A prototype decision support system for strategic planning under uncertainty

Abstract

Strategic planning of the supply chain is an important decision problem determining the long‐term survival and prosperity of companies in the manufacturing, retail, and other industrial sectors. In general such companies rely on their information systems to acquire the essential data that are used in their planning models. The interaction of information systems and decision modelling, and the progressive transformation of data, into information, and knowledge is a key process underlying any decision support system (DSS) for strategic, tactical or operational planning. In this paper we consider a DSS for supply chain planning (SCP) decisions. The SCP system has an embedded decision engine that uses a two‐stage stochastic program as a paradigm for optimisation under uncertainty. The system has been used for decision making in diverse domains, including automotive manufacturing and consumer products.