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This is the authors’ final peer reviewed (post print) version of the item published as: Fayezi,S, Zutshi,A and O'Loughlin,A 2014, Developing an analytical framework to assess the uncertainty and flexibility mismatches across the supply chain, Business Process Management Journal, vol. 20, no. 3, pp. 362-391. Available from Deakin Research Online: http://hdl.handle.net/10536/DRO/DU:30067179 Reproduced with the kind permission of the copyright owner Copyright: 2014, Emerald
Developing an analytical framework to assess the uncertainty and flexibility mismatches across the supply chain Sajad Fayezi, Ambika Zutshi and Andrew O’Loughlin School of Management and Marketing, Deakin University, Melbourne, Australia
Abstract
Purpose – The purpose of this paper is to discuss how decisions regarding organisational flexibility can be improved through targeted resource allocation, by focusing on the supply chain’s level of uncertainty exposure. Specifically, the issue of where and in what ways flexibility has been incorporated across the organisation’s supply chain is addressed.
Design/methodology/approach – A two‐phase methodology design based on literature review and case study was used. Using 83 journal articles in the areas of uncertainty and flexibility an analytical process for assessing uncertainty‐flexibility mismatches was developed. Furthermore, results from ten interviews with senior/middle managers within the Australian manufacturing sector were used to provide preliminary insights on the usefulness and importance of the analytical process and its relationship with organisational practice.
Findings – The paper emphasises the importance of having a systematic and encompassing view of uncertainty‐flexibility mismatches across the supply chain, as well as the significance of socio‐technical engagement. The paper both conceptually and empirically illustrates how, using a structured analytical process, flexibility requirements across the supply, process, control and demand segments of a supply chain might be assessed. A four‐step analytical process was accordingly developed and, its application, usefulness and importance discussed using empirical data.
Practical implications – The analytical process presented in this paper can assist managers to obtain a comprehensive overview of supply chain flexibility when dealing with situations involving uncertainty. This can facilitate and improve their decision‐making with respect to prioritising attention on identified flexibility gaps in order to ensure stability of their performance. Originality/value – The paper presents a supply chain‐wide discussion on the difficulties that uncertainty brings to organisations, and how organisational flexibility might serve to moderate those challenges for supply chain management. It discusses how to identify the flexibility gap and proposes an original analytical process for systematic assessment of uncertainty‐flexibility mismatches. Keywords Uncertainty, Supply chain, Flexibility, Flexibility gap, Required/actual flexibility Paper type ‐ Research paper
1. Introduction Supply chains are complex systems (Surana et al., 2005) with inherent internal and external uncertainties. Uncertainties largely arise from problems within organisational and network relationships, which are the key building blocks of any supply chain system. Traditionally, managers were primarily concerned with inventory control mechanisms to mitigate manufacturing‐related uncertainties, such as, supply disruption,late delivery and
demand fluctuation (Davis, 1993). Advancements in business management theories, tools and practices, together with an integrative view of priorities such as quality, time and cost, have served to foster a better understanding of business excellence benchmarks within uncertain supply chain environments (see, e.g. the idea of the “Seamless Market‐Orientated Supply Chain” by Childerhouse and Towill (2006), and “Supply Chain 2.0” by Christopher and Holweg, 2011). Considerable empirical evidence, with regard to the negative impact of uncertainty on operations and performance of supply chains, has heightened academics’ and practitioners’ concerns for developing practical remedies that assist businesses prosper
during times of turbulence (e.g. Correa and Slack, 1996; Das and Abdel‐Malek, 2003; Fynes et al., 2004; Geary et al., 2002; Merschmann and Thonemann, 2011; van der Vorst et al., 1998; Zhang et al., 2002). Flexibility, the ability of a system to change in response to uncertainties and transformations in its operating environment, has received considerable attention from a variety of scholars (Husdal, 2010; Slack, 1983; Wallace and Choi, 2011), who have tackled the issues from a broad range of perspectives. Research into supply chain flexibility falls into a number of categories, and has been heavily influenced by flexibility dynamics within manufacturing businesses, which has tended to concentrate interest at the functional and operational levels of the organisation (Avittathur and Swamidass, 2007). The characteristics of flexibility have been addressed by a number of researchers, which has led to the development of a variety of differing taxonomies (Lucas and Kirillova, 2011; Stevenson and Spring, 2007), frameworks (Duclos et al., 2003; Ivens, 2005; Kumar et al., 2006; Pujawan, 2004), as
well as measures/perspectives (Giachetti et al., 2003; Sawhney, 2006; Verdu ‐Jover and
G'omez‐Gras, 2009). In their investigations of flexibility, researchers have focused on both the internal and external supply chain processes, such as, procurement (Liao et al., 2010; Tachizawa and Thomsen, 2007), manufacturing (Francas et al., 2009; Francas et al., 2011; Patel, 2011) and distribution (Choy et al., 2008; Mohamed et al., 2006; Naim et al., 2010). Other studies have also explored possible links between flexibility and performance
within the supply chain (Correa, 1994; Fantazy et al., 2009; Merschmann and Thonemann, 2011; Vickery et al., 1999). In spite of the research that has taken place, as suggested by Stevenson and Spring (2007), More and Subash Babu (2008) and also acknowledged by Christopher and Holweg (2011), supply chain flexibility research remains in its infancy and the topic is yet to be fully explored and its dynamics explained. Extending this further, an area that clearly requires additional investigation is flexibility requirement analysis (i.e. analysis of the difference between required and actual flexibility) across the supply chain (Danese, 2011). For the purposes of this paper the authors define required flexibility and actual flexibility as:
Required flexibility is defined as the optimal amount and type of change necessary to respond to supply chain uncertainties. Actual flexibility refers to the existing capabilities of the organisation with respect to amount and type of change.
The authors note that limited research has been conducted into understanding the transformation costs associated with what is optimally required to manage the supply chain and the actual capability of the various organisations (e.g. Tang and Tomlin,
2008; Verdu ‐Jover and G'omez‐Gras, 2009; Verdu ‐Jover et al., 2004). The difference between the two positions is important because it can add significant cost to supply chain activities, and has the potential to create relationship tensions, for example, where a supply chain partner cannot respond quickly or meet their contractual obligations. The
present paper addresses this noted gap in the literature, with the aim of assisting organisations in their transition towards optimal flexibility decisions, and asks the following question: where and in what ways has flexibility been incorporated into an organisation’s supply chain in order to manage issues of uncertainty? In order to answer this question the authors use the uncertainty‐flexibility dichotomy in order to understand organisational flexibility requirements. The central argument of the paper is informed by Contingency Theory (Donaldson, 2001), which assists in identifying the influence that contextual factors (e.g. uncertainty and its sources) have in managing different situations within the supply chain. Hence, Contingency Theory is used in the development of a flexibility taxonomy framework, which is derived from the work conducted on the Uncertainty Circle (Davis, 1993; Mason‐Jones and Towill, 1998). The authors argue that the discussion presented in the paper can be used as the basis for further analysis of the uncertainty and flexibility mismatch across the supply chain. The management of flexibility gaps is important because they serve to indicate the potential for a sub‐optimal level of supply chain performance, thereby creating greater uncertainty. This, in turn, poses a significant threat to supply chain stability, in terms of organisations having to respond to volatile changes in environmental conditions. The authors also contend that the findings might assist managers in controlling business performance and service ability of the supply chain through more effective, contingent‐based decision making. The paper begins by undertaking a review of the literature and highlights a gap in current thinking concerning uncertainty and flexibility within the supply chain. The mechanisms used to identify and select journal articles are explained in the methodology section, as well as procedures undertaken to conduct interviews with managers within the Australian manufacturing sector. The uncertainty‐based classification of flexibility types is then presented and, from this, a supply chain flexibility taxonomy is developed. The paper uses the Uncertainty Circle as its conceptual basis and evaluates its value for supply chain performance analysis. This is followed by an investigation of the four‐step analytical process, which is designed to assist managers in identifying, analysing and potentially eliminating flexibility gaps both within and across the supply chain. Preliminary findings from the case studies are followed by concluding remarks, which summarises the research findings. 2. Methodology The methods used for this paper followed a two‐phase design and are based on a comprehensive literature review followed by a case study. During the first phase (literature review) documentary research (Platt, 1981), which involved collecting information about a specific phenomenon (in this case uncertainty and flexibility), was used. Consequently, keywords, such as, uncertainty, flexibility, supply chain management and supply chain risk were classified using a formal coding framework which was used to search online databases such as Emerald, ScienceDirect and EBSCO in order to find relevant journal articles. The literature search revealed more than 100 articles out of which 83 were identified as important in terms of the coding classification. During this process the title, abstract, keywords and main text of the papers were screened to increase accuracy of the article selection process. The 83 articles (see Table I) used in this paper are all from peer‐reviewed journals, which served to ensure that the literature had been subject to a strict filtering process.
