as measured by sale, employment, productivity and profitability we report the following illustrations:

“The business was not growing as I expected in the niche market where competition was not an issue. The business would not have achieved the improvements without the help from Business Link. Business Link helped to define the focus of its services for technology companies. Business Link has helped me to really understand that I needed to focus on one particular market, whereas originally I was going out to business everywhere, which was a waste of time. Another improvement of the business is increased turnover, as a direct consequence of focusing on technology companies.” (Business Services; 2 employees). “The help provided by Business Link had changed the way of the company’s thinking totally. I changed from being ‘don’t want to know’ to ‘being very game to get the businesses’. Business Link has changed my attitude more than anything else. The company’s overseas business and direct sales has increased primarily from the Web….the company would not have achieved this without the help from Business Link. The company would have just plodded on as we were without any thought in terms of overseas business”. (Business Services; 17 employees).



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“Very satisfied with the IiP course … definite value for money – allowed the business to grow by around £50k for a cost of £1.5k. However, extraneous problems have meant that the business has a lower turnover now than it did 3 years ago”. (Publishing; 1 employee).

“Because the Partners have now seen the strategic impact of IiP on the fee income generated across the legal team…., and if you analyse out our training, the training that we’ve been doing in departments that have been growing, the two match…..and if that’s what you can do by actually organising all this sort of stuff, then perhaps we can do the same with the strategy”. (Financial Services, 100 employees)

“Since 2002 Business Link have worked with the company to improve marketing, including increasing PR work, creating a logo for the firm and improvements to the product catalogue, all of which have helped the business to grow and diversify its markets and generate additional sales as a result”. (Business Services; 13 employees – rural deprived location)

We have already stressed the importance of the subsidised prices of Business Link assistance. The following example illustrates the value in cost reduction of the assistance and connects that outcome to the fact that without the ‘free’ participation in the STEP Programme then these benefits would not have been achieved:

“The company saved thousands on IT by having it set up by this 19 year old on the STEP scheme rather than paying for it commercially, which Mr Mackenzie said would have cost £25,000 minimum. Another benefit has been the saving of £3,000 per year in stationary too. The project completely changed the structure of the information flow within the business… and the company now has …a complete grip of the information within the four walls. We’re a very tight company organisation and systems wise, and all that has been achieved directly through the involvement of Business Link. We would never have been able to achieve anything like this if we had had to pay for it themselves, and …..would never had the time himself to learn and set up a new computer system and so they would have struggled on with the far more inefficient old one”. (Manufacturing; 11 employees)

With respect to the ‘softer’ forms of impact the following example illustrate the diversity of effects that the Business Link package of support has had on the business. The implication of many of these comments is that it may take some time to see the benefits in terms of quantitative business performance measures:

“There were some soft benefits resulting from the help of Business Link. These include increased company image and publicity that may lead to more future business. There was no ‘hard’ benefit like



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increased revenue so far”. (Manufacturing; 3 employees – rural location)

“The impact has been quite large coming in the form of changes of my behaviour and in the form of a better relationship between myself and the workforce. ...we are developing now more team orientated sales than individual orientated sales. I have changed my role…significantly in the business… I have taken a much more hands on role in getting involved than I was previously…I was delegating a lot of the responsibilities to the running of the business to a managing director and sales manager, and to help me spend more time on the development of the business. But what I realised was that the external development of the business, it really needed to be developed from the inside out of the business, this is where my thinking has changed”. (Services; 10 employees – rural deprived location)

“….. the impact on the business of the Business Link assistance had been quite big. The changes made to achieve the ISO9000 had brought substantial improvements in quality control with a few simple changes such as re-arranging the production line and making more careful checks on ‘finished’ products which had resulted in improved customer satisfaction with their products. The Investors in People had also made a difference by helping the business set up a proper structured training programme for employees. The changes brought in to apply for the Investors in People award have helped make a more contented and capable workforce. The company definitely wouldn’t have gone down the Investors in People route had it not been for Business Link who suggested IiP – nor the ISO9000 route either…the two were so intertwined”. (Services; 6 employees)

“Difficult to quantify the contribution Business Link have had to the success of the business but: I would not say they were critical, I would say they were a big part of the overall… scheme of things. I mean without some of their advice and help we may not be as far as we are.” It seems to be in ‘professionalising’ the business and its processes that Business Link has been most useful in improving our performance”. (Manufacturing; 8 employees)

We noted above that there was a high degree of partial additionality present in the overall sample of intensively-assisted businesses. The interviews provide an opportunity to explore the telephone survey ‘self-assessment’ in more detail. The following four examples help us understand the nature of this partial addionality:

“The assistance given by Business Link was important in two ways. Firstly the new computers and the networking of the office computers has brought greater efficiency in the office and secondly, through



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giving the company an improved profile and extra sales. For example having a good website draws in potential customers because the firm looks professional and reliable. …if they see a decent website…it’s not a little tiny company on the edge of nowhere that doesn’t do anything…the website does get your profile…better known…I think it give a professional image. We now get almost daily correspondence through the website whereas prior to the new website there was very little. In addition the company is now selling over the internet too, to places in Kent, Surrey and Doncaster, where we had not sold to before. We probably would have gotten the website done eventually but not as quickly and maybe not as professionally. Business Links role was helping us find good, competent people to carry out the setting up for the website”. (Construction; 15 employees)

“The impact of the assistance given by Business Link was to enable the business to get things started and done earlier than perhaps would have been the case. We would have gone ahead both with starting up the business in the first place and expanding it into cleaning with or without the help of the Business Link advisor. …with their help it was a case of achieving it, in two years as opposed to achieving it in three”. (Business Services; 9 employees) “The website would possibly still not be in existence, as we had not recognised a need for it prior to Business Link’s involvement. We are now getting around 1600 visits per month on the site. Generally, the IiP has improved the efficiency of the business in terms of the way the office and staff are managed; the overall feeling is that ‘we would have achieved the same results, but not as quickly”. (Business Services; 13 employees)

Not all intensively-assisted business that we talked to were as positive about the impact of Business Link assistance as the following comment illustrates:

“The Business Link facilitated support and grants haven’t massively impacted upon the business, but AC feels that this is because they were dealing with fairly mundane things. …….It’s hard to pinpoint whether Business Link have affected the growth or not, although the grants etc. may have sped up the process a little”. (Construction; 15 employees)

6.5 Other-Assisted Businesses

From the 6 interviews with firms in this group it is clear that a variety of assistance was being offered from the Business Link local service ranging from what is considered the minimum of ‘assistance’ such as the provision of information on the ‘How to…’ aspects of business, as well as networking events on general and specialist topics through to the sign-posting to significant inputs of advice eventually provided



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by specialist third parties. Some examples will serve to illustrate the range of assistance. First, there would appear to be what might be termed ‘administration’ support which the following comment illustrates.

“the contact with Business Link came about because we were told that before we were able to go on a Trade Mission to China we needed a letter from the local Business Link – to confirm that we existed more than anything else. I think that then enabled us to access the small amount of support provided - but that was unimportant – we needed the letter before we could get on the place – I had never been in contact with Business Link before then – I had assumed they were for very small start-up businesses.” (Chemical manufacturer; 10 employees).

Second, attendance at networking events brought many businesses into the ‘other-assisted’ category and the range of experience was mixed:

“the networking event was designed to allow businesses to ‘pitch’ to each other in terms of fostering business but on this occasion the mix of businesses was not right for me and I left with no leads to pursue – I got the impression that the event had to be held irrespective of whether the attendees met the objectives for the event.” (Business Consultant; less than 10 employees). “We got some advertising and marketing support following a Business Link event around 2003 - it was their own staff who provided it if I remember - but it was quite basic advice really but it has enabled us to re-think our whole marketing strategy in the last two years which was necessary as we attempted to enter the American market.” (Central Heating System manufacturer; 55 employees).

Finally, there were more significant forms of support provided by third parties after an initial contact with the local Business Link:

“The company must have been on a mailing list as we received literature through the post which I initially dismissed along with other ‘junk’ mail. But I then noticed a feature article in one of them about staff training and it happened to correspond with a need I had identified in the business, in the context of the changes that I was implementing - changing the focus of the business to concentrate on the property development side of the business rather than contracting. All that happened was that Business Link passed on the name of the company who was providing the staff training and we took it from there – the development of the Personal Development Plans for senior and middle management has really changed the culture in the business and has laid the foundations for the future – but this has not really impacted upon the business in terms of increased sales or profitability.” (Property Development; 20 employees).



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“We use Business Link as often as possible as they are a constant source of specialist advice (IT; certification for ISO; IiP and grant applications) and much of this ends up in referrals to third party consultants – we have used them about 6-7 times since 2003 – for us they represent very good value and are very responsive.” (Service Firm – landscape architecture - drainage specialists for recreation areas; less than 50 employees).

The following business in the service sector which provided information for other small firms was a regular attendee at Business Link networking events and was fully aware of the range of support that could be accessed:

“We approached Business Link for help to develop our website…… we were put in touch with a specialist company who undertook the work – at rates considerably higher than others – and this was funded by Business Link.”

From this review of the ‘other-assisted’ group of firms it would be misleading to assume that they were only receiving low-level types of assistance. There is a wide variety of assistance provided to this group of businesses some of which resembles that received by intensively-assisted firms – especially the nature of third part support brokered by the local Business Link. We have no way of knowing how widespread this potential ‘problem’26 might be. Therefore, when we set out differences in the performance of these two groups of assisted firms (see for example, Table 3.7) it is important to remember that the distinction in the nature and scale of assistance received is not as clear as might have been originally envisaged. Of course, it is always possible that this lack of distinction may simply reflect the mis-classification of firms into the two groups by individual Business Links. There is also evidence of these businesses initiating the contact which serves to underline the market presence of the Business Link brand in certain areas. Very few of the interviewed firms could point to a tangible impact of the assistance received but, as with the intensively-assisted group, they were able to identify development sin their business which would not have taken place without the contact with Business Link. 6.6 Summary

The analysis and discussion in this Chapter has revealed the following points:

• There is a general positive endorsement of the Business Link ‘brand’ which

confirms the aggregate assessment. The majority of businesses feel that their needs are being served by a Business Link network which has access to a wider pool of expertise (i.e. the ‘unique’ product) at a subsidised price. This would appear to be true for both intensively-assisted and other-assisted firms.

26 The use of the word ‘problem’ refers solely to the obvious methodological difficulties for this economic impact study when we assume that the nature of support is markedly difference.



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• The time-scale is too short over which to measure the economic impact of Business Link assistance received in the April to September 2003 period. Many of the benefits have still to be realised as much of the assistance relates to ‘changed behaviour’ in terms of, for example, strategic focus and staff training – the expectation is for enhanced business performance in the years ahead.

• The distinction between ‘intensive’ and ‘other’ assist is somewhat blurred in a

number of cases which has implications for the impact assessment.



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7. Developing a Spatial Perspective on the Business Link Local Service

7.1 Introduction The evaluation study has to date provided a ‘national’ overview of the impact of the Business Link Local Service. The purpose of this chapter is two-fold. First, to provide an overview of the similarities and differences between intensively-assisted, other-assisted and non-assisted firms in the different Government Office Regions (GORs) across England. Our objective here is to provide a baseline against which future developments in the profile of assisted firms can be measured. In essence, this extends the analysis of Chapter 2, and highlights some substantial differences across GORs regions in the attributes and characteristics of assisted firms. Second, to provide headline data on the operation of Business Link in rural areas in England. For the purposes of this analysis we adopt a typology of rurality which reflects both morphology and context. As a result we use the following three-fold classification: urban, rural (less sparse) and rural (sparse). 7.2 Regional Baselines We start by considering the age characteristics of both firms and their owners, and then report on regional differences in the legal organisation of firms. Regional data on the sectoral composition of respondent firms, is presented. The next section reviews the strategic direction of respondents and suggests that there is limited regional variation in the strategic priorities of respondent firms. Finally, we present regional data on the number of directors in each firm, gender diversity, ethnic diversity, and the size of firms as measured by the number of employees and total turnover.

7.2.1 The Age Characteristics of Respondent Firms In Section 2.3 we reported that significant differences in the age distribution of intensively, other, and non-assisted firms were evident, and that BL assisted firms were in general younger than non-assisted firms. Table 7.1 sheds further light on this result. First, it suggests that within seven of the nine regions there are significant differences in the age distribution of intensively-assisted firms, other-assisted firms and non-assisted firms. Second, the test statistics for individual regions demonstrate significant differences in the age profile of intensively and other-assisted firms within the North West, Yorkshire and Humberside, and Eastern regions, which are not evident in other regions. This suggests that in these three regions, the age of firms may play a role in determining the type of assistance received by firms. Finally, separate tests for intensively (65.4) and other assisted firms (56.2) both provide statistically significant evidence for regional variation in the age characteristics of assisted firms. Moreover, it is unlikely that this reflects regional differences in the



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age profile of companies in general, because the control group of non-assisted firms do not exhibit such statistically significant variation (43.1). In sum, these findings suggest substantial differences across regions in the age of firms that are selected for BL assistance, differences which cannot be attributed to the underlying regional age profile of firms. Interestingly, a similar result is also evident in Table 7.2 which provides details on regional variations in the age of firm owners. As with firm age, the test statistics suggest statistical significant regional variation in the owner’s age for intensively assisted firms (53.3) and other assisted firms (66.6), while in contrast we find no significant variation for non-assisted firms (47.4). This suggests that there may be regional variation in the probability of receiving BL assistance that is not attributable to a more general regional variation in owner age. However, we also note that the within region tests suggest that only the West Midlands and East regions are characterised by any statistically significant differences in the owner age profile across the three types of firms. In particular, assisted firms in the West Midlands appear to have substantially younger owners than non-assisted firms.



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Table 7.1: Age of Firms by Region and Type

2-3 years

ago 3-4 years

ago 4-5 years

ago 5-10 years

ago 10-20 years

ago

More than 20 years

ago


North East 24.32 8.11 8.11 16.22 23.42 19.82

North West 15.6 6.8 6.1 13.6 30.6 27.2 South East 14.6 9.3 7.8 18.5 26.8 22.9

South West 10.8 4.2 8.3 23.3 21.7 31.7

West Midlands 13.8 5.4 2.3 20.8 30.0 27.7

Yorkshire and Humberside 11.9 3.7 11.9 21.1 16.5 34.9 East Midlands 7.8 5.8 9.7 21.4 28.2 27.2

East 6.9 9.9 8.9 26.7 15.8 31.7

London 8.1 8.1 14.1 21.2 22.2 26.3

All Regions 13.1 6.9 8.3 19.9 24.5 27.3


North East 14.5 12.0 5.1 21.4 25.6 21.4

North West 6.7 5.0 3.4 18.5 28.6 37.8

South East 9.5 7.2 8.7 18.9 28.4 27.3 South West 8.6 3.8 5.7 18.1 26.7 37.1

West Midlands 12.5 6.7 7.7 12.5 32.7 27.9

Yorkshire and Humberside 9.3 7.9 6.6 20.5 29.1 26.5

East Midlands 14.0 8.0 5.0 21.0 28.0 24.0 East 17.2 10.8 1.1 15.1 23.7 32.3

London 13.9 4.6 13.9 22.2 26.9 18.5

All Regions 11.3 7.3 6.7 18.9 27.9 27.9

Non-assisted firms North East 11.8 3.0 7.7 13.0 23.7 40.8

North West 9.4 5.1 5.8 15.9 28.3 35.5

South East 8.7 1.9 4.3 17.9 25.6 41.5

South West 9.1 3.0 7.1 19.2 29.3 32.3 West Midlands 7.0 7.0 3.0 12.0 27.0 44.0


East Midlands 11.1 6.5 3.7 13.0 12.0 53.7

East 10.8 3.6 3.6 15.3 28.8 37.8 London 3.1 5.2 7.3 13.5 29.2 41.7

All Regions 8.8 4.1 5.4 15.2 25.6 40.8 Chi-Squared Tests for Within Region Variation Between Firm Types

Intensively, Other, and

Non-assisted

Firms

Intensively and Other-

Assisted Firms

North East 32.54 5.42

North West 10.56 9.26

South East 30.51 4.32

South West 3.79 2.66

West Midlands 17.17 6.26

Yorkshire and Humberside 17.65 10.05

East Midlands 32.12 3.89

East 24.81 14.75

London 23.66 4.42

All Regions 78.42 6.30

degrees of freedom 10 5 Chi-Squared Tests for Between Region Variation By Firm Type

Intensively assisted firms 65.44

Other assisted firms 56.16 Non-assisted Firms 43.06

degrees of freedom 40 Note: Statistics in bold (bold italics) are significant at the 5% (10%) level.



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Table 7.2: Owner Age by Region and Type

Under 25 25 and 34 35 and 44 45 and 54

55 and

64

65 and over


North East 7.84 29.41 36.27 25.49 0.98

North West 6.5 29.8 30.6 31.5 1.6 South East 7.0 30.8 30.3 27.0 4.9

South West 0.9 9.3 26.9 35.2 25.0 2.8

West Midlands 0.9 14.2 31.9 35.4 13.3 4.4

Yorkshire and Humberside 8.9 26.7 42.6 20.8 1.0 East Midlands 9.4 28.2 40.0 17.6 4.7

East 9.1 25.0 53.4 12.5

London 7.1 32.9 38.8 18.8 2.4

All Regions 0.2 8.7 29.3 36.9 22.2 2.7


North East 14.3 33.7 30.6 18.4 3.1

North West 10.6 24.0 31.7 31.7 1.9

South East 5.8 27.1 34.3 24.2 8.7 South West 8.1 23.3 37.2 26.7 4.7

West Midlands 11.8 21.2 49.4 11.8 5.9


East Midlands 12.3 28.4 29.6 23.5 6.2 East 1.3 9.2 36.8 32.9 17.1 2.6

London 3.8 12.5 31.3 36.3 11.3 5.0

All Regions 0.5 9.7 28.2 35.2 21.1 5.2

Non-assisted firms North East 0.7 10.3 22.1 33.8 26.2 6.9

North West 4.8 37.1 26.6 25.0 6.5

South East 1.6 3.7 33.0 29.8 22.9 9.0

South West 11.4 23.9 38.6 20.5 5.7 West Midlands 3.4 5.7 35.2 29.5 20.5 5.7

Yorkshire and Humberside 9.3 23.7 38.1 22.7 6.2

East Midlands 1.0 9.0 24.0 29.0 33.0 4.0

East 1.0 4.1 25.5 40.8 20.4 8.2 London 1.3 6.4 34.6 28.2 21.8 7.7

All Regions 1.0 7.0 28.9 32.4 23.9 6.9

Chi-Squared Tests for Within Region Variation Between Firm Types

Intensively, Other, and Non-

assisted Firms Degrees of Freedom

Intensively and Other-Assisted

Firms Degrees of

Freedom

North East 14.06 10 4.89 4

North West 12.91 8 1.91 4 South East 13.46 10 3.60 4

South West 4.34 10 1.69 5

West Midlands 18.08 10 5.59 5

Yorkshire and Humberside 7.22 10 4.05 5 East Midlands 9.57 10 2.45 4

East 20.13 10 9.85 5

London 12.32 10 6.91 5

All Regions 31.65 10 10.75 5

Chi-Squared Tests for Between Region Variation By Firm Type

Test Statistic Degrees of Freedom

Intensively-assisted firms 53.32 40

Other-assisted firms 66.61 40 Non-assisted Firms 47.39 40

Note: Statistics in bold (bold italics) are significant at the 5% (10%) level.



