STREAM: Stability-based Realization of Economic Performance and Management

Abstract

A business that makes nothing but money is a poor kind of business. Henry Ford 7.1 Necessity for STREAM The problem of uncertainty is one of the key problems in SCM. In the literature, a set of methods and models to decrease the negative consequences of the influence of uncertainty on SCs is described. At a conceptual level, a set of works on risk management exists, directed, mainly, to the strategic level of decision-making. At the strategic level, increasing the SC stability becomes more and more important. At the tactical level of decision making, there is a large variety of developments on decreasing the influence of fluctuations of demand and mistakes in forecasts of demand (bullwhip effect), optimal inventory control, coordination of SCs, formation of a set of not final decisions (for example, the postponed differentiation) or methods of rolling planning. At the operative level, various methods and models of scheduling and systems of SCMo and regulation in the case of the occurrence of deviations from the plan are presented. For the tactical and operational levels of decision making, in the literature , a number of techniques for the analysis of stability, flexibility and reliability of deliveries are presented. Although there is a wealth of literature on planning economically optimal SCs, mitigating uncertainty in SCs, and event management in SCs, some crucial limitations with regard to the main focus of our research should be named. These are: • the issues of SC economic performance and stability are not explicitly considered as a whole; • the conceptual frameworks of SCM under uncertainty are mostly strategic and hardly supported by consistent engineering quantitative models and methods to ensure SC stability at the tactical and operations levels; • lack of explicit integrated frameworks for SC analysis (monitoring and diagnosis) and decision making for SC performance recovery; • the issues in SC planning and execution are mostly considered in isolation without explicitly linking scenario-driven and event-driven management; and • the domination of qualitative methods in risk management while underestimating quantitative analysis techniques (sensitivity, stability, etc.) can be observed.