ارتباط دادن مدیریت کیفیت به استراتژی تولید: یک تحقیق تجربی از شیوه های مشتری مداری

Quality management (QM) has often been advocated as being universally applicable to organizations. This is in contrast with the manufacturing strategy contingency approach of operations management (OM) which advocates internal and external consistency between manufacturing strategy choices. This article investigates, using the case-study method, whether customer focus practices—a distinctive subset of the whole set of QM practices—are contingent on a plant’s manufacturing strategy context. The study strongly suggests that customer focus practices are contingent on a plant’s manufacturing strategy and identifies mechanisms by which this takes place. The findings inform the implementation of QM programs.

Quality management (QM) has become an all-pervasive management philosophy having found its way into most countries and business sectors. Having been mostly led by practitioners, QM acquired a strong prescriptive stance in its initial diffusion stages (mainly the 1980s and early 1990s) with practices often being advocated as universally applicable to organizations. The emergence of awards such as the Malcolm Baldrige National Quality Award and the European Quality Award have reinforced the universal profile of QM practices at this time. In the early 1990s, the initial enthusiasm over the universality of QM began to be tempered by numerous reports in the practitioner literature of problems in implementing QM (e.g. Harari, 1993, MacDonald, 1993 and Papa, 1993). The proponents of the universal view of QM would argue that these implementation difficulties are part of moving an organization towards quality, but an alternative explanation is that those difficulties result from too great a mismatch between the proposed form of QM and the particular organizational context. This explanation had been largely overlooked by the predominantly practitioner literature on QM implementation. More recently, rigorous academic studies have started to question the universal validity of QM practices by addressing the influence of the organizational context on QM practice (Sousa and Voss, 2002). Of these, only a few studies directly and rigorously addressed this issue within an explicit contingency framework, all of them suggesting that the effectiveness of QM practices is contingent on the organizational context. Relevant contextual variables include managerial knowledge, corporate support for quality, external quality requirements and product complexity (Benson et al., 1991), organizational uncertainty (Sitkin et al., 1994 and Reed et al., 1996), international competition (Das et al., 2000), manufacturing strategy context (Sousa, 2000 and Sousa and Voss, 2001), firm size, capital intensity, degree of diversification, timing of QM implementation and maturity of QM program (Hendricks and Singhal, 2001). Other studies, whose main purpose was not to investigate QM contingencies, have tangentially uncovered other contextual factors affecting QM practices, such as industry (Maani, 1989 and Powell, 1995), country (Madu et al., 1995), and product/process factors (e.g. manufacturing system, Maani, 1989; type of work an organization does, Lawler, 1994; breadth of product line and frequency of product changes, Kekre et al., 1995; work design, Victor et al., 2000). In addition, several large scale empirical studies examining the impact of QM on firm performance have found that some QM practices did not have a significant impact on performance (e.g. Powell, 1995, Dow et al., 1999 and Samson and Terziovski, 1999), some of them suggesting that this may be due to these practices being context dependent (Powell, 1995 and Dow et al., 1999). At a more general level, Dean and Bowen (1994) point out that the universal orientation of QM contrasts with the contingent approach of existing management theory. The contingency perspective is not new in the operations management (OM) field. In fact, OM has been strongly rooted from its inception on a manufacturing strategy contingency approach. The assumption of this approach is that internal and external consistency between manufacturing strategy choices increases performance (e.g. Woodward, 1965, Hayes and Wheelwright, 1979, Hill, 1985 and Ward et al., 1996). Internal consistency refers to the coherence between the different elements of a manufacturing strategy; external consistency refers to the match between this set and the wider organizational context (e.g. marketing strategy). Many of the potential contingency factors uncovered in the QM contingency studies cited earlier have strong associations with the manufacturing strategy context. Despite the tensions identified in the literature—apparent across different streams of research in the QM field—there is still little empirical research directly addressing the question: are QM practices contingent on an organization’s manufacturing strategy context? In order to contribute to this need, this article concentrates on a critical and distinctive subset of the whole set of QM practices, customer focus practices. The importance of investigating the specific links between customer focus practices and manufacturing strategy is two-fold. First, customer focus is seen as the starting point of any quality initiative. Second, while the concept of customer focus has been heavily researched from a marketing perspective, it has not received the attention, it deserves in the OM field. As defined in the context of QM, customer focus practices involve the establishment of links between customer needs and satisfaction and internal processes. However, the emphasis of existing research in marketing has been on the identification and measurement of customer needs and satisfaction, having virtually left untouched the links between these needs and a plant’s internal processes. An OM perspective can therefore effect significant contributions. This article tries to fill this specific gap by investigating links between customer focus practices and manufacturing strategy by addressing two related research