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7.2.2 The Legal Status of Respondent Firms Table 7.3 analyses regional differences in the legal status of firms. Here, we find significant differences between the legal status of intensively, other, and non-assisted firms. Moreover, the test statistic for differences in the distribution of legal status between intensively and other assisted firms (51.55) confirms that a statistically significant difference is present between the regional profile of intensively and other-assisted firms. However, it is also worth noting that while 7 of the 9 regions demonstrate statistically significant variation when all three types of firms are included, only five demonstrate a statistically significant difference between intensively and other assisted firms. This therefore, suggests that the aggregate level finding that non-assisted firms are less likely to be limited companies, than other assisted firms, and that other-assisted firms are in turn less likely to be limited companies than intensively-assisted firms, does not hold in all regions. Separate tests for intensively-assisted (58.67), other-assisted firms (60.58, and non-assisted firms (29.88) provide interesting evidence with regard to the regional variation in the legal status of assisted firms. The control group of non-assisted firms suggest that there is not a statistically significant relationship between regional location of a firm and its legal status. In contrast, in the case of both intensively assisted and other assisted firms, the distribution of firms by legal status is found to be significantly different between regions. Our results, therefore, suggest significant regional variation in the legal status of assisted firms, which is not present amongst non-assisted firms. This further suggests that BL assistance selection criterion vary from region to region.



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Table 7.3: Legal Status of Firms by Region and Type

Sole trader Partnership

Private Limited

Company Other


North East 22.9 18.3 55.0 3.7

North West 21.6 18.9 56.1 3.4 South East 10.3 10.8 73.9 4.9

South West 22.1 12.3 62.3 3.3

West Midlands 9.9 10.7 72.5 6.9

Yorkshire and Humberside 9.0 7.2 76.6 7.2 East Midlands 13.7 10.8 70.6 4.9

East 8.0 10.0 76.0 6.0

London 9.0 7.0 76.0 8.0

All Regions 14.1 12.0 68.7 5.2


North East 27.7 16.0 48.7 7.6

North West 24.4 25.2 47.9 2.5

South East 26.9 11.7 52.3 9.1 South West 30.5 16.2 46.7 6.7

West Midlands 17.3 16.3 55.8 10.6

Yorkshire and Humberside 30.0 14.7 49.3 6.0

East Midlands 19.4 13.6 62.1 4.9 East 13.8 8.5 71.3 6.4

London 21.3 4.6 71.3 2.8

All Regions 24.4 14.0 55.1 6.6

Non-assisted firms North East 33.7 23.7 36.7 5.9

North West 28.1 15.8 50.4 5.8

South East 29.8 15.9 48.6 5.8

South West 25.0 19.0 50.0 6.0 West Midlands 21.0 16.0 59.0 4.0

Yorkshire and Humberside 25.4 23.7 43.9 7.0

East Midlands 32.4 19.8 42.3 5.4

East 31.2 13.8 47.7 7.3 London 22.9 10.4 58.3 8.3

All Regions 28.4 17.8 47.7 6.1 Chi-Squared Tests for Within Region Variation Between Firm Types


Non-assisted

Firms

Intensively and Other-

Assisted Firms

North East 11.87 2.65 North West 6.97 2.42

South East 39.60 27.47

South West 7.51 5.96

West Midlands 12.60 7.24 Yorkshire and Humberside 36.12 24.34

East Midlands 19.83 1.88

East 25.90 1.80

London 14.50 8.44 All Regions 114.90 51.55 degrees of freedom 6 3 Chi-Squared Tests for Between Region Variation By Firm Type

Intensively assisted firms 58.67

Other assisted firms 60.58

Non-assisted Firms 29.88 degrees of freedom 24




129

7.2.3 Regional Differences in the Sectoral Composition of Respondent Firms Tables 7.4 and 7.5 provide an analysis of regional variation in the sectoral distribution of firms in the sample. In Table 7.4, the Chi-squared tests for between region variation for each firm type confirm that intensively assisted (273.35) Other-assisted (150.11) and non-assisted firms (126.38) all exhibit statistically significant regional variation in sectoral composition. This is as we should expect, given an underlying pattern of relative concentration of various industries in different regions of the country. However, the test statistics for within region variation between firm types, also suggest substantial variation in the sectoral distribution of firms. Thus, in 7 of the 9 regions, statistically significant differences are found when we test for differences between the sectoral distribution of intensively, other, and non-assisted firms. However, when narrowing the test to find differences between intensively and other assisted firms, only in the North West, South West, Yorkshire and Humberside regions exhibit statistically significant differences. These results suggest that while in most regions there are substantial differences between non-assisted and assisted firms, in most regions, the sectoral composition of intensively and other assisted firms do not significantly differ. Table 7.4: Test Statistics: Sectoral Composition by Region and Type Chi-Squared Tests for Within Region Variation Between Firm Types


Non-assisted

Firms

Degrees of

Freedom

Intensively and

Other-Assisted

Firms

Degrees of

Freedom North East 31.26 22 10.68 10 North West 38.94 22 16.95 10 South East 50.93 22 16.32 11 South West 47.07 22 20.94 10 West Midlands 30.50 22 10.64 11 Yorkshire and Humberside 44.33 20 29.46 10 East Midlands 44.44 22 11.44 10 East 27.67 20 13.32 9 London 41.38 20 12.17 10 All Regions 155.41 26 23.60 12 Chi-Squared Tests for Between Region Variation By Firm Type Intensively assisted firms 273.35 88 Other assisted firms 150.11 80 Non-assisted Firms 126.38 96




130

Table7.5: Sectoral Composition by Region and Type

Agriculture, hunting &

forestry Fishing Manufact-

uring

Electricity, gas and

water supply Construction

Retail, wholesale & repair of motor vehicles

Hotels and

catering

Transport, storage

and comm-

unication Finance

Real estate,

renting and

business activities Education

Health and social

work

Other community,

social and personal

service activities

Intensively-assisted firms North East 4.55 21.82 3.64 16.36 6.36 5.45 1.82 22.73 7.27 2.73 7.27 North West 11.5 24.3 0.7 6.8 12.2 12.84 2.70 14.19 2.03 6.76 6.08 South East 3.4 16.5 0.5 4.4 14.1 1.94 3.40 1.46 38.83 0.49 10.68 4.37 South West 18.0 18.9 3.3 14.8 6.56 3.28 22.95 1.64 6.56 4.10 West Midlands 3.0 37.9 0.8 3.0 15.9 2.27 3.03 0.76 18.94 1.52 6.06 6.82 Yorkshire and Humberside 1.8 42.7 6.4 15.5 0.91 1.82 20.00 1.82 6.36 2.73 East Midlands 3.9 26.2 3.9 18.4 0.97 2.91 28.16 1.94 7.77 5.83 East 5.0 19.0 12.0 17.0 4.00 4.00 27.00 1.00 6.00 5.00 London 4.0 7.1 10.1 2.02 3.03 2.02 56.57 1.01 3.03 11.11 All Regions 5.8 23.4 0.3 5.4 14.8 4.34 3.10 0.88 27.70 1.95 6.64 5.75 Other-assisted firms North East 5.8 20.0 6.7 16.7 10.83 1.67 0.83 20.00 3.33 8.33 5.83 North West 9.3 19.5 2.5 16.9 10.17 6.78 27.12 1.69 2.54 3.39 South East 3.0 16.7 9.9 16.7 4.94 1.90 0.38 34.98 0.76 5.70 4.94 South West 4.8 11.5 3.8 13.5 6.73 0.96 1.92 42.31 1.92 6.73 5.77 West Midlands 2.9 24.0 4.8 18.3 4.81 1.92 3.85 25.00 1.92 7.69 4.81 Yorkshire and Humberside 4.0 21.3 4.7 22.7 6.67 3.33 24.00 0.67 4.00 8.67 East Midlands 3.9 17.6 10.8 19.6 4.90 2.94 0.98 30.39 0.98 5.88 1.96 East 4.2 31.6 5.3 22.1 1.05 25.26 7.37 3.16 London 0.9 12.1 7.5 15.9 0.93 0.93 47.66 2.80 1.87 9.35 All Regions 4.2 19.0 6.6 18.0 5.67 2.41 0.77 30.95 1.46 5.50 5.42 Non-assisted firms North East 7.6 15.9 1.2 5.9 25.9 12.35 4.71 2.35 12.35 1.76 3.53 6.47 North West 5.1 21.0 5.8 26.1 10.87 2.90 2.17 13.04 0.72 5.80 6.52 South East 2.4 21.1 5.3 30.6 5.26 1.44 1.44 21.53 6.70 4.31 South West 3.0 14.1 2.0 2.0 21.2 13.13 1.01 3.03 21.21 2.02 9.09 8.08 West Midlands 9.0 24.0 8.0 28.0 3.00 2.00 1.00 12.00 1.00 5.00 7.00 Yorkshire and Humberside 5.3 19.3 7.0 30.7 7.89 3.51 0.88 17.54 2.63 5.26 East Midlands 3.6 0.9 18.2 5.5 36.4 7.27 5.45 0.91 10.00 10.91 0.91 East 6.2 0.9 23.0 4.4 26.5 7.96 3.54 16.81 1.77 4.42 4.42 London 1.0 11.5 7.3 27.1 6.25 2.08 4.17 23.96 2.08 6.25 8.33 All Regions 4.8 0.2 18.9 0.3 5.7 28.2 8.3 3.0 1.7 16.5 1.0 5.9 5.6



131

7.2.4 Regional Differences in the Strategic Priorities of Respondent Firms The first panel of Table 7.7 extends the analysis of differences in the strategic priorities of firms that was first presented in Table 2.5 (Table 7.6 presents the basic descriptive data). In this earlier analysis, we reported statistically significant variation across intensively, other, and non-assisted firms for all five strategic priorities identified in the survey. Nevertheless, the region specific tests suggest that these statistically significant differences are not present in all regions. Thus for example, in 6 regions there are statistically significant differences in the likelihood of intensively, other, and non-assisted firms to use a strategy increasing sales in new markets. In contrast, statistically significant differences in the likelihood of intensively, other, and non-assisted firms to engage in the strategy of developing new products for new markets are only evident in three regions. These results suggest the need for caution in generalizing differences in strategies between assisted and non-assisted firms to all regions. The second panel of Table 7.7 focuses solely on differences between intensively and other assisted firms. As a result, we first note that if we look at differences across all regions, there are only statistically significant differences between intensively and other assisted firms for three strategies, while there is no statistically significant difference for the strategies of increasing sales in current markets and developing new products for new markets. Moreover, at the regional level, there is much less evidence of statistically significant differences between intensively and other assisted firms. Thus, while in the South East Region, statistically significant differences in the strategic priorities of intensively and other-assisted firms are evident for four of the five strategies, three regions exhibit no statistically significant difference, two regions exhibit differences in the likelihood of two key strategies, and three regions exhibit differences in only one priority. As a result, we would suggest that much of the variation in key strategies that is evident at the aggregate level between intensively and other-assisted firms is actually attributable to variation in a limited number of regions. In particular, there is evidence of considerable variation in the strategies of intensively- and other-assisted firms in the South East region. Finally, the third panel of Table 7.7 tests for between region variations in strategic priorities for intensively, other, and non-assisted firms. These results largely suggest that there is little variation in strategic priorities that can be attributed to regional location. The primary exception to this appears to be with regard to the strategy of developing new products for existing markets, where statistically significant regional differences are found for all three types of firms. Similarly, we also find evidence of statistically significant regional differences in the likelihood of engaging in the strategy of maintaining sales in present markets, but only for other assisted firms.



132

Table 7.6: Proportion of Firms with a Given Strategic Priority: by Region and Type

Maintain Sales in Present

Markets

Increase sales in current markets

Increase sales in

new markets

New products

for existing markets

New products for new markets


North East 26.36 54.13 19.09 7.27 8.18

North West 28.4 54.7 20.8 5.4 3.4

South East 19.0 54.6 20.0 11.2 5.4

South West 26.2 54.9 11.5 7.4 1.6

West Midlands 23.7 46.6 23.7 13.7 7.6


East Midlands 18.6 57.8 21.6 7.8 3.9

East 24.8 63.4 18.8 5.0 4.0

London 24.8 62.4 23.0 3.0 1.0

All Regions 22.7 55.4 19.4 8.9 4.4


North East 25.2 47.9 13.4 16.0 5.0

North West 27.1 56.3 17.8 4.2 1.7

South East 38.1 49.8 10.9 6.4 1.9

South West 37.1 49.1 14.3 6.7 4.8

West Midlands 28.6 51.9 14.4 7.7 1.0


East Midlands 32.4 51.0 14.6 10.8 2.9

East 25.3 59.4 20.0 5.3 3.1

London 28.7 57.4 18.5 0.9 0.9

All Regions 30.9 52.7 14.3 7.3 2.4

Non-assisted firms

North East 42.0 42.6 8.9 8.3 1.8

North West 33.8 54.3 6.5 3.6 2.9

South East 40.2 47.6 10.5 5.7 0.5

South West 34.7 49.5 10.9 4.0 2.0

West Midlands 30.0 52.0 9.0 11.1 3.0


East Midlands 38.4 50.0 8.9 2.7 0.0

East 32.1 51.3 16.8 4.5 2.7

London 37.1 53.6 10.3 3.1 1.0

All Regions 36.2 50.0 10.4 5.7 1.6



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Table 7.7: Test Statistics for Regional Differences in Strategic Priorities Chi-Squared Tests for Within Region Variation Between Intensive, Other, and Non-Assisted Firms


Markets


Increase sales in

new markets

New products



North East 11.71 3.55 6.14 5.97 6.44

North West 1.62 0.11 12.57 0.57 0.73

South East 26.14 2.15 10.52 5.34 10.80

South West 3.44 0.98 0.65 1.17 2.38

West Midlands 1.32 0.93 9.32 2.15 6.86


East Midlands 10.29 1.53 6.76 5.60 4.12

East 1.83 3.32 0.36 0.07 0.30

London 3.74 1.57 5.68 1.38 0.01

All Regions 50.56 7.11 36.95 8.59 17.17 (All tests have 2 degrees of freedom)

Chi-Squared Tests for Within Region Variation Between Intensive and Other Assisted Firms


Markets


Increase sales in

new markets

New products



North East 0.04 0.88 1.34 4.15 0.92

North West 0.05 0.07 0.38 0.21 0.73 South East 20.14 1.08 7.48 3.43 4.25

South West 3.13 0.78 0.40 0.04 1.84

West Midlands 0.73 0.67 3.14 2.16 5.73

Yorkshire and Humberside 7.23 0.01 0.89 5.10 1.47 East Midlands 5.06 0.97 1.70 0.52 0.15

East 0.01 0.33 0.04 0.01 0.10

London 0.42 0.54 0.64 1.16 0.00

All Regions 19.75 1.85 10.53 2.08 7.16 (All tests have 1 degree of freedom)

Chi-Squared Tests for Between Region Variation By Firm Type


Markets


Increase sales in

new markets

New products



Intensively assisted firms 12.85 9.16 9.02 23.86 12.90

Other assisted firms 13.88 6.32 8.85 24.24 9.56

Non-Assisted Firms 8.59 6.67 9.15 13.56 7.07

(All tests have 8 degrees of freedom)




134

7.2.5 Regional Differences in Diversity, Director Numbers and Firm Size Tables 7.8 and 7.9 provide an analysis of regional variation in the average of several characteristics of firms that were considered earlier in Chapter 2. These include data on the number of company directors, gender and ethnic diversity, and firm size as measured by the number of employees and sales turnover. The first panel of Table 7.9 suggests that except for the case of ethnic diversity, there is little evidence of between region variation in these characteristics. However, with regard to ethnic diversity, we find statistically significant regional differences for intensively, other, and non-assisted firms. This finding should be expected, given substantial regional variation in the distribution of ethnic minorities in the UK. The one surprising result is the finding of statistically significant regional variation in gender diversity for other-assisted Firms. This appears to be driven by above average female representation in the South West and, North East and North West regions, and below average female representation in the West Midlands, East, and London regions. The second and third panels of Table 7.9 also suggest that there is relatively limited within region variation between intensive, other, and non-assisted firms. In fact, in only 13 of 90 tests for within region variation attributable to firm type do we find evidence of statistically significant differences in the regional averages. Of these significant differences, however, the most notable is the finding of statistically significant differences in size of firms, as measured by sales, between intensively and other assisted firms in the South West, West Midlands, and London regions. However, while in London and the West Midlands intensively assisted firms are, on average, larger than other-assisted firms, the opposite relationship is evident in the South West. There is also notable within region variation in gender diversity in both the South and the West Midlands regions, where both the tests including and excluding non-assisted firms find evidence of significant variation attributable to the type of firm. These results suggest that relative to the control group of non-assisted firms, firms in the South West region with female directors are more likely to receive other-assistance. In contrast in the West Midlands, firms with female directors are more like to receive intensive assistance, and less likely to receive other assistance. These results suggest that the gender of directors plays a role in assistance selection in these regions that is not evident in other regions. We also note that there is evidence that intensively-assisted firms are on average substantially larger than other assisted firm in Yorkshire and Humberside, and that the average ethnic diversity of intensively-assisted firm in London is significantly lower than that of other-assisted firms.



135

Table7.8: Average Firm Characteristics: By Region and Type

Directors and

Partners (No)

Gender diversity

– %

female

Ethnic diversity

– %

ethnic Employees

2005 Sales 2005


North East 2.2 29.0 1.9 19.2 1,773.3

North West 2.1 32.6 0.8 17.9 1,242.9

South East 2.1 30.3 2.2 21.9 3,064.0

South West 2.1 26.7 0.4 19.0 1,099.3

West Midlands 2.3 31.4 6.9 21.5 2,043.4

Yorkshire and Humberside 2.4 23.6 2.3 25.6 2,546.3

East Midlands 2.4 24.3 8.5 27.0 3,358.8

East 2.7 28.5 1.7 33.0 4,080.0

London 3.0 29.1 9.6 41.5 2,666.5

All Regions 2.3 28.8 3.5 24.3 2,432.5


North East 2.3 33.0 3.3 20.6 3,686.5

North West 2.2 32.8 2.6 18.5 1,399.2

South East 2.2 27.8 2.7 23.1 4,434.8

South West 2.4 36.1 0.8 15.5 4,062.2

West Midlands 2.7 21.3 4.7 35.9 8,239.9


East Midlands 2.5 30.0 3.3 24.9 2,966.6

East 2.2 23.9 0.5 111.5 2,849.7

London 2.0 24.7 20.5 15.3 1,375.4

All Regions 2.3 28.8 4.8 28.6 3,604.4

Non-assisted firms

North East 2.1 28.9 1.0 15.2 876.3

North West 1.8 28.4 3.0 15.4 1,977.5

South East 2.0 30.9 1.5 15.2 3,003.7

South West 2.2 26.5 0.0 21.2 5,824.2

West Midlands 2.2 25.6 4.2 16.4 4,244.2


East Midlands 2.2 28.1 4.4 13.3 4,720.8

East 2.1 23.6 2.8 21.2 3,984.6

London 2.3 26.3 15.2 38.4 1,648.0

All Regions 2.1 27.2 3.3 18.7 3,000.4



136

Table 7.9 Test Statistics for Regional Variation in Firm Characteristics ANOVA F-Tests for Between Region Variation By Firm Type

directors and

partners (No)

gender diversity

- % female

ethnic diversity

- % ethnic

Employees 2005

Sales 2005

Intensively assisted firms 1.50 0.95 4.96 1.35 0.95

Other assisted firms 0.77 2.01 8.33 0.85 0.33

Non-Assisted Firms 0.85 0.86 7.23 1.16 0.60

ANOVA F-Tests for Within Region Variation Between Intensive, Other, and Non-Assisted Firms

directors and

partners (No)

gender diversity

- % female

ethnic diversity

- % ethnic

Employees 2005

Sales 2005

North East 0.48 0.55 0.94 0.51 1.76

North West 2.95 0.64 1.04 0.36 0.46

South East 0.25 0.47 0.47 0.46 0.13

South West 0.98 2.70 0.77 0.68 1.01

West Midlands 1.74 2.48 0.52 1.92 1.97


East Midlands 0.52 0.66 1.61 3.23 0.08

East 2.06 0.74 0.97 0.59 0.11

London 1.69 0.43 1.94 0.88 1.93

All Regions 3.77 0.78 1.98 0.67 0.77

ANOVA F-Tests for Within Region Variation Between Intensive and Other Assisted Firms

directors and

partners (No)

gender diversity

- % female

ethnic diversity

- % ethnic

Employees 2005

Sales 2005

North East 0.12 0.71 0.44 0.08 1.01

North West 0.49 0.00 1.62 0.03 0.06

South East 0.07 0.58 0.15 0.02 0.15

South West 1.98 4.06 0.32 0.73 2.77

West Midlands 1.50 5.01 0.58 1.59 4.48


East Midlands 0.03 1.27 2.64 0.09 0.02

East 1.50 1.00 0.96 0.49 0.15

London 2.46 0.88 3.62 2.32 2.88

All Regions 0.09 0.00 2.15 0.18 1.59




137

7.3 A Rural Perspective In order to help develop an understanding of the operation of the Business Link network in rural areas DEFRA boosted the size of the national survey to facilitate a more meaningful analysis. Although it has not been possible to develop a rural dimension to the overall aggregate assessment of the value-added of Business Link we are able in this section to set out some of the headline indicators of differential performance of the assisted groups by type of rural area and to provide some assessment of the satisfaction with and additionality of Business Link assistance. As indicated in the introduction we develop a rural perspective to the analysis by adopting the following DEFRA classification: urban, rural (less sparse) and rural (sparse)27. Table 7.10 shows how the sample breaks down by assisted status and degree of rurality. Overall, just over a third of the sample is located in rural areas in England and these 1,233 businesses are split almost equally between sparse and less sparse rural areas: 541 and 692 business respectively. Table 7.10: Assisted Status by Urban/Rural Classification Intensively

-assisted firms No. (%)

Other-assisted firms No. (%)

Non-assisted firms No. (%)

All Firms No. (%)

Urban 709 (63.2) 714 (63.1) 734 (64.6) 2157 (63.6) Rural (less sparse) 252 (22.5) 223 (19.7) 217 (19.1) 692 (20.4) Rural (sparse) 161 (14.3) 194 (17.2) 186 (16.4) 541 (16.0) Total 1122 (100.0) 1131 (100.0) 1137 (100.0) 33901 (100.0) Source: BL Telephone Survey (2005) 1 It has not been possible to allocate 58 respondents to this classification due to problems with postcodes.

