Customer selection and incentivization for SKU rationalization in a packaged gas supply chain

This paper presents customer selection and incentivization methodologies necessary for the implementation of many SKU rationalization schemes. Our work accounts for the problem of business demand loss, which is undesirably associated with the benefits of rationalized product offerings. We apply our methodologies to a particularly complex instance of SKU rationalization established in the literature, namely a case of demand substitution within a packaged gas supply chain planning problem. This is done both to display the value of our contributions, and to provide a business setting for the workflow process we prescribe for decision makers. In our first contribution, we develop a customer selection heuristic which pre-processes targets for demand substitution, subject to demand characteristics and the supply chain features. The heuristic is shown to outperform objectives utilizing random customer selection by 10–20%, dependent on the desired amount of substitution required of the demand-base. Further, we show that the heuristic outperforms an MILP extension, which explicitly includes customer selection as a decision in the underlying supply chain problem's model, by 7% across a variety of cases. Our second contribution regards development of prescriptive incentivization methodologies for a business, in order to secure shifts in demand profiles across the selected customers. We present multiple strategies for both determining offerings and analyzing system implications, while recognizing stochastic and diverse customer behaviors. In addition to providing useful methodologies around SKU rationalization, trade-offs and business implications throughout the execution of such ideas in practice are heavily considered throughout this work.