15_chapter 5.pdf - shodhganga

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5. DATA ANALYSIS & DISCUSSIONS

5.1 QUESTIONNAIRE PART I (Q1- Q6) GENERAL QUESTIONS MEETING OBJECTIVE 1 &

6 FOR ALL RESPONDENTS OF THE SAMPLE POPULATION

To arrive at the objective 1 and 6, comprehensive in-depth literature review was made in

Chapter 2 for the period more than twenty years (1990-2013). Questionnaire Part I (Q1

to Q6) remains almost the same for ERP Customers, Vendors & Consultants. Q1

contains the full address of the company and Q2 about the level of designation in the

company. For the survey, ERP Customers (29%: Top level management, 57%: Middle

level management and 14%: Junior level management), ERP Vendor (45%: Top level

management, 37%: Middle level management and 12%: Junior level management), ERP

Consultants (55%: Top level management, 28%: Middle level management and 17%:

Junior level management) comprise the sample of population available for answering the

questionnaire details.

The 3Q is related with the brand of the ERP software being used in the company in which

SAP tops the chart with 34%, Oracle: 29% and others (like PeopleSoft, Microsoft

Dynamics, Ramco, Baan, Invensys, JD Edwards,WebERP4 World, Epicor, Sage, Navision

etc.) contains 37% of the primary data.

Graph 1. Percentage Share of ERP Companies during 2010-2012

(Source: SPSS V 18.0 & MS-Excel 2007) [Source: Self Made]

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While the graph 2 shows the overall market share distribution for the time period from

February 2005 to May 2012. The collected data conclusively shows that SAP ranks

highest of the three vendors, with more than one-fifth (22-percent) of total market share.

It is followed by Oracle with 15-percent of total market share and Microsoft with 10-

percent of total market share. Tier II solutions (including Infor and Epicor) represent just

16-percent of the market while Tier III and others represent a commanding 37% of the

market.

Graph 2. Percentage Share of ERP Companies during 2005-2012


Q5 deals with the business area/product of the company in which 73% comprises utility

area, 11% manufacturing and rest 16% comprises other areas as depicted in graph 3.

Graph 3. Percentage Share of Business Area / Product of a Company (Source: SPSS V 18.0 & MS-Excel 2007) [Source: Self Made]

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However, the best thing has come out in favour of ERP implementation in SMEs in terms

of objectives achieved as mentioned in Q6. All respondents are unanimously agreed that

more than 80% implementation objectives were achieved in terms of streamlining

business process, improving productivity etc.

5.2 QUESTIONNAIRE PART I Q7 (FOR ERP CUSTOMERS) & Q4 (FOR ERP VENDORS &

CONSULTANTS) “WHAT ORGANIZATIONAL PARAMETERS INFLUENCED THE

SELECTION OF ERP IMPLEMENTATION STRATEGY FOR SMES?”[MEETING

OBJECTIVE 3]

ERP applications are still an expensive affair, lots of doubts about their success

considering the failure-rate statistics floating on the Internet. After comparing the

combined values of each variable (on Likert Scale 1 to 5) for ERP implementation

strategy; the most important variable emerged from Frequencies Statistics table is “Level

of Commitment from Top Management” (3.95%) closely followed by “Information

Integrity” & “Resource Planning” (3.94%) with “Availability of the Resources” (3.88%)

as essential qualifier with companies with meager money and resources. One is not just

buying software; one is also buying into a vendor and their company culture therefore full

commitment from top management is the most vital factor in the analysis. It is a given for

information integrity that acceptable system’s results cannot be achieved when systems

are driven by inaccurate data and untimely, uncontrolled documentation. One of the

major challenges in industry today is the “Resource Planning” i.e. timely right sizing of

operations. Profit margins can be eroded by not taking timely downsizing actions, and

market windows can be missed and customers lost by not upsizing the direct labour force

in a timely manner. Only after acquiring all the above factors in hand, the organization is

able to think “Customer Satisfaction”(3.8%), “Change Management Technology”

(3.73%), “Cycle Time Management” (3.62%), “Size of the Organization”(3.60%),

“Need to Restandardize the Process” (3.58%), “BPR & Software Configuration” (3.53%)

factors. Lastly, “Performance Management” (3.46%) comes after everything else as

measurement systems can be motivational or de-motivational.

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Graph 4. Summated Score Analysis for Combined Data of Customers, Vendors & Consultants


5.3 QUESTIONNAIRE PART I Q8 OF ERP CUSTOMERS, “WHAT WERE THE MOST

COMMON PROBLEMS ENCOUNTERED BY SMES DURING ERP IMPLEMENTATION?”

[FACTOR ANALYSIS & RELIABILITY ANALYSIS] MEETING OBJECTIVES 3 & 4

The central aim of this exploratory factor analysis (EFA) is to evaluate and prioritize the

most critical problems (MCPs) during ERP implementation. In effect, SMEs can take

care of these problems on war footing basis to realize its sustainable success stories with

most critical success factors (MCSFs). Data analysis is the process of ordering and

organizing raw data so that it can provide useful information. For the group of 104 ERPs

users, the data were first perused to check whether the data could be analyzed using

factor analysis on not. The KMO measures the sampling adequacy which should be

greater than 0.5 for a satisfactory factor analysis to proceed. Looking at the table 4 below,

the KMO measure is .627 and the Bartlett's test of sphericity is significant. Taken

together, these tests provide a minimum standard which should be passed before a

principal components analysis (or a factor analysis) should be conducted.

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .627

Bartlett's Test of Sphericity Approx. Chi-Square 1078.443

df 105

Sig. .000

Table 4: KMO and Bartlett's Test of Customer’s MCPs (Source: SPSS V 18.0) [Source: Self Made]

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Communalities are the proportion of each variable's variance that can be explained by the

principal components (e.g., the underlying latent continua). Also known as h2, it can be

also defined as the sum of squared factor loadings. By definition, the initial value of the

communality in a principal components analysis is 1. In table 5 of common factor space,

MCPs with high values are well represented, while MCPs with low values are not well

represented. In this example, we don't have any particularly low values. They are the

reproduced variances from the number of components that we have saved.

