Reliable estimation of suppliers' total cost of ownership: An imprecise data envelopment analysis model with common weights. (September 2019) - Shabani, Amir; Visani, Franco; Barbieri, Paolo; Dullaert, Wout; Vigo, Daniele
Highlights: We address supplier's total cost of ownership (TCO), a key concept for sourcing decisions in wide variety applications but which is known to be difficult to apply. We propose an easily accessible proxy for TCO, which reliably and parsimoniously estimates traditional TCO outcomes based on a novel Common Set of Weight Imprecise Data Envelopment Analysis (CSW-IDEA) model. We are the first to extend the applicability of TCO to the realm of imprecise data to deal with ambiguous cost drivers, conflicting data sources and subjective evaluations commonly occurring in practice, yet largely overlooked in the literature. We validate the applicability of the proposed TCO proxy on large datasets from two worldwide leading mechanical manufacturers used for TCO evaluation of 175 suppliers. Abstract: Total cost of ownership (TCO) is a management accounting technique that evaluates the total cost of a business partnership using a time-consuming activity-based costing procedure. Studies have suggested that TCO-based data envelopment analysis (DEA) can effectively estimate the results of TCO with substantially less effort and time; however, its adoption in practice is limited due to certain shortcomings. First, managers struggle to understand and accept the uncommon weighting schemes of existing TCO-based DEA models because traditional TCO analyses require a common set of weights. Second, both the traditional TCO approach and TCO-based DEA models are designed to handle precise data, whereas TCO analyses often involve imprecise data from conflicting data sources and estimations. To address the managerial and technical issues of handling weighting schemes and imprecise data, this paper proposes a novel TCO-based model: common set of weights imprecise DEA (CSW-IDEA). We validate the proposed methodology using real-life datasets from 175 suppliers that serve five key components to two multinational mechanical manufacturers. For both precise data and imprecise data, the proposed CSW-IDEA reliably approximates traditional TCO calculations significantly better than existing TCO-based DEA. The cost savings that can be theoretically generated by applying the CSW-IDEA approach are similar to the cost savings estimated by the traditional TCO approach.