7.3.1 Firm Size and Performance There area clear size differences in the sample between urban and rural areas and also between less and more sparse rural areas – and indeed across the three assisted groups of firms (Table 7.11). Average employment for all respondents in urban areas was 28 persons which was higher than in the two rural categories (less sparse and sparse) were mean employment was 18 and 10 respectively.28 Median employment is also higher in urban areas compared to rural areas and the differences between the less sparse and more sparse rural areas are confirmed. Median employment in intensively-assisted firms is larger than in the other two groups of firms but the differences are less marked in the two rural areas. Sales data suggests a similar picture with average sales among sample firms in urban areas in the financial year 2004-5 being £3.49m compared to £2.57m and £674.5k in the

27 The recent evaluation report on “Improving Access to Business Advice in Rural Areas” (SBRC, 2005) focused on ‘lagging rural areas’ in terms of economic performance and it may be possible to undertake further analysis of this survey dataset for DEFRA using that typology. 28 The comparable data for the sample as a whole is presented in Chapter 3 (Table 3.6).



138

two rural areas respectively. Median sales figures for these three groups of firms confirm this pattern. Intensively-assisted firms in urban areas have a median sales figure in 2004-05 of £700,000 compared to between £500,000 and £260,000 for the two rural areas respectively. Although there is very little difference between intensively-assisted firms in urban and less sparse rural areas those in more sparse rural areas are markedly smaller. Table 7.11: Urban-Rural Firm Size Contrasts

Intensively

-assisted firms


Non-assisted firms

All Firms

A. Urban

Employment 2005

Mean 27.7 37.9 19.7 28.4 Median 12.0 8.0 6.0 8.0 Valid N 697 694 700 2091

Turnover 2005 (£000s)

Mean 2,728.8 4,412.9 3,839.7 3,491.5 Median 699.5 540.0 500.0 600.0 Valid N 408 222 305 935

Sales per employee

Mean 108,251.5 112,755.6 138,915.3 119,270.5 Median 57,142.9 52,283.3 63,189.2 59,894.0 Valid N 406 216 299 921

B. Rural (less sparse)

Employment 2005



Mean 2,327.5 4,050.6 1,965.4 2,566.7 Median 500.0 395.0 300.0 418.2 Valid N 126 59 94 279

Sales per employee


C. Rural (sparse)

Employment 2005




Sales per employee


Source: BL Telephone Survey (2005) Note: These figures differ slightly from those presented in Table 3.6 due to the 58 respondents that were

not allocated to one of the urban/rural categories.



139

Some interesting contrasts emerge, however, between the performance of firms in urban and the two rural locations (Table 7.12). Patterns of mean employment change are very distinct for urban and rural firms among the intensively-assisted firms, other-assisted firms and non-assisted firms. For example:

• Overall, all firms in less sparse rural areas have grown marginally faster than for the sample as a whole (see Table 3.7) and for firms located in urban areas more sparse rural areas.

• Intensively-assisted firms in less sparse rural areas grew more rapidly than in

urban areas and more sparse rural areas, although in the more sparse rural areas intensively-assisted firms grew marginally faster than their counterparts in urban areas.

• Both groups of other-assisted firms and non-assisted firms in urban areas grew

marginally faster than in the two rural areas but the differences were small. Turnover growth rates portray a great deal of variation between urban and rural areas and across the assisted groups:

• Mean turnover growth rates of firms in less sparse rural areas was significantly lower than in urban areas and, although the performance of firms in the more sparse rural areas was almost identical to that in urban areas, it is clear that this is a function of one or two high growth outliers in the other-assisted category of firms.

• Using median turnover growth rates the pattern is one of slightly higher growth in

less sparse rural areas compared to urban areas with the more sparse rural areas exhibiting the lowest growth rates.

• With respect to assisted status, and focusing on median turnover growth in order

to remove the effect of some extreme outliers in the dataset, the intensively-assisted firms in the less sparse rural areas grew at slightly slower rates than their counterparts in urban areas (8.2% compared to 9.9%) but at almost twice the rate as those intensively-assisted firms in the more sparse rural areas.

• The performance of the other-assisted group of firms was broadly similar across

the three geographical areas, while the non-assisted group performed considerably better in the less sparse rural areas compared to urban areas and the more sparse rural areas.



140

Table 7.12: Urban-Rural Performance Contrasts

Intensively

-assisted firms


Non-assisted firms

All Firms

A. Urban

Employment Growth


Turnover Growth


Sales per employee


B. Rural (less sparse)

Employment Growth


Turnover Growth


Sales per employee


C. Rural (sparse)

Employment Growth


Turnover Growth


Sales per employee


Source: BL Telephone Survey (2005) Finally, with respect to sales per employee there were again marked differences between the three assisted groups and across urban and rural areas:

• Sales per employee was higher in urban areas and in the less sparse rural areas compared to the more remote rural areas. This was particularly the case for other-assisted and non-assisted firms.



141

• Intensively-assisted firms in less sparse rural areas had a sales per employee of twice that observed in the more sparse rural areas and higher than in urban areas, although the median value was lower in the case of the latter comparison.

All these performance differences would suggest further examination in terms a more formal assessment of the impact of the nature and scale of Business Link assistance. In order to shed some light upon these differences we present data in the next section on the degree of satisfaction and perceived impact of Business Link assistance disaggregated by this urban rural classification.

7.3.2 Perceived Impact of Business Link by Rural Area We focus in this section on overall levels of satisfaction with the Business Link assistance received by firms in rural areas compared to urban areas and also present data on the perceived impact of that assistance using the self-assessment additionality question. The main motivation for getting in touch with Business Link follows broadly similar patterns for both assisted groups of firms across the three urban and rural areas except in one important respect. Around one-quarter of both intensively-assisted and other-assisted firms in more sparse rural areas reported that they approached Business Link to obtain funding which compares to an average of 15 per cent in urban and less sparse rural areas. In terms of the frequency of contact with Business Link in the last two years (i.e., 2003-2005) there is very little difference in the pattern for either intensively-assisted or other-assisted firms in urban or the less sparse rural areas: between a fifth and a quarter of firms report contact every month or better. However, for assisted firms in the more sparse rural areas this proportion falls to just over 10 per cent, with a significant increase in those reporting ‘less often than once a year’. Location made no difference to the types of advice provided to assisted firms. Factual advice and basic advice were received by similar proportions of intensively-assisted firms and other-assisted firms (see Chapter 3, Table 3.2), while in-depth assistance and ‘long-term or intensive-assistance’ was received by significantly more firms in the intensively-assisted group (25-28 per cent) than by other-assisted firms (14-21 per cent). We have already established in Chapter 3 that intensively-assisted firms consistently received more different types of support than other-assisted firms in the group of respondents (see Table 3.3). Table 7.13 concentrates on the intensively-assisted firms only it is clear that overall, there is a slightly different and significant pattern of BL assistance received by these firms in sparse rural locations compared to similar firms in urban and less sparse rural locations. In particular, we can see that intensively-assisted firms were slightly more likely to have received assistance on regulation and compliance issues (χ2 (2)=5.74, ρ<0.057) with obtaining funding (χ2(2)=7.87, ρ<0.020) and e-commerce (n.s.) and less likely to have received benchmarking and diagnosis (n.s.), help with finding external consultants (χ2(2)=7.48, ρ<0.024), advice on cost reductions or



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quality improvements (χ2(2)=4.83, ρ<0.089), help with marketing (χ2(2)=5.17, ρ<0.075) and advice on training (χ2(2)=12.87, ρ<0.002).

Table 7.13: Proportions of Intensively-Assisted Firms receiving Different Types of

BL Services by Rural Area

All

Urban

Rural (less

sparse) Rural

(sparse) % % % % General business information 57.3 58.3 55.0 55.6 Business benchmarking or diagnosis 13.6 14.2 14.3 9.6 Business planning, action plan development 39.7 38.4 40.6 40.9 Information on regulation and compliance 34.9 36.9 34.5 26.9 Help with finding external consultants 22.9 24.9 22.7 14.7 Help with raising finance 35.5 36.9 28.1 39.9 Help with making cost/quality improvements 15.4 15.5 18.1 10.1 Help with marketing 35.4 37.4 34.8 27.8 Help with R&D or New Product Development 12.3 12.6 11.3 10.1 Help with exporting 13.5 13.5 14.5 11.9 Help with training 41.0 44.7 37.6 30.2 Help with e-commerce 16.2 14.7 17.7 20.3 Help with IT issues 21.0 19.8 22.5 22.0 Anything else 7.0 6.0 9.2 8.9

Source: BL Telephone Survey (2005) With regards to overall satisfaction with the BL service, which as we have already seen are high from this cohort of firms, there was very little difference between the urban and rural areas (Figure 7.1). There were marginally higher levels of satisfaction in less sparse rural areas, especially among the intensively-assisted group of firms who also record the highest mean score in these rural locations (4.1 – maximum 5).



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Figure 7.1: Satisfaction with BL Service by Assisted Group and Rural Area (% Very satisfied and Satisfied)

0

10

20

30

40

50

60

70

80

90

Intensive Other All

% V

ery

Sat

isfie

d or

Sat

isfie

d

Urban Rural (less sparse) Rural (more sparse) All Firms were asked about the time horizon over which they expected their performance to reflect the benefits from BL assistance received during the previous two years (Table 7.14). We have already seen in Chapter 4 that these profiles differed significantly between intensively-assisted firms and other-assisted firms (see Table 4.8). Around half of firms, a slightly larger proportion of other-assisted firms, reported already having experienced all of the benefits; the remainder expected the benefits to accrue over future years. There are no significant differences in this pattern once we disaggregate the responses from the two assisted groups by the urban/rural status. The only small difference to note is that both groups of assisted firms in more sparse rural areas are more likely to have realised the benefits of BL assistance within the next 5 years than beyond this time horizon.



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Table 7.14: Time Horizons for Experiencing the Benefits of BL Assistance by Rural Area Intensively-

assisted firms Other-

assisted firms All

Firms

Urb

an

Rur

al (

less

sp

arse

)

Rur

al (

spar

se)

Urb

an

Rur

al (

less

sp

arse

)

Rur

al (

spar

se)

Urb

an

Rur

al (

less

sp

arse

)

Rur

al (

spar

se)

% % % % % % % % %

You have already realised all the benefits 47.5 49.6 47.1 52.4 50.7 50.0 49.9 50.1 48.7

You expect to realise all the benefits in the next year 13.5 12.7 14.0 12.6 17.8 15.8 13.1 15.1 15.0

You expect to realise them in the next 2 years 14.1 11.5 11.5 7.6 4.7 9.5 10.9 8.3 10.4

In the next 3 years 2.8 3.3 3.8 2.1 2.8 1.1 2.4 3.1 2.3 In the next 4 years 0.7 0.8 2.5 0.6 0.5 0.5 0.7 0.7 1.4 In the next 5 years 1.2 2.1 1.9 1.6 0.5 0.0 1.4 1.3 0.9 Or it will take more than 5 years to fully realise all the benefits of BL support 7.5 7.4 5.7 3.1 3.3 0.5 5.3 5.5 2.9

(No benefits experienced from Business Link support) 12.8 12.7 13.4 20.0 19.7 22.6 16.4 16.0 18.4

Source: BL Telephone Survey (2005) An additional approach to assessing the perceived impact of BL assistance is the standard additionality approach, designed to investigate whether additionality was ‘full’, or ‘partial’ (Table 7.15). Overall, responses were significantly different between intensively-assisted firms and other-assisted firms although the pattern of responses did not vary significantly across the urban and rural areas. The following points summarise the main urban-rural dimension of the responses:

• Firms in urban and rural areas were just as likely to report that the same business achievements would have been made without BL assistance – i.e. total deadweight was between 22 per cent and 34 per cent in rural areas.29

• Intensively-assisted firms were less likely than other-assisted firms to report ‘total

deadweight’ – although there is some evidence that assisted firms (i.e. both groups) in sparse rural areas were less likely to do so. For these firms the impact of BL assistance was to bring forward the business outcomes.

29 This is consistent with the recent evaluation of the DEFREA/BLO pilot initiatives in lagging rural areas (SBRC, 2005).



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Table 7.15: Additionality of BL Assistance by Rural Area Additionality Question Response Intensively-

assisted firms Other-

assisted firms All

Firms

Urb

an

Rur

al

(less

sp

arse

)

Rur

al

(sp

arse

)

Urb

an

Rur

al

(less

sp

arse

)

Rur

al

(sp

arse

)

Urb

an

Rur

al

(less

sp

arse

)

Rur

al

(sp

arse

)

% % % % % % % % %

Deadweight We would have achieved similar business outcomes anyway 23.2 25.0 21.7 36.6 34.1 34.4 29.9 29.3 28.7

Partial Additionality

We would have achieved similar business outcomes, but not as quickly 24.7 24.2 28.6 19.4 18.4 23.6 22.1 21.5 25.8

We would have achieved some but not all of the business outcomes 28.0 24.2 28.0 16.1 18.8 20.0 22.0 21.7 23.6

Full Additionality

We probably would not have achieved similar business outcome 9.5 9.5 8.7 5.0 5.4 6.7 7.2 7.6 7.6

We definitely would not have achieved similar business outcomes 2.4 3.6 1.9 2.9 1.3 1.5 2.7 2.5 1.7

No Response (None of these)

12.3 13.5 11.2 19.9 22.0 13.8 16.1 17.5 12.6

Source: BL Telephone Survey (2005) 7.4 Summary Regional Baselines In this chapter we have examined differences between the structural characteristics of intensively-assisted firms and other-assisted firms in each GOR. Detailed baseline results for each region are provided in the tables but it is useful to consider some general summary points. First, in terms of firm age we find significant regional variation which is not attributable to the underlying regional age profile of firms. The implication is that BLOs in different GORs are targeting assistance at significantly different age cohorts of firms. Second, an essentially similar result arises in terms of the legal status of assisted firms. Again, the suggestion is that BLOs in different GORs are targeting assistance at groups of firms with different ownership profiles. Third, there is a marked difference between the sectoral composition of assisted firms and the general population of firms in most regions. This suggests that in general terms there is effectively some sectoral targeting of assistance by BLOs. Fourth, ethnic diversity within the leadership teams of assisted firms also differs between regions. However, this is likely to reflect underlying differences in the distribution of ethnic minority populations within the UK. More surprising perhaps is that there is also



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significant variation in levels of gender diversity between the leadership teams of assisted firms, although the pattern varies between regions. While this does suggest that BLOs in some regions are more likely to be assisted female-led businesses it is not clear whether this is due to either targeting or differences in the underlying business population. In Southern regions, for example, where the opportunities for service sector activity are greater, female-led businesses may account for a larger proportion of all potential client firms. Finally, it is worth noting that there are also robust differences between regions in the size distribution of assisted firms. In London and the West Midlands intensively assisted firms are, on average, larger than other-assisted firms, the opposite relationship is evident in the South West. The differences identified between regions in the characteristics of assisted firms provide some support for the importance of the analysis in this chapter, and the development of differentiated baseline statistics for each region. They also emphasise, however, that significant regional differences did exist during the reference period in the support strategies being adopted by BLOs. As Chapter 5 suggests some of these alternative models of delivery are were being more effective than others in terms of their impact on business performance, something that may be important in determining future regional support strategies. Rural Perspective With respect to an urban – rural perspective on the operation of the business link local service we can conclude that there are differences in the headline performance data for intensively-assisted areas and that those located in less sparse rural areas perform better than in the more remote rural areas and urban areas. We have also seen that the ‘package’ of assistance received by intensively-assisted firms in the more remote rural areas differs significantly in a number of ways to similar firms in other locations. Satisfaction levels with the assistance received similar across the three locations with marginally higher levels reported in rural areas. The assessment of the perceived impact of Business Link assistance revealed that there was very little difference in the time horizon over which benefits were anticipated to be realised and that the proportion of firms reporting that they would have achieved similar business outcomes without BL assistance was similar in urban and the two rural locations. In general, this provides some evidence that the BL ‘brand’ is having broadly similar effects in both urban and rural areas across England.



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8. Conclusions and Discussion

8.1 Introduction

We set out below the main findings and conclusions from this economic impact study of the Business Link Local Service interventions in the period April to September 2003. The results are based on a large-scale telephone survey of intensively-assisted, other-assisted and non-assisted businesses which was undertaken in the May to July 2005. An important aspect is to compare the findings of the current evaluation with earlier evaluations of the Business Link network which include Value for Money and economic impact indicators.

8.2 Value for Money

We estimated in Chapter 4 the Value for Money of Business Link assistance using data on interventions during the 6 month period April to September 2003 period and its impact over the subsequent business year. We differentiate in the analysis between the impact on intensively-assisted firms and other-assisted firms, something which proves important in our econometric modelling of the impact of Business Link assistance on individual firms. In particular, our modelling – based on a two-stage Heckman approach which allows for selectivity – suggests that while Business Link assistance has a range of positive impacts on sales growth and productivity (sales per employee) these effects are generally statistically insignificant. More robust is the effect of intensive Business Link assistance on employment growth, which is statistically significant and positive. This effect provides the basis for our subsequent value for money calculations. Our central (i.e., mid-point) estimates are that this Business Link assistance nationally increased employment by between 25,912 and 31,891 which generated £699-£753m of additional value added on an annualised basis (see Table 4.10). Two factors have to be borne in mind in considering these estimates, however. First, they are subject to relatively wide confidence intervals, reflecting the coefficient standard errors in the equations. Second, these figures probably under-estimate the overall impact of BL due to:






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• The exclusion of any positive multiplier effects which may stem from the additional demand generated by more rapidly growing employment.

Value for money reflects both value added generated net the cost of operating the Business Link network. We estimate the overall cost of operating the network for six months at around £150m based on the income of BLOs from different sources. Comparing this cost to the mid-point of our two value added estimates suggests that over a six-month period additional value-added is £362.5m, and so every £1 spent by the public authorities through the BLO network (including EU, SRB etc) would generate £2.26 of value. In our opinion this represents good value for money. Overall, the extent of any displacement from BL assistance is unlikely to be significant either at local or national level. The small firm context is one where there is a great deal of churn. Business Link advisory services are inevitably involved in that churn. Nonetheless, Business Link firms are younger than average and more likely to be limited companies; the firms that Business link help are less likely to be competing solely with other local firms; the nature of competition is non-price; and the firms are too small to make any impact on local labour markets.

