In an article published in 2007, my co-author and I describe and test a theory of complementarities between design–manufacturing integration (DMI) and usage of advanced manufacturing technologies (AMT). This study extends prior AMT research by examining the role of complementary assets in explaining how AMT adoption contributes to manufacturing performance. In addition, the study provides a finer-grained analysis of associations between Process and Planning AMT usage and various aspects of manufacturing performance.We analyze data from 224 manufacturing plants in order to test the hypotheses that DMI moderates the relationships between AMT usage and manufacturing performance. Regression analysis results indicate that DMI plays the role of complementary asset to AMT usage when quality, delivery and process flexibility are considered. A complementary role is not observed for cost efficiency and new product flexibility. In fact, the results suggest that combined high levels of DMI and AMT usage can be costly. We discuss the implications of the findings for a contingency theory of AMT success, for future research, and for managerial practice.
The significant main effects of AMT on manufacturing performance uncovered in our analysis in some ways confirmed arguments forwarded in prior studies, and in other ways offered some surprises. Both Planning and Process AMT are positively associated with new product and manufacturing process flexibilities. Associations with delivery performance are not as significant. A positive bivariate correlation between Process AMT usage and delivery disappears in the regression analyses. These findings support the notion that AMT’s greatest potential benefits apply to manufacturing flexibilities. Interestingly, however, our results also suggest that Planning AMT usage may be costly, as it is associated with lower cost efficiency relative to competitors. The high costs of implementation for
advanced planning technologies such as ERP have been well documented. One interpretation of this result is that high implementation costs have not been sufficiently offset by transactional efficiencies.
In fact, our data analysis indicates that both Processing and Planning AMT usage are negatively associated with cost efficiency when high levels of DMI are present. Using the complementary
assets perspective one could surmise that the resources required to install the routines and communication protocols associated with DMI are especially costly when specialized technologies must be analyzed and integrated into the design, planning, and execution of production operations. For example, the creation of design-for-manufacture guidelines may be more difficult and costly when more sophisticated manufacturing technologies are present, especially if the technologies are new to the firm. Both AMT and DMI activities require a significant amount of overhead resources, including highly trained engineering, maintenance, and other technical staff. Costs associated with these resources, as well as significant capital equipment costs, may offset direct cost efficiencies offered by
AMT. It is also possible that a manufacturing organization’s DMI activities may involve people that are inadequately trained or experienced in the use of Process and Planning AMT.
Since our data are cross-sectional, it could alternatively be argued that these findings indicate that companies with higher cost structures are more likely to use AMT. For example, if a company is pursuing a strong product differentiation strategy based on wide product variety, it may accept having higher costs than competitors who offer simpler product lines. In this case, AMT usage may not necessarily be expensive; rather it may be more common in companies that have high costs of production because of complexities in their products or processes. In order to investigate this possibility, we repeated the regression analyses with two additional variables as controls: (1) "our manufacturing strategy emphasizes being the lowest cost producer" and (2) "our manufacturing strategy emphasizes highly customized products" (7 point scale, strongly disagree–strongly agree). The results with the added controls were essentially unchanged; the negative main effect of Planning AMT and both negative interaction effects remained significant at the same levels as before. These findings argue against the alternative interpretation.
Though potentially costly, DMI activities appear to produce benefits in terms of product quality, delivery, and process flexibility. Positive associations of DMI main effects with performance improvement were indicated for quality, delivery and new product flexibility, with the strongest direct effect being evidenced for quality performance. In accordance with our expectations, DMI appears to be especially important in achieving Process AMT’s potential benefits to quality, delivery, and process flexibility. Process AMT usage is positively associated with each manufacturing performance dimension. However, relationships between Process AMT usage and manufacturing performance dimensions are actually negative when DMI is low.
