Reducing Product Expiration by Aligning Salesforce Incentives: A Data-driven Approach

摘要

Product expirations at retail stores erode profits and burden the environment. We investigate whether manufacturers can leverage salesforce compensation design as a waste-reduction tool. We propose a data-driven framework that uses structural econometric modeling and agency theory. Our analysis starts with a game theoretic model in which a salesperson interacts with a manufacturer that reimburses retailers and penalizes its own salesforce for expired products. We then use our model's equilibrium outcome to estimate factors that determine the effort exerted by the sales representatives of a consumer-packaged-goods manufacturer. We first show theoretically that a manufacturer can simultaneously increase profits and reduce waste by increasing its sales representatives' penalty for product expiration that occurs at the retailer. Based on this, we formulate a manufacturer's profit maximization problem to compute optimum expiration penalties. Solving this problem for the manufacturer, we find the potential to simultaneously reduce waste and improve profits for 14% of the product-market combinations in our dataset. For these cases, we find that charging the salesperson 2.1 times the commission (on average) for each expired unit can increase the manufacturer's profits by 0.58% and reduce waste by 23.3%. This study determines that a profit-seeking manufacturer can reduce waste at retailers by optimizing its salesforce incentive structure. Our work bridges the salesforce compensation and sustainable operations literatures. Furthermore, our framework allows consumer-packaged-goods manufacturers to identify win-win opportunities for the environment and their bottom line.