questions: (i) are customer focus QM practices contingent on a plant’s manufacturing strategy context (analysing)? and (ii) if so, what are the mechanisms by which manufacturing strategy context affects those practices (explaining)? The study adds to the sparse empirical contingency work in QM mentioned earlier in that while most studies were geared towards hypotheses testing based on large survey samples (e.g. Benson et al., 1991, Das et al., 2000 and Hendricks and Singhal, 2001), the study in hand is mainly theory-building based on case studies with the objective of not only uncovering contingency effects but also to produce empirically grounded explanations for them. Survey type studies lack this explaining ability. For example, Benson et al.’s (1991) landmark study found that only one product/process factor—product complexity—among several others of this type (e.g. rate of product/process change) affected QM. But no explanation could be derived of why only product complexity mattered and how this factor affected QM. Subsequently, other studies found evidence of the influence of product/process factors on QM practices (e.g. Sousa and Voss, 2001). Understanding the mechanisms by which context affects QM may contribute to reconciling such results and is also valuable to develop levers for proactive managerial action (e.g. how to overcome eventual obstacles posed by context on the use of QM practices). The structure of the article is as follows. First, it describes the multiple case-study research design that was used to address the research questions. Second, the methodology of the study, including sample selection and data collection, is addressed. Next, it describes a first stage of analysis consisting of the reduction of case data on the several research variables in preparation for a second stage of deeper analysis. It then addresses the second stage of analysis directed at answering the research questions. This includes the analysis of the reduced case data for the uncovering of contingency effects and using the richness of the case data for the building of explanatory models linking manufacturing strategy context variables to customer focus practices. Finally, it presents the overall conclusions, limitations and suggestions for future research.

This study makes a contribution to the understanding of the influence of manufacturing strategy context on customer focus QM practices. It strongly suggests that customer focus practices are contingent on a plant’s manufacturing strategy and identifies mechanisms by which this takes place. The study also highlights the importance of the interactions between individual practices, forming an internally coherent customer focus practice configuration matching a plant’s context. This research offers a strong OM perspective on customer focus, bridging the gap between marketing (which has focused mainly on the identification of customer needs) and OM by providing insights on the links between customer needs and a plant’s manufacturing strategy context. Content wise, the study’s findings are not entirely surprising. However, many of the areas of manufacturing strategy that have been accepted for many years have had very little good research done to confirm the accepted relationships and gain deeper knowledge about them. In addition, examples abound in the field of OM of prescriptive and universalistic statements being made about the universal validity of many of its best practices, prominently among which are QM practices, and in particular, customer focus practices. This study contributes to tempering these statements, forging links between best practice and manufacturing strategy within a contingency framework. The identification of the specific mechanisms by which manufacturing strategy context impacts on customer focus also provides managers with important levers for action (see later). The results of this study can be used to inform the implementation of QM programs along one or both of the following two dimensions: the mix of customer focus practices that should be adopted; those adverse context characteristics that should be modified. A search for links between the study’s findings and existing theory (theory triangulation, Miles and Huberman, pp. 266–267) found relevant links between the results and the concepts of the “service factory” (Chase, 1978 and Chase and Garvin, 1989) and “mass customization” (e.g. Pine et al., 1993 and Kotha, 1995). These links with theory shed further light on the implications of the study for the implementation of QM. Regarding the mix of practices to adopt, the study suggests that plants exhibiting different manufacturing strategy contexts should use customer focus practices to different extents. The patterns displayed in Table 6 can be used as a starting point (see discussion on the limitations of the study later). In particular, they seem to suggest that it may not be beneficial for a provider of a commodity product to force a high level of use of customer focus practices onto its operations. This finding is consistent with Chase’s (1978) recommendations that low contact service operations keep their “technical core” isolated from the customers as much as possible in order to increase efficiency (typically, the positioning of a plant as a provider of a commodity product implies a position analogous to a low contact service operation). In the mass customization literature, it is also recognized that increasing customization may add unnecessary cost and complexity to operations (Gilmore and Pine, 1997) and that mass customization is not appropriate for all markets (Pine et al., 1993 and Kotha, 1995). Concerning the modification of adverse manufacturing strategy context characteristics, this study identified critical context characteristics which appear to strongly affect customer focus practices, namely, the degree of product customization and the degree of service differentiation. Although these characteristics are inherent to a plant’s manufacturing strategy context—thus being difficult to change in the short-term—they do provide an extra