Optimization of Business Transactional Processes in a Digital Supply Chain

Abstract

A new continuous time multistage scheduling Mixed-Integer Linear Programming (MILP) model is proposed to optimize the business transactional processes in supply chains. The novelty of this approach is in using techniques from the Process Systems Engineering (PSE) and Operations Research (OR) communities to address a side of supply chain optimization (information flow) that has not been targeted previously. This model accounts for the allocation of resources in processing orders at each of the stages of a business transactional process. The objective of the model is to improve customer experience, using on-time-delivery (OTD) as a surrogate metric for this target. An illustrative example, featuring a subset of the business transactional steps in the Order-to-Cash (OTC) process is presented, showing the potential of using mathematical programming to improve supply chain performance. The model enables identifying bottlenecks in the processes and determining where additional resources should be allocated. The model can also be used as a valuable tool to assist customer service representatives in establishing realistic promise-to-delivery dates for their clients.