An additional 26 articles (various publication types; conference papers and books) were also used to support the construction of the analytical framework. During the second phase, the analytical framework, which was developed from the literature, was examined against the data obtained via ten interviews conducted with Name of journal Number of
Articles International Journal of Productions Economics 10 Journal of Operations Management 7 International Journal of Operations and Production Management, International Journal of Physical Distribution and Logistics Management 5 Supply Chain Management: An International Journal 4 Journal of Supply Chain Management, International Journal of Logistics Management 3 California Management Review, Journal of Manufacturing Technology Management Industrial Management and Data Systems, Journal of Purchasing and Supply Management, Industrial Marketing Management, International Journal of Logistics Research and Applications, International Journal of Production Research, International Journal of Flexible Manufacturing Systems 2 European Journal of Operational Research, International Journal of Logistics Systems and Management, Expert Systems with Applications, Computer Integrated Manufacturing Systems, MIT Sloan Management Review, Journal of Business Logistics Supply Chain Management Review, International Journal of Agile Manufacturing Systems, Omega, Review of Economic Studies, Clinical Psychology Review, American Economic Review, Journal of Enterprise Information Management, Supply Chain Forum: An International Journal, International Journal of Business Excellence, Computers & Industrial Engineering, APICS Production and Inventory Management, International Journal of Integration Supply Management, CIRP Journal of Manufacturing Science and Technology, Advances in Strategic Management, Strategic Management Journal, Production Planning and Control, Decision Sciences, International Journal of Industrial Ergonomics, Harvard Business Review, International Transactions in Operational Research, Journal of Organizational Change Management, International Journal of Service Industry Management, Studies in Informatics and Control, Journal of Engineering and Technology Management 1
Table I. Name of the journals and number of the articles from these journals used in the study
senior/middle managers within the Australian manufacturing sector. Multiple face‐to‐face, semi‐structured interviews were conducted, and a two‐layer analytic technique was used to facilitate the data analysis process (Yin, 2009) by using the Nvivo 8 software tool. Relevant qualitative data was used to examine the applicability and significance of the developed analytical process and its ability to explain the uncertainty‐flexibility dynamics of a manufacturing organisations’ supply chain. 3. Change‐response synchronisation The increasingly dynamic nature of the business environment has given rise to the need for organisations to synchronise their operations, culture and strategy with each other in order to maximise efficiencies in the supply chain. Uncertainty refers to a situation, or situations, that are replete with unknowns (Geary et al., 2002) where unpredictable events impact organisational performance (Koh and Saad, 2002). Uncertainty is often attributed to the lack of accurate information available for proactive decision making (van der Vorst and Beulens, 2002), and may occur within all operational and functional levels of the organisation. Importantly, change is often
conceived of as specific – possible – manifestations of the uncertainty. Baramichai et al. (2007), using the work of van der Vorst and Beulens (2002) and Zsidisin et al. (2004),
argue that change is an omnipresent force within supply chains and is most notable in the following areas: quality, design and features, volume and quantity, supply lead time, supply availability, supply cost and legal issues. In an attempt to manage uncertainty risk estimates are normally used by managers to shortlist and prioritise various environmental changes. Measurements of risk are commonly expressed in terms of loss, which can be classified, for example, as financial, performance, physical, psychological and social (Brenchley, 2000, cited in Harland et al., 2003). As a response mechanism to various uncertainties, scholars and practitioners have researched the development and maintenance of flexibility as a possible solution. The principal idea underpinning flexibility is derived from organisational theories such as Contingency Theory. In essence, Contingency Theory recognises the inseparability of the organisation from the environment it operates in, and suggests that the function of management is, of necessity, situation‐specific (Donaldson, 2001; Vecchio, 2006). This has given rise to a broader discussion within the literature concerning issues surrounding the mechanistic and organic design of the organisations (Burns and Stalker, 1994; Sherehiy et al., 2007). A mechanistic organisation has a highly structured hierarchy with formal processes, procedures and rules. In contrast, organic organisations are more fluid with informal communication, decentralised control and few rules and procedures (Burns and Stalker, 1994; Donaldson, 2001; Hatch and Cunliffe, 2006; Sherehiy et al., 2007; Vecchio, 2006). Historically, flexibility has attracted the attention of a variety of different disciplines. For example, psychology considers flexibility to be a dynamic and temporal construct which entails “how a person: (1) adapts to fluctuating situational demands, (2) reconfigures mental resources, (3) shifts perspective, and (4) balances competing desires, needs, and life domains” (Kashdan and Rottenberg, 2010, p. 866). Jones and Ostroy’s (1984, p. 59) economic analysis of supply chains argues that, “the way flexibility is used to exploit forthcoming information may be dictated by attitudes towards risk; but flexible positions are attractive not because they are safe stores of value, but because they are good stores of options”. Within the manufacturing literature, Upton (1994, p. 73) has defined flexibility to include “the ability to change or react with little penalty in time, effort, cost or performance”. In spite of the differences there are a common set of elements used to define flexibility, namely, uncertainty, information processing, change, risk assessment and decision making. The next section will discuss some of these elements as they relate to flexibility within the context of supply chains.
4. Supply chain flexibility Within the literature it is acknowledged that managing supply chains requires the administration of upstream and downstream relationships and processes (internal/ external) with suppliers/customers, in order to bring value to the customer (products/ services) at the least possible expense. This includes but is not limited to, for example, finance, physical effort, resource allocation and the propensity to absorb risk‐taking behaviour (Christopher, 2005). Flexibility plays a pivotal role in fostering stronger supply chain management as changes in relationship structures (in terms of intensity and type), cross‐functional processes (e.g. procurement, manufacturing and distribution), and management (Lambert and Cooper, 2000) are needed to maintain supply chain operations
Essentially, flexibility enables a supply chain to respond to internal and external uncertainties in equal measure as a reactive and proactive response. This has been made clear within both the goods‐ and service‐ supply chain flexibility literature, where the relationship between the causes of uncertainty and flexibility responses have been
investigated in some detail (Correa and Gianesi, 1994; Correa and Slack, 1996; Gerwin,
1987; Sawhney, 2006). Here, discussions about flexibility centre mostly on the types (e.g. machine, materials and mix), the various dimensions (e.g. range, cost and time), enablers (culture, structure and technology), levels (e.g. operational and strategic), and measures (e.g. aggregate and attribute) of flexibility (Beach et al., 2000; Sethi and Sethi, 1990; Shewchuk and Moodie, 1998). Even with extensive exploration, flexibility within service supply chains is still regarded as a developing area of research, where no prevailing perspective, conceptualisation and/or measurement tools have evolved (More and Subash Babu, 2008; Stevenson and Spring, 2007). Similarly, although the manufacturing system flexibility literature has been dominant in shaping various theoretical perspectives and arguments within the discipline, as an area of study it is still very much in its theoretical and empirical infancy. For example, while authors such as Fawcett et al. (1996), Vickery et al. (1999), Narasimhan and Das (1999) and Golden and Powell (1999) have all attempted to provide some level of context with regard to the antecedents of flexibility and its impact on the supply chain, their studies have not pushed the discipline beyond a basic understanding, and are now somewhat dated. Fawcett et al. (1996) emphasised that achieving flexibility advantage, in terms of performance improvement, can only be realised when managers view flexibility as a cross‐functional priority. The problem is that managers need a range of devices to do this, and the same problem occurs again, as mentioned with service supply chains, there are very few tools suitable for managers to use. As an alternative, Vickery et al. (1999, p. 16) suggested that a change in thinking about the integrated nature of supply chain flexibility is needed, which might be brought about through the inclusion of product, volume, launch, access, and target market responsiveness, and considering them as “[…]the shared responsibility of two or more functions along the supply chain”, rather than disaggregated concepts. This relies on management’s ability to conceptualise the supply chain in different ways, which can be extremely challenging and difficult to achieve because of a variety of organisational (e.g. culture) and personal issues (e.g. individual cognitive abilities). Adding extra dimensions often ensures a higher level of complexity, and does not necessarily assure a greater understanding of supply chain dynamics. Narasimhan and Das (1999) and Golden and Powell (1999) have adopted a different strategy and investigated the impact that supply chain management practices (e.g. early supplier involvement in product design) and inter‐organisational systems (e.g. electronic data interchange) have on flexibility. The problem here is that management practice is like management thinking – incredibly variable and bound up in organisational culture – and reconciling these differences has proved to be no easy task. Zhang et al. (2002) have sought to expand the notion of flexibility from a purely intra‐organisational process to one that encompasses inter‐organisational relationships, and, in doing so, their study overlooks the fact that supply chains are multi‐dimensional and often globally orientated. Duclos et al. (2003) and Stevenson and Spring (2007) agree that supply chain flexibility can be broadly understood as an integration of intra‐ and inter‐organisational flexibilities and their inter‐relationships. The multi‐dimensional characteristics of flexibility are clearly illustrated in Stevenson
and Spring’s (2007) definition of supply chain flexibility, where they contend attributes, such as, robust network flexibility, re‐configuration flexibility, active flexibility, potential flexibility and network alignment, are crucial for the smooth operation of the supply chain. Implied in their work is also recognition of the role that globalisation plays on supply chain relationships. Other researchers have adopted a contrary view of supply chain dynamics by examining how flexibility can lead to efficiency trade‐offs, where, for example, the negative aspects of flexibility (in terms of cost) are partially mitigated through control
mechanisms, such as, monitoring/forecasting and maintenance/update/training (Correa and Slack, 1996; Kulatilaka and Marks, 1988), but there complete elimination, while desirable, is not practical or possible. It is important to understand that while all of these studies make significant contributions to the discipline, an end‐to‐end understanding of supply chain‐wide flexibility currently remains little more than an elusive goal. For the purpose of this paper, and taking the above discussion into consideration, the authors have built upon the work of Wadhawa and Rao (2003) and More and Subash Babu (2008) to define supply chain flexibility as:
The ability of an organisation to manage the internal (e.g. manufacturing) and interfacing (e.g. procurement and distribution) processes, as well as its key suppliers/customers to respond to expected changes in supply, product and demand in an efficient manner enabled by both technological and social platforms.
