Knowledge that Transforms

This paper presents a variant of the popular beer game. We call the new game the stationary beer game, which models the material and information flows in a production‐distribution channel serving a stationary market where the customer demands in different periods are independent and identically distributed. Different players, who all know the demand distribution, manage the different stages of the channel. Summarizing the initial experience with the stationary beer game, the paper provides compelling reasons why this game is an effective teaching tool.

This paper is concerned with the problem of order picking in mail order companies. Order picking is the retrieval of items from their warehouse storage locations to satisfy customer orders. Five order picking policies, strict order, batch, sequential zone, batch zone, and wave, are evaluated using labor requirements, processing time, and customer service as performance measures. A simulation model was developed to investigate these picking policies in a mail order environment. Prior research has focused on the study of individual picking policies. This study extends the prior research by evaluating multiple picking policies under varying operating conditions. The results of the study seem to indicate that (1) wave picking and batch picking perform well across the range of operating conditions considered in this study, and (2) sequential zone and batch zone picking do not perform well, especially as the order volume increases. However, the benefits and drawbacks to each picking policy must be taken into account. The key to effective implementation of an order picking system is to match the firm's business strategy, capabilities, technology, and space requirements with an order picking policy that maximizes the benefits of order picking to the firm and its customers.

This research considers a multi‐item newsvendor problem with a single capacity constraint. While this problem has been addressed in the literature, the focus here is on developing simple, closed‐form expressions for the order quantities. The benefit of such an approach is that the solutions are straightforward to calculate and have managerial appeal. Additionally, we show these expressions to be optimal under a variety of conditions. For more general cases when these optimality conditions do not hold, we use these expressions as heuristic solutions. Via computational studies, we demonstrate that these heuristics are extremely effective when the optimality conditions are not satisfied.

Cyclicality is a well‐known and accepted fact of life in market‐driven economies. Less well known or understood, however, is the phenomenon of amplification as one looks “upstream” in the industrial supply chain. We examine the amplification phenomenon and its implications through the lens of one upstream industry that is notorious for the intensity of the business cycles it faces: the machine tool industry. Amplification of demand volatility in capital equipment supply chains, e. g., machine tools, is particularly large relative to that seen in distribution and component parts supply chains. We present a system dynamics simulation model to capture demand volatility amplification in capital supply chains. We explore the lead‐time, inventory, production, productivity, and staffing implications of these dynamic forces. Several results stand out. First, volatility hurts productivity and lowers average worker experience. Second, even though machine tool builders can do little to reduce the volatility in their order streams through choice of forecast rule, a smoother forecasting policy will lead companies to retain more of their skilled work force. This retention of skilled employees is often cited as one of the advantages that European and Japanese companies have had relative to their U. S. competitors. Our results suggest some insights for supply chain design and management: downstream customers can do a great deal to reduce the volatility for upstream suppliers through their choice of order forecast rule. In particular, companies that use smoother forecasting policies tend to impose less of their own volatility upon their supply base and may consequently enjoy system‐wide cost reduction.

Testing and cross‐validation of theories and paradigms are necessary to advance the field of manufacturing strategy. When the findings of one study are also obtained in other studies, using entirely different databases, we become more confident in the results. Replication alleviates concerns about spurious results and is one motivation for this study. We examine aspects of the tradeoffs concept, production competence paradigm, and a manufacturing strategy taxonomy framework. In regard to the tradeoffs concept, we found evidence of tradeoffs between some, but certainly not all, manufacturing capabilities of quality, cost, delivery, and customization. The relationships get sharper when controlling for process choice. For example, the tradeoff between cost and customization is particularly strong between plants that have different process choices. We find that such tradeoffs can change, or even disappear, however, once the process choice is in place. With respect to the production competence paradigm, our analysis shows a statistically significant correlation between production competence and operations performance in batch shops, but not in plants with other process choices. Finally, using variables similar to those of Miller and Roth, our data produced three similar clusters even though their unit of analysis was much more macro than ours. Controlling for process choice is consistent with the current manufacturing strategy literature that emphasizes dynamic development of capabilities within the context of path dependencies. A major argument of this strand of research is that operations decisions not only affect current capabilities, but also set the framework for development of capabilities in the future. That being the case, controlling for process choice (or other factors such as industry or markets) should contribute to the understanding of capability‐development paths adopted by different manufacturing plants. In short, we found at least partial support for each of the theories examined here, even though the theories seem on the surface to be contradictory and mutually exclusive. Controlling for process choice or other measures of dependency goes a long way in uncovering consistency across different theories and empirical studies in operations management.

For decades, the Beer Game has taught complex principles of supply chain management in a finished good inventory supply chain. However, services typically cannot hold inventory and can only manage backlogs through capacity adjustments. We propose a simulation game designed to teach service‐oriented supply chain management principles and to test whether managers use them effectively. For example, using a sample of typical student results, we determine that student managers can effectively use end‐user demand information to reduce backlog and capacity adjustment costs. The game can also demonstrate the impact of demand variability and reduced capacity adjustment time and lead times.

Flowshop scheduling problems with setup times arise naturally in many practical situations. This paper provides a review of static and deterministic flowshop scheduling research involving machine setup times. The literature is classified into four broad categories, namely sequence independent job setup times, sequence dependent job setup times, sequence independent family setup times, and sequence dependent family setup times. Using the suggested classification scheme, this paper organizes the flowshop scheduling literature involving setup and/or removal times and summarizes the existing research for different flowshop problem types. This review reveals that, while a considerable body of literature on this subject has been created, there still exist several potential areas worthy of further research.

Research in the area of operations strategy has made significant progress during the past decade in terms of quantity of articles published, as well as the quality of these articles. Recent studies have examined the published literature base and determined that, in general, the field has progressed beyond an exploratory stage to a point where there is a core set of basic terminology and models. Concurrent with the formation and solidification of a core terminology, there is an increasing emphasis on developing and employing a set of reliable, valid, and reproducible methods for conducting research on operations strategy. We provide a review of common methods for assessing the degree of reliability and agreement of the responses provided by multiple raters within a given organization to a set of qualitative questions. In particular, we examine four methods of determining whether there is evidence of disagreement or bias between multiple raters within a single organization in a mail survey.

This paper discusses a framework for strategic supply chain design that rests on an assortment of conceptual approaches. These approaches include benchmarking fast‐evolving industries to posit principles of supply chain dynamics and integrating supply chain design into the concurrent processes of product and manufacturing system design. These approaches yield insights into sourcing strategy as well as implementation of concurrent engineering.