Choosing the right manufacturing paradigm
By Giovani D.C. Da Silveira and Rui S. Sousa
Developing superior manufacturing competitiveness is back on the agenda of developing economies. Different approaches for decision making have been proposed to achieve this objective. This article discusses the extent to which the three main approaches of building capabilities, adopting best practices, and maintaining fit may explain improvements in quality, delivery and flexibility performance in manufacturing.
In the current harsh economic environment, the quest for manufacturing competitiveness has re-emerged as a key priority for developed economies. In this context, it is useful to revisit and reassess the main sources of operational performance in manufacturing. In a seminal article published in the International Journal of Operations and Production Management in 1995, Chris Voss identified three different sources of performance, which he called manufacturing strategy paradigms: strategic choice (fit), best practice and competing through manufacturing (capabilities).
The fit paradigm recommends that manufacturers make choices that are internally and externally consistent. Internal consistency means adopting coherent choices within a manufacturing plant. For example, if production is high volume, then the plant should adopt line layouts, invest in process automation and keep direct labor costs low. External consistency refers to the alignment of manufacturing choices with markets. In the above example, the internal manufacturing choices are only appropriate for serving markets that require standard products at a low cost. Serving markets that are not cost-sensitive and that require high flexibility instead would demand a different set of choices. According to this paradigm, there are trade-offs between choices. For example, a plant cannot be superior on both cost and flexibility. And internal and external misalignments hurt performance.
The best practice paradigm emphasizes the adoption of best, or worldclass, practices in order to achieve superior performance. Best practices include, among others, quality management, lean and new product development. Practices often are advocated as universally applicable to organizations and organizational activities, challenging the trade-off view of fit. For example, under the fit paradigm, keeping high levels of finished goods inventory might be adequate for high volume production with long production lead times, but lean proponents would see this inventory as waste and would recommend it to be as low as possible. Similarly, they would argue that a plant should be able to compete simultaneously on cost and flexibility.
The capabilities paradigm sees performance as resulting from the building of competencies for sustainable competitive advantage. Roger G. Schroeder, Kimberly A. Bates and Mikko A. Junttila showed in the Strategic Management Journal in 2002 that key capabilities were developed through the following:
- Internal learning: Training of multifunctional employees, employee involvement and empowerment
- External learning: Inter-organizational learning through problem solving with customers and suppliers
- Proprietary processes and equipment: Equipment protected by patents and state-of-the-art equipment and processes developed exclusively by the plant
Each paradigm has its merits and limitations, and because they constitute alternate sources of performance, savvy managers should not ignore any of them. For example, a plant exhibiting high levels of internal fit but employing obsolete practices most likely would not be a top performer. Similarly, a plant with high levels of adoption of best practices but with serious misalignments would be at a competitive disadvantage. Likewise, a manufacturer that ignores the development of capabilities may become vulnerable to rapid changes in the competitive environment and remain exposed to imitation strategies from competitors.
In the current business environment, manufacturers are faced with scarce resources for investing in performance improvement programs. Therefore, it is important to assess the relative contribution of each paradigm to performance. This recent research looked at the performance impacts of the three paradigms simultaneously in a large international sample of manufacturers of fabricated metal products, instruments and equipment.
Paradigms and performance
The study tested the extent to which manufacturing decisions based on each of the three perspectives had a meaningful relationship with performance improvements. The analyses were based on one given set of manufacturing respondents to control for the influence of context on the relative merits of each individual paradigm. We wanted to know whether building capabilities through external and internal learning; adopting best practices such as quality management (QM) and new product development (NPD); and keeping internal consistency among choices in areas such as process design, inventories and supervisory structures could explain improvements over three years in manufacturing quality, flexibility and delivery performance.
Building capabilities is significant. Capability building through external learning, such as that obtained from suppliers and customers, had a significant relationship with improvements in quality, flexibility and delivery. In addition, internal learning through employee training and involvement also was associated with quality and delivery outcomes. Current competitive standards suggest that advantages in these performance areas cannot be sustained by ad-hoc, casual improvements. Instead, systematic processes of learning from internal and external sources must be in place to attain superior performance in quality, flexibility and delivery.