4.1 Types and dimensions of flexibility A variety of flexibility types and dimensions have been discussed within the manufacturing‐specific literature, and our review shows that they often have similar defining principles, but a very different emphasis/use (e.g. Lucas and Kirillova, 2011; Zhang et al., 2003). For example, process flexibility, which overlaps with operations flexibility, entails routing, machine and materials handling flexibility (Zhang et al., 2003). Beach et al. (2000), building on the work of Sarker et al. (1994) have maintained the importance of a thorough understanding of the relationship that exists between flexibility types, particularly regarding the measurement of flexibility. Sethi and Sethi (1990) have attempted to cluster flexibility types and explain how they are related and affect one another. Their work determined that there is a hierarchical relationship between different types of flexibility in terms of basic system and aggregate flexibility. The literature that focuses on service organisations also provides useful insights in terms of flexibility types and their role in managing service operations. This is important because services are both produced and consumed at the same time, they are intangible and are dependent upon the customer to actively participate in its
implementation and consumption (Gro nroos, 2000). A further consideration is the variability of, as well as the uncertainty that exists within, the delivery of the services
themselves (Correa and Gianesi, 1994). Therefore, any uncertainty in the supply chain has to be dealt with immediately, so as to possibly avoid losing the customer. Drawing on services’ key features, Ivens (2005) has highlighted the importance of timeliness, resource availability and sensitivity of services in the delivery process, and as a consequence, design, packaging, delivery time/location, volume and customer recovery flexibility have all
been recognised as critical factors in the literature (Correa and Gianesi, 1994; Silvestro, 1993). These need to be integrated into any supply chain flexibility framework in order to reduce bias towards simply seeing flexibility in a production‐dominant context.
With regard to the dimensions of flexibility, there is general agreement amongst researchers concerning the core aspects. Time, cost and uniformity are crucial with regard to achieving high‐levels of flexibility. Upton (1994) views time and cost as the mobility parameter of a flexible organisation. Hence, flexibility is also driven by the availability of competitive options, termed as range within the literature. It has also been argued that a flexible organisation can exert operational changes without affecting its output state, and this is known as uniformity (Upton, 1994) or output stability (Zhang et al., 2003).
A number of scholars have attempted to incorporate a variety of dimensions (i.e. range, mobility, uniformity) into their investigations (Upton, 1994; Beach et al., 2000; Zhang et al., 2003). Research indicates that much of the literature is skewed more towards the manufacturing aspects of the organisation (e.g. operations, automation, routing, design) (Zhang et al., 2003; Sherehiy et al., 2007; Liao et al., 2010; Richter et al., 2010). This is in spite of the fact that social and behavioural systems can vary significantly within organisational operations and settings, and demand appropriate response through provision of corresponding flexibilities (Upton, 1995). As a consequence, further attention needs to be paid to how different types of flexibility can contribute towards better management of the supply chain.
5. Uncertainty‐flexibility in the supply chain Research into risk management has been very influential in developing a better understanding of the role that uncertainty plays in the supply chain, and how it can be
managed, as well as mitigated (see, e.g. Ju ttner et al., 2003; Peck, 2006; Tang and Nurmaya Musa, 2011; Zsidisin and Ritchie, 2008). The literature posits that uncertainty is a complex and inter‐related phenomenon that can occur at any point along the supply chain (Davis, 1993; van der Vorst and Beulens, 2002). The so‐called “vicious circle” of supply chain uncertainties has been discussed in some detail by Childerhouse and Towill (2004, p. 587). They concluded that it is vital for managers to have a comprehensive understanding of the cause and effect dynamics that exist both across, as well as between internal and external, and upstream and downstream relationships in the supply chain. Traditionally, uncertainty within the supply chain has tended to be managed through the use of buffering strategies (Giunipero and Eltantawy, 2004; Zsidisin et al., 2000). This is where organisations seek to minimise the impact that change has on the supply chain by developing various operational safeguards and protective response times targeted at keeping potential costs to a minimum. Researchers have reported that, for example, information sharing, product consistency, decision support systems and partnering schemes may also serve to reduce uncertainty (e.g. Mason‐Jones and Towill, 2000; van der Vorst and Beulens, 2002). Following on from this, it is clear that the supplementary addition of flexibility within “activities, subsystems, resources, processes and functions” of the supply chain is very likely to enhance the organisation’s ability to respond to uncertainties (More and Subash Babu, 2008, p. 306). Researchers have discussed flexibility as the (organisation’s) ability to respond to
uncertainties in the business environment (Correa, 1994; Correa and Slack, 1996; Gerwin, 1987; Merschmann and Thonemann, 2011; Prater et al., 2001; Sawhney, 2006). Gerwin (1987) posits that, for example, uncertainty associated with the product acceptance (by customers) could be better managed through developing what they
term product mix flexibility. In a separate assessment, Vickery et al. (1999) identified volume and launch flexibilities as enabling organisations to deal with marketing practices and product uncertainties, thereby enabling them to manage the product mix issues. In spite of the development of detailed taxonomies and functional characteristic identification, there is still no comprehensive framework that allows for the mapping of uncertainty with flexibility requirements both within and throughout the supply chain. The literature also suggests that the greater the level of supply chain uncertainty, the higher is the likelihood that some form of change will occur (Khan and Burnes,
2007; Sanchez‐Rodrigues et al., 2008). As a consequence, it is important for operations and supply chain managers to have an in‐depth supply chain‐wide understanding of the uncertainties and subsequent changes that could take place within their organisations. This understanding has the potential to guide and optimise organisational flexibility development and management, both within and between the processes of an organisation’s supply chain. An important tool that might assist managers in this process is the Uncertainty Circle (see Figure 1), which was first developed by Davis (1993) and updated by Mason‐Jones and Towill (1998), and subsequently validated by a number of supply chain‐related researchers (see Childerhouse and Towill, 2011). The Uncertainty Circle’s advantage is derived from the fact that it is comprehensive and provides a better fit with the theoretical and conceptual foundations of supply chain management, both in terms of scope and scale (see, e.g. Childerhouse and Towill, 2004; Geary et al., 2002; Mason‐Jones and Towill, 1998, 2000; Sanchez‐Rodrigues et al., 2008, 2010). The authors recognise that the Uncertainty Circle provides a useful tool for interpreting organisational flexibility within the supply chain, and have used this to explain the relationship between uncertainty and flexibility. Essentially, the Uncertainty Circle provides an opportunity for a systematic and structured review of the major sources of uncertainty in the supply chain, and suggests tools for its analysis. For example, managers may brainstorm a comprehensive list of supply‐sourced uncertainties for a more targeted decision and treatment of upstream supply chain issues. In addition, the Uncertainty Circle allows for sources of uncertainty to be reviewed together or independently, so as to obtain greater insight into various interfacing problems. This, in turn, provides managers with the possibility of comparing uncertainties, for example, around control issues with supplier uncertainty, in order to understand the source of potential supply chain problems. In order to use the Uncertainty Circle effectively it is important that managers use the cause and effect typologies discussed earlier to avoid any miscalculation in uncertainty levels. In particular, the effect component can assist decision makers in understanding whether a particular scenario should be reviewed as a real threat to the supply chain that requires further analysis, or whether it is just a minor operational failure which can be easily addressed. It is, however, important to recognise that internal management protocols in terms of organisational perception of uncertainty have the potential to influence the Uncertainty Circle application. Building further on this discussion and using the Uncertainty Circle as a guide for optimised resource allocation, a framework for mapping uncertainty and flexibility is proposed in the following section.
Physical flow Information flow
Figure 1 – The Uncertainty Circle
Source: Mason‐Jones and Towill (1998, p. 17
6. Mapping uncertainty and flexibility in the supply chain Table I maps out the uncertainty sources (drawn from the Uncertainty Circle) against supply chain flexibility types (at both strategic and operational levels). An immediate observation from Table II is that, in response to different types of uncertainty, supply chains can develop, maintain or configure specific types of flexibility (Gerwin, 1987; Sawhney, 2006). The issue of managing an organisation’s strategic flexibility usually falls to senior management, as they are the individuals most closely associated with an organisation’s strategic orientation. It is the accumulation of organisational knowledge obtained over years of operation under various political, social and economic shifts (across national and international markets) that drives strategic flexibility decisions. By way of contrast, operational flexibilities are predominantly seen at lower levels of decision hierarchy that play a primary role in shielding the organisation against the more expected, episodic changes. In short, strategic flexibilities are illustrative of the organisation’s long‐term, proactive treatment of uncertainties, whereas operational flexibilities are short‐term, reactive measures of response. The framework used for mapping uncertainty and flexibility is further explained through an analysis of the sources of uncertainty in supply, process, control and demand.