Initial Extraction

MCP 1 High Cost of ERP System 1.000 .583 MCP 2 Inability to accurately Map Business Process & IT 1.000 .880 MCP 3 Lack of Proper Management System 1.000 .816 MCP 4 Poor IT Infrastructure 1.000 .824 MCP 5 ERP Software Misfit 1.000 .753 MCP 6 Lack of Tailoring of Software 1.000 .834 MCP 7 Inaccurate Data 1.000 .779 MCP 8 Unkempt Knowledge Base 1.000 .856 MCP 9 Elongated Implementation Time 1.000 .866 MCP 10 Inability to Calculate Hidden Costs 1.000 .759 MCP 11 Lack of Proper Monitoring Systems 1.000 .889 MCP 12 Inadequate Training & Documentation 1.000 .820 MCP 13 Improper Gap Analysis 1.000 .815 MCP 14 High Turnover Rate of Project Team Members 1.000 .693 MCP 15 Lack of Will to Join World Class ERP

Implementation with Lean Six Sigma 1.000 .739

Extraction Method: Principal Component Analysis

Table 5. Communalities of Customer’s MCPs (Source: SPSS V 18.0) [Source: Self Made]

Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared

Loadings Rotation Sums of Squared

Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Total % of

Variance Cumulative

%

1 4.924 32.827 32.827 4.924 32.827 32.827 3.064 20.427 20.427

2 2.476 16.509 49.336 2.476 16.509 49.336 2.908 19.384 39.811

3 1.838 12.252 61.588 1.838 12.252 61.588 2.144 14.291 54.102

4 1.417 9.444 71.032 1.417 9.444 71.032 2.030 13.535 67.637

5 1.252 8.347 79.378 1.252 8.347 79.378 1.761 11.742 79.378

6 .740 4.934 84.313

7 .587 3.914 88.226

8 .495 3.300 91.526

9 .402 2.681 94.207

10 .272 1.810 96.018

11 .189 1.257 97.275

12 .154 1.025 98.300

13 .110 .735 99.035

14 .085 .569 99.604

15 .059 .396 100.000

Extraction Method: Principal Component Analysis.

Table 6. Total Variance Explained of Customer’s MCPs (Source: SPSS V 18.0) [Source: Self Made]

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In Table 6, Total Variance Explained (TVE) is the third criterion in solving the number of

factors problem. Factor loading shows straightforward correlation between the factors

and all the MCPs. It involves retaining a component if it accounts for a specified

proportion (or percentage) of variance in the data set. Eigen values are represented in the

total column of the table. Eigen value MCPs (TVE) with greater than 1 value can be

incorporated in final solutions. MCPs with highest Eigen value will be the most important

factor and so on. Each succeeding component will account for less and less variance. %

of Variance column contains the percentage of each principal component variance. The

cumulative% column contains the cumulative percentage of variance accounted by the

current and all preceding principal components. For example, the last row shows a value

of 79.378. This means that the first five components together account for 79.378% of the

total variance.

Rotated Component Matrix (a)

Factors [Most Common Problems as MCPs]

Component

1 2 3 4 5

MCP7 Inaccurate Data .791 .370 -.053 .115 -.013

MCP6 Lack of Tailoring of Software .764 .403 .124 .000 .269

MCP1 High Cost of ERP System .756 .006 -.097 .045 .020

MCP8 Unkempt Knowledge Base .614 .257 .271 -.381 .442

MCP2 Inability to accurately Map Business Process & IT .246 .879 -.015 -.184 .111

MCP15 Lack of Will to Join World Class ERP Implementation with Lean Six Sigma

.034 .810 .222 -.118 -.137

MCP12 Inadequate Training & Documentation

.247 .802 .076 .194 .267

MCP4 Poor IT Infrastructure -.150 .100 .850 .259 .044

MCP14 High Turnover Rate of Project Team Members -.057 -.042 .799 -.214 .055

MCP3 Lack of Proper Management System .410 .328 .709 -.157 .114

MCP11 Lack of Proper Monitoring Systems -.103 -.044 -.122 .926 -.069

MCP13 Improper Gap Analysis .479 .079 .206 .650 .339

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MCP5 ERP Software Misfit .582 -.207 -.057 .604 -.068

MCP10 Inability to Calculate Hidden Costs .111 -.077 .190 -.011 .840

MCP9 Elongated Implementation Time .017 .541 -.163 .049 .737

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 6 iterations.

Table 7. Rotated Component Matrixa of Customer’s MCPs (Source: SPSS V 18.0) [Source: Self Made]

In Table 7 for Rotated Component Matrix, all 15 factors have reduced into five

constructs. The first component is the most highly correlated with maximum

component’s value. After going through each row, we concentrated on the components

that each variable loaded most strongly on. Based on the factor loadings, the first Factor

or the most critical problem Construct 1 comprises of MCP 7, MCP 6, MCP 1, MCP 8

can be termed “Project Process related Problems” as Inaccurate Data and Unkempt

Knowledge Base leads to High Cost of ERP for SMEs. Further Lack of Tailoring of ERP

Software adding miseries to the woes. Since accurate data and knowledge base is the

lifeline of proper ERP implementation; the joint efforts of consultants, vendors and

customers can automate core activities of the organization by re-engineering vital

business activities or by making adjustment in the software (tailoring) according to

organizations requirement (Holland & Light, 2001)[47]. Taking full advantages from

ERP implementation requires Business Process Reengineering (BPR) and it is achieved

through an exhaustive analysis of current business processes. It helps to identify potential

changes in the business processes to avoid customization of the software (Al-Mashari et

al., 2002) [74].

