Johannes Kunze von Bischhoffshausen, Markus Paatsch, Melanie Reuter-Oppermann, G. Satzger, H. Fromm
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An Information System for Sales Team Assignments Utilizing Predictive and Prescriptive Analytics
Many companies have transformed their businesses from selling products in isolated transactions to selling solutions in long-term relationships. This transformation poses new requirements for designing the sales force structure: solution selling companies often approach the customer with sales teams, composed of different sales roles with specific responsibilities and skills. However, little attention is given to this challenge in sales force analytics, especially from an information systems research perspective. In particular, there is still a lack of decision support with regard to assigning sales reps to customer accounts in a solution selling setting. This work addresses this research gap by proposing an information system for planning sales force assignments utilizing predictive and prescriptive analytics. The information system integrates a predictive component which applies mining of historical sales data in order to predict the sales impact for any particular assignment of sales teams to customer accounts. Furthermore, the information system integrates a prescriptive component which utilizes a linear programming model to compute the optimal assignment that maximizes revenue. This work presents the prototypical implementation of this approach and, thus, develops an artifact that integrates predictive and prescriptive analytics into an information system. The derived solution offers a promising approach for increasing the sales effectiveness of solution selling firms.