6.1 Supply Item, market and supplier characteristics provide a foundation from which to analyse upstream supply chain uncertainties (Zsidisin, 2003). In this regard, supply‐related uncertainties, which might arise from, for example, non‐compliance, insufficient capacity, or the financial instability of suppliers, all have the potential to affect an organisation’s performance (Childerhouse and Towill, 2004; Giunipero and Eltantawy, 2004). It is supplier flexibility coupled with procurement process flexibility that enables an organisation to manage the various levels of uncertainty it might encounter (Tachizawa and Thomsen, 2007). As a consequence, flexibility within supplier relationships may be perceived as a strategic imperative for managing supply side uncertainties (Sanchez, 1995; Stevenson and
Control
Systems
Supply Side Manufacturing/Service process
Demand side
Spring, 2007; Zomorrodi and Fayezi, 2011). Currently, purchasing contract dynamics in both manufacturing (e.g. Krajewski et al., 2005; Pettersen and Rokkan, 2006; Sethi et al., 2004) and service operations (e.g. Ivens, 2005; Richter et al., 2010) have come to dominate research surrounding relationship flexibility. More recently, however, relationship flexibility has started to receive attention from researchers interested in elasticity and tolerance thresholds, particularly in supplier relationships (see, e.g. Das and Abdel‐Malek, 2003; Wilson, 2006; Zomorrodi and Fayezi, 2011). In spite of increased interest in supply‐side flexibility, there is still a need for further research into relationship development and maintenance, and how organisations might jointly respond to external environmental uncertainties.
6.2 Process Process failure, the lack of skilled labour and pressure from the market are all sources of uncertainty within manufacturing and service operations (Ellram et al., 2004). As highlighted earlier, manufacturing system flexibility possesses a diverse range of flexibility taxonomies, both in terms of type as well as dimension (e.g. Browne et al.,
1984; Correa and Slack, 1996; D’Souza and Williams, 2000; Gerwin, 1987; Golden and Powell, 2000; Sethi and Sethi, 1990; Slack, 1983; Upton, 1994, 1995). The management of process uncertainties may occur both across and within the operational and
functional parts of the organisation. For example, a flexible workforce which is able to perform at least “[...] operations preceding and succeeding their own job [...]” (Sawhney, 2006, p. 482) has the potential to contribute to the stability of organisational performance because of the overlapping nature of their roles (Lucas and Kirillova, 2011). Importantly, when employees align key inputs into the production process with strategic objectives, it is possible for an organisation’s responsiveness to increase substantially. This is known as materials handling flexibility and has the potential to mitigate uncertainties associated with the production process (Sethi and Sethi, 1990; Vokurka and O’Leary‐Kelly, 2000; Zhang et al., 2003).
6.3 Control Information systems flexibility refers to the ability of the firm to manage information requirement changes (Duclos et al., 2003), whereas information dissemination embraces the capacity to collect and disseminate various types of information in a speedy manner (Zhang et al., 2002). Flexibility within information systems is important because poor control systems (e.g. stock auditing and quality control) have the potential to create high levels of uncertainty across the entire supply chain (Sanchez‐Rodrigues et al., 2008). The concern is that distorted information has the potential to flow from the downstream to the upstream supply side, thereby potentially leading
Table II.
Uncertainty‐based
classification of the supply
chain flexibility types
Note: Refer to Appendix for
definitions and references
Source: The authors
to supply‐demand mismatches as caused by the bullwhip effect (Childerhouse et al., 2003; Lee and Whang, 2000; Mason‐Jones and Towill, 2000). While many researchers recognise that information systems and dissemination flexibility are among the most critical flexibilities for coping with uncertainties within the supply chain (e.g. Duclos et al., 2003; Zhang, 2005), there is still a need for further research into understanding exactly how information systems might provide flexibility, as evidence suggests that information systems have the potential to act as information gatekeepers or constraints on supply chain information flows (O’Loughlin and Clements, 2007).
6.4 Demand Downstream‐oriented supply chain flexibilities are classified as demand flexibility (see Table I). Organisations can better manage uncertainties caused by, for example, forecasting errors, demand volatility, lack of marketplace transparency/information visibility and sub‐optimal inventory policy by developing demand flexibility (Chen and Paulraj, 2004; Childerhouse and Towill, 2004; Sanchez‐Rodrigues et al., 2010). The importance of demand flexibility rests with an organisation’s ability to respond to its customers’ requirements. Speedy responses have the potential to increase customer satisfaction and encourage the development of long‐term
relationships (e.g. Childerhouse et al., 2008; Ju ttner et al., 2007; Lee, 2002). Delivery flexibility is fundamental to the organisation’s ability to deliver products and services under changing market conditions (Davis, 1993; Pujawan, 2004; Stevenson and Spring, 2007; Zhang et al., 2002), and may result in transaction cost dissipation between supply chain partners due to responsiveness and co‐compliance, which, in turn, leads to improved partnering arrangements.
7. Assessment of the supply chain uncertainty‐flexibility match
As discussed in the preceding section, organisational flexibility is essential for the management of environmental uncertainties, such as, possible surges in supply and/or demand (Sanchez, 1993). Research has shown that the performance of supply chains is largely contingent on the trade‐offs between uncertainty and flexibility across the entire chain (e.g. Merschmann and Thonemann,
2011). Correa (1994) and Correa and Gianesi (1994), have suggested that, while control and flexibility are complementary mechanisms for dealing with uncertainty in the manufacturing and service systems environment, performance is always likely to be conditional and dependent upon the organisation’s strategic focus. A supply chain‐wide perspective of the uncertainty‐flexibility relationship provides an opportunity to consider network dynamics in decision making. To this end, this paper proposes a systematic mechanism for managing the uncertainty‐flexibility matches across the supply chain. The concept of fit, stemming from Contingency Theory, has
been used, for example, in Verdu ‐Jover et al. (2004) and Verdu ‐Jover and G'omez‐Gras (2009) to
discuss how flexibility fit may provide the foundation for a detailed analytical process. Verdu ‐Jover
and G'omez‐Gras (2009) contend that flexibility fit can be assessed by identifying the difference between required and actual managerial flexibility. In essence, “[f]it is determined by the interconnection of two variables, an internal and an external one; however, flexibility can be classified as a purely internal variable”, while uncertainty permeates both internal and external
operating environments (Verdu ‐Jover et al., 2004, p. 501). Within these explanations there is also the suggestion of positive performance gains, where an organisation achieves a recognised flexibility fit
by aligning its key functions (Verdu ‐Jover et al., 2004). As a consequence, flexibility requirement analysis becomes an important management tool that can be used to identify flexibility fit across the supply chain. Figure 2 illustrates the analytical process for the assessment of a match between uncertainty and flexibility that is based on the
The flexibility gap is the difference between optimal and actual flexibility across the four dimensions of supply, manufacturing/service process, control and demand. Once the gap is identified it needs to be analysed against various dynamics, such as organisation’s perceived uncertainty, power-dependency relationships and operational-strategic flexibility trade- offs. Ultimately, appropriate mitigation strategies need to be formulated
authors’ interpretation of the flexibility fit. We consider that the required flexibility is the amount of change‐ability that assists
organisations to truly respond to the internal and external fluctuations and uncertainties within the supply chain. The optimal level of flexibility can be measured by using the Uncertainty Circle, while aggregate levels of actual flexibility can be obtained by measuring the existing operational and strategic flexibility levels within the supply chain system. A number of assumptions have been used to develop the analytical process some of which requires further explanation. As various uncertainty reduction strategies (or control filters) are employed by management, it is assumed that the required flexibility is equivalent to the extent of residual supply chain uncertainty, in order to manage the uncertainties which “pass through the
control filter” (Correa and Gianesi, 1994, p. 3). Moreover, the permeability of the analytical process is limited to the value stream units within the supply chain. According to Childerhouse and Towill (2006), each supply chain consists of multiple value streams. Value stream refers to “the special activities required to design, order, and provide a specific product, from concept to launch, from order to delivery, and from raw materials into the hands of the customer” (Womack and Jones, 1996, cited in Childerhouse and Towill, 2006, p. 358). In the first step of the analytical process (see Figure 2), the Uncertainty Circle should be utilised by
Steps Remarks
1. Measure uncertainty and determine required level of flexibility
Measurement across each dimension of the uncertainty circle, i.e., supply, manufacturing/service process, control and demand
2.Identify flexibility gap
3. Analyse flexibility gap
4. Mitigate flexibility gap
Figure 2. Analytical framework (process) for the assessment of uncertainty and flexibility match
Source: The Authors
managers to measure uncertainty and flexibility across supply chain processes (Bohme, 2009; Childerhouse and Towill, 2004; Mason‐Jones and Towill, 1998, 2000; Naim et al., 2002). Additional tools, such as quick‐scan audit methodology are useful, as they provide a systematic approach for diagnosing supply chain integration and performance, by using the Uncertainty Circle for uncertainty estimation (Naim et al., 2002). The outcome of the first step of the proposed analytical process is the estimation of uncertainty levels (which indicates the required level of flexibility response) as well as the actual level of flexibility across supply, manufacturing/service process, control and demand dimensions. These measures form the basis for identification, analysis and mitigation of the flexibility gaps identified by the Uncertainty Circle. While there are a variety of methodologies
suggested within the literature (e.g. see Pujawan, 2004; Verdu ‐ Jover and G'omez‐Gras, 2009), a conversion process will be required in order to evaluate the relationship between the two variables of uncertainty and flexibility, and how the organisation might respond with regard to making any strategic decisions. The second step involves the identification of the flexibility gap status. Having completed this,
three outcomes are likely; deficiency, fit or excess flexibility (Verdu ‐ Jover and G'omez‐Gras, 2009). For the purpose of this paper, deficiency is defined as where actual system flexibility is less than the required level. Excess flexibility is where more resources are used than are actually required. Both can be considered negative outcomes with regard to supply chain performance, as they illustrate inefficient use of resources. In the third step, management needs to analyse the identified flexibility gaps and ask the following questions; are the gaps strategically important, and does the organisation need to respond? How much will it cost the organisation to invest in the introduction of new flexible processes? Will the cost of implementation outweigh the cost of losing market share? Having obtained the answers to these questions, and in order to complete the third step, inputs from across the organisation’s various functions are required to support senior management decision making.