While MCP 2, MCP 15 and MCP 12, all loaded strongly on Construct 2 “Project

Management related Problems” which can be defined as “Inability to accurately Map

Business Process & IT, Inadequate Training & Documentation and Lack of Will to Join

World Class ERP Implementation with Lean Six Sigma become instrumental in

escalating cost, complexity and failure risk of ERP implementation.” These factors badly

need lean approach for immediate gain and six sigma concepts for continuous evaluation,

control and improvement. In the implementation phase, training and education become

other important factors. The implementing organizations must think about proper training

and education from the vendors/consultants before deciding to implement a particular

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ERP solution (Al-Mashari et al., 2002)[74]. Sia (2002) argued that the SMEs are evident

to fail to achieve the benefits from the ERP project because of the lack of staff with

appropriate education and training on technology related to the ERP systems [98]. Hence

it is an important that the implementing organization evaluates whether the vendors or

Suppliers of ERP solutions provide enough training and education. Johansson and

Sudzina (2009) also identified that it is an important selection criteria of Open Source

ERP Selection. Further, better knowledge about Lean ERP is suitable strategic method

for achieving SME’s objectives [54].

Later MCP 4, MCP 14 and MCP 3 loaded strongly on Construct 3 “Project

Implementation related Problems” as Poor IT Infrastructure, High Turnover Rate of

Project Team Members and Lack of Proper Management System. These issues occur all

the time, typically due to poor planning or a lack of proper execution of the project.

Simply buying an ERP system is not a quick fix for a business. Implementing a system

requires a concerted effort across an organization. If companies are unable to administer

proper implementation techniques, it may be best to contact a managed services provider

that can assist with ERP operations and allow business to profit from their investment.

By optimizing project management for better ERP implementation, too much software

modifications or tailoring can also be prevented.

The Construct 4 contains MCP 11, MCP 13 and MCP 5 can be summarized as “Change

Management related problems” tells that “Lack of Proper Monitoring, Improper Gap

Analysis and ERP Software Misfits lead to Cost Overruns”. While ERP systems, in

theory, are acquired to assist in efficient, cost-saving strategies; improper functioning

without change management could end up costing more money in continuous

maintenance and convoluted operations. Without using best practices with the changing

environment, involving the procurement and implementation of a solution, an ERP

system could in fact make matters worse.

Further, the MCP 10 and MCP 9 define Construct 5 as “Hidden Hurdles for SMEs”.

It reflects in “Elongated Implementation Time and Inability to Calculate Hidden costs”.

In addition to the cost of purchase, most organizations often fail to factor in hidden costs

during evaluation, consulting, implementation, training, transition, delayed ROI and post

implementation support. All the above factors can lead to cost overruns, schedule

http://www.compasys.com/managed-it.php

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overruns and functionality overruns. This ultimately results in negative ROI and a

prolonged payback period. Elongated implementation time often leads to fatigue, stressed

and dubious state of mind in customers which affect the growth period of ERP, to a

greater extent.

After examining factor scores for all the five constructs, reliability test was conducted

separately. Reliability analysis is determined by obtaining the proportion of systematic

variation in a scale, which can be done by determining the association between the scores

obtained from different administrations of the scale. Thus, if the association in reliability

analysis is high, the scale yields consistent results and is therefore reliable. Cronbach's

alpha is a measure of internal consistency (reliability), i.e.; how closely related a set of

items are as a group. A "high" value of Cronbach alpha as depicted in table 8 (Construct

1 scored .832), table 9 (Construct 2 scored .839) as quite good suggesting that the items

have relatively high internal consistency, table 10 (Construct 3 scored .730) and table 11

(Construct 4 scored .712) as OK. Table 11 constructs having low value of alpha could be

poor interrelatedness between items that can be further revised or discarded.

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.832 .830 4

Table 8. Reliability Statistics for Construct 1(Source: SPSS V 18.0) [Source: Self Made]


.839 .841 3

Table 9. Reliability Statistics for Construct 2 (Source: SPSS V 18.0) [Source: Self Made]


.730 .739 3




.712 .739 3



.578 .596 2

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In conclusion, the results are completely a root cause analysis for SMEs where actual

results are below goals or when goal are significantly below external benchmarks. SMEs

10 years back could manage without ERP, but no more! Optimized Project Management

and Change Management are about setting expectations that lessen the pain of change. If

Indian SMEs can adapt the ERP software with only essential customization/tailoring, not

only can it benefit by the global practices incorporated in the system, but also save huge

money and time. Thus cost of an ERP depends on the management’s willingness to go

with the ERP or the extent of tailoring it needs. Besides ERP can be the road to

prosperity if one can implement world class ERP to product and process improvement/

benchmarking through the effective use of statistical methods in Lean Six Sigma skills. In

view of the above result and discussions, with all its pros & cons clubbed together, the

journey to MCPs to MCSFs is safe and feasible reality for SMEs towards a sustainable

growth of ERP.

5.4 QUESTIONNAIRE PART I Q5 OF ERP VENDORS “WHAT ARE THE MOST COMMON

PROBLEMS VIEWED BY VENDORS DURING ERP IMPLEMENTATION?” [FACTOR

ANALYSIS & RELIABILITY ANALYSIS] MEETING OBJECTIVES 3 & 4

Part 1 Q5 investigates the most common problems (MCPs) viewed by ERP Vendors

during ERP implementation. The KMO and Bartlett’s test in table 13 was in favour of

factor analysis with KMO measure of sampling adequacy is .630 for the group of 70 ERP

Vendors. TVE (in table 14) and Scree plot for the data show cumulative percentage of

variance accounted by the first five components (having Eigen value > 1) together

contain a value of 78.234 of the total variance.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .630


df 120

Sig. .000

Table 13. KMO and Bartlett's Test for MCPs of Vendors

(Source: SPSS V 18.0) [Source: Self Made]

http://www.essindia.com/undefined/

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Component

Initial Eigenvalues

Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

dimension0

1 5.554 34.714 34.714 5.554 34.714 34.714 3.276 20.477 20.477

2 2.534 15.840 50.555 2.534 15.840 50.555 3.229 20.182 40.659

3 1.740 10.877 61.431 1.740 10.877 61.431 2.194 13.711 54.370

4 1.446 9.040 70.471 1.446 9.040 70.471 2.048 12.799 67.169

5 1.242 7.763 78.234 1.242 7.763 78.234 1.770 11.065 78.234

6 .775 4.844 83.079

7 .690 4.311 87.390

8 .560 3.502 90.892

9 .429 2.679 93.571

10 .290 1.815 95.386

11 .210 1.313 96.699

12 .180 1.124 97.823

13 .136 .850 98.673

14 .103 .645 99.318

15 .070 .436 99.754

16 .039 .246 100.000


Table 14. Total Variance Explained of MCPs of Vendors (Source: SPSS V 18.0) [Source: Self Made]

Graph 5. Scree Plot of TVE for Vendor’s MCPs (Source: SPSS V 18.0) [Source: Self Made]

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In Rotated Component Matrix as depicted in table 15, all 16 MCPs as variables have

reduced into five characteristics/ constructs.

