‪Three Essays on the Value of Responsiveness for a Manufacturer‬

This thesis studies the value of responsive manufacturing. Responsiveness is the capacity to effectively match supply to demand. I study how and when responsiveness can increase competitiveness. My work contributes to the understanding of when responsiveness can justify the higher cost of local production as compared to low-cost offshore production. The thesis consists of three self-contained papers. The first, investigates an approach called the Volatility Portfolio and Option-based Costing. This approach suggests that by using a balanced portfolio of products with different time-sensitivity characteristics, a firm can achieve a good balance of speed and efficiency. The volatility portfolio leads to higher profitability of local production. We apply the approach in four cases, in differing supply chain environments, and observe
how the solution is developed from theory to practice. Our cases validate the approach and show the volatility portfolio is particularly potent, when the marginal value of time is high and capacity is inflexible. The second paper explores the benefits to innovation and learning made by implementing the volatility portfolio. Based on empirical observations, we describe causal mechanisms that link manufacturing responsiveness to innovation. We use System Dynamics modeling with previous literature on innovation processes to quantify a model of these causal mechanisms. Using simulation, we observe how the learning mechanisms, when activated, increase the value of responsiveness for a manufacturer. The profit optimizing investment in responsiveness is increased, when the innovation dynamics are accounted for. The third paper studies the value of lead time reduction. We extend the available models with a non-constant residual value modeling. We show that the commonly used constant residual value assumption is not valid in numerous practical situations, and that this assumption leads to systematic underestimation of the value of lead time reduction. Based on our empirical data, we provide practical models to implement lead time valuation with variable residual value.