Optimism vs. Pessimism: Design Decisions in the Face of Process Capability Uncertainty

Abstract

Product development firms continually struggle to simultaneously keep product cost low while increasing product quality. This paper focuses on variation and its impact on the quality-failure costs—scrap, rework, extra labor, customer dissatisfaction, and product returns. In many cases, reducing quality failures requires an increase in product cost. Balancing these two costs is challenging because perfect information about process variability is rarely, if ever, available. As a result of process variation uncertainty, there is no clear optimal solution to the quality-failure cost/unit cost tradeoff. The author has observed that companies take one of two approaches to this dilemma: optimistic or pessimistic. The optimistic approach risks high rework costs to ensure the lowest cost product. On the other hand, the pessimistic approach forgoes potential unit cost reductions to avoid any quality failure. This paper presents a utility theory model of decision making under process capability uncertainty. This model is used to describe why either approach can be optimal depending on the organization, market, and product characteristics. In addition, information value theory is applied to explain the relative value of process capability information and variation reduction in the two approaches. The paper uses a frequently encountered design scenario to demonstrate the approach. In addition, a variety of other examples from industry are used to describe how the theory can be applied.