Rotated Component Factors of MCPs Component

1 2 3 4 5

MCP2 Inability to accurately Map Business Process & IT .889 .199 .002 -.187 .068

MCP13 Inadequate Training & Documentation .815 .220 .078 .190 .216

MCP16 Lack of Will to Join World Class ERP Implementation

with Lean Six Sigma

.801 .042 .254 -.161 -.134

MCP7 Cost Overruns .460 .407 .396 -.441 .303

MCP8 Inaccurate Data .368 .804 -.034 .001 .016

MCP1 High Cost of ERP System .049 .749 -.098 -.015 .024

MCP6 Lack of Tailoring of Software .424 .744 .152 -.087 .247

MCP5 ERP Software Misfit -.201 .712 -.028 .448 -.048

MCP9 Unkempt Knowledge Base .320 .513 .253 -.427 .475

MCP4 Poor IT Infrastructure .104 -.137 .838 .259 -.032

MCP15 High Turnover Rate of Project Team Members -.047 -.070 .747 -.215 .141

MCP3 Lack of Proper Management System .354 .354 .696 -.206 .086

MCP12 Lack of Proper Monitoring Systems -.066 .040 -.104 .935 -.078

MCP14 Improper Gap Analysis .080 .530 .221 .567 .362

MCP11 Inability to Calculate Hidden Costs -.046 .095 .167 -.066 .834

MCP10 Elongated Implementation Time .598 -.037 -.190 .095 .677

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 6 iterations.

Table 15. Rotated Component Matrixa of Vendor’s MCPs (Source: SPSS V 18.0) [Source: Self Made]

Further Item analysis/ Reliability analysis helps in evaluating the correlation of related

survey items with only a few statistics. Most important is Cronbach's alpha, a single

number that tells that how well a set of items measures a single characteristic. This

statistic is an overall item correlation where the values range between 0 and 1. Values

above 0.7 are often considered to be acceptable. In the same way, a group of 4 questions

Q5b, Q5m, Q5p and Q5g can be summarized in “Project management related problems

with ERP & lean six sigma” with Cronbach’s Alpha value .850 (Good) as the foremost

and most important factor. Second construct/characteristics can be defined as “Project

process related problems” having Cronbach’s Alpha value .808 (Good). The third

construct ”Project implementation related problems” having α value .697 (nearly Good)

and the fourth construct “Change management related factors” construct with α value

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.613 and the fifth one “Hidden hurdles for SMEs” (α value .528) suggest that respondents

gave markedly different ratings which can be adjusted further.

5.5 QUESTIONNAIRE PART I Q5 OF ERP CONSULTANTS “WHAT ARE THE MOST

COMMON PROBLEMS VIEWED BY CONSULTANTS DURING ERP IMPLEMENTATION?”

[FREQUENCY ANALYSIS ON LIKERT SCALE 1 TO 5] MEETING OBJECTIVES 3 & 4

To know how to get the best from an ERP package, it is important to first analyze the key

factors that are responsible for ERP failures. According to ERP Consultants, lack of

proper monitoring system (on the whole) is the leading problem (4.33%), leaving project

management (as a part of whole system) far behind (3.73%). It needs top management

intervention at the priority basis. Elongated implementation time coupled with

inadequate training and documentation (4.2%) sequenced by combined effect of high cost

of ERP system with lack of tailoring of ERP software (4.13%) are the next major

headache related with project management related problems.

Graph 6: MCPs Encountered by SMEs Consultants (Source: SPSS V 18.0 & MS-Excel 2007) [Source: Self Made]

Next frequent problems come under the purview of change management & software

engineering related areas. These are improper gap analysis (4.10), inability to accurately

map business process & IT (3.90), high turnover rate of project team members (3.8), poor

IT infrastructure (3.77%), a mixed effect of inaccurate data, unkempt knowledge base

(3.73%), lack of will to join world class ERP implementation with lean six sigma

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(3.63%) and ERP software misfit. Obviously, inability to calculate hidden cost (3.37%)

comes in last but this ultimately results in negative ROI and a prolonged payback period.

5.6 QUESTIONNAIRE PART I Q9 OF ERP CUSTOMERS, “WHAT THE END CUSTOMER OF

SMES IS LOOKING FROM THE ERP SOFTWARE?” [FACTOR ANALYSIS][MEETING

OBJECTIVE 3]

The topic of the questionnaire is very relevant and the terms coined as end customer

factors (ECF1 to ECF8) to denote the concepts used here. For the group of 104 ERP

customers, the KMO measure of sampling adequacy in table 16 is .619 and the Bartlett's

test of sphericity is .000 (less than 0.05) is noteworthy to conduct factor analysis. As

shown in table 17, TVE table and Scree plot for the data show collective percentage

accounted by the first four major components around 67.451 of the total variance.




df 28

Sig. .000

Table 16. KMO Bartlett's Test for ECF Analysis of Customers (Source: SPSS V 18.0) [Source: Self Made]

TVE Table

Component

Initial Eigenvalues


Loadings


Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

dimension0

1 2.011 25.135 25.135 2.011 25.135 25.135 1.929 24.111 24.111

2 1.279 15.983 41.118 1.279 15.983 41.118 1.176 14.695 38.806

3 1.101 13.769 54.886 1.101 13.769 54.886 1.166 14.580 53.386

4 1.005 12.565 67.451 1.005 12.565 67.451 1.125 14.065 67.451

5 .799 9.989 77.440

6 .737 9.210 86.649

7 .592 7.395 94.044

8 .476 5.956 100.000


Table 17. Total Variance Explained for ECF Analysis for Customers (Source: SPSS V 18.0) [Source: Self Made]

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By using rotation method (Varimax with Kaiser Normalization), 8 factors have reduced

into four constructs.