8.3 Comparison with Previous Studies

We highlight two previous evaluations for comparative purposes. First, a national “Value for Money” evaluation of Business Links carried out by PACEC (1998) represented a significant contribution to our understanding of the effects of BLs on small businesses. This study sought to provide both a qualitative and quantitative assessment of the effects of Business Link assistance on the performance of users and non-users of BL services for the period 1994-97. Second, the Business Link Tracker Study (Roper et al., 2001; Roper and Hart, 2005) which used a treatment model correcting for potential selection bias to evaluate the performance effect of Business Links assistance on small firms in England. More specifically, the study considered the growth and productivity effects over the 1996 to 2000 period of assistance provided in 1996 to 1998.

8.3.1 PACEC (1998)

PACEC concluded that using Business Links had a positive performance effect, with regression analysis showing that use of Business Links was a significant variable in explaining growth in assisted firms' turnover and employment. It is important to note that, unlike this study and the Business Link Tracker Study (section 8.3.2) the PACEC study alluded to, but did not apply, the econometric approach controlling for sample selection identified as best practice by Storey (2000)30. Instead, PACEC highlighted the specific data requirements of this approach, most notably the requirement to identify variables influencing the probability of assistance but not business performance.

30 This has obvious implications for the comparison of any of the economic impact indicators and VfM estimates.



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The PACEC analysis implied that Business Link use per se had added nearly £55,000 to the turnover, and 1.63 workers to the employment, of the average firm. From the qualitative analysis the results indicated that business growth can be attributed directly to Business Links. During the three year period covered by the research, the average firm increased its employment by 0.4 jobs, its turnover by £76,000, its profits by £9,000, its net assets by £13,000 and its exports by £6,000 because it had received Business Link support.

The key Value for Money indicators for Business Links in the three year period 1994-97 were as follows:

• 8,000 jobs;

• nearly £1 billion extra business turnover;

• more than £300 million extra profits;

• £145 million worth of extra net assets

• nearly £400 million of extra exports

8.3.2 Business Link Tracker Study (2001)

Econometric Results The econometric analysis of the effect of Business Links assistance to firms over the period 1996-98 suggests two main substantive results (Roper et al., 2001; Roper and Hart, 2005). First, there was little evidence that Business Link assistance was being targeted effectively at firms with a track record of rapid prior growth. Secondly, there was little evidence that after allowing for selection bias Business Link assistance over the period 1996-98 had any significant effect on firms’ sales, employment or productivity growth performance over the period 1996-2000. Making no allowance for selection bias, does however, suggest a positive employment growth effect from Business Link assistance over the period 1996-2000. This effect is biased upwards, however, by the selection process, emphasising the importance of allowing for possible selection bias in this type of policy evaluation (Storey, 2000).

Additionality

A further approach to assessing the perceived impact of Business Link assistance is the standard additionality approach, designed to investigate whether additionality was ‘full’, or ‘partial’. Responses from the current study were significantly different between intensively-assisted firms and other-assisted firms.

• 23 per cent of intensively-assisted firms and 36 per cent of other-assisted firms reported that the same business achievements would have been made without Business Link assistance – i.e. total deadweight.



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• 25 per cent of intensively-assisted firms and 20 per cent of other-assisted firms said outcomes would have been the same without assistance but Business Link assistance helped to accelerate business development.

• Remaining firms (40 per cent of intensively-assisted firms and 25 per cent of

other-assisted firms) reported business outcomes which, without Business Link assistance, they would not have achieved.

The Business Link Tracker Study did not ask the same question in 2001 but rather focused specifically on how the business would have performed in the absence of assistance from Business Links:

“Now, thinking specifically about the performance of your business over the period 1996-2000 can you indicate how the support from Business Links impacted upon that performance? In the absence of assistance would your business have?”

Overall, one-quarter of the assisted firms reported additionality with respect to Business Link support while two-thirds reported deadweight in that they would have grown at the same rate over the period 1996-2000. The rest (one in twelve) did not know. This crude deadweight ratio compares to the average of 64 per cent obtained over five performance measures in the PACEC study for the 1994-97 period.



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8.4 Business Link Delivery Models

Four models which may broadly reflect the range of ways in which BLOs operate were developed as part of this economic evaluation study. The four models are referred to as:


• Some BLOs suggest that they were ‘lean and mean’ with low levels of ‘touch with their clients and not too much follow-up.

• Philosophy is ‘Lets solve the business problem there and then’ • The payoff is in the high penetration rate • ‘Light touch’ BLOs are likely to be in areas that receive little non-core

funding such as EU supported funds. Model 2 Managed brokerage

• The dominant model. Many BLOs believe that to retain customers they needed to manage the relationships between client, BL and consultant.

• The account manager who oversees the process with a project management role throughout the assistance and follow-up

• - almost all now have contracts between the consultant and client - an exception is Northumberland’s three way contract between consultant, client and BLO.


• ‘Trigger points’ to identify firms that may be ‘amenable’ to intensive assistance. They are very keen to get a high proportion of firms through to the end of the funnel






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Using these four models, and allocating each of the 43 BLOs to one of the four models, we are able to make the following conclusions about service delivery and impact. Service Profile For intensively-assisted firms, significant differences were evident between the profiles of BLO assistance relating to business planning and action plan development, raising finance, help with e-commerce and help with IT issues. The key differences between the four models of BL assistance/BLOs were:

• Managed brokerage BLOs were most likely to be providing intensively-assisted firms with business planning assistance or action plan development;.


brokerages;

• Managed brokerages and BLOs operating both managed brokerage and Pipeline Forcing managed pipeline forcing brokerage were most likely to be providing assistance with e-commerce and IT.

More significant difference were evident in the service profiles being provided to other-assisted firms, with managed brokerages generally providing a higher proportion of client firms with each service than other types of BLO. Key points were:

• Managed brokerages were providing 42.3 per cent of their clients with help for raising finance compared to only 19.7 per cent of the clients of light touch brokerages;

• Managed brokerages were also providing more of their clients help with

exporting, e-commerce and IT than other types of BLOs;

• BLOs operating as managed pipeline forcing brokerage were most likely to be offering their clients help with training.

Impact of the Delivery Model

We consider two indicators of impact – the impact perceived by firms and the econometrically modelled impact of BLO assistance on business growth. Reflecting the pattern of service provision for intensively-assisted firms, two significant differences were evident between the proportions of Business Link clients in each category in the Mole typology reporting that Business Link services has been an important catalyst for change within their business.



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Intensively-assisted firms were significantly more likely to cite Managed Brokerage BLOs as having been an important source of change in financial sourcing than other types of BLO, and were more likely to cite managed pipeline forcing brokerage BLOs as having had an important impact on training than other types of BLO. Only in terms of innovation capability were there significant differences in the proportion of intensively-assisted firms citing BLOs as the crucial factor in change in the firm. Here, light touch brokerages were said to have most commonly been the crucial factor. For other-assisted firms, significant differences between the proportions of firms reporting BLO assistance as important were evident only for financial sourcing and innovation capability. In both cases other-assisted firms were most likely to cite Managed Brokerage BLOs as being an important factor in stimulating change. The econometric estimates of the growth impact of the different types of BLO in the Mole typology reveal that:

• as in the aggregate results, we find no significant effect of Business Link assistance on other-assisted firms for sales or employment growth. Significant positive and negative productivity growth effects are evident with the (positive) effect of light-touch brokerage of more absolute importance given the relatively small number of BLOs (and firms) in the managed pipeline forcing brokerage category.

• no significant productivity effects were evident on intensively-assisted firms from any type of BLO, although the small group of managed pipeline forcing brokerage BLOs were having a positive sales growth effect. More notable perhaps are the

• employment growth effects where the managed brokerage and light-touch groups

of BLOs both had strongly positive and significant effects. Notably BLOs in the managed brokerage group had an employment impact (6.9 percentage points) almost three times that of those in the light-touch brokerage group.

8.5 Sub-National Issues

Regional Baselines We have examined differences between the structural characteristics of intensively-assisted firms and other-assisted firms in each Government Office Region (GOR) (Chapter 7). In light of the new administrative arrangements for the Business Link network since April 2005 the following points are of particular interest:

• First, in terms of firm vintage we find significant regional variation which is not attributable to the underlying regional age profile of firms. The implication is that



154

BLOs in different GORs are targeting assistance at significantly different age cohorts of firms.

• Second, an essentially similar result arises in terms of the legal status of assisted

firms. Again, the suggestion is that BLOs in different GORs are targeting assistance at groups of firms with different ownership profiles.

• Third, there is a marked difference between the sectoral composition of assisted

firms and the general population of firms in most regions. This suggests that in general terms there is effectively some sectoral targeting of assistance by BLOs.

• Fourth, ethnic diversity within the leadership teams of assisted firms also differs

between regions. However, this is likely to reflect underlying differences in the distribution of ethnic minority populations within the UK. More surprising perhaps is that there is also significant variation in levels of gender diversity between the leadership teams of assisted firms, although the pattern varies between regions. While this does suggest that BLOs in some regions are more likely to be assisted female-led businesses it is not clear whether this is due to either targeting or differences in the underlying business population. In Southern regions, for example, where the opportunities for service sector activity are greater, female-led businesses may account for a larger proportion of all potential client firms.

• Finally, it is worth noting that there are also robust differences between regions in

the size distribution of assisted firms. In London and the West Midlands intensively assisted firms are, on average, larger than other-assisted firms, the opposite relationship is evident in the South West.

The differences identified between regions in the characteristics of assisted firms provide some support for the development of differentiated baseline statistics for each region. They also emphasise, however, that significant regional differences did exist during the reference period in the support strategies being adopted by BLOs. As Chapter 5 suggests some of these alternative models of delivery are were being more effective than others in terms of their impact on business performance, something that may be important in determining future regional support strategies. Rural Perspective With respect to an urban – rural perspective on the operation of the business link local service we can conclude that there are differences in the headline performance data for intensively-assisted areas and that those located in less sparse rural areas perform better than in the more remote rural areas and urban areas. We have also seen that the ‘package’ of assistance received by intensively-assisted firms in the more remote rural areas differs significantly in a number of ways to similar firms in



155

other locations. Satisfaction levels with the assistance received similar across the three locations with marginally higher levels reported in rural areas. The assessment of the perceived impact of Business Link assistance revealed that there was very little difference in the time horizon over which benefits were anticipated to be realised and that the proportion of firms reporting that they would have achieved similar business outcomes without BL assistance was similar in urban and the two rural locations. In general, this provides some evidence that the BL ‘brand’ is having broadly similar effects in both urban and rural areas across England. 8.6 Methodological Critique The methodological approach adopted in this study comprised three main elements reflecting both the demand and supply sides of the market for business support as well as the outcomes of BL support for the assisted businesses. Fieldwork included:

(d) An extensive survey of c3,500 companies covering BL intensively- and other- assisted businesses and a similarly sized control group with the survey being specifically designed to support an econometric approach designed to overcome any systematic bias in the type of assisted firms.

(e) A detailed interview survey with 34 companies with a focus on those who

received intensive assistance. This provided more detailed information on the more organisational and strategic impact of BL support, particularly on those firms receiving intensive assistance.

(f) Interviews with 18 Business Link Organisations (BLOs) and the development of a

detailed typology of alternative brokerage models. This multi-dimensional approach was designed to accord with current best practice methodology in terms of ex post evaluation combining rigorous econometric analysis with more in-depth qualitative approaches related both to the pattern of supply and its outputs. The large sample size in the survey, in particular, was important in enabling us to develop sub-sample comparisons by region and also to examine the effectiveness of alternative brokerage models. A key input to the development of the sampling frame for the survey was data on other-assisted firms and intensively-assisted firms provided at start of project by all individual BLOs. It is perhaps worth highlighting some of the key advantages of the approach adopted here involving sample selection models:

(a) The use of an explicit two stage approach to modelling the impact of BL support explicitly allows us to examine the factors which affect whether individual firms received support. From a policy point of view this is interesting in providing information about the ability of firms with different characteristics (e.g. gender,



156

ethnicity) to access BL services. It also provides information about the effectiveness of any targeting.

(b) The sample selection approach allows us to identify separately the ‘selection’ and

‘assistance’ effects. This avoids potential bias in the estimation of the ‘assistance’ effects and provides a direct way of assessing the ‘additional’ impact of BL assistance on firms’ growth. If there is no additionality clearly there is no additional performance effect. Note that the survey was designed explicitly to support this modelling approach collecting information on factors which were likely to determine the probability of receiving BL assistance but not firm performance. It turned out that the selection effects were not significant and the models presented in the main report are OLS.

(c) The performance models enable us to explore the impact of many different factors

on firm performance and identify their relative importance. This may guide future policy intervention.

(d) Large sample sizes allow us to split the assistance effect into its impact on sub-

groups of firms, enabling us, for example, to examine the effects of alternative brokerage models etc.

Two main issues limit the ability of our study to provide a comprehensive view of the value for money of Business Links, however. First, as the responses from assisted firms suggest, the impact of BL assistance on performance in around half of firms occurs more than two years after the assistance is provided. In our study, however, in order to provide information at this point in time we were restricted to an 18-24 month period over which impact could be assessed. The implication is that our modelling work will underestimate the true impact of BL assistance. Moreover, as any multiplier effects are likely to occur over a longer time horizon than that considered here this may also contribute to a degree of under-estimation of the true impact of BL assistance. Addressing these issues clearly require a longer-term view with the possibility that respondent firms could simply be re-surveyed at some point in the future although a better approach is probably to collect more longitudinal information on firms’ future performance. Second, our attempts at collecting value added data from BL clients as part of the telephone survey proved ineffective yielding low response rates. It did prove possible, however, to obtain high response rates for turnover and employment growth in the survey and we have therefore used these figures in the modelling work. This is clearly not ideal, however, and in future it would be useful to consider the potential for linking one-off value for money studies such as ours to statutory survey resources such as the Annual Business Inquiry which do provide value added information.



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References Barkham, R; Gudgin, G; Hart, M and Hanvey, E (1996) The Determinants of Small Firm Growth: an inter-regional study in the UK, 1986-90 Jessica Kingsley, London Bennett, R. J. and Robson, P. J. A. (1999) Intensity of Interaction in Supply of Business Advice and Client Impact: A Comparison of Consultancy, Business Associations and Government Support Initiatives for SMEs. British Journal of Management 10 (4), 351-369. Bennett RJ, Robson PJA, Bratton WJA, 2001 “The influence of location on the use by SMEs of external advice and collaboration” Urban Studies 38 1531-1557 Bennett, R.J. and Robson, P.J.A. (2003) ‘Changing use of external business advice and Government support during the 1990s’, Regional Studies, vol. 37,8: 795-811 Bennett R, Robson P, 2004 “Support services for SMEs: does the 'franchisee' make a difference to the Business Link offer?” Environment and Planning C 22 859 - 880 Bryson JR, Churchward S, Daniels PW, 1997 “From Complexity to Simplicity? Business Link and the Evolution of a Network of One-Stop-Advice Shops: A Response to Hutchinson, Foley and Oztel Regional Studies 31 720-723 Bryson, J.R. and Daniels, P.W. (1998) ‘Business Link, strong ties, and the walls of silence: small and medium-sized enterprises and external business-service expertise’, Environment and Planning C, 16 (3): 265-280 Disney, R., Haskel, J., and Heden, Y. (2003a). Entry, exit and establishment survival in UK manufacturing, Journal of Industrial Economics, 51(1), pp. 91-112. Disney, R., Haskel, J., and Heden, Y. (2003b). Restructuring and Productivity Growth in UK manufacturing, Economic Journal, 113, pp. 666-694. Donaldson S.I. and Gooler L.E. (2003) Theory-driven evaluation in action: lessons from and $20 million statewide Work and Health Initiative, Evaluation and Program Planning, 26, 355-366 DTI (2006) DTI Public Service Agreement Targets 2003-2006 http://www.dti.gov.uk/about/psa/ accessed 10/4/06 Gee D. (2004) Active Brokerage SAT Report, available on the SBS extranet. June 2004 Greene F.J., (2002) An Investigation into Enterprise Support For Younger People, 1975-2000, International Small Business Journal, 20, 315-336



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Greene, F.J., Mole, K.F., and Storey, D J (2004) Does More Mean Worse? UK enterprise policy over three decades, Urban Studies, 41, 303-324 HM Treasury (2004) Devolving decision making: 2 Meeting the regional economic challenge: Increasing regional and local flexibility, HMSO, London. Keogh, W and Mole, K (2005) The changing role of the small business adviser, Paper presented at 28th ISBE conference, November, Blackpool copy available from Kevin Mole, CSME, Warwick Business School, University of Warwick, Coventry, CV4 7AL Love, J H and Roper, S (2005) ‘Innovation, Productivity and Growth: An Analysis of Irish Data’, Presented at the EARIE Annual Congress, Porto. Love, J H and Roper, S (2005) ‘Economists’ perceptions versus managers’ decisions: an experiment in transaction cost analysis’, Cambridge Journal of Economics, 29: 19-36. Mole, K., (2002) Business Advisers Impact on SMEs: An Agency Theory Approach, International Small Business Journal, Vol. 20, 137-157. Mole, K., (2004) 2004 International Review of Business Support and Brokerage Small Business Service at http://www.sbs.gov.uk/content/analytical/InternatReviewBrokerage.pdf PACEC (1998) Business Links – Value for Money Evaluation Final Report, October, Cambridge. Rigby A (2004) Has the take-up of business advice reached tipping-point yet? Business Adviser, no 21, Institute of Business Advisers, Chesterfield. Roper, S; Hart, M; Bramley, G; Dale, I and Anderson, C (2001) ‘Paradise Gained-the Business Link Tracker Study’, presented to the 24th ISBA Conference, Leicester; copy available from Mark Hart, SBRC, Kingston University, Kingston Hill, Kingston-upon-Thames, Surrey, UK, KT2 7LB Roper, S and Hewitt-Dundas, N (2001) ‘Grant Assistance and Small Firm Development in Northern Ireland and the Republic of Ireland’, Scottish Journal of Political Economy, 48, 1, 99-117. Roper, S and Hart, M (2005) ‘Small Firm Growth And Public Policy In The UK: What Exactly are the Connections?’ Working Paper, Aston Business School (RP0504). SBS (2003) Government action plan for small business, Small Business Service, Sheffield URN 03/1592 SBS, (2004) Business Plan 2004, London, DTI URN 04/330. at http://www.sbs.gov.uk/content/whoweare/sbs_busplan2004.pdf



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SBS (2006) Annual Survey of Small Businesses, 2004/5 http://www.sbs.gov.uk/SBS_Gov_files/researchandstats/ASBS-Report.pdf accessed 10/4/06 Sear, L, and Agar, J, (1996) ‘A Survey of Business Link Personal Advisers: Are They Meeting Expectations?’ Durham University Business School, Durham Storey, D J (1994) Understanding the Small Business Sector Routledge, London Storey DJ, (2003) ‘Entrepreneurship, Small and Medium Sized Enterprises and Public Policies’ in The Handbook of Entrepreneurship Eds D Audretsch Z Acs (Kluwer, London) 473-511. Turok I, and Raco M, (2000) ‘Developing expertise in small and medium-sized enterprises: an evaluation of consultancy support’ Environment and Planning C: Government and Policy 18 409-427. Wren, C and Storey, D J (2002) ‘Evaluating the effect of soft business support upon small firm performance’ Oxford Economic Papers 54 334-365.



