A Multistage Decision Model for Salesforce Management

Abstract

Salesforce decisions consist of a series of interrelated processes including (1) determining the role of personal selling in the organization, (2) allocating selling effort to customers, geographic areas, or products, (3) setting salesforce size, (4) designing sales territories, and (5) managing the salesforce. Efforts to develop quantitative models for these decision areas have been hindered by the complex interactions among the areas. Attempts to isolate these decision areas for model simplification have resulted in considerable suboptimization. A multistage decision model is presented which treats the salesforce decision areas as an aggregate decision process consisting of a series of interrelated stages. Model decisions are based on a response function which relates sales in a control unit to the many determinants of performance including potential, workload, company effort, salesman quality and experience, and prior sales history. The use of an extremely fast dynamic programming algorithm for the allocation of selling time to control units is demonstrated and the interaction between model and manager is emphasized. Model output indicates the optimum salesforce size and provides a basis for designing sales territories. Use of the model in forecasting and performance evaluation also is discussed. The model is general in that it can be applied to most companies employing a field salesforce. The results of a promising application are presented. Reaction of sales management in the test firm indicates that model output is very useful in identifying problem areas, evaluating salesmen, and modifying territorial design to achieve the optimal allocation of selling effort.