ECFs for ERP Selection Component

1 2 3 4

ECF7 Focused Performance Measure .765 .142 -.145 .178

ECF6 Data Conversion & Integrity .740 -.096 .125 -.171

ECF8 Ease of Customization .634 .071 -.071 .385

ECF5 Vendor Customer Relationship .121 .825 .202 .009

ECF1 Fast Turnaround .429 -.518 .371 -.041

ECF4 Low Unit Cost -.015 .132 .863 -.051

ECF2 High Quality of Product .437 .417 -.448 -.249

ECF3 User Friendliness .074 -.016 -.007 .922


Table 18. Rotated Component Matrixa for ECF Analysis for Customers


In conclusion, the most important characteristics that have emerged in the scenario can be

contrived as “Lean ERP”, which the end customer is looking for. “Vendor customer

relationship for fast turnaround” comes at the next position, thirdly “User benefit” and

lastly “User friendliness”.

5.7 QUESTIONNAIRE PART I Q6 FOR ERP VENDORS, “WHAT SALE CRITERIA OF ERP IS

THE MOST IMPORTANT FOR ERP VENDORS?” [FACTOR ANALYSIS] [MEETING

OBJECTIVE 3]

In table 19, the KMO measure of sampling adequacy is .598 and the Bartlett's test of

sphericity is .000, enough to conduct factor analysis. TVE table for the data show

collective percentage accounted by the first three major components around 56.260 of the

total variance.




df 28

Sig. .000

Table 19. KMO and Bartlett's Test for Sale Criteria of Vendors (Source: SPSS V 18.0) [Source: Self Made]

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Table 20. Total Variance Explained for Sale Criteria of Vendors (Source: SPSS V 18.0) [Source: Self Made]

By using rotation method (Varimax with Kaiser Normalization), 8 factors have reduced

into three constructs only in comparison of four for ERP customers (as mentioned in table

21). From the Vendor point of view, the most important requirement for the user is again

“Lean ERP” with one feature extra as high quality of product that the user craves for. At

the second place, “User friendliness” and lastly, “User benefit” in terms of vendor

customer relationship. It is really surprising to note here that low unit cost does not carry

much importance in comparison of high quality of product.

Rotated Component Matrixa

SALE CRITERIA FOR ERP VENDORS Component

1 2 3

Focused Performance Measure .831 .038 .074

High Quality of Product .776 -.270 -.051

Ease of Customization .605 .321 -.085

Data Conversion & Integrity .567 .331 .276

User Friendliness .036 .704 -.008

Fast Turnaround .106 .507 -.102

Vendor Customer Relationship .162 -.288 .797

Low Unit Cost -.206 .515 .560


Table 21. Rotated Component Matrixa for Sale Criteria of Vendors (Source: SPSS V 18.0) [Source: Self Made]


Component

Initial Eigenvalues


Loadings


Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

dimension0

1 2.105 26.313 26.313 2.105 26.313 26.313 2.062 25.770 25.770

2 1.373 17.166 43.479 1.373 17.166 43.479 1.388 17.352 43.122

3 1.022 12.781 56.260 1.022 12.781 56.260 1.051 13.138 56.260

4 .951 11.892 68.152

5 .855 10.689 78.841

6 .803 10.040 88.881

7 .482 6.030 94.911

8 .407 5.089 100.000


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5.8 QUESTIONNAIRE PART I Q6 OF ERP CONSULTANTS, “WHAT THE END CONSULTANT

IS LOOKING FROM THE ERP SOFTWARE?” [FREQUENCY ANALYSIS ON LIKERT SCALE

1 TO 5] [MEETING OBJECTIVE 3]

From the survey, it is clear that “High quality of product” (4.43%) with “Ease of

customization” (4.3%) & “Fast turnaround” (4.23%) commands the topmost position for

the Consultants just as Customer’s requirement list. SMEs require flexibility of the ERP

system (tailoring / optimizing parameters) because of their individual operational process.

“Data conversion and integrity” (4.20%) is the next important prerequisite, sequenced by

“Vendor-Customer relationship” & “Focused Performance Measure” (having same rating

of 4.10%). Unexpectedly, “Low unit cost” (3.63%) matters least for them followed by

“User friendliness” (4.0%) as they emphasis most on best quality of product.

Graph 7: End Customer’s Factors (ECFs) for Consultants (Source: SPSS V 18.0 & MS-Excel 2007) [Source: Self Made]

5.9 QUESTIONNAIRE PART I Q10 FOR ERP CUSTOMERS, Q7 FOR ERP VENDORS &

CONSULTANTS, “HOW SMES MAKE DECISION FOR SELECTING AN ERP VENDOR?”

[COMPARATIVE FREQUENCY ANALYSIS WITH SUMMATED SCORES FOR ALL

RESPONDENTS] [MEETING OBJECTIVE 3]

ERP Vendor Selection process can be a very complicated and problematic for SMEs if

they don't know how to approach it from the very start. Different clients have different

needs ranging from functional requirements, technical maturity, tolerance for risk,

budget, and a host of other factors. These variables influence not only the choice of

vendor, but also the choice of specific solution offered by the vendors. Since the number

103

of decision factors (DF1to DF7) is less for the criterion set for ERP Customers, Vendors

and Consultants, we opt for combined frequency analysis in which the maximum

summated score gained by the factor “Vendor Credentials” (4.29%). Reputation of the

vendor is the most important factor for selecting the vendor and is fully supported by the

primary and secondary data of the Survey. SAP tops the chart with 34%, Oracle: 29%

and others (like PeopleSoft, Microsoft Dynamics, Ramco, Baan, Invensys, JD

Edwards,WebERP4 World, Epicor, Sage, Navision etc.) contains 37% of the primary

data. The secondary report shows that majority of companies (77 percent) adopted Tier I

ERP software in which people refer SAP: 35 percent, Oracle: 28 percent, Microsoft: 14

percent and Tier II: 23 percent. “Flexibility / Well Managed User Interface” (4.21%) is

the second major factor, sequenced by “Total Cost of the ERP system” (4.11%), “ERP

Functionality” (4.9%) and other factors also have more than 4 value. “Maintenance

(3.75%) reaches to the last of ladder (in between Agree and Neutral of Likert scale) as it

is self managed by the IT staff of the company.

