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Our research addresses the confusion and inconsistency associated with “lean production.” We attempt to clarify the semantic confusion surrounding lean production by conducting an extensive literature review using a historical evolutionary perspective in tracing its main components. We identify a key set of measurement items by charting the linkages between measurement instruments that have been used to measure its various components from the past literature, and using a rigorous, two-stage empirical method and data from a large set of manufacturing firms, we narrow the list of items selected to represent lean production to 48 items, empirically identifying 10 underlying components. In doing so, we map the operational space corresponding to conceptual space surrounding lean production. Configuration theory provides the theoretical underpinnings and helps to explain the synergistic relationships among its underlying components.

In 360 BC, Plato (in Cratylus) suggested that linguistic confusion arises because multiple terms may refer to the same object or idea, a single term may refer ambiguously to more than one object or idea, and terms may be confusing because they are out of date. The same observations can be made today with respect to a number of management approaches. The current study addresses these issues with regard to lean production. We believe that the price paid for lacking a clear, agreed-upon definition is high because empirical testing of inexact and imprecise concepts lead to a body of research that examines slightly different aspects of the same underlying constructs masked by different terminology. Consequently, results from such testing do not improve our understanding, make marginal contributions to the existing knowledge base, and prevent academic fields from making real progress ( Meredith, 1993). If theory and empirical work are to advance in this area, semantic differences between lean production and its predecessors must be resolved, the conceptual definition of lean production must be clarified, and operational measures must be more clearly specified. In this paper, we address these three issues. The approach now known as lean production has become an integral part of the manufacturing landscape in the United States (U.S.) over the last four decades. Its link with superior performance and its ability to provide competitive advantage is well accepted among academics and practitioners alike (e.g., Krafcik, 1988, MacDuffie, 1995, Pil and MacDuffie, 1996, Shah and Ward, 2003 and Wood et al., 2004). Even its critics note that alternatives to lean production have not found widespread acceptance (Dankbaar, 1997) and admit that “lean production will be the standard manufacturing mode of the 21st century” (Rinehart et al., 1997, p. 2). However, any discussion of lean production with managers, consultants, or academics specializing in the topic quickly points to an absence of common definition of the concept. This lack of clarity is evident from the multiplicity of descriptions and terms used with respect to lean production. The ambiguity stems in part because lean production evolved over a long period of time (Hopp and Spearman, 2004, Womack et al., 1990 and Spear and Bowen, 1999) and because of its mistaken equivalence with other related approaches. Hopp and Spearman (2004) note that using closely related terms in the titles of some of the earliest publications may have also contributed to this confusion (see for example Sugimori et al., 1977). These primarily semantic differences between lean and its predecessors are unfortunate but can be resolved fairly easily. A greater source of confusion, however, is the more substantive disagreement about what comprises lean production and how it can be measured operationally. Our objectives in this paper are as follows. First, we attempt to resolve the semantic confusion surrounding lean production and explain the different perspectives invoked in describing it using a historical evolutionary lens. Second, in our pursuit of a commonly agreed upon definition of lean production, we propose a conceptual definition that encompasses its underlying multidimensional structure. Finally, using a rigorous empirical method, we identify a set of 48 items to measure lean production and its main components. Additionally, we chart the linkages among the items and the components and map the operational space as it corresponds to the conceptual space. In short, we develop the concept of lean production based on extant knowledge and use data from a sample of manufacturers to develop an operational measure that consists of 10 reliable and valid scales.

