After-Sales Service Contracting: Condition Monitoring and Data Ownership

Abstract

Problem definition: Condition monitoring (CM) of durable assets, whereby sensors continuously monitor the health of an asset, is heralded as a key application of the Internet of Things. However, questions about ownership of the sensor data are seen as a key barrier to adoption. We model an after-sales supply chain in which the asset manufacturer provides maintenance and repair services to a customer that operates the asset. The asset condition deteriorates in a stochastic fashion and will eventually fail if not repaired. Methodology/results: We analyze a performance-based contracting problem considering manufacturer maintenance effort (the condition at which preventive maintenance is performed) and customer operating effort (which reduces the rate of condition deterioration). With information asymmetry on the customer’s effort cost, we analyze this contracting problem in a principal-agent model with double moral hazard. In the centralized setting, we establish that the benefit of CM increases and then decreases in the asset’s deterioration rate and that CM may increase or decrease the benefit of customer effort depending on the deterioration rate. In the decentralized setting, we prove that CM always benefits the manufacturer and the supply chain, but it may hurt the customer if the asset reliability is sufficiently high. Managerial implications: These results have important implications for the effect of sensor-data ownership. The manufacturer will adopt CM if it owns the data, but the customer may block CM adoption if it owns the data. We show that this CM adoption barrier can be overcome by the manufacturer offering to pay an appropriate data access fee. However, under this arrangement, the manufacturer may not benefit from a more-effective customer operating effort. We discuss the resulting implication on the manufacturer’s product design and the business model between selling and leasing.