Thus, even though passively “riding on the learning curve” still may be helpful in a few cases of process ramp-up, it most likely will fall short when competitive advantage relies on disruptive technologies and expanding the performance envelope. Identifying suitable methods of learning and development for each organization may be considered itself a dynamic capability of manufacturing management.
Adopting best practices is significant. Not surprisingly, adopting well-established QM practices such as quality control, total productive maintenance, and environmental sustainability related positively with improvements not only in quality, but also in flexibility and delivery. Quality practices may lead to such a level of skill and precision in business processes that even problems not readily associated with quality specifications, like customer-initiated changes in order mix or delivery dates, may be easier to respond to as management develops greater control and cognizance of the process.
Likewise, adopting superior NPD practices appeared to explain not only better quality but also improved delivery performance. Although in this study, at least, NPD did not seem related to flexibility changes. NPD standards that include product modularity, design for manufacturing, and CAD-CAM integration have well-known effects on product conformance and reliability. By considering process capabilities at earlier design stages, they also would help to reduce production lead times and secure on-time deliveries.
Of course, adopting best practices must be a thoughtful process that considers their match to existing capabilities, the operating strategy and the industrial context. For each success story, there will be one or more cases of implementation failure, often explained by mismatches between new practices and the internal and external environment. Many practices are context-dependent or not suitable for certain circumstances. For example, the lean practice of just-in-time production does not work well in nonrepetitive manufacturing. Other procedures need to be adapted. For instance, NPD practices aiming at removing most problems before volume production begins need to be toned down in companies working with a high rate of new product introduction and short product lifecycles. In these cases, fast prototyping and on-the-fly process debugging make more sense. This points out a second dynamic capability for industrial managers, namely the ability to scan the environment for best practices followed by judging, testing and adapting the practice to their own business environment.
Fit is a complex undertaking. The study tested specifications of internal rather than external fit. We found no significant associations between internal fit and quality or delivery improvements. Moreover, it appeared to relate negatively with flexibility improvements, as being constrained to “matching” alternatives might reduce the ability to deal with variety and uncertainty requirements.
Fit can be considered the most complex and elusive of the three decision-making paradigms. The idea of fit suggests matching among different internal and external variables. Internal fit considers the manufacturing process as a closed system where each new design choice must be in agreement with the existing configuration. For example, the decision on how much work-in-process to maintain should match the product mix and process integration. More product-oriented, continuous processes should be able to operate with relatively lower levels of semi-finished goods than more taskoriented, intermittent processes.
On the other hand, external fit views operations as an open system that exchanges with and is consistent with industry realities. From this perspective, work-in-process might be justified when customers demand customized goods but cannot wait too long for product delivery. In such circumstances, manufacturers may need to build inventories of standardized parts that can be personalized later based on postponement principles.
From a managerial perspective, both approaches can be accommodated as long as customer demands and technology do not send conflicting messages about the right choices in operations structure and infrastructure. For example, high variety manufacturers may find little compensation for building work-in-process when customers can wait longer for personalized orders, or technologies such as rapid manufacturing allow for highly customized goods to be turned over quickly. In such circumstances, work-in-process implies waste rather than competitive advantage, and even low-integrated manufacturing processes may be under pressure to reduce volumes in the pipeline.
We cannot assert whether this study’s nonsignificant findings on internal fit and performance could be explained directly by environmentally constrained options for internal systems design. However, a 2005 study published by the first author in the Journal of Operations Management did find a significant relationship between an internal-external fit measure and market share in another sample drawn a few years earlier from the same population (international manufacturers of fabricated metal products, instruments and equipment) as the current study. Taken together, the two studies suggest that matching internal design with the competitive environment may be a way to win customers. But focusing only on the internal matching of structure and infrastructure may not always translate into sustainable competitive advantage. In some cases it might lead to performance losses.
