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, Ramesh Sharda

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations

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.

Original languageEnglish
Pages (from-to)503-517
Number of pages15
JournalInterfaces
Volume43
Issue number6
DOIs
StatePublished - Nov 2013

Keywords

  • Available-to-promise
  • Optimization-based decision support
  • Prescriptive analytics

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