Graph 8: ERP Vendor‘s Selection Factors for All Respondents (Source: SPSS V 18.0 & MS-Excel 2007) [Source: Self Made]

104

5.10 QUESTIONNAIRE PART I Q11 FOR ERP CUSTOMERS AND PART1 Q8 FOR ERP

VENDORS & CONSULTANTS “WHAT IS THE BEST WAY OF ERP SOFTWARE

TAILORING/ ADAPTING?” [COMPARATIVE FREQUENCY ANALYSIS WITH

SUMMATED SCORES OF ALL RESPONDENTS] [MEETING OBJECTIVE 5]

The next important modification in implementation phase can be made by optimization /

tailoring of parameters (called configuration), rather than by traditional programming. In

all options, “Data fit of ERP” and “User Fit of ERP” (4.34%) get the maximum

representation of the data from the combined samples of all respondents. The next factor

“Process Fit of ERP” with 4.31% scores gives a tough competition to both the factors.

“Organization Fit of the ERP” (4.00%) is also a strong variable especially in SMEs in

which scarcity of the five M's”: men, machines, methods, materials and money is the

precious word to deal with. “Consultant fit of ERP” is the last option with 2.84% score on

Likert scale in between Neutral and Disagree. The representation found in survey result

may be useful for helping practitioners assess risk and plan appropriate risk mitigation

efforts. The basis for the analysis can be the whole project or a specific area of the

project, e.g. production planning and control in one line of business. The ERP package

tailoring typology can also be used to predict success both during the initial

implementation phase and during the maintenance and post implementation phase of the

ERP system life cycle.

Graph 9: ERP Software Tailoring for All Respondents


105

5.11 QUESTIONNAIRE PART II OF ERP CUSTOMERS ABOUT LATEST TREND IN ERP

[FACTOR ANALYSIS & RELIABILITY ANALYSIS] [MEETING “OVERALL

OBJECTIVES OF THE RESEARCH”]

For the group of 104 ERPs users, the data were first perused to check whether the data

could be analyzed using factor analysis on not. As in Table 22, we notice that the Kaiser-

Meyer-Olkin measure of sampling adequacy is .855 which is quite high same as

excellent. Therefore, factor analysis will prove helpful in reducing twenty variables into

the smaller one based on common dimensions, characteristics or features.




df 190

Sig. .000

Table 22. KMO and Bartlett's Test for ERP Customers Meeting Overall Objectives of the Research


From table 23 and Graph 10 for Scree plot, only factors with Eigen value (total variance

explained) greater than 1 are included in final solutions of the analysis.

Component

Initial Eigenvalues


Loadings Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

dimension0

1 10.164 50.820 50.820 10.164 50.820 50.820 5.218 26.090 26.090

2 1.437 7.187 58.007 1.437 7.187 58.007 4.196 20.980 47.070

3 1.230 6.152 64.159 1.230 6.152 64.159 3.418 17.089 64.159

4 .964 4.819 68.978

5 .908 4.541 73.519

6 .843 4.217 77.736

7 .706 3.529 81.265

8 .601 3.006 84.271

9 .555 2.777 87.048

10 .546 2.729 89.778

11 .430 2.149 91.926

12 .310 1.548 93.474

13 .260 1.300 94.775

14 .253 1.264 96.039

15 .217 1.087 97.126

16 .179 .894 98.020

17 .121 .604 98.624

18 .113 .565 99.189

19 .086 .431 99.620

20 .076 .380 100.000

Table 23. TVE for ERP Customers Meeting Overall Objectives of the Research (Source: SPSS V 18.0)

[Source: Self Made]

106

Graph 10. Scree Plot of PC Number for ERP Customers Meeting Overall Objectives of the Research


Factor loading shows the simple correlation between the factors and all the variables

which can be further used to fix on which variable belongs to which factors. The PCs are

ordered and assigned a number label, by decreasing order of contribution to total

variance. The PC with the highest loading or with the largest fraction contribution is

labeled with new label name for the emerged factors.

Rotated factor matrix is the best solution for this. In table 24, each variable belongs to

the factors with which it has the highest loading. From this process, we are able to find

out all the constituent variables of each factor. It is seen from the TVE table that only 3

factors have Eigen value over 1. Cumulative variance of 64.159 % also proves that a

good factor analysis has been done. The factor analysis performed on 20 items resulted

into the extraction of 3 components.

Table 24 : Rotated Component Matrix (Source: SPSS V 18.0)

Component

1 2 3

F15 Is Lean Six Sigma useful for managing other

IS (Information Projects) similar to ERP? .724 .065 .235

F7 SMEs can use the Benchmark Analysis of other

companies to maximize the benefits .722 .218 .211

F19 Network with similar companies brings

quicker results. .717 .253 .252

107

F14 Does Lean Six Sigma makes the system less

vulnerable and more foolproof with the risks

related to SMEs?

.713 .467 -.023

F5 ERP's Software Development Life Cycle

(SDLC) explicates the process of Lean Six Sigma

implementation.

.681 .313 .295

F8 Is Control independent Lean expertise needed

to help ERP team in selecting right software,

implement effectively and manage organizational

change?

