In Chap. 2, we argue that supply chain configuration is one of the principal supply chain management decisions and that it has a profound impact on other subsequent managerial decisions. As described therein, the supply chain configuration problem is a complex problem, which is composed of several sub-problems. It is also emphasized that the solutions to these problems require design, modeling, and problem-solving techniques based on knowledge from various fields such as systems science, systems engineering, operations research, industrial engineering, decision sciences, management science, statistics, information sciences, computer science, and artificial intelligence. Some of the prominent techniques utilized from these fields are information modeling, process modeling, simulation modeling, data mining, and optimization. We build on this proposition by adopting a key problem of information integration in the supply chain, which has an embedded structure representing various sub-problems, and how its management relates many of the concepts espoused in this book about supply chain configuration. Also, this problem serves as a prime example of how crosscutting approaches drawn from various disciplines highlighted above may be adopted in devising solutions for the complex supply chain configuration problem. Before we proceed further, let us first develop a clear understanding of the information integration problem in the supply chain.
CITATION STYLE
Chandra, C., & Grabis, J. (2016). Knowledge Management as the Basis of Crosscutting Problem-Solving Approaches. In Supply Chain Configuration (pp. 111–136). Springer New York. https://doi.org/10.1007/978-1-4939-3557-4_6
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