Once all of the priorities have been identified, action plans focusing on the mitigation of possible gaps in flexibility need to be drafted, appraised and implemented. This forms the fourth step in the process. Adopting a systematic process, such as this, will enable supply chain managers to continually evaluate any changes in the supply chain, as well as monitor their organisation’s capacity to respond to any fluctuations and uncertainties. In order to maximise organisational efficiencies, managers also need to simultaneously consider both operational and strategic supply chain flexibilities, rather than seeing it as a sequential process (Sawhney, 2006). Viewing these processes concurrently will allow for better strategic decision making with regard to flexibility provision. Supply chains are composed of a network of organisations, often bound legally to one another through various contractual obligations, or through more casual arrangements. Careful attention to the dynamics of network systems is deemed critical when employing the analytical process discussed above. Perceived uncertainty is an important issue that needs to be factored into any decision making, as it differs from calculated uncertainty (step 1). Perceived uncertainty is highly subjective and is tied to the organisation’s propensity to engage in risk‐taking behaviour. Factors, such as, the locus of control and degree of organisational confidence can significantly influence the organisation’s level of perceived uncertainty. This has implications for steps 2 and 4 of the analytical process. The decision to include or exclude perceived uncertainty from decision‐making has the potential to artificially inflate or reduce the flexibility gap, and can lead to sub‐optimal decisions. For example, where there are high levels of trust present between supply chain partners, it is possible that perceived uncertainty might be reduced and contractual obligations relaxed. As a consequence, the organisation might be unknowingly exposed to higher levels of risk. Contrasting this, an organisation might, for instance, refuse to undertake business with a potential partner because of perceived political uncertainty. This is clearly evident in Europe, where social, political
and economic disruption has caused a number of US businesses to re‐evaluate their partnering arrangements, and while there may be some foundation with regard to their concerns, the actual level of exposure is still relatively small (Yasu, 2012). In extending further the issue of social dynamics, there appears to be limited research examining the impact that a fully integrated and networked socio‐technical system might have on supply chain flexibility. From the evidence that is available, however, it appears that relational factors (in addition to technologies) in terms of communication, information sharing and incentive alignment have the potential to foster greater relationship flexibility in the supply chain (Das and Abdel‐Malek, 2003). The socio‐technical perspective has some important implications for the proposed analytical process. When analysing the flexibility gap, it is important for organisations to consider what the authors have termed forced flexibility. This category of flexibility is a consequence of the various power‐dependency relationships that exist and are formed within their supply chains, and it erodes the socio‐technical base by overriding relationship development. For example, within an oligopolistic retail environment, a manufacturer might be highly dependent on a small number of retailers and, thus, forced to exert some level of flexibility to respond favourably to changes in the retailers’ behaviour. In this situation, the calculated (or perceived) uncertainty level provides little information, and an analysis of the flexibility gap is unlikely to provide usable data, as the oligarch has already forced flexibility upon the manufacturers so that they work to the retailers’ maximum flexibility threshold. As a result, the socio‐technical structure is placed under a higher level of duress, while the retailer seeks to achieve greater levels of efficiency from the supply chain.
When managers use the analytical process, it is important that they consider how the network is both physically structured and cognitively configured (these should be the same, and any difference serves to indicate possible zones of uncertainty within the network) (O’Loughlin and Clements, 2007). A key underlying assumption is that any analysis should be limited to a single value stream. It is important to note that network structures and configurations (i.e. dyadic, triadic or tetradic) have the potential to affect decisions regarding the identification, analysis and mitigation steps of the analytical process. For example, where an organisation has a large supply base, it may be necessary for managers to structurally align their own organisation’s operational flexibility with those of their partners in order to maximise operational flows. In doing so, there may also be a requirement for managers to explain the cause and effect logic underpinning any structural realignment to the network partners. This needs to be undertaken in order to overcome any possible resistance and misunderstanding regarding the introduction of changes to the structural flexibility dimensions. The next section presents some preliminary findings from interviews with manufacturing managers which shed light on the usefulness and significance of the above discussed analytical process.
8. Findings from the case studies Findings from the case studies provide support for the applicability of the developed analytical process as well as its significance to practice. It was established that managers are very likely to allocate substantial resources in order to both understand and then seek a possible solution in order to manage business uncertainty and flexibility (see Tables III‐V) within their organisations and the supply chain. In this process, however, the use of systematic analytical mechanisms to assess the uncertainty‐ flexibility mismatches – hence ensuring responsiveness – was found to be limited. The research findings reveal that resource allocation to mitigate uncertainty is not systematic within organisations and that there are clear thresholds that need to be reached before an investment is made in uncertainty and flexibility mismatches across the supply chain. Importantly, while many organisations are familiar with the first step in the developed analytical process, they often do not
correctly diagnose the conditions that give rise to uncertainty and flexibility (i.e. steps 2‐4 of the analytical process). The interview findings also show that organisations are unaware of the benefits that systematic treatment of uncertainty and flexibility may accrue to them, particularly within the supply chain level. An analysis of the interviews indicates that, many managers clearly misunderstand how structural flexibility interacts with their own business model, particularly as a mechanism for dealing with environmental uncertainty. This confusion can be summarised in terms of two major problems in managing organisational responsiveness when based on supply chain flexibility:
(1) a poor comprehension of flexibility; and
(2) no analytical processes to facilitate decision making.
Evidence of this can be found in Table IV where, for example, supplier review and inventory management were used to improve organisational flexibility (and also used to mitigate uncertainty). Importantly, many of these practices are embedded into an organisation’s internal processes, and without them basic business operations cannot be maintained and flexibility provision is considered less effective. Consequently the two problems identified above directly impair the ability of the supply chain participants to respond to conditions of uncertainty, undermining organisational efficiency. An additional level of complexity is introduced when assumptions are made about whether a managers’ judgement about their own organisation’s level of required
Table III. Identified uncertainties across supply, process, control and demand segments of the case companies
Table IV. Identified flexibility practices across upstream and downstream sides of the case companies
Table V.
Interviewed managers’ judgement about their supply chain’s level of required and actual flexibility
and actual flexibility can be relied upon, for example, as a basis of decision making for flexibility implementation. The research shows that manager’s assumed knowledge about gaps in flexibility response often prevents organisations from maximising their performance potential (see highlighted areas in Table V). It is the authors’ contention that the origin of the above problems can be, at least partially, attributed to the heavily practitioner‐based orientation of supply chain management, and the cost‐focused approach of organisation. The latter has caused managers to divert their attention towards business improvement principles, such as, lean and just‐in‐time management processes. What is missing in this process is an attention to the improved treatment of other drivers of efficiency, both across and within the supply chain, such as, minimising uncertainty and operationalising flexibility. Moreover, managers need to be cognisant of flexibility’s key and distinguishing features and elements, and also be able to separate these from basic business operations requirements in order to improve the responsiveness of the organisation. Therefore, the findings illustrate the usefulness and importance of the developed analytical framework, which can be used to manage uncertainty‐flexibility mismatches and maximise supply chain performance. Our findings highlighted that future research needs to focus on providing further insights into the practical application of the analytical framework, as well as validation of flexibility gap identification process across a number of different businesses. How management’s understanding, concerning the emergence of conditions of uncertainty, might be mitigated through strategically focused improvements in supply chain flexibility also need to be further investigated.
9. Concluding remarks This paper has addressed an important management concern with regard to flexibility requirement analysis within supply chain systems. It discussed that while flexibility, its antecedents and consequences have been well understood within manufacturing and operations environments, it is only recently that researchers have shown interest in leveraging this understanding in order to improve supply chain processes. Moreover, attention needs to be given to under‐developed areas, such as, the various uncertainty‐ flexibility dynamics taking place at the supply chain level. Although much of the work has centred on defining flexibility, creating taxonomies and developing frameworks, this paper has shown that little has been done to draw these disparate concepts together into a meaningful framework for analysing flexibility in the supply chain. For example, problems clearly exist concerning how supply chain managers might perceive uncertainty (cognitive processing) arising in the supply chain, and how this is reflected in individual organisational and clustered network action and reaction (match and mismatched responses). In answering the question of where and in what ways has flexibility been incorporated into an organisation’s supply chain in order to manage issues of uncertainty, this paper first utilised the concept of the Uncertainty Circle (Mason‐Jones and Towill, 1998) and provided a systematic, supply chain‐wide classification of the flexibility types at both operational and strategic levels. Following this, an analytical process for the assessment of uncertainty‐flexibility interactions was outlined. It is argued that the analytical process helps to identify flexibility gaps within each supply chain process (e.g. procurement, manufacturing and distribution), and provides managers with a systematic tool for analysing uncertainty and supply chain flexibility which was evidenced by results from interviews with managers. It was also suggested that flexibility gaps, being the difference between the required and actual flexibilities, occur at two levels – deficiency and excess flexibility. There is a third level, flexibility “fit” where uncertainty and organisational flexibility responses are synchronised so that the gap is eliminated. The authors contend that ensuring managers understand how flexibility gaps arise,
along with the available organisational and network flexibility response levels, will go some way to improving organisational performance. Findings from the interviews with senior/middle managers provided an example of the application of the analytical process.