.634 .123 .306

F12 Six sigma improves the way for overall quality

of products in measurable terms .629 .582 .101

F6 Before ERP implementation, SMEs must use

the information regarding Lean Six Sigma from

other companies

.619 .300 .334

F1 Heavy ERP Tailoring Increases Cost and

Complexity .486 .365 .433

F11 Implementation of Lean Six sigma reduces

project completion time and cost remarkably. .486 .459 .258

F18 Is Education of the top management

accountable for success of ERP implementation for

SMEs.

.341 .813 .052

F17 Too much software modifications can increase

maintenance cost, complexity and failure risk for

SME's ERP implementation.

.190 .762 .255

F16 Using Lean Six Sigma tools, SMEs can

improve the ERP processes by eliminating Wastes

(time, money, material, effort, knowledge etc)

.227 .743 .323

F4 Efficient Project Management and Change

Management are critical to the Success of ERP

industry

.219 .592 .563

F13 Can lean approach improves the decision

making capabilities of SMEs?

.472 .495 .313

F9 Lean approach to Six Sigma driven by Senior

Management always.

.329 .001 .764

F2 Lack of Knowledge transfer at any stage of

Indian ERP implementation leads to dissatisfaction

.139 .478 .746

F20 In different companies, implementation of six

sigma brings different results in terms of

percentage of objectives achieved.

.444 .214 .621

F10 Every level of management is responsible for

the success of Lean six sigma

.145 .507 .572

F3 Lean Six Sigma suitable strategic method for

ERP implementation for SMEs

.459 .232 .508


Rotation Method: Varimax with Kaiser Normalization.

Table 24. Rotated Component Matrix for ERP Customers Meeting Overall Objectives of the Research (Source: SPSS V 18.0) [Source: Self Made]

The Rotated Component Matrix in table 24 above shows the factor loadings for each

variable. On the basis of the content, feature, characteristics of each component, suitably

names are assigned to each factor. In this way, factor analysis is used here to identify the

basic constructs that influence the latest trends of ERP implementation at Indian SMEs.

108

After going through each row, we concentrated on the components that each variable

loaded most strongly on. Based on the factor loadings, the first construct or the most

important factor Factor 1 comprises of F1 F5 F6 F7 F8 F11 F12 F15 F14 F19 can be

renamed as “Aligning Lean Six Sigma to ERP brings better results for SMEs”. While F4

F13 F16 F17 F18 all loaded strongly on Factor 2 which can be defined as “Education of

the top management is instrumental in optimizing project management & change

management process for better ERP implementation”. In effect of this, too much software

modifications or tailoring can be prevented that results in reduced cost, complexity and

failure risk of ERP implementation for SMEs. Later F2 F3 F9 F10 F20 loaded strongly

on Factor 3. The Factor 3 can be summarized as “For all level of management, better

knowledge about Lean ERP is suitable strategic method for achieving SME’s objectives”.

Though lean approach to six sigma always driven by senior management, every level of

management is responsible for its success. These are concentration-intensive tasks

applicable on all level. Lack of knowledge transfer at any stage of Indian ERP

implementation leads to dissatisfaction and bad performance.


.917 .918 10

Table 25. Reliability Statistics for Construct 1 for ERP Customers Meeting Overall Objectives of the Research



.872 .872 5




.841 .842 5



After examining factor scores for all the three constructs, reliability test was conducted

separately. A "high" value of Cronbach alpha in table 6, table 7 and table 8 for Construct

1 scored .917 as excellent, Construct 2 scored .872 and Construct 3 scored .841 also as

very good. Therefore high association in reliability analysis shows the consistent and

reliable result, fulfilling all the objectives defined in the paper.

109

In view of the above analysis and discussions, subsequent to the exploratory study of

current ERP implementation status in India, we can conclude that optimizing software

engineering, project management and lean six sigma techniques lead to successful and

pragmatic implementation of ERP in SMEs as represented beneath in theoretical model in

figure 8.

Optimized Software

Engineering Process

Optimized Project

Management Process

Lean Six Sigma

A Journey of Excellence to

Next-Gen ERP for SMEs

A THEORETICAL FRAMEWORK OF ERP

IMPLEMENTATION FOR SMEs

Figure 8. Result based Model of SME’s Next-Gen ERP towards Journey of Excellence

(Source: MS PowerPoint 2007) [Source: Self Made]

Since ERP's software development life cycle (SDLC) explicates the process of lean six

sigma implementation, it must modify ERP system functionality with customer

requirements and change management that will allow SMEs to get the benefits of its use

and will also help in getting the right results, in the right timeframe, at the right cost as

mentioned in figure 9 below.

Figure 9: ERP Software Development Life Cycle with Lean Six Sigma

(Source: MS PowerPoint 2007) [Source: Self Made]

110

Before ERP implementation, SMEs can use the benchmark analysis of other companies

to maximize the benefits. Control independent Lean expertise needed to help ERP team

in selecting right software, implement effectively and manage organizational changes at

all level. At the same time, Six Sigma improves the way for overall quality of products in

measurable terms [151]. If companies considerably concentrate on these points, they will

survive, thrive profitably in the future ERP market.

5.12 QUESTIONNAIRE PART II OF ERP VENDORS ABOUT LATEST TREND IN ERP

[FACTOR ANALYSIS & RELIABILITY ANALYSIS] [MEETING “OVERALL


The KMO measure of sampling adequacy is .839 for the group of 70 ERP Vendors which

is really good and the Bartlett's test of sphericity is .000 (less than 0.05) is also

significant. These observations provide the ground for principal components analysis (or

a factor analysis) to be conducted.




df 190

Sig. .000

Table 28. KMO and Bartlett's Test for ERP Vendors Meeting Overall Objectives of the Research


TVE table 29 and Scree plot in Graph 11 for the data show cumulative percentage of

variance accounted by the first four components (having Eigen value > 1) together

contain a value of 67.535 of the total variance.

