71 research outputs found

    Manufacturing Flexibility and Performance: Bridging the Gap between Theory and Practice

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    How firms scan and interpret their environments has implications for the flexibility strategy that they choose, as well as for the performance of that strategy. We extend Daft and Weick's (Acad Manage Rev 9(2):284-295, 1984) model of firms as interpretation systems into a theoretical model of flexibility performance through extended iterations between observations of a failed flexibility initiative and relevant literature. We test the model using well-known teaching cases. We argue that the use of an iterative process that involves cases and theory both stimulates creativity in integrating theory and lays an initial foundation for evidence-based practice

    Economies of Extremes: Lessons from Venture-Capital Decision Making

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    An organization's ability to exploit extreme events such as exceptional opportunities depends on its capacity strategy. The venture capital industry illustrates the interplay of expensive capacity and negative externalities from high utilization. The cost of adding a venture capitalist provides a strong incentive to run lean, but such leanness may make it impossible to evaluate all interesting investment opportunities. Using concepts from extreme-value theory, we analyze the trade-off between the costs and benefits arising from an increase in the number of evaluated deals. We ground our analysis in 11 years of archival data from a venture capital firm, representing 3631 deals, the decisions made, the reasons for those decisions, and the decision lead times. The firm identified 20% of arriving deals as worth evaluating during the screening process, but was not able to evaluate approximately 9% of those interesting deals due to a lack of capacity. We show that the value of increasing the number of deals evaluated increases with the tail weight of the distribution of deal values. When the right tail is light, increasing the number of deals evaluated may provide too modest a benefit to justify the cost. When, however, the right tail is heavy, the value of increasing the number of deals is likely to more than compensate for the cost of capacity. Our results provide new insight into the relative value of a chase capacity strategy that emphasizes responsiveness versus a high-utilization heuristic that emphasizes productivity. Our approach can be applied to other search operations such as personnel selection, quality circles seeking to identify root causes, and making employee capacity available for innovation

    Constant Salvage Value Models: A Source of Systematic Bias in Predicting the Value of Lead-Time Reduction

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    The assumption that unsold goods can be liquidated at a constant salvage value is widespread in inventory theory. We show that, under general mathematical conditions, this modeling assumption will cause companies to underestimate both the value of lead-time reduction and the cost of lead time increases. Our result does not require that companies actively consider the possibility of non-constant salvage values. Rather we show that, in an environment where salvage values are allowed to depend on the amount of overage, a firm that cuts lead times according to a strategy that assumes a constant salvage value will earn more money than predicted from its lead-time reduction

    How to Fail at Flexibility

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    Flexibility plays a key role both in supply chain management and in manufacturing strategy. Increasing flexibility, however, tends to be difficult for many organizations, and all too often ends in failure. In this paper, we take a humorous approach to summarizing managerially-relevant findings from the academic literature on flexibility

    Losing the Fight with Flexibility: the Xygma Plant

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    One area where supply chains constantly get into trouble is that of flexibility: when is it correct to respond to customer requests for increased flexibility, and when is it wise to refuse in the name of process consistency? This issue's case will probably feel very familiar to most readers, as it describes a situation that is all too common

    It May Be Cheaper to Manufacture at Home

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    Conventional financial tools can lead to supply chain mistakes. Most managers use the discounted cash flow (DCF) model to help them make decisions such as where to locate a new manufacturing plant or whether to use a foreign or domestic supplier. But DCF typically undervalues flexibility and as a result, companies may end up with supply chains that are low cost as long as everything proceeds according to plan but extremely expensive if problems arise. De Treville, of the University of Lausanne, and Trigeorgis, of the University of Cyprus, argue that you can avoid this pitfall by complementing a DCF analysis with a real options valuation. This technique lets you put a dollar figure on flexibility in the supply chain and helps you assess the value of having direct control. The authors explain how a real options approach helped the Swiss company Flexcell decide whether to Locate a new plant at home or abroad. The CEO was able to show his board that the flexibility afforded by a factory near company headquarters would more than make up for the 15% per unit cost savings that would have been realized at a factory elsewhere. He also demonstrated that the costs resulting from a disruption to a Swiss plant would be much lower than those resulting from a disruption to a foreign plant. The decision to manufacture at home has paid off handsomely, especially in view of the uncertainties created by the current economic crisis

    Equipping Students to Reduce Lead Times: The Role of Queuing-Theory-Based Modeling

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    Time is power. A company that gets products to its customers faster than its competitors strengthens its market position; therefore management students should learn how to reduce lead times. The counterintuitive mathematical principles that drive lead time and the complex system dynamics of operations management make the skills of reducing lead times difficult to teach. Mathematical modeling (queuing-theory or simulation-based) is an effective tool for teaching these skills. In evaluating modeling approaches in the classroom, it is important to consider model quality and student affective outcomes, such as motivation and empowerment. Queuing-theory-based models increase students' abilities to reduce lead times more than simulation-based models. Using a classic teaching case, we compare the two approaches
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