(301l) Assessment of Traditional Key Performance Indicators for Supply Chain Management in the Batch Chemical Industry

The tight profit margins under which the chemical process industries (CPI) operate are forcing companies to pay more and more attention to the design and operation of their Supply Chains (SC). Recent advances in Process Systems Engineering have focused on devising enterprise wide modeling and optimization strategies integrating decisions of distinct functions of a business into a global model. Nevertheless, despite the effort made in the area, almost all of the models developed to date focus on the process operations side and neglect the financial part of the problem. Furthermore, although such models should improve an overall business performance measure they usually pursue a myopic key performance indicator as the objective to be optimized. Specifically, diverse objectives have been proposed in the literature; being most of them mainly based on the classical transactional analysis of cost and benefits, or in key operative parameters that act as intermediate cost-related performance measures. The main aim of this work is to analyze the consequences of implementing different key performance indicators in SCM and study the trade-off between the most relevant objective functions proposed and value creation measures. A suitable key performance indicator should lead to plans that increase value, which constitutes a powerful driver for business activity. This way, shareholder wealth is maximized which is recognized as the goal of a firm. To carry out the comparison, a joint design/planning and financial model, which includes process operations as well as financial constraints, is extended to incorporate multiple objectives. The model is then mathematically posed as a multi-objective Mixed-Integer-Linear-Programming (MILP) problem and solved by applying standard multi-objective mathematical techniques. To illustrate the performance of the different indicators, a case study of a supply chain network comprising several plants, warehouses and retailers is solved. The results obtained suggest that a financial key performance indicator accounting for value creation and an integrated model are crucial for making most valuable supply chain decisions. Moreover, it is demonstrated that traditional planning/scheduling models accounting for the maximization of traditional key performance indicators simply do not posses the formulation needed to validate decisions through wealth maximization, leading to overall firm's suboptimal decisions.