Database models and managerial institution: 50% model + 50% manager
Management Science
Interaction of judgemental and statistical forecasting methods: issues &
Management Science
Working Knowledge: How Organizations Manage What They Know
Working Knowledge: How Organizations Manage What They Know
Customizing Promotions in Online Stores
Marketing Science
An expert system to derive carryover effect for pharmaceutical sales detailing optimization
Expert Systems with Applications: An International Journal
Knowledge-based approach to improving micromarketing decisions in a data-challenged environment
Expert Systems with Applications: An International Journal
Using text classification and multiple concepts to answer e-mails
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
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. The output 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.