We develop the first structural model of a multitasking salesforce to address questions of job design and incentive compensation design. The model incorporates three novel features: (i) multitasking effort choice given a multidimensional incentive plan; (ii) salesperson’s private information about customers and (iii) dynamic intertemporal tradeoffs in effort choice across the tasks. The empirical application uses data from a micro nance bank where loan officers are jointly responsible and incentivized for both loan acquisition repayment but has broad relevance for salesforce management in CRM settings involving customer acquisition and retention. We extend two-step estimation methods used for unidimensional compensation plans for the multitasking model with private information and intertemporal incentives by combining flexible machine learning (random forest) for the inference of private information and the first-stage multitasking policy function estimation. Estimates reveal two latent segments of salespeople-a “hunter” segment that is more efficient in loan acquisition and a “farmer” segment that is more efficient in loan collection. We use counterfactuals to assess how (1) multi-tasking versus specialization in job design; (ii) performance combination across tasks (multiplicative versus additive); and (iii) job transfers that impact private information impact firm profits and specific segment behaviors.
At many firms, incentivized salespeople with private information about customers are responsible for CRM. While incentives motivate sales performance, private information can induce moral hazard by salespeople to gain compensation at the expense of the firm. We investigate the sales performance–moral hazard tradeoff in response to multidimensional performance (acquisition and maintenance) incentives in the presence of private information. Using unique panel data on customer loan acquisition and repayments linked to salespeople from a microfinance bank, we detect evidence of salesperson private information. Acquisition incentives induce salesperson moral hazard leading to adverse customer selection, but maintenance incentives moderate it as salespeople recognize the negative effects of acquiring low-quality customers on future payoffs. Critically, without the moderating effect of maintenance incentives, adverse selection effect of acquisition incentives overwhelms the sales enhancing effects, clarifying the importance of multidimensional incentives for CRM. Reducing private information (through job transfers) hurts customer maintenance, but has greater impact on productivity by moderating adverse selection at acquisition. The paper also contributes to the recent literature on detecting and disentangling customer adverse selection and customer moral hazard (defaults) with a new identification strategy that exploits the time-varying effects of salesperson incentives.
In many firms, incentivized salespeople with private information about their customers are responsible for customer relationship management (CRM). Private information can help the firm by increasing sales efficiency, but it can also hurt the firm if salespeople use it to maximize own compensation at the expense of the firm. Specifically, we consider two negative outcomes due to private information — ex-ante customer adverse selection at the time of acquisition and ex-post customer moral hazard after acquisition. This paper investigates potential positive and negative responses of a salesforce to managerial levers — multidimensional incentives for acquisition and retention performance and job transfers that affect the level of private information.
Salespeople are responsible for managing customer relationships and compensated through multidimensional performance incentives for customer acquisition and maintenance at many firms. This paper investigates how a salesperson’s private information on customers affect their response to multiple dimensions of incentives. Using unique matched panel data that links individual salesperson performance metrics with customer level loans and repayments from a microfinance bank, we find that sales people indeed possess private information that is not available to the firm. Salespeople use the private information to engage in adverse selection of customers in response to acquisition incentives. Customer maintenance incentives serve a dual purpose; they not only reduce loan defaults, but also moderate adverse selection in customer acquisition. Transfers that eliminate private information reduces the adverse selection effects of acquisition incentives, but increase loan defaults — customer moral hazard. Despite the potential negative adverse selection effects due to private information, the effort increasing effect of each of the three dimensions of sales management we investigate — acquisition incentive, maintenance incentive and transfers all have a net positive effect on firm value. Methodologically, the paper introduces an identification strategy to separate customer adverse selection and customer moral hazard (loan repayment), by leveraging the multidimensional incentives of an intermediary (salesperson) responsible for both customer selection and repayment with private information about customers.