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Appendices

Appendix A: Telephone Survey Questionnaire Appendix B: Survey Weighting Protocols Appendix C: Face-to-Face Topic Guide

Appendix D: Additional Estimation Results Including Selection Effects Appendix E: Excerpt from Conference Paper on the Impact on

Employment growth



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Appendix A: Telephone Survey Questionnaire



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BLO ECONOMIC IMPACT QUESTIONNAIRE

April 2005

OMB Research; Warwick Business School; Kingston Uni versity and Aston Business School for the Small Business Service

SAMPLE GROUPS: X1 = INTENSIVELY ASSISTED FIRMS X2 = OTHER ASSISTED FIRMS Y = NON-ASSISTED FIRMS

IF SAMPLE GROUP X: Ask for named respondent Good morning/afternoon, my name is … and I’m callin g on behalf of OMB Research, an independent market research agency. W e have been commissioned by the Department of Trade & Industry to conduct an evaluation of the various services and support provided through Business Link . You should recently have received a letter explaini ng that we were conducting this research IF SAMPLE GROUP Y: Could I speak to the owner/managing director or the person responsible for business development within your organisation? Good morning/afternoon, my name is … and I’m callin g on behalf of OMB Research, an independent market research agency. W e have been commissioned by the Department of Trade & Industry to conduct an evaluation of the effectiveness to businesses of various activities a nd support they provide. ALL SAMPLE GROUPS: This research will cover areas such as your usage o f business advice and support services, the impact they have had on your firm and your general business performance, and will take around < IF X 20 minutes / IF Y 15 minutes> depending on your answers. Is it convenient to speak to you now or would you prefer to make an appointment for another time? FOR ALL SAMPLE GROUPS ADD IF NECESSARY

� The research is being conducted under the Code of P ractice of the Market Research Society, which means that al l of the answers you give are strictly confidential and anonymous. Parti cipation in this survey is voluntary.

� The responses of all organisations taking part will be combined into a statistical report

� Your organisation was selected at random < IF X: from a list supplied by your local Business Link / IF Y: from a list of all UK businesses>



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� If you wish to check that OMB Research is a bona fi de market research agency, you can contact the Market Research Society on 0500 396999, or call James Murray at OMB Research on 01622 790900

� IF Y: If you would like to find out more about Business L ink and their services you can visit www.businesslink.gov.uk

OFFER FAX REASSURANCE IF NECESSARY



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ASK ALL S1a. Can I just confirm that you are the person bes t qualified to talk about < IF X your experience of Business Link and the services t hey offer? / IF Y these issues?> INTERVIEWER NOTE: IF KNOW ALREADY THAT SPEAKING TO CORRECT PERSON THEN CODE YES AUTOMATICALLY. REFERRALS CAN BE TAKEN TO ANYONE IN THE COMPANY THAT THE CONTACT FEELS IS BETTER PLACED TO ANSWER QUESTIONS ON THE AREAS OUTLINED. Yes ............................................................................................. 1 No – taken referral and being transferred ................................... 2 No – taken referral and arranged call back ................................. 3 No – refused referral .................................................................. 4 - CLOSE ASK ALL S1b. Firstly, can I just check that you’re not a public sector organisation? INTERVIEWER NOTE: SOCIAL ENTERPRISES, NOT-FOR-PROFIT ORGANISATIONS AND CO-OPERATIVES CAN BE INTERVIEWED. NON-BUSINESSES SHOULD BE SCREENED OUT Not a public sector organisation ................................................. 1 Public sector organisation .......................................................... 2 - CLOSE (Not a business) ......................................................................... 3 - CLOSE (Don’t know) ............................................................................... 4 IF SAMPLE GROUP X S2a. We understand from our records that your busin ess was helped by Business Link at some point between April and October 2003. Can I just check that this is correct? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 IF NO OR DON’T KNOW AT S2a S2b. Has your business used Business Link at all in the last 2 years? Yes ............................................................................................. 1 No .............................................................................................. 2 - CLOSE (Don’t know) ............................................................................... 3 - ASK FOR REFERRAL IF SAMPLE GROUP X S2c. And did your business use Business Link at all before this time? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 IF SAMPLE GROUP X S2d. And are you still using Business Link, or plan ning to do so in the future? Yes ............................................................................................. 1



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No .............................................................................................. 2 (Don’t know) ............................................................................... 3



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IF SAMPLE GROUP Y S3a. Has your business ever used Business Link as a source of advice or assistance? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 IF YES AT S3a (CODE 1) S3b. When was the last time you used Business Link? Was it…? READ OUT In the last 2 years, that is since April 2003 ................................. 1 - CLOSE Or more than 2 years ago .......................................................... 2 (Don’t know) ............................................................................... 3 IF NO OR DON’T KNOW AT S3a (CODES 2 OR 3) S3c. Can I just check, had you heard of Business Li nk before this interview today? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3



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SECTION A: BUSINESS BACKGROUND ASK ALL Now we would just like to get some information on t he background to your business and the markets in which you operate: A1. So firstly, how long ago was your business esta blished? READ OUT AS NECESSARY. IF NEEDED CLARIFY THAT THIS MEANS WHEN THE BUSINESS STARTED TRADING Less than 2 years ago ................................................................ 1 - CLOSE 2-3 years ago ............................................................................. 2 3-4 years ago ............................................................................. 3 4-5 years ago ............................................................................. 4 5-10 years ago ........................................................................... 5 10-20 years ago ......................................................................... 6 More than 20 years ago ............................................................. 7 (Don’t know) ............................................................................... 8 (Refused) ................................................................................... 9 A2a. Record gender of respondent. DO NOT ASK – INTERVIEWER TO CODE Male ........................................................................................... 1 Female ....................................................................................... 2 A2b. And what is your position within the business? READ OUT AS NECESSARY. SINGLE CODE Owner/proprietor ........................................................................ 1 Managing Director ...................................................................... 2 Partner ....................................................................................... 3 Director ...................................................................................... 4 Senior Manager .......................................................................... 5 Company Secretary.................................................................... 6 General Manager ....................................................................... 7 Chief Executive (CEO) ............................................................... 8 Chairman ................................................................................... 9 Office Manager ........................................................................... 10 Other (SPECIFY) ....................................................................... 11 (Don’t know) ............................................................................... 12 (Refused) ................................................................................... 13 A3. Which of the following best describes the curre nt status of your business? READ OUT. SINGLE CODE Sole trader ................................................................................. 1 Partnership ................................................................................. 2 Private Limited Company (Ltd) ................................................... 3 Public Limited Company (plc) ..................................................... 4 Limited Liability Partnership ........................................................ 5



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Social Enterprise (AS NECESSARY: whose main purpose is to pursue social or environmental goals and any profit or surplus generated is primarily reinvested for this purpose) ..................................................................................... 6 Other (SPECIFY) ....................................................................... 7 (Don’t know) ............................................................................... 8 (Refused) ................................................................................... 9



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A4. And is the business…? READ OUT. SINGLE CODE An independent single site organisation ..................................... 1 The headquarters of a multi-site organisation ............................. 2 Or a subsidiary or associated company ...................................... 3 (Other – SPECIFY) .................................................................... 4 (Don’t know) ............................................................................... 5 (Refused) ................................................................................... 6 TEXT IF HEADQUARTERS OR SUBSIDIARY (CODES 2-3 AT A4) From now on when I ask about your business I’d like you to answer just for the site at which you work. ASK ALL A5. What is the main activity of your business…? RECORD VERBATIM. PROBE FOR INDUSTRY TYPE – IF MANUFACTURING, WHAT TYPE OF MANUFACTURING? IF FINANCIAL SERVICES, WHAT KIND? ETC. (WILL BE CODED TO 1 LEVEL SIC CODE) ………………………………………………………………………………………………………… A6a. Does your business export overseas? IF NECESSARY: By that I mean sell goods or services to businesses or individuals base d overseas. Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4 IF EXPORT AT A6a (CODE 1) A6b. Approximately what proportion of your current sales are accounted for by exports? Would you say that it is…? READ OUT. Up to 5% .................................................................................... 1 Between 6 - 15% ........................................................................ 2 Between 15 - 25% ...................................................................... 3 Between 26 - 50% ...................................................................... 4 Between 51 - 75% ...................................................................... 5 Or between 76 - 100% ............................................................... 6 (Don’t know) ............................................................................... 7 (Refused) ................................................................................... 8 ASK ALL A7a. In the last 2 years, has your business introdu ced any new or significantly improved products or services ? IF YES, PROBE FOR WHETHER NEW, IMPROVED OR BOTH. SINGLE CODE. Yes, new products or services .................................................... 1 Yes, improved products or services ............................................ 2 Yes, both .................................................................................... 3 No .............................................................................................. 4 (Don’t know) ............................................................................... 5



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IF NEW OR BOTH AT A7a (CODES 1 OR 3) A7b. Are these just new to your business or are the y completely new, and by that I mean that to the best of your knowledge they have n ot been introduced by anyone before you? SINGLE CODE. Just new to the business ............................................................ 1 Completely new .......................................................................... 2 (Don’t know) ............................................................................... 3 ASK ALL A8a. And still thinking about the last 2 years, has your business introduced any new or significantly improved processes in this time? IF YES, PROBE FOR WHETHER NEW, IMPROVED OR BOTH. SINGLE CODE. Yes, new processes ................................................................... 1 Yes, improved processes ........................................................... 2 Yes, both .................................................................................... 3 No .............................................................................................. 4 (Don’t know) ............................................................................... 5 ASK ALL A10a. I’d now like you to think about your business es’ competitors. First of all, how would you describe the nature of the competitio n in your main markets. Would you say that there is…? READ OUT. SINGLE CODE. Very intense competition ............................................................ 1 Intense competition .................................................................... 2 Moderate competition ................................................................. 3 Weak competition ....................................................................... 4 Or no competition at all .............................................................. 5 (Don’t know) ............................................................................... 6 ASK ALL EXCEPT THOSE WITH NO COMPETITION AT A10a (CODE 5) A10b. If your business were to cease trading tomorr ow, who do you think would take up your current sales? Would it mainly be comp etitors based…? READ OUT. AIM FOR SINGLE CODE BUT MULTI CODE ALLOWED. Locally, and by that I mean within 20 miles of your business ...... 1 Elsewhere in the UK ................................................................... 2 In other countries in the EU ........................................................ 3 Or, in countries outside of the EU ............................................... 4 (No one would take up our sales) ............................................... 5 (Don’t know) ............................................................................... 6



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ASK ALL EXCEPT THOSE WITH NO COMPETITION AT A10a (CODE 5) A10c. Thinking specifically about your main competitor, if they reduced their prices by 10%, to what extent do you think this wou ld impact on your sales? Would your sales be…? READ OUT. AS NECESSARY: Please just give me your best estimate. INTERVIEWER NOTE: ASK IN TERMS OF VOLUME OF SALES RATHER THAN PRICE The same ................................................................................... 1 Up to 10% lower ......................................................................... 2 10 - 20% lower ........................................................................... 3 20 - 30% lower ........................................................................... 4 Or, more than 30% lower ........................................................... 5 (Higher) ...................................................................................... 6 (Don’t know) ............................................................................... 7 (Refused) ................................................................................... 8 ASK ALL A10d. Now thinking specifically about your own prices, if you were forced by cost increases to raise your prices by 10%, to what extent do you think th is would impact on your sales? Would your sales be…? READ OUT. AS NECESSARY: Please just give me your best estimate. The same ................................................................................... 1 Up to 10% lower ......................................................................... 2 10 - 20% lower ........................................................................... 3 20 - 30% lower ........................................................................... 4 Or, more than 30% lower ........................................................... 5 (Higher) ...................................................................................... 6 (Don’t know) ............................................................................... 7 (Refused) ................................................................................... 8



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SECTION B: STRATEGIC DIRECTION OF THE BUSINESS ASK ALL B1a. Thinking now about your main business objectiv es, which ONE of the following would you say is the key focus for your b usiness at this time? READ OUT. SINGLE CODE Maintaining sales of your current products or services ............... 1 Increasing sales of your current products or services ................. 2 Or, developing new products or services .................................... 3 (None of these) .......................................................................... 4 (Don’t know) ............................................................................... 5 IF INCREASING SALES OF CURRENT PRODUCTS OR SERVICES (CODE 2 AT B1a) B1b. Are you mainly looking to…? READ OUT. SINGLE CODE Increase sales in markets in which you are already operating .................... 1 Or, introduce your current products or services into new markets .............. 2 (Both) ......................................................................................................... 3 (None of these) .......................................................................................... 4 (Don’t know) ............................................................................................... 5 IF DEVELOPING NEW PRODUCTS OR SERVICES (CODE 3 AT B1a) B1c. Would these new products or services be aimed at customers based in…? READ OUT. SINGLE CODE Markets in which you are already operating ............................................... 1 Or, new markets ......................................................................................... 2 (Both) ......................................................................................................... 3 (None of these) .......................................................................................... 4 (Don’t know) ............................................................................................... 5 ASK ALL B2. Thinking now about the way in which the busines s is managed, which ONE of the following best describes your key strategy for managing your staff? READ OUT. SINGLE CODE. RANDOMISE. Teamworking across staff and management ................................................................... 1 Close supervision ............................................................................................................ 2 The establishment of standard working procedures ........................................................ 3 Or, careful initial staff selection, and investment in training and development ................ 4 (None of these) ............................................................................................................... 5 (No staff) ......................................................................................................................... 6 (Don’t know) .................................................................................................................... 7 B3. Does your business have a formal written busine ss plan? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3



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IF HAVE BUSINESS PLAN (CODE 1 AT B3) B4. How long ago was this business plan written or last revised? Was it…? READ OUT. INTERVIEWER NOTE: IF PLAN HAS BEEN REVISED RECORD TIME OF MOST RECENT UPDATE Within the last 2 years ................................................................ 1 2 - 5 years ago ........................................................................... 2 Or over 5 years ago.................................................................... 3 (Don’t know) ............................................................................... 4 IF HAVE BUSINESS PLAN (CODE 1 AT B3) B6. And was this business plan created primarily fo r external use, such as to obtain funding from a bank or for approval by an ac countant? Yes, primarily for external use .................................................... 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3



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SECTION C: SOURCES OF EXTERNAL ADVICE/ASSISTANCE INCLUDING BUSINESS LINKS ASK ALL C1a. Over the last 2 years < IF X:, and other than the support you have received through Business Link,> have you used any external sources of information, advice or support to help you develop the business. Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 IF USED OTHER SOURCES OF SUPPORT AT C1a (CODE 1) C1b. Who did you get this from? PROBE AS PER PRECODES. CODE ALL THAT APPLY Friends or relatives ............................................................................................ 1 A customer or supplier ...................................................................................... 2 Another business owner .................................................................................... 3 An accountant ................................................................................................... 4 A bank ............................................................................................................... 5 A solicitor .......................................................................................................... 6 A management consultant ................................................................................. 7 Another consultant ............................................................................................ 8 A Trade Association .......................................................................................... 9 An Employers Federation (e.g. Confederation of British Industry) ..................... 10 The Inland Revenue .......................................................................................... 11 A regulatory body (e.g. Health & Safety Executive, Environment Agency) ......... 12 Department of Trade & Industry ........................................................................ 13 An Enterprise Agency ........................................................................................ 14 The Chamber of Commerce .............................................................................. 15 Other (SPECIFY) .............................................................................................. 16 (Don’t know/can’t remember) ............................................................................ 17 IF USED OTHER SOURCES OF SUPPORT AT C1a (CODE 1) C1c. Did you have to pay for any of this informatio n, advice or support? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3



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ASK ALL Y MENTIONING AT LEAST 2 SOURCES AT C1b C2. Thinking about these sources of advice or suppo rt, which one has been the most important for your business? CATI TO DISPLAY ALL USED AT C1b. READ OUT AS NECESSARY. SINGLE CODE. Friends or relatives ............................................................................................ 1 A customer or supplier ...................................................................................... 2 Another business owner .................................................................................... 3 An accountant ................................................................................................... 4 A bank ............................................................................................................... 5 A solicitor .......................................................................................................... 6 A management consultant ................................................................................. 7 Another consultant ............................................................................................ 8 A Trade Association .......................................................................................... 9 An Employers Federation (e.g. Confederation of British Industry....................... 10 The Inland Revenue .......................................................................................... 11 A regulatory body (e.g. Health & Safety Executive, Environment Agency) ......... 12 Department of Trade & Industry ........................................................................ 13 An Enterprise Agency ........................................................................................ 14 The Chamber of Commerce .............................................................................. 15 Other advice or support ..................................................................................... 16 (Don’t know/can’t remember) ............................................................................ 17 ASK ALL MENTIONING AT LEAST 1 SOURCE AT C1b C3. Still thinking about these sources of external information, advice or support, <IF X: and not including Business Link,> can you tell me which of the following forms this assistance took? Was it…? READ OUT. RANDOMISE. CODE ALL THAT APPLY. Factual information ....................................................................................................... 1 Basic advice ................................................................................................................. 2 An in-depth discussion ................................................................................................. 3 Long-term or intensive assistance ................................................................................ 4 Or, something else (SPECIFY) ..................................................................................... 5 (Don’t know) ................................................................................................................. 6 ASK C4a – g IF SAMPLE GROUP X, OR SAMPLE GROUP Y AND AWARE OF BUSINESS LINK (CODE 1 AT S3c). OTHERS SKIP TO C14a RANDOMISE QUESTIONS C4a – f I’d now like you to think specifically about your a wareness of Business Link and any contact they have had with you. First of all… C4a. Have you ever received any mailings or mail sh ots from Business Link? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 C4c. Have you ever visited the Business Link websit e? Yes ............................................................................................. 1 No .............................................................................................. 2



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(Don’t know) ............................................................................... 3



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C4d. Has a member of Business Link staff ever conta cted you directly to tell you about their services? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 C4e. Are you familiar with any other businesses tha t have received help or support from Business Link? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 C4f. Have you ever been directed or referred to Bus iness Link by any external organisations or advisors? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 IF DIRECTED TO BUSINESS LINK AT C4f (CODE 1). ASK DIRECTLY AFTER C4f C4g. Who has directed you to Business Link? PROBE AS PER PRECODES. CODE ALL THAT APPLY Accountant ................................................................................. 1 Bank ........................................................................................... 2 Consultant .................................................................................. 3 Solicitor ...................................................................................... 4 Customer ................................................................................... 5 Supplier ...................................................................................... 6 Chamber of Commerce .............................................................. 7 Department of Trade and Industry (DTI) ..................................... 8 Department for Educations and Skills (DfES) ............................. 9 Enterprise Agency ...................................................................... 10 Farm Business Advisory Service ................................................ 11 Higher Education Institution (e.g. university) .............................. 12 Investors in People ..................................................................... 13 Learning and Skills Council (LSC) .............................................. 14 Regional Development Agency (RDA) ....................................... 15 Trade Association ...................................................................... 16 Training provider ........................................................................ 17 Other (SPECIFY) ....................................................................... 18 (Don’t know/can’t remember) ..................................................... 19



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IF SAMPLE GROUP X C5a. Over the last 2 years, on average how often ha s your business been in contact with Business Link? Would you say that you r business has been in contact with them…? READ OUT. SINGLE CODE. INTERVIEWER NOTE: If in doubt please calculate the average based on number of days – e.g. if respondent saw them on 24 days over the course of a couple of months but did not see them at any other time in the 2 years, then record as ‘every month’ (24 times in 2 years = once a month) Every week ................................................................................ 1 Every fortnight ............................................................................ 2 Every month ............................................................................... 3 Every 3 months .......................................................................... 4 Every 6 months .......................................................................... 5 Once a year ............................................................................... 6 Or, less often .............................................................................. 7 (Don’t know) ............................................................................... 8 IF SAMPLE GROUP X C5b. And which of the following forms did the assis tance you received from Business Link take? Was it…? READ OUT. RANDOMISE. CODE ALL THAT APPLY. Factual information ....................................................................................................... 1 Basic advice ................................................................................................................. 2 An in-depth discussion ................................................................................................. 3 Long-term or intensive assistance ................................................................................ 4 Or, something else (SPECIFY) ..................................................................................... 5 (Don’t know) ................................................................................................................. 6 IF SAMPLE GROUP X C6. Which ONE of the following would you say best d escribes your main motivation for getting in touch with Business Link? READ OUT. RANDOMISE. SINGLE CODE Our business was in difficulty ..................................................................................... 1 Our business was not growing fast enough ................................................................ 2 We were looking for funding ....................................................................................... 3 We just wanted to find out what Business Link could offer.......................................... 4 We wanted some specific information ........................................................................ 5 Someone recommended that we get in touch with them ............................................ 6 Or, was there another reason? (SPECIFY) ................................................................ 7 (Don’t know) ............................................................................................................... 8



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IF SAMPLE GROUP X C7. As you probably know, Business Link provides a wide range of advice and support. I’m going to read out a list of possible types of advice and support, and for each one I’d like you to tell me whether or not this is something that your business has received from Business Link over the l ast 2 years? READ OUT. RANDOMISE. BUT KEEP l and m TOGETHER.

