Knowledge-based approach to improving detailing plan in multiple product situations using PDE weights

Any pharmaceutical company relying heavily on its sales force to detail multiple products knows the importance of optimizing a short time window to detail its products to physicians effectively, in the right sequence. With the trend toward decreasing detailing time that is now averaging less than a minute, the optimization of this period is critical to success, especially in today’s challenging selling environment. This paper develops a knowledge-based approach that integrates domain experts’ knowledge of the definition of promotional responsiveness with a hybrid model of neural networks and a nonlinear program to accurately determine the physician detail equivalent (PDE) weights that reflect the weighted sequence of detail and portfolio size while identifying the physicians who are responsive to details. tput from this approach drives physician detailing planning, as well as planning for market share of detailing volume, which is known as share of voice (SOV) planning. Results based on six months of implementation indicate that the knowledge-based approach performs significantly better than the traditional approach by more than 12% in profit.