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Product-Generation Transition Decision Making for Bayer's Hemophilia Drugs: Global Capacity Expansion Under Uncertainty with Supply-Demand Imbalances

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  • Jeffrey S. Stonebraker

    (Department of Business Management, Poole College of Management, North Carolina State University, Raleigh, North Carolina 27695)

Abstract

We present an application of decision analysis to global production capacity expansion under uncertainty for Bayer Group's proposed new biotechnology drug to treat hemophilia A. This decision analysis developed an improved approach to Bayer's decision for product-generation transition and global production capacity expansion that more realistically addresses potential regional supply shortages and overages due to demand and supply uncertainties that can result in supply-demand imbalances. With the added confidence provided by this more realistic approach, Bayer's executive leadership team acted on the recommendation from the decision analysis in contrast to an earlier analysis that had not resulted in management action. The paper makes two major contributions: First, it describes the details of what is involved in conducting applied decision analysis in a real-world setting in more detail than what is typically in textbooks on decision analysis. Second, the paper illustrates the important role of economic modeling in a large-scale applied decision analysis. The approach is applicable to other product-generation transition decision making for expanding global production capacity under uncertainty in a supply-constrained environment, especially for new product introductions and new product development decisions when supply is limited.

Suggested Citation

  • Jeffrey S. Stonebraker, 2013. "Product-Generation Transition Decision Making for Bayer's Hemophilia Drugs: Global Capacity Expansion Under Uncertainty with Supply-Demand Imbalances," Operations Research, INFORMS, vol. 61(5), pages 1119-1133, October.
    • Handle: RePEc:inm:oropre:v:61:y:2013:i:5:p:1119-1133
    DOI: 10.1287/opre.2013.1204
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    Cited by:

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    2. Yi Song & Bin Hu & Zhihan Lv, 2018. "A computational analysis of capital chain rupture in e-commerce enterprise," Electronic Commerce Research, Springer, vol. 18(2), pages 257-276, June.
    3. Tinglong Dai & Sridhar Tayur, 2020. "OM Forum—Healthcare Operations Management: A Snapshot of Emerging Research," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 869-887, September.

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