A Specialty Steel Bar Company Uses Analytics to Determine Available-to-Promise Dates

Foad Mahdavi Pajouh (), Dahai Xing (), Yingjue Zhou (), Sharethram Hariharan (), Balabhaskar Balasundaram (), Tieming Liu () and Ramesh Sharda
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Foad Mahdavi Pajouh: Department of Industrial and Systems Engineering, University of Florida, Shalimar, Florida 32579
Dahai Xing: Operations Analysis, FedEx Corporate, Memphis, Tennessee 38120
Yingjue Zhou: School of Industrial Engineering and Management, Oklahoma State University, Stillwater, Oklahoma 74078
Sharethram Hariharan: Global Planning Business Intelligence, Dell Inc., Round Rock, Texas 78682
Balabhaskar Balasundaram: School of Industrial Engineering and Management, Oklahoma State University, Stillwater, Oklahoma 74078
Tieming Liu: School of Industrial Engineering and Management, Oklahoma State University, Stillwater, Oklahoma 74078

Interfaces, 2013, vol. 43, issue 6, 503-517

Abstract: In this paper, we describe an application of prescriptive analytics to enhance data-driven decision making at a specialty steel bar products supplier and manufacturer in North America. As part of the company’s daily business, it must make available-to-promise (ATP) decisions, which determine in real time the dates by which it can promise delivery of products that customers requested during the quotation stage. Previously, a salesperson had to make such decisions by analyzing reports on available inventory. To support these ATP decisions, we developed a real-time decision support system (DSS) to find an optimal assignment of the available inventory and to support additional what-if analysis. The DSS uses a suite of mixed-integer programming models and commercial software to solve the models. The company has incorporated the DSS into its enterprise resource planning system to seamlessly facilitate its use of business analytics.

Keywords: prescriptive analytics; optimization-based decision support; available-to-promise (search for similar items in EconPapers)
Date: 2013
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