Yes No (Don’t know)

a. General business information 1 2 3 b. Business benchmarking or diagnosis, where you compare your business performance with others 1 2 3

c. Business planning, such as developing an action plan 1 2 3 d. Access to information and advice on regulation and compliance 1 2 3 e. Help with finding external consultancy services 1 2 3 f. Help with raising finance 1 2 3 g. Help with making cost reductions or quality improvements 1 2 3 h. Help with marketing 1 2 3 i. Help with research and development or new product development 1 2 3

j. Help with exporting 1 2 3 k. Help with training 1 2 3 l. Help with e-commerce, and by that I mean on-line trading 1 2 3 m. Help with IT issues 1 2 3 n. Anything else? (SPECIFY) 1 2 3

IF SAMPLE GROUP X C8a. Was all of this advice and support provided to you by Business Link directly, or was any of it provided by external parties refer red to you by Business Link? All provided by Business Link ..................................................... 1 At least some was referred to an external party ......................... 2 (Don’t know) ............................................................................... 3 IF SAMPLE GROUP X C8b. Can I just check, did your business have to pa y Business Link for any of this advice and support? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 IF SAMPLE GROUP X AND REFERRED TO EXTERNAL PARTY (CODE 2 AT C8a) C8c. And did your business have to pay any external parties that Business Link referred you to for any of this advice and support? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3



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IF SAMPLE GROUP X C9a. Overall, how satisfied are you the services yo u have received from Business Link over the last 2 years? Please give me a score of 1 to 5, where 5 would mean that you are very satisfied and 1 would mean that y ou are very dissatisfied? 1 – Very dissatisfied ................................................................... 1 2 ................................................................................................. 2 3 ................................................................................................. 3 4 ................................................................................................. 4 5 – Very satisfied ........................................................................ 5 (Don’t know) ............................................................................... 6 IF RATING OF ‘1’, ‘2’ OR ‘3’ AT C9a C9b. Why do you say that? What could they improve? PROBE FULLY. RECORD VERBATIM .............................................................................................................................................. .............................................................................................................................................. IF SAMPLE GROUP X C10. Now thinking about the overall package of supp ort your firm has received from Business Link over the last 2 years, do you ag ree or disagree with the following statements? READ OUT. RANDOMISE.

Agree Disagree (Neither agree nor disagree)

(Don’t know)

a. DELETED 1 2 3 4 b. We received all the support and help that we needed 1 2 3 4

c. We have a trusting relationship with our Business Link advisor 1 2 3 4

d. We have a trusting relationship with Business Link as an organisation 1 2 3 4

e. DELETED 1 2 3 4 f. DELETED 1 2 3 4 g. We would recommend Business Link to other businesses needing help 1 2 3 4

h. DELETED 1 2 3 4 i. DELETED 1 2 3 4 j. We could have got the same quality of advice from other external sources of business support

1 2 3 4

k. DELETED 1 2 3 4



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IF SAMPLE GROUP X C11a. I’m going to read out a list of possible ways in which the support you have received from Business Link over the last 2 years m ay have impacted on your business. For each one, I’d like you to tell me wh ether or not this is something you have experienced AS A DIRECT RESULT of receivin g Business Link’s assistance. READ OUT. RANDOMISE DISPLAY ON EACH SCREEN a-m – AS NECESSARY: Is this something you have experienced AS A DIRECT RESULT of receiving Busines s Link’s assistance

a. The business is now more inclined to use externa l business support for general information and advice

b. The business is now more inclined to use special ist consultancy services c. The image of the business has improved d. The business has improved its technical capacity e. The business has improved its financial manageme nt skills f. The business is better at planning g. The business has developed a greater capacity to engage in export activity h. The business is better equipped to seek external finance i. The business is better able to deal with regulat ion and compliance issues j. The business has invested more resources in trai ning staff, in terms of

time and money k. DELETED l. The business has more capability to develop new products or services m. The business has improved the quality of its pro ducts or services

Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 ASK FOR EACH OF A-M THAT RESPONDENT AGREES THEY HAVE EXPERIENCED (CODE 1 AT C11a). ASK C11b DIRECTLY AFTER EACH STATEMENT AT C11a WHERE RESPONDENT SAYS YES C11b. And to what extent? Please give me a score o f 1 to 5, where 5 means to a critical extent and 1 means to no extent. AS NECESSARY: By this I mean to what extent has this happened as a direct result of the support you’ve received from Business Link. 1 – To no extent ......................................................................... 1 2 ................................................................................................. 2 3 ................................................................................................. 3 4 ................................................................................................. 4 5 – To a critical extent ................................................................ 5 (Don’t know) ............................................................................... 6



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IF SAMPLE GROUP X C12. Thinking about all of the benefits that your b usiness might experience as a result of the help and support you have received fr om Business Link over the last 2 years, when do you expect to fully realise these benefits? Would you say that…? READ OUT. SINGLE CODE You have already realised all the benefits .................................. 1 You expect to realise all the benefits in the next year ................ 2 You expect to realise them in the next 2 years ........................... 3 In the next 3 years ..................................................................... 4 In the next 4 years ..................................................................... 5 In the next 5 years ..................................................................... 6 Or it will take more than 5 years to fully realise all the benefits ... 7 (No benefits experienced from Business Link support) ............... 8 (Don’t know) ............................................................................... 9 ASK ALL C14a. I’d now like to focus on how your business ha s developed over the last 2 years. First of all, how many people are currently employed by your business at the site where you work? Please give me the full t ime equivalent, so count part time employees according to the proportion of time that they work. Write in number (0+): (Refused) (Don’t know) – PROMPT WITH RANGES IF DON’T KNOW AT C14a C14b. If you had to estimate, approximately how man y people are employed by your business at this site? PROMPT WITH RANGES Zero ........................................................................................... 1 1-4 .............................................................................................. 2 5-9 .............................................................................................. 3 10-19 .......................................................................................... 4 20-49 .......................................................................................... 5 50-99 .......................................................................................... 6 100-199 ...................................................................................... 7 200-249 ...................................................................................... 8 250-499 ...................................................................................... 9 500 or more ................................................................................ 10 (Don’t know) ............................................................................... 11 (Refused) ................................................................................... 12 ASK ALL C15a. And approximately how many people were employ ed at this time last year? Again, please give me the full time equivalent. Write in number (0+): (Refused) (Don’t know) – PROMPT WITH RANGES



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IF DON’T KNOW AT C15a C15b. If you had to estimate, approximately how man y people were employed at this time last year? PROMPT WITH RANGES Zero ........................................................................................... 1 1-4 .............................................................................................. 2 5-9 .............................................................................................. 3 10-19 .......................................................................................... 4 20-49 .......................................................................................... 5 50-99 .......................................................................................... 6 100-199 ...................................................................................... 7 200-249 ...................................................................................... 8 250-499 ...................................................................................... 9 500 or more ................................................................................ 10 (Don’t know) ............................................................................... 11 (Refused) ................................................................................... 12 ASK ALL C16a. What is the current annual turnover of your b usiness? IF NECESSARY CLARIFY THAT WE WANT THE TURNOVER IN THEIR LAST COMPLETED FINANCIAL YEAR Write in amount (£ - ALLOW ZERO) (Refused) (Don’t know) – PROMPT WITH RANGES IF DON’T KNOW AT C16a C16b. If you had to estimate your total turnover, i nto which of the following bands would you put yourself? PROMPT WITH RANGES Zero/nothing ............................................................................... 1 Up to £100,000 ........................................................................... 2 £100,001 - £500,000 .................................................................. 3 £500,001 - £2million ................................................................... 4 £2,000,001 - £10 million ............................................................. 5 £10,000,001 - £50 million ........................................................... 6 More than £50million ................................................................. 7 (Don’t know) ............................................................................... 8 (Refused) ................................................................................... 9 IF SAMPLE GROUP X C20. Which ONE of the following statements best des cribes your view on the contribution the support you have received from Bus iness Link has made, or will make, to your firm? READ OUT. SINGLE CODE. ENSURE ALL STATEMENTS ARE READ OUT BEFORE CODING A RESPONSE We would have achieved similar business outcomes anyway ..........................1 We would have achieved similar business outcomes, but not as quickly ..........2 We would have achieved some but not all of the business outcomes ...............3 We probably would not have achieved similar business outcomes ...................4 We definitely would not have achieved similar business outcomes ..................5 (None of these) ................................................................................................6



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ASK ALL X ALSO USING ALTERNATIVE SOURCES OF SUPPORT AT C1a (CODE 1) C21. You mentioned earlier that over the last 2 yea rs you have received support from xxx < CATI TO INSERT ALL SOURCES USED AT C1b> as well as Business Link. Which one of these sources of advice or suppo rt, including Business Link, has been the most important for your business? CATI TO DISPLAY ALL USED AT C1b PLUS BUSINESS LINK (BUSINESS LINK ALWAYS TO BE SHOWN AT TOP OF LIST). READ OUT AS NECESSARY. SINGLE CODE. Business Link .................................................................................................... 1 Friends or relatives ............................................................................................ 2 A customer or supplier ...................................................................................... 3 Another business owner .................................................................................... 4 An accountant ................................................................................................... 5 A bank ............................................................................................................... 6 A solicitor .......................................................................................................... 7 A management consultant ................................................................................. 8 Another consultant ............................................................................................ 9 A Trade Association .......................................................................................... 10 An Employers Federation (e.g. Confederation of British Industry....................... 11 The Inland Revenue .......................................................................................... 12 A regulatory body (e.g. Health & Safety Executive, Environment Agency) ......... 13 Department of Trade & Industry ........................................................................ 14 An Enterprise Agency ........................................................................................ 15 The Chamber of Commerce .............................................................................. 16 Other advice or support ..................................................................................... 17 (Don’t know/can’t remember) ............................................................................ 18



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SECTION D: PARTNERS/DIRECTORS

ASK ALL D1. Now I’d like to ask you some questions about th e owners, partners and directors in your business. Including yourself, ho w many owners, partners or directors are there in day to day control of the bu siness (at this site)? IF NECESSARY: Please do not include any non-executive directors. PROBE FOR BEST ESTIMATE Enter number (ALLOW FOR ZERO) (Don’t know) (Refused) IF ANY NUMBER GIVEN AT D1 (1+) D2. And how many of these owners, partners or direc tors are female? PROBE FOR BEST ESTIMATE Enter number (ALLOW FOR ZERO) (Don’t know) (Refused) IF ANY NUMBER GIVEN AT D1 (1+) D3a. And how many are from ethnic minority groups? PROBE FOR BEST ESTIMATE Enter number (ALLOW FOR ZERO) (Don’t know) (Refused) IF AT LEAST ONE ETHNIC MINORITY AT D3a D3b. Which ethnic minority groups? PROBE AS PER PRECODES. CODE ALL THAT APPLY. Mixed – White and Black Caribbean ........................................... 1 Mixed – White and Black African ................................................ 2 Mixed – White and Asian ............................................................ 3 Mixed – Other............................................................................. 4 Asian or Asian British - Indian .................................................... 5 Asian or Asian British - Pakistani ................................................ 6 Asian or Asian British - Bangladeshi ........................................... 7 Asian or Asian British - Other ..................................................... 8 Black or Black British - Caribbean .............................................. 9 Black or Black British - African ................................................... 10 Black or Black British - Other ...................................................... 11 Chinese ...................................................................................... 12 Any other ethnic group ............................................................... 13 (Don’t know) ............................................................................... 14 (Refused) ................................................................................... 15 ASK ALL D4. In addition to the owners, partners or director s in day to day control of the business, does your business have any non-executive directors?



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Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4



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SECTION E: MAIN PARTNER/MANAGING DIRECTOR

ASK ALL EXCEPT OWNER OR MANGING DIRECTOR AT A2b (CODES 1-2) – CODE THESE AUTOMATICALLY AS YES AT E1 E1. Are you the main partner or managing director i n this business? INTERVIEWER NOTE: IF RESPONDENT IS AN EQUAL PARTNER IN THE BUSINESS CODE ‘YES’. Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4 TEXT IF NOT MAIN PARTNER/MD (CODE 2 AT E1) For the following questions I’d like you to answer, to the best of your knowledge, about the main partner or managing director. If yo u’re not sure of the answer just let me know and I’ll move on to the next question. INTERVIEWER NOTE: IF MORE THAN ONE MAIN PARTNER OR MANAGING DIRECTOR ASK RESPONDENT TO ANSWER ABOUT THE ONE THEY KNOW BEST ASK ALL E2. <IF CODE 1 AT E1: Do you / IF CODE 2-4 AT E1: Does the main partner or managing director> hold more than 20% of the equity in this firm? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4 E3. Is this the only business with which < IF CODE 1 AT E1: you are / IF CODE 2-4 AT E1: they are> currently involved in any capacity? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4 E4. What is the highest level of qualification < IF CODE 1 AT E1: that you hold / IF CODE 2-4 AT E1: that they hold>? PROBE AS PER PRECODES. STOP AFTER FIRST ONE CODED. SINGLE CODE. A degree, HND, masters degree or other higher degree ............ 1 A-levels, AS-levels or OND ........................................................ 2 5 or more GCSEs grades A to C, 5 or more O-levels, NVQ level 2 or similar ................................................................. 3 CSEs or less than 5 GCSEs grades A to C or NVQ level 1 ........ 4 Other (SPECIFY) ....................................................................... 5 None .......................................................................................... 6 (Don’t know) ............................................................................... 7 (Refused) ................................................................................... 8



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E5. And which of the following age bands do < IF CODE 1 AT E1: you / IF CODE 2-4 AT E1: they> fall into? READ OUT. SINGLE CODE. Under 25 .................................................................................... 1 25 - 34 ........................................................................................ 2 35 - 44 ........................................................................................ 3 45 - 54 ........................................................................................ 4 55 - 64 ........................................................................................ 5 65 and over ................................................................................ 6 (Don’t know) ............................................................................... 7 (Refused) ................................................................................... 8 ASK ALL E8. Have <IF CODE 1 AT E1: you / IF CODE 2-4 AT E1: they> been involved in starting any other businesses apart from this one? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4 IF STARTED OTHER BUSINESSES (CODE 1 AT E8) E9. How many? READ OUT AS NECESSARY Just one other company ............................................................. 1 Two or three other companies .................................................... 2 More than three other companies ............................................... 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4 E10b. <IF CODE 1 AT E1: Would you / IF CODE 2-4 AT E1: To the best of your knowledge, would your main partner or managing dire ctor> be willing to issue equity and dilute < IF CODE 1 AT E1: your / IF CODE 2-4 AT E1: their> own ownership of the business to improve its long-term business performance? Yes ............................................................................................. 1 No .............................................................................................. 2 (Don’t know) ............................................................................... 3 (Refused) ................................................................................... 4



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SECTION F: GVA ASK ALL F1. For the final part of this research, we just ne ed to collect from you a few pieces of financial performance information, for wh ich you will need to refer to your most recent set of annual accounts. REASSURE AS NECESSARY: The information we need relates to your operating profit, employee costs, depreciation and assets. O nce again, the research is being conducted on behalf of the Department of Trad e and Industry and any financial information you provide will only be used by the research team in their analysis, treated as strictly confidential and will not be passed on in attributable form. Are you able to get a copy of your accounts in fron t of you now? ALLOW RESPONDENT TO PUT YOU ON HOLD AS NECESSARY Yes ............................................................................................. 1 - GO TO F4 No .............................................................................................. 2 – GO TO F2 (Don’t have any accounts) .......................................................... 3 – GO TO F11 IF NO (CODE 2 AT F1) F2. In that case, could I please send you a short q uestionnaire to fill out? I can either send you an electronic copy by email, or a p aper copy in the post. Either way, you will need to refer to your most recent set of accounts when completing the questions, returning your answers to us either by email or in the post. Alternatively you could simply fax or post us a cop y of < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP just the relevant pages of > your most recent accounts and we will complete the questionna ire for you. Which would you prefer – an email questionnaire, a paper questionnaire sent in the post or to fax or post us < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP the relevant pages from > your accounts? Email questionnaire ........................................................................... 1 Paper questionnaire sent in the post ................................................. 2 Fax copy of accounts ........................................................................ 3 Post copy of accounts ....................................................................... 4 (Refused to supply accounts information) .......................................... 5 – GO TO F11 IF PREFER EMAIL QUESTIONNAIRE (CODE 1 AT F2) F3a. Could I please take a note of your email addre ss? INTERVIEWER NOTE: CLARIFY ALL SPELLING AND PUNCTUATION READ ADDRESS BACK TO RESPONDENT TO CHECK IT IS CORRECT ..........................................................................................................



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IF PREFER PAPER QUESTIONNAIRE (CODE 2 AT F2) F3b. Can I confirm that your address is…? READ OUT – CATI TO DISPLAY ADDRESS FROM SAMPLE (INCLUDING COMPANY NAME) Yes - correct ...................................................................................... 1 No (ENTER CORRECT ADDRESS) ................................................. 2 IF PREFER TO FAX ACCOUNTS (CODE 3 AT F2) & NOT A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 1, 2, 6, 7 OR 8 AT A3) F3c. Could you please fax a copy of your accounts t o 01622 790902 quoting reference < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to contact us on 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK FAX AND REFERENCE NUMBER TO CHECK CORRECT IF PREFER TO FAX ACCOUNTS (CODE 3 AT F2) & A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) F3c. We only need you to fax us the following pages – your statutory profit and loss statement (this should be near the front of yo ur accounts), your balance sheet (which should be the page after your statutor y profit and loss statement) and your trading and profit and loss statement (whi ch should form the last pages of your accounts). Please fax copies of these to 01 622 790902 quoting reference < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to contact us on 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK FAX AND REFERENCE NUMBER TO CHECK CORRECT IF PREFER TO POST ACCOUNTS (CODE 4 AT F2) & NOT A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 1, 2, 6, 7 OR 8 AT A3) F3c. Could you please post a copy of your accounts to OMB Research Limited, 259 Forstal Road, Aylesford, Kent, ME20 7AP quoting reference < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to co ntact us on 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK ADDRESS AND REFERENCE NUMBER TO CHECK CORRECT IF PREFER TO POST ACCOUNTS (CODE 4 AT F2) & A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) F3c. We only need you to post us the following page s – your statutory profit and loss statement (this should be near the front of yo ur accounts), your balance sheet (which should be the page after your statutor y profit and loss statement) and your trading and profit and loss statement (whi ch should form the last pages of your accounts). Please post copies of these to O MB Research Limited, 259 Forstal Road, Aylesford, Kent, ME20 7AP quoting ref erence < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to contact us o n 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK ADDRESS AND REFERENCE NUMBER TO CHECK CORRECT



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IF HAVE ACCOUNTS TO HAND (CODE 1 AT F1) (OTHERS GO TO F11) F4. Can I just check that you have your most recent annual accounts in front of you, and that they contain information for your las t 2 financial years for which you have accounts? IF NO, ASK RESPONDENT TO GET ACOUNTS Yes .................................................................................................... 1 (Decided to give financial info by other method e.g. email, post, fax) 2 – GO TO F99a F5a1. Firstly, can you tell me the year end date of the most recent year shown on these accounts? IF NECESSARY: The most recent year is normally the left hand column on each page, and the year end date is shown at the top. INTERVIEWER: CODE MONTH FIRST, THEN YEAR January ............................................................................................. 1 February ............................................................................................ 2 March ................................................................................................ 3 April ................................................................................................... 4 May ................................................................................................... 5 June .................................................................................................. 6 July ................................................................................................... 7 August ............................................................................................... 8 September ........................................................................................ 9 October ............................................................................................. 10 November ......................................................................................... 11 December ......................................................................................... 12 (Don’t know) ...................................................................................... 13 (Refused) .......................................................................................... 14 (Decided to give financial info by other method e.g. email, post, fax) 15 – GO TO F99a F5a2. CODE YEAR 2002 .................................................................................................. 1 2003 .................................................................................................. 2 2004 .................................................................................................. 3 2005 .................................................................................................. 4 (Pre 2002) ......................................................................................... 5 (Don’t know) ...................................................................................... 6 (Refused) .......................................................................................... 7 (Decided to give financial info by other method e.g. email, post, fax) 8 – GO TO F99a F5b. And how long did this accounting year cover? Was it 12 months or some other period? 12 months ......................................................................................... 1 Other period (SPECIFY NUMBER MONTHS) ................................... 2 (Don’t know) ...................................................................................... 3 (Refused) .......................................................................................... 4 (Decided to give financial info by other method e.g. email, post, fax) 5 – GO TO F99a



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F5c1. And what is the year end date of the previous year? IF NECESSARY: This is normally the right hand column on each page, and th e year end date is shown at the top. INTERVIEWER: CODE MONTH FIRST, THEN YEAR January ............................................................................................. 1 February ............................................................................................ 2 March ................................................................................................ 3 April ................................................................................................... 4 May ................................................................................................... 5 June .................................................................................................. 6 July ................................................................................................... 7 August ............................................................................................... 8 September ........................................................................................ 9 October ............................................................................................. 10 November ......................................................................................... 11 December ......................................................................................... 12 (Don’t know) ...................................................................................... 13 (Refused) .......................................................................................... 14 (Company only has accounts covering one year) .............................. 15 (Decided to give financial info by other method e.g. email, post, fax) 16 – GO TO F99a IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F5c2. CODE YEAR 2002 .................................................................................................. 1 2003 .................................................................................................. 2 2004 .................................................................................................. 3 2005 .................................................................................................. 4 (Pre 2002) ......................................................................................... 5 (Don’t know) ...................................................................................... 6 (Refused) .......................................................................................... 7 (Decided to give financial info by other method e.g. email, post, fax) 8 – GO TO F99a IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F5d. And how long did this accounting year cover? AS NECESSARY Was it 12 months or some other period? 12 months ......................................................................................... 1 Other period (SPECIFY NUMBER MONTHS) ................................... 2 (Don’t know) ...................................................................................... 3 (Refused) .......................................................................................... 4 (Decided to give financial info by other method e.g. email, post, fax) 5 – GO TO F99a



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IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP: Looking now at your statutory profit and loss statement, which sho uld be near the front of your accounts. IF GAVE EXACT TURNOVER FIGURE AT C16a (OTHERS GO TO E6b) F6a. You mentioned previously that your current tur nover is < CATI TO INSERT FROM C16a>. Can I just check that this is the exact figure shown in your accounts for your most recent year? IF NECESSARY There should be one figure given for turnover in your accounts, but it may be referred to as income , sales or receipts .