9.1 Practical implications and future research As noted, the analytical process presented in Figure 2 provides the basis for quantification of the flexibility gap within supply chains. From an operational perspective, flexibility requirement analysis can assist in organisational planning for supply chain flexibility, as it identifies those areas which need further investigation. The analytical process (see Figure 2) also provides a suitable framework for the structured analysis of uncertainty‐flexibility gaps across four important segments within the supply chain: supply, process, control and demand. To this end, the inclusion of the flexibility items provided in Table I (operational and strategic flexibilities) allows managers to focus on the key issues as they relate to their own organisation and network maintenance. The output can help managers to both identify and then prioritise actions to address any possible mismatches that have been identified across the supply chain such as those identified across the Tables III‐V. While responsiveness is important for organisational success, it does, however, require significant investment (time, resources and capital). The analytical process has the potential to provide organisations with valuable information that will assist them in making better investment decisions concerning targeted flexibility. Transformation costs can then be managed and resources directed to where they are essential (based on prioritisation). Further research needs to be conducted into understanding how managers might use the analytical tool to decide on optimal levels of flexibility for the organisation and the supply chain network – is it through structural analysis, cognitive matching, or possibly a mixture of both? Similarly, there is a need to understand how the analytical process might work when two or more managers from different organisations use it in order to synchronise their own parts of the supply chain. Finally, although the analytical tool allows for better decision making, research needs to be conducted to understand how it might fare against managers who do not use a structured decision‐ making approach. It should be noted that this paper, in addition to providing a structured view of supply chain
flexibility, has expanded the concept of flexibility gaps within the supply chain itself (Verdu ‐
Jover and G'omez‐Gras, 2009; Verdu ‐Jover et al., 2004). Further research needs to be conducted to quantify the flexibility gap in both manufacturing‐ and service‐dominant supply chains across different industries. This has the potential to shed light on the “context‐specific and application‐oriented” (More and Subash Babu, 2008, p. 330) nature of the flexibility, and provide further insights into the dynamics of uncertainty and flexibility in the manufacturing and the service sectors. References
Avittathur, B. and Swamidass, P. (2007), “Matching plant flexibility and supplier flexibility: lessons from small suppliers of US manufacturing plants in India”, Journal of Operations Management, Vol. 25 No. 3, pp. 717‐735.
Baramichai, M., Zimmers, E.W. Jr and Marangos, C.A. (2007), “Agile supply chain transformation matrix: an integrated tool for creating an agile enterprise”, Supply Chain Management: An International Journal, Vol. 12 No. 5, pp. 334‐348.
Beach, R., Muhlemann, A.P., Price, D.H.R., Paterson, A. and Sharp, J.A. (2000), “A review of manufacturing flexibility”, European Journal of Operational Research, Vol. 122 No. 1, pp. 41‐57.
Bo hme, T. (2009), “Supply chain integration: a case‐based investigation of status, barriers, and paths
to enhancement”, unpublished PhD, University of Waikato, Hamilton.
Brenchley, R. (2000), “Project report to understand how trade compliance risk should be identified, assessed and managed in increasingly dis‐integrated global supply networks”, Part‐Time Executive MBA, University of Bath, Hewlett Packard.
Browne, J., Dubois, D., Rathmill, K., Sethi, S. and Stecke, K. (1984), “Classification of flexible manufacturing systems”, The FMS Magazine, April, pp. 114‐117.
Burns, T. and Stalker, G.M. (1994), The Management of Innovation, Oxford University Press, London.
Chen, I.J. and Paulraj, A. (2004), “Towards a theory of supply chain management: the constructs and measurements”, Journal of Operations Management, Vol. 22 No. 2, pp. 119‐150.
Childerhouse, P. and Towill, D. (2004), “Reducing uncertainty in European supply chains”, Journal of Manufacturing Technology Management, Vol. 15 No. 7, pp. 585‐598.
Childerhouse, P. and Towill, D. (2006), “Enabling seamless market‐orientated supply chains”, International Journal of Logistics Systems and Management, Vol. 2 No. 4, pp. 357‐370.
Childerhouse, P. and Towill, D. (2011), “Effective supply chain research via the quick scan audit methodology”, Supply Chain Management: An International Journal, Vol. 16 No. 1, pp. 5‐10.
Childerhouse, P., Disney, S.M. and Towill, D.R. (2008), “On the impact of order volatility in the European automotive sector”, International Journal of Production Economics, Vol. 114 No. 1, pp. 2‐13.
Childerhouse, P., Hermiz, R., Mason‐Jones, R., Popp, A. and Towill, D.R. (2003), “Information flow in automotive supply chains: identifying and learning to overcome barriers to change”, Industrial Management & Data Systems, Vol. 103 No. 7, pp. 491‐502.
Choy, K.L., Chow, H.K.H., Tan, K.H., Chan, C.‐K., Mok, E.C.M. and Wang, Q. (2008), “Leveraging the supply chain flexibility of third party logistics – hybrid knowledge‐based system approach”, Expert Systems with Applications, Vol. 35 No. 4, pp. 1998‐2016.
Christopher, M. (2005), Logistics and Supply Chain Management: Creating Value‐Adding Networks, Prentice‐Hall, London.
Christopher, M. and Holweg, M. (2011), “ ‘Supply Chain 2.0’: managing supply chains in the era of turbulence”, International Journal of Physical Distribution & Logistics Management, Vol. 41 No. 1, pp. 63‐82.
Correa, H. (1994), Linking Flexibility, Uncertainty and Variability in Manufacturing Systems: Managing Unplanned Change in the Automotive Industry, Avebury, Aldershot, Brookfield, WI.
Corre a, H. and Gianesi, I. (1994), “Service operations flexibility”, in Neely, A. (Ed.), International Annual EurOMA Conference, MCB University Press, Bradford, pp. 385‐390.
Corre a, H. and Slack, N. (1996), “Framework to analyse flexibility and unplanned change in manufacturing systems”, Computer Integrated Manufacturing Systems, Vol. 9 No. 1, pp. 57‐64. Danese, P. (2011), “Towards a contingency theory of collaborative planning initiatives in supply networks”, International Journal of Production Research, Vol. 49 No. 4, pp. 1081‐1103.
Das, S.K. and Abdel‐Malek, L. (2003), “Modeling the flexibility of order quantities and lead‐times in supply chains”, International Journal of Production Economics, Vol. 85 No. 2, pp. 171‐181.
Davis, T. (1993), “Effective supply chain management”, MIT Sloan Management Review, Vol. 34, Summer, pp. 35‐46.
Donaldson, L. (2001), The Contingency Theory of Organizations, Sage Publications, Thousands Oaks, CA.
D’Souza, D.E. and Williams, F.P. (2000), “Toward a taxonomy of manufacturing flexibility dimensions”, Journal of Operations Management, Vol. 18 No. 5, pp. 577‐593.
Duclos, L., Vokurka, R. and Lummus, R. (2003), “A conceptual model of supply chain flexibility”, Industrial Management & Data Systems, Vol. 103 No. 6, pp. 446‐456.
Ellram, L.M., Tate, W.L. and Billington, C. (2004), “Understanding and managing the services supply
chain”, Journal of Supply Chain Management, Vol. 40 No. 4, pp. 17‐32.
Fantazy, K., Kumar, V. and Kumar, U. (2009), “An empirical study of the relationships among strategy, flexibility, and performance in the supply chain context”, Supply Chain Management: An International Journal, Vol. 14 No. 3, pp. 177‐188.
Fawcett, S., Calantone, R. and Smith, S. (1996), “An investigation of the impact of flexibility on global reach and firm performance”, Journal of Business Logistics, Vol. 17 No. 2, pp. 167‐196.
Francas, D., Kremer, M., Minner, S. and Friese, M. (2009), “Strategic process flexibility under lifecycle demand”, International Journal of Production Economics, Vol. 121 No. 2, pp. 427‐440.
Francas, D., Lo hndorf, N. and Minner, S. (2011), “Machine and labor flexibility in manufacturing networks”, International Journal of Production Economics, Vol. 131 No. 1, pp. 165‐174.
Fynes, B., De Bu rca, S. and Marshall, D. (2004), “Environmental uncertainty, supply chain relationship quality and performance”, Journal of Purchasing & Supply Management, Vol. 10 Nos 4‐5, pp. 179‐190.
Geary, S., Childerhouse, P. and Towill, D. (2002), “Uncertainty and the seamless supply chain”, Supply Chain Management Review, Vol. 6 No. 4, pp. 52‐61.
Gerwin, D. (1987), “An agenda for research on the flexibility of manufacturing processes”, International Journal of Operations & Production Management, Vol. 7 No. 1, pp. 38‐49.
Giachetti, R., Martinez, L., S'aenz, O. and Chen, C. (2003), “Analysis of the structural measures of flexibility and agility using a measurement theoretical framework”, International Journal of Production Economics, Vol. 86 No. 1, pp. 47‐62.
Giunipero, L. and Eltantawy, R. (2004), “Securing the upstream supply chain: a risk management approach”, International Journal of Physical Distribution & Logistics Management, Vol. 34 No. 9, pp. 698‐713.
