Make-to-order: Supply chain structure and inventory strategies

Make-to-order (MTO) business models have gained popularity in recent years due to the trend of mass customization and the growth of information and manufacturing technologies. This dissertation studies the supply chain structure and the corresponding inventory strategies of make-to-order businesses. We first present a unifying framework for make-to-stock (MTS) and MTO based on a push-pull or MTS-MTO supply chain and introduce an approach for identifying appropriate supply chain strategies.; Delayed product differentiation (DPD) or postponement is a viable mechanism for achieving make-to-order. However, industry practices and literature show that we lack a comprehensive approach to evaluate the benefits of postponement initiatives. We develop a framework for identifying the value of postponement in a supply chain and discuss the approach and models to quantify the value. These methods have been applied to the Electronic Control Units (ECU) flash programming project at General Motors (GM) and the results obtained have provided inputs to several strategic decisions at GM.; Based on the identified and quantified value of postponement, we develop a model for optimizing supply chain structure under delayed product differentiation. For a firm that offers products with multiple customization components, we determine whether the suppliers or the manufacturer should perform the customization tasks given the manufacturer has a customization capacity constraint. The basic model has been applied to optimize the ECU in-plant flash programming at GM and developed into an Internet-based decision support system, which is currently in use at GM.; After the appropriate supply chain structure is determined, we investigate the optimal inventory strategies at the MTS-MTO boundary. We develop an inventory model capturing essential characteristics of make-to-order businesses. A demand prioritization rule and weighted critical fractile solutions are shown to be optimal for generalized make-to-order systems. We drive bounds and suggest a search process to solve the weighted critical fractile equations and obtain the optimal order quantity. Structural properties and managerial insights shed light on the strategic advantages of make-to-order.