Yes .................................................................................................................... 1 No (RECORD ACTUAL TURNOVER TO NEAREST WHOLE POUND) ............ 2 (Don’t know) ...................................................................................................... 3 (Refused) .......................................................................................................... 4 (Decided to give financial info by other method e.g. email, post, fax) ................ 5 – GO TO F99a INTERVIEWER - CONFIRM TURNOVER FIGURE BY READING BACK TO RESPONDENT AS INDIVIDUAL FIGURES (E.G. 1 – 2 – 1 – 4 – 6 – 7) IF DID NOT GIVE EXACT TURNOVER FIGURE AT C16a (OTHERS GO TO F6c) F6b. What is the turnover figure shown in your acco unts for the most recent year? IF NECESSARY There should be one figure given for turnover in yo ur accounts, but it may be referred to as income , sales or receipts . RECORD TURNOVER TO NEAREST WHOLE POUND .................................. (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a INTERVIEWER - CONFIRM TURNOVER FIGURE BY READING BACK TO RESPONDENT AS INDIVIDUAL FIGURES (E.G. 1 – 2 – 1 – 4 – 6 – 7) IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F6c. And what is the turnover figure shown in your accounts for the previous year? RECORD TURNOVER TO NEAREST WHOLE POUND .................................. (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a INTERVIEWER - CONFIRM TURNOVER FIGURE BY READING BACK TO RESPONDENT IF HAVE ACCOUNTS TO HAND (CODE 1 AT F1) (OTHERS GO TO F11) F7a. < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP Still looking at your statutory profit and loss statement > what is the operating profit



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shown in your accounts for the most recent year? IF NECESSARY Operating profit may be shown as operating loss , net profit or profit to owners’ capital account . IF NECESSARY: Please include any income arising from disposal of assets, but do not deduct any interest payable. RECORD OPERATING PROFIT TO NEAREST WHOLE POUND .................... (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a INTERVIEWER - CONFIRM PROFIT FIGURE BY READING BACK TO RESPONDENT



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IF VALUE GIVEN AT F7a (I.E. NOT ‘DON’T KNOW’ OR ‘REFUSED’) F7b. Can I just check, is that a profit or a loss? Profit ................................................................................................................. 1 Loss .................................................................................................................. 2 (Don’t know) ...................................................................................................... 3 (Refused) .......................................................................................................... 4 (Decided to give financial info by other method e.g. email, post, fax) ................ 5 – GO TO F99a IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F7c. And what is the operating profit shown for the previous year? RECORD OPERATING PROFIT TO NEAREST WHOLE POUND .................... (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a INTERVIEWER - CONFIRM PROFIT FIGURE BY READING BACK TO RESPONDENT IF VALUE GIVEN AT F7c (I.E. NOT ‘DON’T KNOW’ OR ‘REFUSED’) F7d. Again, can I just check, is that a profit or a loss? Profit ................................................................................................................. 1 Loss .................................................................................................................. 2 (Don’t know) ...................................................................................................... 3 (Refused) .......................................................................................................... 4 (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a IF HAVE ACCOUNTS TO HAND (CODE 1 AT F1) (OTHERS GO TO F11) F8a. < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) Turning now to your trading and profit and loss sta tement, which should form the last pages of your accounts, IF NOT A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 1, 2, 6, 7 OR 8 AT A3) Now > I’d like to focus on your total employee costs for the most recent year. These will probably be spread across several entries in your a ccounts, so please look for any entries referring to items such as salaries , wages , labour , pay, pensions and social security costs, but please ignore any payments made to subc ontractors or dividends paid to the owners or directors. What is the total value of all these types of employee costs? INTERVIEWER NOTE: IF EASIER FOR RESPONDENT, RECORD EACH TYPE OF COST SEPARATELY ON A SHEET OF PAPER, ADDING TOGETHER BEFORE ENTERING INTO CATI. ALLOW RESPONDENT PLENTY OF TIME TO ENSURE THAT ALL RELEVANT ENTRIES HAVE BEEN INCLUDED RECORD EMPLOYEE COSTS TO NEAREST WHOLE POUND ...................... (Don’t know) ...................................................................................................... (Refused) ..........................................................................................................



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(Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a Can I just check, that you’ve included all entries referring to salaries , wages , labour , pay, pensions and social security costs. INTERVIEWER: IF NOT, GO BACK AND INCLUDE ADDITIONAL ITEMS



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IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F8b. And what is the total value of your employee c osts for the previous year? Again, please look for all entries referring to ite ms such as salaries , wages , labour , pay, pensions and social security costs, but please ignore any payments made to subcontractors or dividends paid to the own ers or directors. RECORD EMPLOYEE COSTS TO NEAREST WHOLE POUND ...................... (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a IF HAVE ACCOUNTS TO HAND (CODE 1 AT F1) (OTHERS GO TO F11) F9a. < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) Still looking at your trading and profit and loss s tatement IF NOT A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 1, 2, 6, 7 OR 8 AT A3) Next > could you give me a figure for depreciation for the most recent year. IF NECESSARY There could be more than one entry for this, but th ey should all contain the word ‘depreciation’. Please provide a total for all these entries. INTERVIEWER NOTE: IF EASIER FOR RESPONDENT, RECORD EACH TYPE OF DEPRECIATION SEPARATELY ON A SHEET OF PAPER, ADDING TOGETHER BEFORE ENTERING INTO CATI. ALLOW RESPONDENT PLENTY OF TIME TO ENSURE THAT ALL RELEVANT ENTRIES HAVE BEEN INCLUDED RECORD DEPRECIATION TO NEAREST WHOLE POUND ............................ (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F9b. And what is the total figure for depreciation shown for the previous year? IF NECESSARY Again, there could be more than one entry. RECORD DEPRECIATION TO NEAREST WHOLE POUND ............................ (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a IF HAVE ACCOUNTS TO HAND (CODE 1 AT F1) (OTHERS GO TO F11) F10a. Finally, could you give me the figure for tan gible fixed assets for the most recent year. This should be shown on your balance sheet < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) which should be the page after your statutory profi t and loss statement, near the front of your accounts >. IF NECESSARY Your accounts may break down fixed assets into tangible assets, intangible assets and investments, but if so please



201

just give me the figure for tangible assets . If your accounts only refer to fixed assets , without any breakdown, then please give me this f igure. RECORD TANGIBLE FIXED ASSETS TO NEAREST WHOLE POUND ........... (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a



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IF COMPANY HAS ACCOUNTS FOR PREVIOUS YEAR (I.E. NOT CODE 15 AT F5c1) F10b. And what is the figure for tangible fixed ass ets shown for the previous year? IF NECESSARY Again, if your accounts break down fixed assets int o tangible assets, intangible assets and investments, just give me the figure for tangible assets . If your accounts only refer to fixed assets , without any breakdown, then please give me this figure. RECORD TANGIBLE FIXED ASSETS TO NEAREST WHOLE POUND ........... (Don’t know) ...................................................................................................... (Refused) .......................................................................................................... (Decided to give financial info by other method e.g. email, post, fax) ................ – GO TO F99a N.B: F99a-d are the same as F2-F3c and just give respondents the option of opting out of the telephone GVA and completing by another method IF PREFER OTHER METHOD AT F5a1, F5a2, F5b, F5c1, F5c2, F5d, F6a, F6b, F6c, F7a, F7b, F7c, F7d, F8a, F8b, F9a, F9b, F10a or F10b F99a. In that case, could I please send you a short questionnaire to fill out? I can either send you an electronic copy by email, or a p aper copy in the post. Either way, you will need to refer to your most recent set of accounts when completing the questions, returning your answers to us either by email or in the post. Alternatively you could simply fax or post us a cop y of < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP just the relevant pages of > your most recent accounts and we will complete the questionna ire for you. Which would you prefer – an email questionnaire, a paper questionnaire sent in the post or to fax or post us < IF LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP the relevant pages from > your accounts? Email questionnaire ........................................................................... 1 Paper questionnaire sent in the post ................................................. 2 Fax copy of accounts ........................................................................ 3 Post copy of accounts ....................................................................... 4 (Refused to supply accounts information) .......................................... 5 – GO TO F11 IF PREFER EMAIL QUESTIONNAIRE (CODE 1 AT F99a) F99b. Could I please take a note of your email addr ess? INTERVIEWER NOTE: CLARIFY ALL SPELLING AND PUNCTUATION READ ADDRESS BACK TO RESPONDENT TO CHECK IT IS CORRECT .......................................................................................................... IF PREFER PAPER QUESTIONNAIRE (CODE 2 AT F99a) F99c. Can I confirm that your address is…? READ OUT – CATI TO DISPLAY ADDRESS FROM SAMPLE (INCLUDING COMPANY NAME) Yes - correct ...................................................................................... 1 No (ENTER CORRECT ADDRESS) ................................................. 2



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IF PREFER TO FAX ACCOUNTS (CODE 3 AT F99a) & NOT A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 1, 2, 6, 7 OR 8 AT A3) F99d. Could you please fax a copy of your accounts to 01622 790902 quoting reference < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to contact us on 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK FAX AND REFERENCE NUMBER TO CHECK CORRECT IF PREFER TO FAX ACCOUNTS (CODE 3 AT F99a) & A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) F99d. We only need you to fax us the following page s – your statutory profit and loss statement (this should be near the front of yo ur accounts), your balance sheet (which should be the page after your statutor y profit and loss statement) and your trading and profit and loss statement (whi ch should form the last pages of your accounts). Please fax copies of these to 01 622 790902 quoting reference < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to contact us on 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK FAX AND REFERENCE NUMBER TO CHECK CORRECT IF PREFER TO POST ACCOUNTS (CODE 4 AT F99a) & NOT A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 1, 2, 6, 7 OR 8 AT A3) F99d. Could you please post a copy of your accounts to OMB Research Limited, 259 Forstal Road, Aylesford, Kent, ME20 7AP quoting reference < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to co ntact us on 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK ADDRESS AND REFERENCE NUMBER TO CHECK CORRECT IF PREFER TO POST ACCOUNTS (CODE 4 AT F99a) & A LIMITED COMPANY, PLC OR LIMITED LIABILITY PARTNERSHIP (CODES 3, 4 OR 5 AT A3) F99d. We only need you to post us the following pag es – your statutory profit and loss statement (this should be near the front of yo ur accounts), your balance sheet (which should be the page after your statutor y profit and loss statement) and your trading and profit and loss statement (whi ch should form the last pages of your accounts). Please post copies of these to O MB Research Limited, 259 Forstal Road, Aylesford, Kent, ME20 7AP quoting ref erence < xxx CATI TO INSERT ‘OMBREF NUMBER’ FROM SAMPLE > and your company name. If you encounter any problems please do not hesitate to contact us o n 01622 790900. INTERVIEWER NOTE: ASK RESPONDENT TO READ BACK ADDRESS AND REFERENCE NUMBER TO CHECK CORRECT



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ASK ALL F11. That’s the end of < IF NOT PROVIDED FINANCIAL INFORMATION NOW AND AGREED TO SUPPLY LATER (I.E CODE 1, 2, 3 OR 4 AT F2 OR CODE 1,2,3, OR 4 AT F99a) this part of > the survey, thank you for taking the time to help us with this important research < IF NOT PROVIDED FINANCIAL INFORMATION NOW AND AGREED TO SUPPLY LATER (I.E CODE 1, 2, 3 OR 4 AT F2 OR CODE 1,2,3, OR 4 AT F99a) and we look forward to receiving your financial inf ormation in due course >. Would you be willing to take part in any future res earch on this topic conducted on behalf of the DTI or Business Link? Yes .................................................................................................... 1 No ..................................................................................................... 2 (Don’t know) ...................................................................................... 3 ASK ALL F12. We are working with academic researchers at th e Business Schools at Warwick, Kingston and Aston Universities on this pr oject, who would like to be able to analyse the answers you have provided us wi th alongside data you may provide to central Government, such as through Comp anies House. Would you be willing for us to provide the academic research tea m with your company name alongside your answers? INTERVIEWER NOTE: READ OUT F12 EXACTLY AS SCRIPTED AS NECESSARY: This will allow the researchers to ‘look up’ other data held on your business by central Government, which will in turn allow them to conduct a fuller and more meaningful analysis of this survey data. Yes .................................................................................................... 1 No ..................................................................................................... 2 (Don’t know) ...................................................................................... 3 ASK ALL EXCEPT THOSE CONFIRMING THEIR ADDRESS AT F3b F13. Could I just confirm that your business postco de is…? CATI TO DISPLAY POSTCODE FROM SAMPLE – AMEND IF MISSING OR INCORRECT F14. And may I take a note of your name? WRITE IN……………………………………………

STANDARD THANK & CLOSE

AS NECESSARY: If you would like to find out more about Business L ink and their services you can visit www.businesslink.gov.uk



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Appendix B: Survey Weighting Protocols



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ALL BLO USERS - VOLUMES 1 - 5 (NUMBERS) ALL BLO USERS - VOLUMES 1 - 5 (PROPORTIONS)

Less than 10

"10-49"

"50-249" Grand Total

Less than 10

"10-49"

"50-249"

Grand Total

Primary 5436 517 134 6087 Primary 4% 0% 0% 4%

Production 13810 10507 4352 28669 Production 10% 7% 3% 20%

Construction 5110 2826 727 8663 Construction 4% 2% 1% 6%

Services 67410 26514 7579 101503 Services 47% 18% 5% 70%

Grand Total 91766 40364 12792 144922 Grand Total 63% 28% 9% 100%

INTENSIVE BLO USERS - VOLUMES 1 - 5 (NUMBERS) INTENSIVE BLO USERS - VOLUMES 1 - 5 (PROPORTIONS)

Less than 10

"10-49"

"50-249" Grand Total

Less than 10

"10-49"

"50-249"

Grand Total

Primary 884 80 18 982 Primary 5% 0% 0% 6%





OTHER BLO USERS - VOLUMES 1 - 5 (NUMBERS) OTHER BLO USERS - VOLUMES 1 - 5 (PROPORTIONS)

Less than 10

"10-49"

"50-249" Grand Total Sole trader

"10-49"

"50-249"

Grand Total

Primary 4552 437 116 5105 Primary 4% 0% 0% 4%







208

Appendix C: Face-to-Face Topic Guide

(Note: This is the version used for the Intensively-Assisted Firms)



209

BLO ECONOMIC IMPACT STUDY: TOPIC GUIDE

Thank you for agreeing to meet me/us. The SBRC has been commissioned by the Small Business Service to conduct a study looking at the impact of Business Link services and support (delivered in the period April to September2003) on your business. You have already participated in the national telephone survey undertaken between May and July of this year. The purpose of our visit now is to probe in more detail on the precise nature of the services and support provided the way it has influenced the development of your business and to gauge your overall experience of the relationship with Business Link. Rather than simply looking for ‘yes/no’ answers, the questions allow you to give your answers at length if you wish. Your replies will, of course, be treated in the strictest confidence. At the end of the study we will send you a summary of the research findings so you can compare your own experiences with those of other business owners.

Name of respondent (with position) Name of business Business address Interviewer Date of interview Assistance Category: Intensively Assisted Other Assist Non-Assisted Business Link Operator:

Appropriate warm up questions – e.g. about the nature of the business? When was it established? Future aims for the business? About the interviewee – e.g. brief employment history? What were their reasons and objectives for setting up (or buying, joining) business? Introduction

• What have been the major events since 2003 which have altered the firm's growth pattern? Probe:



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- Were they unforeseen? - How did the business react to them? - What was the outcome? - Was the performance of the business better or worse than expected in that

period? - What are your reasons for saying that?

Contact with Business Link I’d like to now ask you a few background questions about your relationship with your local Business Link.

• How did you first find out about your local Business Link? Probe: When was this?

• In what year did the business first contact BL?

Probe: - What was your reason? (expectations and motivations) - What was the outcome?

• Thinking back two years, what were your motives for seeking assistance (or

accessing services and support) from your local Business Link in the period April to October 2003 (this is the specific period we are interested in as part of this study): Probe:

- Did you initiate the contact? - Was the business growing or declining? - facing tough competition? - struggling to maintain sales/market share? (see QC6 responses to

elaborate).

• What did you expect to achieve from the relationship with Business Link? Probe:

- …and the reality? - How are they able to arrive at this opinion with respect to expectations –

benchmarked against what other experiences? Nature of Assistance

• How would you describe your initial meetings with the Business Link? Probe: How did the business advisor present him/herself:

- as an expert (on the issues you were seeking advice and assistance - critical friend who you bounce ideas off



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- as doctor who diagnosed what problems you business was facing

• How did you (and adviser?) decide that the particular assistance that you received was the right one for you? Probe:

- Had you decided that the problem was the most pressing for you before the meeting?

- Did you prioritise with your advisor, which issues to tackle? - Or did it feel like you ended up focussing on a problem that Business

Link/consultant had a fix for?

• What services and support did you receive from Business Link in the period April to October 2003? Probe: Nature of the IDB ‘model’ – and the range of services.

- What were the most important aspects of the services and support provided? Why do you say that?

- Was the solution tailored to your business needs? - Were you able to draw on existing product offers?