Golden, W. and Powell, P. (1999), “Exploring inter‐organisational systems and flexibility in Ireland: a case of two value chains”, International Journal of Agile Management Systems, Vol. 1 No. 3, pp. 169‐176.
Golden, W. and Powell, P. (2000), “Towards a definition of flexibility: in search of the Holy Grail?”, Omega, Vol. 28 No. 4, pp. 373‐384.
Gro nroos, C. (2000), Service Management and Marketing: A Customer Relationship Management Approach, Wiley, Chichester and West Sussex.
Harland, C.M., Brenchley, R. and Walker, H. (2003), “Risk in supply networks”, Journal of Purchasing & Supply Management, Vol. 9 No. 2, pp. 51‐62.
Hatch, M.J. and Cunliffe, A.L. (2006), Organization Theory: Modern, Symbolic, and Postmodern Perspectives, Oxford University Press, Oxford and New York, NY.
Husdal, J. (2010), “A conceptual framework for risk and vulnerability in virtual enterprise networks”, in Ponis, S. (Ed.), Managing Risk in Virtual Enterprise Networks: Implementing Supply Chain Principles, IGI, Hershey, pp. 1‐27.
Ivens, B.S. (2005), “Flexibility in industrial service relationships: the construct, antecedents, and performance outcomes”, Industrial Marketing Management, Vol. 34 No. 6, pp. 566‐576.
Jones, R.A. and Ostroy, J.M. (1984), “Flexibility and uncertainty”, Review of Economic Studies, Vol. 51 No. 1, pp. 13‐32.
Ju ttner, U., Christopher, M. and Baker, S. (2007), “Demand chain management‐integrating marketing and supply chain management”, Industrial Marketing Management, Vol. 36 No. 3, pp. 377‐392.
Ju ttner, U., Peck, H. and Christopher, M. (2003), “Supply chain risk management: outlining an agenda for future research”, International Journal of Logistics: Research and Applications, Vol. 6 No. 4, pp. 197‐210.
Kashdan, T.B. and Rottenberg, J. (2010), “Psychological flexibility as a fundamental aspect of health”,
Clinical Psychology Review, Vol. 30 No. 7, pp. 865‐878.
Khan, O. and Burnes, B. (2007), “Risk and supply chain management: creating a research agenda”, International Journal of Logistics Management, Vol. 18 No. 2, pp. 197‐216.
Koh, S.C.L. and Saad, S.M. (2002), “Development of a business model for diagnosing uncertainty in ERP environments”, International Journal of Production Research, Vol. 40 No. 13, pp. 3015‐3039.
Krajewski, L., Wei, J.C. and Tang, L.‐L. (2005), “Responding to schedule changes in build‐to‐order supply chains”, Journal of Operations Management, Vol. 23 No. 5, pp. 452‐469.
Kulatilaka, N. and Marks, S.G. (1988), “The strategic value of flexibility: reducing the ability to compromise”, American Economic Review, Vol. 78 No. 3, pp. 574‐580.
Kumar, V., Fantazy, K., Kumar, U. and Boyle, T. (2006), “Implementation and management framework for supply chain flexibility”, Journal of Enterprise Information Management, Vol. 19 No. 3, pp. 303‐319.
Lambert, D.M. and Cooper, M.C. (2000), “Issues in supply chain management”, Industrial Marketing Management, Vol. 29 No. 1, pp. 65‐83.
Lee, H. (2002), “Aligning supply chain strategies with product uncertainties”, California Management Review, Vol. 44 No. 3, pp. 105‐119.
Lee, H. and Whang, S. (2000), “Information sharing in a supply chain”, International Journal of Manufacturing Technology and Management, Vol. 1 No. 1, pp. 79‐93.
Liao, Y., Hong, P. and Rao, S.S. (2010), “Supply management, supply flexibility and performance outcomes: an empirical investigation of manufacturing firms”, Journal of Supply Chain Management, Vol. 46 No. 3, pp. 6‐22.
Lucas, M.T. and Kirillova, O.M. (2011), “Reconciling the resource‐based and competitive positioning perspectives on manufacturing flexibility”, Journal of Manufacturing Technology Management, Vol. 22 No. 2, pp. 189‐203.
Mason‐Jones, R. and Towill, D.R. (1998), “Shrinking the supply chain uncertainty circle”, Control, September, pp. 17‐22.
Mason‐Jones, R. and Towill, D. (2000), “Coping with uncertainty: reducing ‘bullwhip’ behaviour in global supply chains”, Supply Chain Forum: An International Journal, Vol. 1 No. 1, pp. 40‐45. Merschmann, U. and Thonemann, U.W. (2011), “Supply chain flexibility, uncertainty and firm performance: an empirical analysis of German manufacturing firms”, International Journal of Production Economics, Vol. 130 No. 1, pp. 43‐53.
Mohamed, M.N., Andrew, T.P., Robert, J.M. and Nicola, B. (2006), “The role of transport flexibility in logistics provision”, International Journal of Logistics Management, Vol. 17 No. 3, pp. 297‐311.
More, D. and Subash Babu, A. (2008), “Perspectives, practices and future of supply chain flexibility”, International Journal of Business Excellence, Vol. 1 No. 3, pp. 302‐336.
Naim, M., Aryee, G. and Potter, A. (2010), “Determining a logistics provider’s flexibility capability”, International Journal of Production Economics, Vol. 127 No. 1, pp. 39‐45.
Naim, M., Childerhouse, P., Disney, S. and Towill, D. (2002), “A supply chain diagnostic methodology: determining the vector of change”, Computers and Industrial Engineering, Vol. 43 No. 1, pp. 135‐158.
Narasimhan, R. and Das, A. (1999), “Manufacturing agility and supply chain management practices”, Production and Inventory Management Journal, Vol. 40 No. 1, pp. 4‐10.
O’Loughlin, A. and Clements, M. (2007), “Relational exchange, supply chain myopia and zones of turbulence”, paper presented at the International Research Conference on Quality Innovation and Knowledge Management, New Delhi.
Patel, P.C. (2011), “Role of manufacturing flexibility in managing duality of formalization and environmental uncertainty in emerging firms”, Journal of Operations Management, Vol. 29
Nos 1‐2, pp. 143‐162.
Peck, H. (2006), “Reconciling supply chain vulnerability, risk and supply chain management”, International Journal of Logistics: Research and Applications, Vol. 9 No. 2, pp. 127‐142.
Pettersen, I. and Rokkan, A. (2006), “Buyer tolerance of conflict in cross‐national business relationships: an empirical study”, in Solberg, C.A. (Ed.), Relationship Between Exporters and Their Foreign Sales and Marketing Intermediaries (Advances in International Marketing, Volume 16), Emerald Group Publishing, Yorkshire, pp. 213‐243.
Platt, J. (1981), “Evidence and proof in documentary research: 1”, Sociological Review, Vol. 29 No. 1, pp. 31‐52.
Prater, E., Biehl, M. and Smith, M. (2001), “International supply chain agility: trade offs between flexibility and uncertainty”, International Journal of Operations & Production Management, Vol. 21 Nos 5/6, pp. 823‐839.
Pujawan, I. (2004), “Assessing supply chain flexibility: a conceptual framework and case study”, International Journal of Integrated Supply Management, Vol. 1 No. 1, pp. 79‐97.
Richter, A., Sadek, T. and Steven, M. (2010), “Flexibility in industrial product‐service systems and use‐oriented business models”, CIRP Journal of Manufacturing Science and Technology, Vol. 3 No. 2, pp. 128‐134.
Sanchez, R. (1993), “Strategic flexibility, firm organization, and managerial work in dynamic markets: a strategic options perspective”, Advances in Strategic Management, Vol. 9 No. 1, pp. 251‐291.
Sanchez, R. (1995), “Strategic flexibility in product competition”, Strategic Management Journal, Vol. 16 No. S1, pp. 135‐159.
Sanchez‐Rodrigues, V., Potter, A. and Naim, M.M. (2010), “Evaluating the causes of uncertainty in logistics operations”, International Journal of Logistics Management, Vol. 21 No. 1, pp. 45‐64.
Sanchez‐Rodrigues, V., Stantchev, D., Potter, A., Naim, M. and Whiteing, A. (2008), “Establishing a transport operation focused uncertainty model for the supply chain”, International Journal of Physical Distribution & Logistics Management, Vol. 38 No. 5, pp. 388‐411.
Sarker, B.R., Krishnamurthy, S. and Kuthethur, S.G. (1994), “A survey and critical review of flexibility measures in manufacturing systems”, Production Planning & Control, Vol. 5 No. 6, pp. 512‐523.
Sawhney, R. (2006), “Interplay between uncertainty and flexibility across the value‐chain: Towards a transformation model of manufacturing flexibility”, Journal of Operations Management, Vol. 24 No. 5, pp. 476‐493.
Sethi, A.K. and Sethi, S.P. (1990), “Flexibility in manufacturing: a survey”, International Journal of Flexible Manufacturing Systems, Vol. 2 No. 4, pp. 289‐328.
Sethi, S.P., Yan, H. and Zhang, H. (2004), “Quantity flexibility contracts: optimal decisions with information updates”, Decision Sciences, Vol. 35 No. 4, pp. 691‐712.
Sherehiy, B., Karwowski, W. and Layer, J.K. (2007), “A review of enterprise agility: concepts, frameworks, and attributes”, International Journal of Industrial Ergonomics, Vol. 37 No. 5, pp. 445‐460.