degree of freedom offering limited opportunities for plants to try to match QM practice to their context. For example, the provider of a commodity product may attempt to change its context by offering some kind of product customization or service differentiation, effectively becoming a bit closer to Chase and Garvin’s (1989) concept of the “service factory”. The fundamental question is whether this change will be worthwhile under the plant’s business environment (e.g. given the intrinsic nature of its markets and the sunk investments already made). An interesting area for future research would be to investigate, from a manufacturing strategy perspective, general courses of action that would make it worthwhile for providers of commodity products to break their context barrier and move to more differentiated manufacturing strategy contexts. In this connection, the strategies for achieving cost-effective customization discussed in the mass customization literature may be a useful starting point (e.g. Gilmore and Pine, 1997 and Feitzinger and Lee, 1997). The hypothesized three configurations of service offering—commodity product, physical product and architecture/service, and manufacturing service—were also found to have strong resonance in the four service roles that Chase and Garvin (1989) suggest for a factory. (i) Dispatcher: Supporting customer delivery needs, the distribution function and the after sales needs. (ii) Showroom: Offering sales support through showing off its products, processes, people and quality commitment. (iii) Laboratory: Furnishing critical data on processes, such as fast product-build feedback to customers. Consultant: Assisting customers in problem solving in areas such as quality improvement, cost reduction and new uses for the customer’s products. In fact, the commodity product configuration may be seen as offering the dispatcher role, with the physical product and architecture/service plant adding the showroom role, and the manufacturing service plant offering all four service roles. Despite this theoretical support, these configurations received only moderate literal replication in the study because the research sample encompassed only one plant representing the commodity product and the physical product and architecture/service configurations. Future research should conduct observations in more plants representing these two configurations. The study’s findings can be the object of good generalization to manufacturing plants in discrete goods industries. The replication logic permits analytical generalization, i.e. the generalization of a particular set of results to some broader theory (Yin, 1994). Although the single industry design undoubtedly reduces generalizability, one is still able to make theoretical—as opposed to statistical—inferences about other industries based on this single industry study. In fact, one would expect to observe the same positioning of plants along the manufacturing strategy configuration spectrum in most discrete good industries (e.g. Hayes and Wheelwright, 1979) and one would also expect that the strategic forces shaping QM practice identified under carefully controlled conditions in the electronics industry would also be in play in other industries (although its effects might be felt alongside other industry specific variables). The effects of these strategic forces, although empirically grounded, had their abstraction level raised to general characteristics of manufacturing strategy configurations, beyond the immediate cases. Nevertheless, further research should ascertain whether these results replicate in other industries. The small sample size did not allow for the testing of whether the uncovered configurations of customer focus practices led to superior overall plant performance. In fact, because of the many factors affecting plant performance (Hackman and Wageman, 1995, p. 320), only a large sample would be likely to reveal any statistically significant effects. Therefore, the study should be complemented with future large scale cross-sectional studies to test the proposed customer focus QM configurations by ascertaining whether plants adopting practice configurations proposed to match their context exhibit superior performance. It would also be important to study the effects of the “improper” use (as suggested by this study’s findings) of practices in relation to a plant’s context. At the methodological level, this study pioneers the use of causal network analysis as a tool for theory-building in the field of OM. It also shows how case-study research, if properly designed (e.g. tight research controls coupled with careful sample selection), can be adequately used to test propositions, a less frequent application of the case method. Overall, the study may be seen as an example of how case-study research, when conducted with rigor, can yield valid and powerful insights, strengthening its credibility as a research method in the OM field (McCutcheon and Meredith, 1993 and Meredith, 1998). Finally, this study will hopefully contribute to the advancement of the QM philosophy. It has been suggested that the success of early adopters of QM resulted from them having had no easy prescribed solution to turn to and having had to think hard and work it out for themselves (MacDonald, 1993). On the contrary, late followers already had packaged solutions available and there was not the same need for hard thinking, which may have led to a much lower rate of success of QM programs. Part of this hard thinking may have to do with adapting the standard QM practice package to a plant’s manufacturing strategy context. It is important to identify the boundaries of applicability of the several QM practices, so that they can be successfully adopted in suitable contexts and not be discredited by failures caused by their forced adoption in unsuitable contexts. This study contributes to this goal by providing implementation guidance for customer focus practices. More contingency studies of this sort are likely to be a promising avenue for taking the maturing QM field further forward.