• What alternative sources of business support were available? Probe:

- Were you aware of these alternatives at time? - Did you try to use these alternatives? – if so what was the outcome? - How do you think BL rank compared to these other sources of services

and support? - What did you get from BL that they couldn't get from elsewhere - was it a

subsidised price or a unique service? Delivery of Assistance

• How were those services provided by Business Link between April to October 2003 delivered? Probe:

- Directly from the BL or via third parties? - How was the external individual or organisation chosen? - How much control did you have of this process?

• Thinking back, how satisfied were you with the way those services and support

were delivered?

Probe: - Relationship with the Business Advisor? - Competence of third parties?



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- Specific knowledge of your business – and was this necessary to deliver the services and support required?

- (where third party – did BL help you manage, get the most of the contractor ?)

- If rural – did the business advisor have specific awareness of the issues facing you as a business located in a rural area? If so, what are those issues?

• Did you pay for any of the services provided by or through Business Link?

Probe: - If yes did you feel they you getting value for money?

• What were your experiences of the development of the Strategic Action Plan?

Probe: - How closely involved were you with its development? - Did you agree with all of its contents and proposed actions? - Relationship with the Business Advisor? - Did it identify issues that you were already aware/unaware of? - Did you implement all/some/any of the changes proposed in the Strategic

Action Plan? Impact on the Business

• In what ways has the support provided by Business Link in 2003 impacted upon your business over the last 2 years? Probe: See responses to QC11a for the range of possible areas we are seeking to cover here.

- How critical was the BL support to these changes? - Why do you say that? - Have all the benefits been realised? – why not? - Important to cover ‘hard’ and ‘soft’ outcomes – the latter picking up on

aspects of changing the way the business operates … and then leading into the additionality question …..

• Which ONE of the following statements best describes your view on the contribution the support you have received from Business Link has made, or will make, to your firm?

i. We would have achieved similar business outcomes anyway

ii. We would have achieved similar business outcomes, but not as quickly iii. We would have achieved some but not all of the business outcomes iv. We probably would not have achieved similar business outcomes v. We definitely would not have achieved similar business outcomes vi. (None of these)



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Probe: What is the reason for saying that? – need to explore the response in detail here – seeking precise examples of timing and scale – if all outcomes not achieved which ones?. How has this affected the performance of the business? If ‘zero’ additionality need to probe on why they say that and relate to earlier responses on the BL relationship and their motivations for going to them in the first place.



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Finally….

• Have you used Business Link since October 2003? Probe: When and what for? Have you maintained contact with any providers initially brokered by the contact with Business Link?

• What improvements would you suggest could be made to the nature and delivery of the services and business support provided by Business Link? Probe: Refer to the 2003 assistance and/or the most recent assistance received. Internal/External brokerage? What are your general perceptions of BL? Were there any unmet needs from the assistance?

• Have you used other business advice services since 2003? Probe: When and what for?

Any other comments? Thank you and close interview.



215

Appendix D: Additional Estimation Results Excluding Selection Effects



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Box 4.1: Econometric Approach – Allowing for Selectivity in BL Assistance

Our focus here is the causal effect of BL assistance provided during the April to September 2003 period on business performance between the 2004 and 2005 business years. If π is any potential indicator of business growth, a basic model that encapsulates these effects can be defined as follows:

εδβπ ++= zx (1)

Where: x is a vector of firm, market and owner-manager characteristics, and z is a binary variable taking value 1 if a firm received BL assistance, and 0 otherwise. In this model, the size, sign and significance of the coefficient on the ‘treatment’ term (i.e. δ) will give an indication of the impact of BL assistance on business growth. Other studies have shown, however, that such treatment coefficients will give an unbiased indication of the real effect of assistance only if assistance is randomly distributed across the population of small firms. Where there is any element of systematic targeting or selection, the coefficient on the treatment term will reflect a combination of ‘assistance’ and ‘selection’ effects. Rather than direct estimation of equation (1) a preferable approach is therefore to allow explicitly for this type of selection bias. Specifically, we assume that the likelihood or probability of receiving BL assistance (z*) is itself related to a set of business and owner-manager characteristics, v. This suggests a model of the form (Greene, 1995, p. 642):

εδβπ ++′= zx '

z*= γ’v + w (2) What is observed, however, is not the probability of receiving BL assistance (zi*) but a categorical variable which indicates whether a firm was intensively assisted, other assisted or not-assisted. In this situation the standard estimation method for this type of model is the two-stage procedure outlined in Heckman (1979). This involves the estimation of a Probit model to estimate the probability of a firm being either intensively assisted, other assisted or not assisted and the incorporation of a selection parameter in the treatment model for business performance (see Greene, 1995, p. 639 for details). An important issue in operationalising the Heckman type model is the avoidance of too much overlap between the selection and performance models. This is a particular problem in secondary analysis where the variable set may be limited. Our choice of variables here was shaped by awareness of this problem as well as (a) our previous experience of the BL Tracker Study (e.g. Roper and Hart, 2005) (b) our understanding of the small business literature and the determinants of business growth (e.g. Storey, 1994)31. In the probit models we therefore focus on informational variables and objective and observable characteristics of firms – factors which may have provided the basis for administrative criteria for the targeting of assistance. In the growth models we control for more organisational factors and the characteristics of the entrepreneur – both of which have been shown to be important in the small business literature.

31 Roper, S and Hart, M (2005) ‘Small Firm Growth And Public Policy In The UK: What Exactly Are The Connections? Working Paper, Aston Business School (RP0504). Storey, D (1994) ‘Understanding the Small Business Sector’, Routledge, London.



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Table D.1: Impact of Intensive Assistance: Full Model

Employ Growth

Sales Growth

Productivity Growth

Coeff t-stat Coeff t-stat Coeff t-stat Constant 0.014 0.52 -0.037 -0.53 -0.046 -0.62 Firm Characteristics

Firm Size -0.0002 -0.65 -

0.0001 -0.18 0.0004 0.70 Size squared 0.0004 0.40 0.002 0.83 0.0001 0.04 Firm age: 3-4 years -0.027 -1.49 0.041 0.90 0.031 0.59 Firm age: 4-5 years -0.020 -1.20 0.019 0.43 0.030 0.61 Firm age: 5-10 years -0.015 -1.07 -0.014 -0.39 -0.036 -0.89 Firm age: 10-20 years -0.019 -1.41 -0.049 -1.42 -0.050 -1.25 Firm age: 20 plus years -0.027 -1.99 -0.057 -1.59 -0.040 -0.98 Legal Partnership 0.008 0.64 0.034 1.12 0.025 0.76 Ltd Liability Company 0.015 1.48 0.038 1.49 0.017 0.62 Other type of company -0.003 -0.11 0.008 0.09 0.003 0.03 Multi-plant firm 0.024 2.05 -0.019 -0.71 -0.023 -0.77 Exporter 0.001 0.06 0.005 0.26 0.019 0.87 Market Characteristics No. of competitors -0.011 -1.41 -0.009 -0.50 0.030 1.51 Own Price Elasticity -0.006 -0.43 -0.020 -0.69 -0.047 -1.53 Business Strategy Focus: Sales in current markets 0.024 3.09 -0.007 -0.36 -0.013 -0.68 Focus: Sales in new markets 0.016 1.53 0.078 3.59 0.051 2.14 Focus: New products, new markets 0.009 0.62 -0.007 -0.22 -0.014 -0.40 Formal Business Plan 0.026 3.26 0.008 0.42 -0.029 -1.45 Non-executive Directors -0.002 -0.13 0.038 1.35 0.019 0.61 Owner Manager O-M has equity 0.003 0.23 0.034 1.26 0.020 0.67 O-M age 25-34 0.020 0.94 0.033 0.63 0.002 0.04 O-M age 35-44 0.001 0.07 0.021 0.52 0.021 0.49 O-M age 45-54 -0.007 -0.39 0.046 1.17 0.056 1.35 O-M age 55 plus -0.018 -1.03 0.022 0.56 0.047 1.13 Serial Founder -0.002 -0.21 0.015 0.84 0.013 0.69 Intensively-Assisted Firms 0.023 2.40 0.009 0.41 -0.022 -0.88 Selection Parameter -0.005 -0.58 0.030 1.43 0.017 0.75

Note: Models also include a full set of Industry Dummies to control for industry specific differences in employment, turnover, and productivity growth.



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Table D.2: Impact of Other Assistance: Full Model

Employment

Growth Sales

Growth Productivity


Constant 0.030 1.27 0.106 1.28 0.004 0.05 Firm Characteristics Firm Size -0.00004 -0.56 -0.001 -1.63 -0.0002 -0.44 Size squared 0.000003 0.63 0.0003 1.48 0.00005 0.22 Firm age: 3-4 years -0.00038 -0.02 0.115 1.95 0.139 2.06 Firm age: 4-5 years 0.004 0.22 0.021 0.34 0.081 1.20 Firm age: 5-10 years -0.007 -0.56 -0.013 -0.27 0.071 1.22 Firm age: 10-20 years -0.012 -1.01 -0.036 -0.75 0.050 0.89 Firm age: 20 plus years -0.019 -1.54 -0.063 -1.28 0.021 0.37 Legal Partnership 0.007 0.72 -0.008 -0.24 0.003 0.07 Ltd Liability Company 0.019 2.37 0.036 1.28 0.003 0.10 Other type of company -0.014 -0.52 -0.079 -0.79 -0.094 -0.87 Multi-plant firm 0.022 2.12 0.067 1.81 0.031 0.77 Exporter 0.004 0.48 -0.022 -0.78 -0.027 -0.91 Market Characteristics No. of competitors -0.016 -2.38 -0.004 -0.17 0.028 1.14 Own Price Elasticity -0.023 -1.79 -0.104 -2.56 -0.085 -2.00 Business Strategy Focus: Sales in current markets 0.020 2.84 -0.048 -2.10 -0.063 -2.60 Focus: Sales in new markets -0.008 -0.71 0.057 1.97 0.078 2.46 Focus: New products, new markets 0.029 2.21 -0.070 -1.63 -0.060 -1.26 Formal Business Plan 0.001 0.13 0.037 1.49 -0.003 -0.11 Non-executive Directors 0.005 0.48 -0.004 -0.10 0.002 0.04 Owner Manager O-M has equity -0.021 -1.96 0.014 0.41 0.025 0.69 O-M age 25-34 0.015 0.83 -0.014 -0.25 -0.005 -0.08 O-M age 35-44 0.019 1.28 -0.001 -0.03 -0.009 -0.19 O-M age 45-54 0.015 1.08 0.024 0.55 -0.005 -0.11 O-M age 55 plus 0.002 0.10 0.014 0.33 0.025 0.54 Serial Founder 0.009 1.23 0.027 1.20 0.042 1.72 Other-Assisted Firms 0.006 0.66 0.021 0.70 0.049 1.49 Selection Parameter 0.004 0.46 0.030 1.19 0.007 0.27

Note: Models also include a full set of industry dummies to control for industry specific differences in employment, turnover, and productivity growth.



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Table D.3: Impact of Intensive Assistance: Restricted Models

Employ Growth

Sales Growth

Productivity Growth

Coeff t-stat Coeff t-stat Coeff t-stat Constant 0.014 0.985 0.040 0.923 0.019 0.423 Firm Characteristics Firm age: 5-10 years -0.051 -1.810 Firm age: 10-20 years -0.013 -1.606 -0.060 -3.241 -0.063 -2.382 Firm age: 20 plus years -0.022 -2.675 -0.074 -3.976 -0.056 -2.111 Market Characteristics No. of competitors -0.020 -1.307 0.029 1.563 Own Price Elasticity -0.039 -1.380 Business Strategy Focus: Sales in current markets 0.023 3.438 Focus: Sales in new markets 0.074 3.917 0.046 2.042 Formal Business Plan 0.030 4.257 Non-executive Directors 0.046 1.900 Owner Manager O-M has equity 0.035 1.580 O-M age 35-44 O-M age 45-54 -0.014 -1.907 0.036 1.823 O-M age 55 plus -0.020 -2.422 0.027 1.228 Intensively-Assisted Firms 0.028 3.263 0.019 1.007 -0.028 -1.279 Selection Parameter -0.007 -0.929 0.018 1.005 0.016 0.727

Note: Models Also Include a Full Set of Industry Dummies to Control for Industry Specific Differences in employment, turnover, and productivity growth.



220

Table D.4: Impact of Other Assistance: Restricted Models

Employment

Growth Sales

Growth Productivity


Constant 0.049 2.96 0.086 1.81 0.070 1.45 Firm Characteristics Firm age: 3-4 years 0.107 2.61 0.076 1.78 Firm age: 10-20 years -0.016 -1.99 -0.030 -1.16 Firm age: 20 plus years -0.021 -2.70 -0.043 -1.73 Ltd Liability Company 0.016 2.47 Multi-plant firm 0.021 2.08 Market Characteristics No. of competitors -0.018 -2.68 Own Price Elasticity -0.021 -1.69 -0.116 -3.26 -0.092 -2.49 Business Strategy Focus: Sales in current markets 0.022 3.26 -0.045 -2.15 Focus: Sales in new markets 0.073 2.79 0.083 2.96 Formal Business Plan 0.037 1.72 Owner Manager O-M has equity -0.018 -1.87 O-M age 55 plus -0.013 -1.75 Serial Founder 0.043 2.04 0.054 2.43 Other-Assisted Firms 0.007 0.82 0.030 1.12 0.041 1.47 Selection Parameter 0.004 0.48 0.018 0.80 0.002 0.08

Note: Models Also Include a Full Set of Industry Dummies to Control for Industry Specific Differences in employment, turnover, and productivity growth.



221

Appendix E: Excerpt from Conference Paper on the Impact on Employment growth



222

So who benefits from Business Link assistance?

In other words, younger, limited, firms with boards of directors exhibiting higher

gender diversity were more likely to take up intensive assistance. Other assistance

was also being targeted at younger firms with statistically weaker evidence of a

similar gender effect. Also, clear evidence exists that firms in different industries

have different probabilities of receiving assistance. However, a clear distinction also

exists between which industries are likely to receive intensive or other assistance.

Finally, in both cases direct action by BL to recruit contacts seems to have

substantially increased the probability of using BL services.

However, our second question concerns the type of firm and assistance that most

benefits the recipient. To answer this we ‘reverse engineer’ an OLS model of the

impact of intensive assistance on the firm. The OLS model will estimate the

independent effects of firm age, limited liability and business strategy on the firm,

having controlled for these we add a co-efficient for intensive assistance and tested

that. The result is an estimate of effects on employment growth of a number of

factors. If we then take these estimates and strip out their effects on employment

growth we are left with the residual which OLS would on average set at nought and

the impact of the assistance. Using this variable we can then try to understand the

types of firms etc that can explain the impact. In this way the idea is to explain why

some firms gain more impact from assistance that others. Table 12 reports the

descriptive statistics for the variable.

Table 12 Partialed Impact on Employment Growth

N Min Max Mean Std. Deviation

lnva-partintgr

1094 -1.64 2.46 .0674 .29356

The number that we are interested in is only those intensively assisted firms since

that was the impact that we are trying to explain, hence N=1094 in table 12. We

report correlations between the partialled impact on growth and factors that may

help to explain the impact in table 13.

Table 13 Correlates with the Partialled Employment Impact

Factor Correlation P

value

The Firm

Employment category (1=sole trader, 2=1-9, 3=10-49,4=50-

249)

-.074 .015

Age of business category (1=2-3years…) -.091 .003

Age of owner (1=under 25…) -.073 .015

Would you be willing to dilute equity? (1=yes, 2=no) -.083 .006

New or significantly improved processes (1=new, 2=improved,

4=no)

-0.071 .018

Over the past two years have you used any external sources of

information (1=yes, 2=no)

-0.071 .019

Still thinking about these external sources of advice was it basic

advice? (1=Yes, 0= No)

0.071 .018



223

Still thinking about these external sources of advice was it an

in-depth discussion? (1=Yes, 0= No)

0.101 .001

Still thinking about these external sources of advice was it

IT/website related? (1=Yes, 0= No)

0.060 .046

Still thinking about these external sources was this advice from

an accountant? (1=Yes, 0= No)

0.068 .025

Still thinking about these external sources was this advice from

a bank? (1=Yes, 0= No)

0.086 .004

What did you get from Business Link

On average how many times did you contact Business Link

p.a.? (number)

0.062 .044

was it an in-depth discussion? People (1=Yes, 0= No) 0.063 .038

was it Investors in People advice (1=Yes, 0= No) 0.085 .005

IT website related (1=Yes, 0= No) -0.074 .014

Help with finding external consultancy services (1=Yes, 2= No) -0.090 .003

Help with training (1=Yes, 2= No) -0.069 .022

Help with e-commerce, and by that I mean on-line trading (1=Yes, 2= No)

-0.109 .000

Help with IT issues (1=Yes, 2= No) -0.084 .005

Anything else? (SPECIFY) (1=Yes, 2= No) -0.085 .005

Help with advertising (1=Yes, 0= No) 0.299 .010

Was this provided directly by Business Link? (1=all by Business

Link, 2= some referred to outside party)

0.085 .005

Did you have to pay Business Link? (1=Yes, 2= No) -0.061 .044

Behavioural Impact on the Business

The image of the business has improved (1=Yes, 2= No) -0.077 .011

The business has improved its technical capability (1=Yes, 2=

No)

-0.103 .001

The business has improved its financial management skills

(1=Yes, 2= No)

-0.078 .010

The business has improved its planning (1=Yes, 2= No) -0.078 .010

The business has improved its ability to deal with regulation

(1=Yes, 2= No)

-0.067 .026

The business has improved its investment in staff training

(1=Yes, 2= No)

-0.099 .001

The business has improved its ability to introduce new products

or services (1=Yes, 2= No)

-0.116 .000

The business has improved the quality of its products/services

(1=Yes, 2= No)

-0.140 .000

The business has improved (1=Yes, 2= No) -0.078 .010

As a result

How satisfied are you with the services provided by Business

Link? (1=very dissatisfied, 5= very satisfied)

0.018 .553

What could they do better – more knowledgeable advisers

(1=Yes, 0= No)

0.148 .032

What could they do better – continuity of personnel (1=Yes, 0=

No)

-0.152 .027

What could they do better – keep contact (1=Yes, 0= No) 0.281 .000

Are you still using Business Link or planning to in the future?

(1=Yes, 2= No)

-.061 .043

The business is now more inclined to use external business 0.095 .002



224

support for general information and advice (1=Yes, 2= No)

The business is now more inclined to use specialist consultancy

(1=Yes, 2= No)

0.073 .016

Table 13 is rather like a trawl through the factors that make for the impact on

employment growth. Moreover, the table is simply showing correlations with the

partialled employment impact. Nevertheless the data is suggestive. One of the

biggest surprises was the impact of help with advertising yet marketing was not

something that showed any impact.

Different characteristics of firms seemed to make a difference. The firms that were

more innovative had better impacts, those firms that planned also had higher

impacts. As did those managers or firms that took advice from other sources.

The second set of factors concerned the type of advice that Business Link provided.

Here beneficial impacts were found through the provision of simply having the

chance of an in-depth discussion, with an impartial observer. There were

contributions made by the provision of Investors in people and by help with IT and e-

commerce. Also in this section was the ‘write-in’ surprise of advertising. The was not

one of the prompts in the telephone interview but was something that had to be

added by the respondents. One might suggest that the advertising could have been

for employees and therefore would not be causal nevertheless it is intriguing. It

suggests that the ability of Business Links to help with a wider range of specific

needs may be a help rather than a hindrance as has been previously suggested

(Bennett and Robson, 2003).

Finally there are some other resulting issues. In the period covered the brokerage

model for Business link was being introduced. As such the impact of Business Link

might have been through a brokering in of other expertise. At this point in time the

provision of direct advice was correlated with the partialled employment impact of

Business Link. Free advice was also correlated significantly with the impact. In terms

of the future there was a build up of trust amongst those who had good impacts with

Business link although the p value on this factor was only just significant at the 5%

critical value. What was clear was that the Business Link advice had given the

recipients a taste for external advice even if that advice might be found from re-

visiting the Business Link.

economic impact study of business link local...

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