Shewchuk, J.P. and Moodie, C.L. (1998), “Definition and classification of manufacturing flexibility types and measures”, International Journal of Flexible Manufacturing Systems, Vol. 10 No. 4, pp. 325‐349.
Silvestro, R. (1993), “The measurement of service flexibility”, paper presented at the Eighth Annual Conference of the Operations Management Association, 25‐26 May, Warwick.
Slack, N. (1983), “Flexibility as a manufacturing objective”, International Journal of Operations & Production Management, Vol. 3 No. 3, pp. 4‐13.
Stevenson, M. and Spring, M. (2007), “Flexibility from a supply chain perspective: definition and review”, International Journal of Operations & Production Management, Vol. 27 No. 7, pp. 685‐713.
Surana, A., Kumara, S., Greaves, M. and Raghavan, U. (2005), “Supply‐chain networks: a complex adaptive systems perspective”, International Journal of Production Research, Vol. 43 No. 20, pp. 4235‐4265.
Swafford, P.M. (2003), “Theoretical development and empirical investigation of supply chain agility”, unpublished PhD, Georgia Institute of Technology, Atlanta, GA.
Tachizawa, E. and Thomsen, C. (2007), “Drivers and sources of supply flexibility: an exploratory study”, International Journal of Operations & Production Management, Vol. 27 No. 10, pp. 1115‐1136.
Tang, C. and Tomlin, B. (2008), “The power of flexibility for mitigating supply chain risks”, International Journal of Production Economics, Vol. 116 No. 1, pp. 12‐27.
Tang, O. and Nurmaya Musa, S. (2011), “Identifying risk issues and research advancements in supply chain risk management”, International Journal of Production Economics, Vol. 133 No. 1, pp. 25‐34.
Upton, D.M. (1994), “The management of manufacturing flexibility”, California Management Review, Vol. 36 No. 2, pp. 72‐89.
Upton, D.M. (1995), “What really makes factories flexible?”, Harvard Business Review, Vol. 73 No. 4, pp. 74‐84.
van der Vorst, J.G.A.J. and Beulens, A.J.M. (2002), “Identifying sources of uncertainty to generate supply chain redesign strategies”, International Journal of Physical Distribution & Logistics Management, Vol. 32 No. 6, pp. 409‐430.
van der Vorst, J.G.A.J., Beulens, A.J.M., de Wit, W. and van Beek, P. (1998), “Supply chain management in food chains: improving performance by reducing uncertainty”, International Transactions in Operational Research, Vol. 5 No. 6, pp. 487‐499.
Vecchio, R.P. (2006), Organizational Behavior: Core Concepts, Thomson/South Western, Mason, OH.
Verdu ‐Jover, A. and G'omez‐Gras, J. (2009), “Measuring the organizational responsiveness through managerial flexibility”, Journal of Organizational Change Management, Vol. 22 No. 6, pp. 668‐690.
Verdu ‐Jover, A., Llorens‐Montes, F. and Garcıa‐Morales, V. (2004), “The concept of fit in services flexibility research: an empirical approach”, International Journal of Service Industry Management, Vol. 15 No. 5, pp. 499‐514.
Vickery, S., Calantone, R. and Droge, C. (1999), “Supply chain flexibility: an empirical study”, Journal of Supply Chain Management, Vol. 35 No. 3, pp. 16‐24.
Vokurka, R.J. and O’Leary‐Kelly, S.W. (2000), “A review of empirical research on manufacturing flexibility”, Journal of Operations Management, Vol. 18 No. 4, pp. 485‐501.
Wadhawa, S. and Rao, K. (2003), “Flexibility and agility for enterprise synchronization: knowledge and innovation management towards flexagility”, Studies in Informatics and Control, Vol. 12 No. 2, pp. 111‐128.
Wallace, S.W. and Choi, T.M. (2011), “Flexibility, information structure, options, and market power in robust supply chains”, International Journal of Production Economics, Vol. 134 No. 2, pp. 284‐288.
Wilson, M. (2006), unpublished PhD, Lincoln University, Lincoln.
Womack, J.P. and Jones, D.T. (1996), Lean Thinking, Simon and Schuster, New York, NY.
Yasu, M. (2012), “Dentsu’s excellent foreign adventure”, Bloomberg Businessweek, 23‐29 July, pp. 22‐23.
Yin, R.K. (2009), Case Study Research: Design and Methods, Sage, Thousand Oaks, CA.
Zhang, M.J. (2005), “Information systems, strategic flexibility and firm performance: an empirical investigation”, Journal of Engineering and Technology Management, Vol. 22 No. 3, pp. 163‐184.
Zhang, Q., Vonderembse, M.A. and Lim, J.S. (2002), “Value chain flexibility: a dichotomy of competence and capability”, International Journal of Production Research, Vol. 40 No. 3, pp. 561‐583.
Zhang, Q., Vonderembse, M.A. and Lim, J.‐S. (2003), “Manufacturing flexibility: defining and analyzing relationships among competence, capability, and customer satisfaction”, Journal of Operations Management, Vol. 21 No. 2, pp. 173‐191.
Zomorrodi, M. and Fayezi, S. (2011), “Understanding the concept of elasticity in supply chain relationships: an agency theory perspective”, Asian Journal of Management Research, Vol. 1 No. 2, pp. 452‐472.
Zsidisin, G.A. (2003), “Managerial perceptions of supply risk”, Journal of Supply Chain Management: A Global Review of Purchasing and Supply, Vol. 39 No. 1, pp. 14‐26.
Zsidisin, G.A. and Ritchie, B. (2008), “Supply chain risk management: developments, issues and challenges”, in Zsidisin, G.A. and Ritchie, B. (Eds), Supply Chain Risk: A Handbook of Assessment, Management, and Performance, Springer‐Verlag, New York, NY, pp. 1‐12.
Zsidisin, G.A., Panelli, A. and Upton, R. (2000), “Purchasing organization involvement in risk assessments, contingency plans, and risk management: an exploratory study”, Supply Chain Management: An International Journal, Vol. 4 No. 4, pp. 187‐197. Zsidisin, G.A., Ellram, L.M., Carter, J.R. and Cavianto, J.L. (2004), “An analysis of supply risk assessment techniques”, International Journal of Physical Distribution & Logistics Management, Vol. 34 No. 5, pp. 397‐413. (The Appendix follows overleaf.)
Appendix
Flexibility type
Relationship flexibility: “level of tolerance threshold of co‐operating parties in presence of their sudden behaviour change” Inbound/outbound delivery flexibility: “ability of the system to shorten or lengthen its delivery time, that is, to bring forward or put back production” Purchasing flexibility: “the availability of a range of options and the ability of the purchasing function to effectively exploit them to respond to changing requirements for the supply of purchased components” Expansion flexibility: “the ease with which its capacity and capability can be increased when needed” Machine/equipment flexibility: “the various types of operations that the machine can perform without requiring a prohibitive effort in switching from one operation to another” Labour flexibility: “range of tasks that an operator can perform within the manufacturing system” Materials handling flexibility: “ability to move different part types efficiently for proper positioning and processing through the manufacturing facility it serves” Routing flexibility: “ability to produce a part by alternate routes through the system” Operations flexibility: “ability to configure assets and operations to react to emerging customer trends … at each note of the supply chain” Production flexibility: “the universe of part types that the manufacturing system can produce without adding major capital equipment”
Reference(s)
Zomorrodi and Fayezi (2011, p. 452) Slack (1983, p. 10) Swafford (2003, p. 21) Sethi and Sethi (1990, p. 309) Sethi and Sethi (1990, p. 298)
Vokurka and O’Leary‐Kelly (2000, p. 486) Sethi and Sethi (1990, p. 300) Sethi and Sethi (1990, p. 305) Duclos et al. (2003, p. 450) Sethi and Sethi (1990, p. 311)
Table A.I. Flexibility typologies
Information system flexibility: “the ability to align information system architectures and systems with the changing information needs of the organisation as it responds to changing customer demands” Market flexibility: “the ease with which the manufacturing system can adapt to a changing market environment” Strategy development flexibility: “ability of the organisation to develop strategy based on internal competence and external customer needs, continuously and effectively” Organisational flexibility: “the ability to align labour force skills to the needs of the supply chain to meet customer service/demand requirements” Information dissemination flexibility: “ability of the organisation to collect and disseminate quickly the variety of data needed along the supply chain to meet customer needs” New product flexibility: “the range of products a manufacturing system can produce” Mix flexibility: “ability of the organisation to produce different combinations of products economically and performance‐effectively given certain capacity”
Volume flexibility: “ability to be operated profitably at different overall output levels” Modification/specification flexibility: “ability of the manufacturing process to implement minor design changes in a given product to accommodate customer specifications”
Customer recovery flexibility: “the ability to recover the customer after something goes wrong ability to align information system architectures and systems with the changing information needs of the organisation as it responds to changing customer demands”
Duclos et al. (2003, p. 451) Sethi and Sethi (1990, p. 312) Zhang et al. (2002, p. 572)
Duclos et al. (2003, p. 451) Zhang et al. (2002, p. 572 Slack (1983, p. 8) Zhang et al. (2002, p. 569) Sethi and Sethi (1990, p. 307)
Gerwin (1987, p. 399)
Corre a and Gianesi (1994, p. 5) (continued)
Corresponding author Sajad Fayezi can be contacted at: [email protected]