This research takes an initial step toward clarifying the concept of lean production and develops and validates a multi-dimensional measure of lean production. Following Whetten (1989), we organize the discussion of our results into three sections: what is lean production (i.e. identify critical factors), how are the various factors of lean production related to each other, and why are they related. 5.1. “What” is lean production? In this research, we propose a conceptual definition of lean production and derive an operational measure from the content and objectives of its historical roots in TPS. To that end, we identified 48 practices/tools to represent the operational space surrounding lean production. Using a multi-step construct development method, we distill the measurement items into 10 factors which also map onto the conceptual definition well. Fig. 3 summarizes this mapping. Of the 10 factors identified in this study, three measure supplier involvement, one measures customer involvement, and the remaining six address issues internal to the firm. Together, these 10 factors constitute the operational complement to the philosophy of lean production and characterize 10 distinct dimensions of a lean system. They are: 1. SUPPFEED (supplier feedback): provide regular feedback to suppliers about their performance 2. SUPPJIT (JIT delivery by suppliers): ensures that suppliers deliver the right quantity at the right time in the right place. 3. SUPPDEVT (supplier development): develop suppliers so they can be more involved in the production process of the focal firm. 4. CUSTINV (customer involvement): focus on a firm's customers and their needs. 5. PULL (pull): facilitate JIT production including kanban cards which serves as a signal to start or stop production. 6. FLOW (continuous flow): establish mechanisms that enable and ease the continuous flow of products. 7. SETUP (set up time reduction): reduce process downtime between product changeovers. 8. TPM (total productive/preventive maintenance): address equipment downtime through total productive maintenance and thus achieve a high level of equipment availability. 9. SPC (statistical process control): ensure each process will supply defect free units to subsequent process. 10. EMPINV (employee involvement): employees’ role in problem solving, and their cross functional character. 5.2. “How” are the factors of lean production related? The 10 factors derived during empirical analysis are positively and significantly correlated with each other (p < 0.001), thereby providing support to the multi-dimensional and integrated nature of lean production systems ( Table 6). As a set, the statistical and empirical results associated with the CFA model suggest that lean production can be represented with 10 factors where each factor represents a unique facet. The high inter-correlation between the factors lends further support to the “configuration” argument and suggests that managers are able to discern the close relationship and yet make distinctions between them. More specifically, our results indicate that practicing managers recognize the contribution of each individual factor and their collective importance when pursuing lean production. These results allow us to build on existing agreement related to “bundles of lean practices” ( Shah and Ward, 2003) and, at the same time, to add clarity to the confusing array of terms and concepts associated with lean production. The correlations between factors range from 0.77 (between SUPPJIT and SUPPDEVT) to 0.12 (between TPM and CUSTINV). A closer inspection of the correlation matrix revealed that TPM is the least associated with other scales. This pattern in the correlation matrix was also observed in Sakakibara et al. (1993), where preventive maintenance exhibited low and insignificant correlations with five other scales. However we could not examine this relationship in other published research because none of them included the correlation matrix between TPM and other factors (McKone and Weiss, 1999, Cua et al., 2001 and Shah and Ward, 2003). Even so, the CFA results suggest that a well-developed lean strategy will include many different lean practices. Therefore, a state of the art implementation will require firms to exert considerable effort along several dimensions simultaneously. 5.3. “Why” are the factors of lean production related? Lean production is an integrated system composed of highly inter-related elements. In explaining inter-relationships, researchers frequently rely on the statistical significance of the empirical results. However, statistical significance is a necessary but not a sufficient condition to explain the inter-relationships in a system. Researchers must also judge the reasonableness of the logic used to explain the inter-relatedness of the elements because reasonable logic provides the theoretical glue that holds a model together (Whetten, 1989). We explain our logic below. The main objective of lean production is to eliminate waste by reducing or minimizing variability related to supply, processing time, and demand. Reducing variability related to only one source at a time helps a firm in eliminating only some of the waste from the system; not all waste can be addressed unless firms can attend to each type of variability concomitantly. That is, processing time variability cannot be eliminated unless supply and demand variability is also reduced. For instance, variability in setup times and delivery schedule by suppliers both contribute to firms holding excess inventory in order to prevent starving downstream work stations. But reducing setup time variability alone does not eliminate excess inventory from the system, because firms will continue to hold excess inventory to accommodate variability in supplier delivery. To reduce excess inventory of all types, firms will have to secure reliable suppliers in addition to developing a reliable process. The 10 underlying factors/dimensions of lean production proposed here jointly enable firms to address variability in the following manner. To facilitate continuous flow (FLOW), products are grouped according to product families, and equipment is laid out accordingly; and to prevent frequent stop-and-go operations, equipment undergoes frequent and regular preventive maintenance (TPM). Closely grouped machines and the similarity of products allow employees to identify problems while cross-trained, self-directed teams of workers are able to resolve problems more quickly and effectively (EMPINV). Actively involved customers (CUSTINV) enable firms to predict customer demand accurately. Reduced setup times (SETUP) and stricter quality assurance (SPC) allow firms to predict process output more exactly. To produce the kind of units needed, at the time needed, and in the quantities needed, firms use kanban and pull production systems (PULL), which require that suppliers deliver sufficient quantities of the right quality product at the right time. This JIT delivery by suppliers (SUPPJIT) is predicated on providing suppliers with regular feedback on quality and delivery performance (SUPPFEED), and providing training and development for further improvement (SUPPDEVT). Because no firm has infinite resources to expend, the supplier base needs to be limited to a few key suppliers with whom firms can have long term relationships rather than short term contracts. It is the complementary and synergistic effects of the 10 distinct but highly inter-related elements that give lean production its unique character and its superior ability to achieve multiple performance goals. While each element by itself is associated with better performance, firms that are able to implement the complete set achieve distinctive performance outcomes that can result in sustainable competitive advantage. Sustainability of advantage follows from the difficulty in implementing several aspects of lean simultaneously. Because simultaneous implementation of so many elements is difficult to achieve, it is also difficult to imitate. 5.4. Contributions We make three substantive contributions to existing research. First, viewing lean production in its historical context with an evolutionary lens helps to reconcile the overlap among its various components. We argue that, viewed separately, none of the components are equivalent to the system, but together they constitute the system. Lean production is not a singular concept, and it cannot be equated solely to waste elimination or continuous improvement, which constitute its guiding principles, nor to JIT, pull production, kanban, TQM, or employee involvement, which make-up some of its underlying components. Lean production is conceptually multifaceted, and its definition spans philosophical characteristics that are often difficult to measure directly. Further, the practices/tools used to measure lean production, even when associated uniquely with a single component, indicate mutual support for multiple components. By juxtaposing the historical evolution of lean production and the perspective used in describing it, we can begin to understand the multiplicity of terms associated with lean production and attempt to resolve some of the confusion surrounding it. Second, we propose a conceptual definition of lean production which captures the integrated nature of lean systems. Our definition includes both the people and the process components on one hand, and internal (related to the firm) and external (related to supplier and customer) components on the other hand. In this sense, our definition of lean production highlights mechanisms needed to achieve the central objective of waste elimination. This definition maximizes the potential for concept-traveling so that lean production can precisely fit a variety of applications (Osigweh, 1989). Yet, it minimizes the problem of concept-stretching, or broadening the concept's meaning beyond reason. In order for a system to be lean, it has to address not only variability reduction, but also the specific operationalization of supplier and customer relationships which may differ depending on the unit of analysis. Finally, we develop an operational measure of lean production and provide a framework that identifies its most salient dimensions. Our operational measure is more comprehensive than other measures observed in literature as it reflects the lean landscape more broadly by including both internal and external dimensions. An empirical test of our operational measures suggests that it is reliable and meets established criteria for assessing validity. We identified a broad set of items that can be distilled into fewer components to represent multiple facets of a lean production system. In identifying 10 dimensions of lean production, we help to establish its underlying dimensional structure. Specifically, we characterize lean production with 10 unique sub-dimensions, and in our attempt to resolve the confusing array of concepts and measurement schemes witnessed in the previous literature, we show that concepts and measurement scales change with time. This is consistent with Devlin et al.'s (1993) argument that there are no “best” or “perfect” scales and Schmalensee (2003), who argued that the choice of scales changes with research objective. The empirically validated measurement instrument we provide here is useful for researchers who are interested in conducting survey research related to lean production systems. This instrument will allow the researchers to assess the state of lean implementation in firms and to test hypotheses about relationships between lean production and other firm characteristics that affect firm performance. The findings provide guidance for empirical research seeking parsimony in data collection. To adequately measure lean production, instrumentation should reflect all 10 underlying constructs. Additionally, the study provides a tool for managers to assess the state of lean production in their specific operations. For instance, scales developed here may be used by managers to self-evaluate their progress in implementing lean production. The findings also suggest that every one of the 10 dimensions of lean production is an important contributor and that none should be eliminated. The framework forms a foundation for research in lean production and should prove helpful in enabling researchers to agree on a definition. It is imperative to come to agreement on both a conceptual definition and an operational measure because, if history is any guide, old concepts will continue to evolve and we in the academic community will lag farther behind practice. The new and emerging concept of “lean-sigma” is a case in point. Lean-sigma is being forwarded as a management philosophy based on integrating lean production principles and practices with Six Sigma tools. If we cannot consistently define lean production, how can we differentiate it from other management concepts and verify its effectiveness to practicing managers? It is our intention to contribute to scholarly agreement on such a stipulative definition and to the emerging academic literature related to lean production (Narasimhan et al., 2006, De Treville and Antonakis, 2006 and Hopp and Spearman, 2004). We intend that our operational measure of lean production will complement the conceptual definition presented earlier.