Evaluation of Customer Bad-Will in Service Business A study of Service Operations & Technology at Volvo Group

Abstract

This thesis examines how customer bad-will is represented in Volvo Group’s total cost model for spare parts planning. In the current model, bad-will is intended to capture the customer-related consequences of spare parts shortages and to influence service level decisions. However, the parameter has not been substantially revised for many years, and its current design is based mainly on static part-related attributes. This raises the question of whether the model reflects how customers actually experience service failures in today’s aftermarket context. The study was conducted as a qualitative case study at Volvo Group Service Operations & Technology. It combined a literature review, internal interviews and document analysis, and semi-structured interviews with dealer-facing actors in European markets. The purpose was to map how the current bad-will parameter is defined and used and to identify which factors are perceived to drive bad-will in practice. The findings show that Volvo’s current bad-will parameter primarily reflects spare part attributes such as criticality and life cycle phase, but underrepresents several important drivers of customer dissatisfaction. In particular, the results highlight the importance of time sensitivity, ETA (Estimated Time of Arrival) transparency, communication quality, market conditions, and internal escalation capability to handle shortages effectively and efficiently. The study further suggests that these drivers differ in how suitable they are for inclusion in the model. Some factors, such as more granular criticality and lead-time-related proxies, appear implementable as model refinements. Others are strategically relevant for service prioritization but do not represent customer bad-will in a strict sense. A third group, including ETA quality and communication during shortage situations, is better understood as organizational and process-related capabilities than as stable model parameters. The thesis concludes that the gap between the current bad-will parameter and customer reality cannot be closed through parameter refinement alone. Improving the representation of bad-will in the total cost model may increase decision quality, but some of the most important opportunities to reduce bad-will lie in process improvements outside the model.