Process AMT usage is thought to improve product quality through the greater consistency that automation provides. It is thought to improve delivery and process flexibility through improved changeover and processing speed which allow small production lot sizes and less work-in-process inventory. Importantly, our findings suggest that Process AMT usage is less likely to lead to these improved capabilities if the firm is not able to create substantial integrative capabilities. Arguments for the necessity of integration again stem from the high levels of appropriability and uncertainty that are endemic to AMT adoptions. Design–manufacturing integration activities address ambiguities and interdependencies that surround product and process functional specifications. Thus, DMI leads designers to a deeper understanding of AMT capabilities and limitations. This greater understanding leads to better applications of technology, and better fit between product and process designs. Presumably, a manufacturing organization that achieves high levels of DMI creates a source of
competitive advantage that compensates for AMT’s widespread availability. It is likely that the capabilities of Process AMT are best utilized when product designers are made fully aware of them through DMI activities. Our results offer evidence of the purported benefits of concurrent engineering and design-for-manufacture types of integrative activities.
As for the benefits of Planning AMT, the results indicate that they pertain mostly to improvements in flexibility, the strongest positive association being with process flexibility. The results indicate that a positive association between Planning AMT usage and process flexibility is made even more positive when high levels of DMI are present. Planning AMT purportedly offers at least two main benefits. It can improve efficiency by optimizing production schedules in order to more fully utilize manufacturing resources. In addition, the computational power and speed of Planning AMT offers the ability to create more complex and responsive schedules, thereby allowing greater flexibility in production. DMI augments these benefits.We posit that, in the same way that DMI uncovers technical dependencies between product design and machine processing requirements, DMI also serves to clarify the impacts on production flows that result from aspects of product complexity and variety created in product design. The interaction of Planning AMT and DMI reflects the combination of greater planning and product flow visibility provided by Planning AMT with the insights of manufacturing experience made available through DMI. By integrating these two sources of knowledge into product design decisions, companies may achieve higher levels of process flexibility. For example, product designers may create
more effective uses of shared components within product architectures, leading to more efficient
production flows and to faster lead times.
It is important to note that DMI involves both "organic" and "mechanistic" organization design aspects. While the organic practices underlying DMI focus on social integration by means of broad role descriptions for the design and manufacturing personnel and by horizontal communication protocols (e.g., via concurrent engineering); the mechanistic practices focus on procedures, guidelines and rules for efficient integration of design and manufacturing activities (i.e., design-for-manufacturing). In contrast to the concurrent engineering literature that mostly focuses on organic practices, our conceptualization of DMI considers a combination of mechanistic practices (use of manufacturability guidelines, use of Design for Manufacture/ Assembly methods) as well as organic practices (coordination mechanisms for design–manufacturing issues, manufacturing involvement in new product development). Thus, we contend that a more holistic characterization of DMI in this study presents a richer role of DMI and firmly positions the construct within the extant literature base investigating AMT–performance relationship. Even so, our study of DMI is limited by its focus on one-way communication of manufacturing knowledge to product designers. Valuable extensions of this research would examine DMI from more of a two-way perspective that also includes communications of product knowledge to manufacturing process designers and managers.
Overall, the different effects on different dimensions of manufacturing performance uncovered in this research might be used to explain inconsistent findings regarding AMT’s relationships to profitability and growth. Trade-offs appear to be at work. Investors in AMT may lose cost advantages in trade for improved quality, delivery, and flexibility. The findings have several interesting implications for managers seeking to maximize the potential of AMT. Our results suggest that managers seeking to improve time-based outcomes do well to invest in Process and Planning AMT. Thus, Process and Planning AMT investments would support a time-based or product differentiation-based manufacturing strategy. In general, the data from our study and others suggest that AMTs are not well suited for strategies that emphasize low cost.
DMI enhances AMT-driven capabilities, though it too may be costly. The net effect of DMI on each of the dimensions of manufacturing performance is in most cases strongly positive and at worst negligible. So DMI appears to be a good investment. However, in order to reap maximum benefits from DMI in conjunction with AMT, managers should be prepared for potential monetary costs, and there may be an associated learning curve. We speculate that risks associated with DMI are probably tied to suboptimal implementation or poorly developed supporting resources. History, culture, and leadership may also be important factors that explain why some firms are more adept at DMI than others.
Source: Swink, M. and Nair, A. 2007. “Capturing the competitive advantage of AMT: Design-Manufacturing integration as a complementary asset,” Journal of Operations Management, Vol. 25 (3): 736-754