Implications for manufacturing strategy
So what does this all mean for manufacturing companies? To start with, they should focus their efforts on developing manufacturing capabilities and adopting best practices, which are both at the core of producing performance. Concerning capabilities, plants should invest in programs geared toward learning from customers and suppliers, as these have been shown to impact many dimensions of performance simultaneously. Examples include collaboration in new product development, as well as collaborative planning, forecasting and replenishment. One promising emerging trend on the customer side is open sourcing, or engaging communities of end users in the design of new products. Overall, companies should look at their supply/demand network as an important source of learning. Internal learning achieved through a collaborative and empowered workforce also should have a positive impact, particularly on quality and delivery.
Concerning best practices, managers should continue to invest in QM and NPD programs. In particular, QM practices provide a solid foundation for implementing other best practices, as well as for improvements in a broad range of performance dimensions. Because QM is mature and widely disseminated, it has been difficult for some manufacturers to sustain motivation, enthusiasm and resources for these programs, especially when they compete with more recent and glamorous best practices. But the results show that manufacturers should resist the temptation of overlooking quality in favor of new, more fashionable practices. There are synergies between investments in best practices and capabilities. On the one hand, the impact of best practices is enhanced by sufficiently developed capabilities. Capabilities allow an organization to know why, how and when to execute a certain practice. A plant with poor capabilities may not have the necessary knowledge to recognize the value of and assimilate best practices. This is especially true in today’s business environment, where many of these practices are generated externally and usually proclaimed as one-fits-all solutions.
On the other hand, the use of best practices enhances the development of capabilities by contributing to further learning. For example, many studies have shown that the use of QM practices is an important driver of learning and knowledge creation. As an illustration, the use of statistical process control allows a manufacturer to improve its knowledge about processes, which in turn may lead to developing state-of-the-art proprietary processes and equipment. Likewise, having a formal problem-solving process in place leads to the building of cumulative experience and knowledge.
Fit must be pursued with care. Always trying to match an operations system’s variables to the internal environment might lead not to improved competitiveness but rather to limited innovation and crippled performance. Managers should evaluate alternate solutions, such as what technology to adopt and what customization options to incorporate in product design, based not only on the existing structure and infrastructure, but more broadly on the external environment, the current and future stock of capabilities, and the portfolio of best practices available for consideration.
Does this mean that fit should be ignored? We don’t think so, but it may need to be prioritized. That is, refraining from adopting best practices and developing capabilities for the sake of maintaining fit should be avoided. For example, high volume manufacturers should not take high finished goods inventory as a given (trade-off view) and ignore lean practices that can help reduce inventory levels at least to some extent, without hurting other performance dimensions.
However, serious misalignments should be avoided. A plant with severely incoherent choices will be fraught with problems that will require substantial managerial resources. This will make it difficult to reap the benefits from adopting best practices, such as trying to get benefits from using statistical process control in a line process that is inadequately matched to a low-volume/high-variety market. It also will make it difficult to develop competencies that depend on dynamic capabilities or assets that are absent from operations, such as trying to offshore production of low-cost components in the absence of reliable supply coordination systems in a high-volume/low-variety market.
Giovani J.C. da Silveira is an associate professor at the Haskayne School of Business, University of Calgary. He holds a bachelor’s degree in business administration and a master’s degree in industrial engineering from the Federal University of Rio Grande do Sul in Brazil, as well as a doctoral degree in industrial and business studies (operations management) from Warwick Business School. His studies on manufacturing strategy, mass customization and supply chain management have been widely published in prominent journals.
Rui S. Sousa is an associate professor at the Catholic University of Portugal and a board member of the European Operations Management Association. He holds a doctoral degree in operations management from London Business School, a master’s degree in management science from Lancaster University and a licentiate in electrical and computer engineering from the University of Porto (Portugal). Sousa has published in leading international journals and consulted with a number of manufacturing and service companies. His present research and consulting interests include multichannel services, quality management and manufacturing strategy.