A specialty steel bar company uses analytics to determine available-to-promise dates

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.