Sales Environments Research Articles

Order point/order quantity models with random yield

We show how to incorporate yield randomness into the classical order point/order quantity inventory model, and discuss its implications. We address both binomial and stochastically proportional yields in both backordering and lost sales environments.

Compensating Heterogeneous Salesforces: Some Explicit Solutions

This paper considers the question of how a sales manager should design the optimal compensation scheme for his salesforce when it consists of salespersons of varying selling skills, i.e., when the salesforce is heterogeneous. The manager's problem is to reward the salespersons based on observable, uncertain sales achieved by the salespersons. Under the assumption that both the manager and the salespersons are risk neutral, the optimal compensation scheme is derived. It consists of the manager offering a menu of plans, consisting of a quota, a payment for meeting quota, and a constant commission rate for sales above or below quota. Such schemes using constant commission rates are also called menus of linear plans. Salespersons choose the quota which best suits them, achieve sales, and are then rewarded based on their actual performance. This scheme, variants of which are often observed in practice, is shown to be optimal for sales environments characterized by commonly encountered sales response functions, and a large class of frequency distributions of selling skills in the salesforce. The problem is solved using the methods of principal-agent models. The key differences in managing homogeneous and heterogeneous salesforces are highlighted. Finally, the paper discusses the issues involved in practically implementing the optimal compensation scheme.

Use of Multiple Discriminant Analysis to Improve the Salesman Selection Process

A recurring marketing decision is that of selecting new sales personnel. New salesmen, armed with vicarious experience obtained in costly training programs, are entrusted with one of the company's most valued assets-an income-producing territory. Their selection is approached with varying degrees of sophistication, often in ways that make the decision little more than a gamble. Five major tools aid in the selection process: interviews, application blanks, physical exams, references, and personnel tests. Clearly, the appropriateness of each of these tools is situational, but none is more consistently misused, maligned, and misinterpreted than personnel tests.' The purpose of this article is to offer managers an operational procedure for classifying sales applicants according to personnel test scores. The technique of multiple discriminant analysis is utilized to derive explicit probabilities of successful sales performance for each sales applicant. Personnel test scores from specialized sales divisions of two companies listed in Fortune's top 100 industrial firms are used to illustrate the efficacy of the technique. While both firms employed personnel tests in their salesman selection decisions, neither possessed much evidence (or even confidence) that the tests were valid indicators of sales performance. In such situations multiple discriminant analysis offers two benefits. First, it presents an illuminating mathematical relationship between test scores and sales performance. Second, it permits individual variation in the patterns of test scores which predict sales success, rather than requiring conformity to a single average. Such an average may not represent any single real person or may impose an unnecessary cultural or other stereotype. The worth of any selection tool lies primarily in its predictive validity -the degree to which its results can be used to gauge future performance. In using tests, the sales manager may be tempted to choose those which have been successfully used in similar sales environments. This course of action is both appealing and hazardous. Predictive validity is not transferable between firms or jobs, and even if the sales manager is willing to assume it is, the federal government is not. Personnel tests are acceptable to the Federal Equal Employment Opportunity Commission (EEOC) as part of