An expert system to derive carryover effect for pharmaceutical sales detailing optimization

摘要

Most pharmaceutical companies that rely heavily on their sales force for success do not fully understand the effect of details made in previous quarters have on the current quarter, which is also known as the carryover effect. This paper proposes an expert system that utilizes neural networks with nonlinear programming to accurately derive the carryover effect at the customer level. Results suggest that using this adaptive and easy-to-implement expert system helped a firm increase its sales by 3.4% while reducing its sales force expenditure by 8.9%, compared to the control group. The implications of this approach are considered.