Component

Initial Eigenvalues Extraction Sums of Squared

Loadings Rotation Sums of Squared

Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Total % of

Variance Cumulative

%

1 9.604 48.021 48.021 9.604 48.021 48.021 4.457 22.286 22.286

2 1.530 7.651 55.672 1.530 7.651 55.672 3.353 16.766 39.052

3 1.342 6.711 62.383 1.342 6.711 62.383 3.252 16.261 55.313

4 1.030 5.151 67.535 1.030 5.151 67.535 2.444 12.221 67.535

5 .966 4.829 72.363

6 .821 4.104 76.467

7 .694 3.472 79.940

111

8 .649 3.245 83.184

9 .616 3.081 86.265

10 .533 2.664 88.929

11 .445 2.225 91.154

12 .360 1.799 92.953

13 .306 1.528 94.481

14 .277 1.387 95.868

15 .206 1.028 96.896

16 .191 .957 97.853

17 .144 .721 98.574

18 .114 .570 99.144

19 .094 .470 99.614

20 .077 .386 100.000


Table 29: TVE for ERP Vendors Meeting Overall Objectives of the Research


Graph 11. Screed Plot of PC Number for ERP Vendors [Meeting Overall Objectives of the Research]


112

In Rotated Component Matrix table 30, all 20 factors have reduced into four constructs

instead of three construct for the factor analysis done for 104 ERP users. Surprising all

the constructs for vendors can be summarized in the same way as the previous one with

the addition of fourth one which can be termed as “Proper training and education are

necessary for all level of management for successful ERP implementation”.

Rotated Component Matrix

(a)

FACTORS Component

1 2 3 4

F15 Is Lean Six Sigma useful for managing other IS (Information Projects) similar to ERP? .742 .073 .086 .228

F7 SMEs can use the Benchmark Analysis of other companies to maximize the benefits

.715 .150 .241 .171

F14 Does Lean Six Sigma make the system less vulnerable and more foolproof with the risks related to SMEs? .663 .492 .052 .074

F12 Six sigma improves the way for overall quality of products in measurable terms .646 .498 .322 -.121

F8 Is Control independent Lean expertise needed to help ERP team in selecting right software, implement effectively and manage organizational change? .646 .145 .015 .478

F6 Before ERP implementation, SMEs must use the information regarding Lean Six Sigma from other companies .612 .195 .479 .088

F19 Network with similar companies brings quicker results. .593 .266 .314 .211

F1 Heavy ERP Tailoring Increases Cost and Complexity .482 .307 .281 .390

F13 Can lean approach improve the decision making capabilities of SMEs? .471 .432 .373 .154

F17 Too much software modifications can increase maintenance cost, complexity and failure risk for SME's ERP implementation. .173 .795 .112 .292

F18 Is Education of the top management accountable for success of ERP implementation for SMEs. .342 .772 .187 -.039

F16 Using Lean Six Sigma tools, SMEs can improve the ERP processes by eliminating Wastes (time, money, material, effort, knowledge etc) .138 .547 .529 .126

F4 Efficient Project Management and Change Management are critical to the Success of ERP industry .097 .545 .529 .392

F11 Implementation of Lean Six sigma reduces project completion time and cost remarkably. .335 .516 .228 .380

F10 Every level of management is responsible for the success of Lean six sigma .025 .326 .716 .227

F3 Lean Six Sigma suitable strategic method for ERP implementation for SMEs .333 .060 .706 .246

F5 ERP's Software Development Life Cycle (SDLC) explicates the process of Lean Six Sigma implementation. .561 .237 .602 -.031

F20 In different companies, implementation of six sigma brings different results in terms of percentage of objectives achieved. .385 .084 .579 .333

F9 Is Lean approach to Six Sigma driven by Senior Management always? .254 .023 .226 .842

F2 Lack of Knowledge transfer at any stage of Indian ERP implementation leads to dissatisfaction. .114 .401 .341 .743

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 11 iterations.

Table 30. Rotated Component Matrix for ERP Vendors [Meeting Overall Objectives of the Research] (Source: SPSS V 18.0) [Source: Self Made]

113

Thereafter, Reliability analysis performed on all the four constructs resulted in

Cronbach’s Alpha value .902 (Excellent), .852(Good), .801(Good) and .804 (Good)

respectively (showing very good interrelation all variables within the construct and

strongly supporting the result meant for ERP Vendors.

Reliability Statistics

Cronbach's Alpha N of Items

.902 9

Table 31. Reliability Statistics for Construct 1 for ERP Vendors Meeting Overall Objectives of the Research (Source: SPSS V 18.0) [Source: Self Made]



.852 5




.801 4




.804 2


114

5.13 QUESTIONNAIRE PART II OF ERP CONSULTANTS ABOUT LATEST TREND IN ERP,

[FREQUENCY ANALYSIS ON LIKERT SCALE 1 TO 5] [MEETING “OVERALL


As factor analysis is suitable for a large number of respondents only, comparatively

frequency analysis is the more viable option for the data obtained by the direct

interaction with 30 ERP Consultants in Delhi-NCR areas (mentioned below in graph 12).

Graph 12. Frequency Analysis of ERP Consultants [Meeting Overall Objectives of the Research]

(Source: SPSS V 18.0 & MS Excel 2007) [Source: Self Made]

Unanimously consultants are giving maximum choice (4.53%) in favour to avoiding too

much software modification for ERP as it can increase maintenance cost, complexity and

failure risk for SME’s ERP implementation. To avoid this lacuna, they are positively

looking the application of lean six sigma with ERP processes (with 2nd

most effective

rating of 4.47%). Thirdly, as lack of knowledge transfer at any stage will prove

disastrous, education of the top management is considered necessary (4.4%). Fourthly,

in view of that efficient project management and change management can prove critical

to the success of ERP industry (4.2%). Fifthly, SMEs can use benchmark analysis of

other companies to maximize the benefits as people look lean six sigma for making the

system less vulnerable and more fool proof with the risks related to SMEs. It also helps

115

in improving the ways for overall quality of product in measurable terms (4.13%). Other

process related issues arise in between and the least consensus (3.3%) received for the

statement “Lean approach to six sigma is driven by senior management always” draws

the flak as every level of management is responsible for its success.

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