Identified physicians at risk for a large pharmaceutical manufacturer

Case Studies:Mu Sigma
Published On: 06 November 2015
Views: 728

What We Did: Enabled the sales force of a pharma company to pro-actively target physicians whose activity could potentially decline

 

The Impact We Made: An intelligent system to proactively identify physicians at risk arrested decline in sales by more than 40%

 

Summary - More transparent physician intelligence

Pharmaceutical manufacturers spend billions of dollars on their sales force who call on physicians to influence prescription behavior. The sales teams however lack insights into leading behavior of these physicians, which may be indicative of potential decline in prescription of their products. Mu Sigma created an intelligent system to proactively identify physicians who were at risk of switching to a competitor drug. This helped the client reduce the number of physicians with declining sales by more than 40%.

 

About The Client - Leading global pharma company

The client is a Fortune 100 global pharmaceutical manufacturer and healthcare products company.

 

The Challenge - Limited information available to identify physicians at risk

Mu Sigma was helping the client’s sales organization create and maintain dashboards that captured prescription trends for each of their brands at a physician level. These dashboards were used by the sales leadership to track competitive market share and sales against internal plan for each of their products in each of their territories on a weekly and monthly basis. The dashboards would trigger inquisitive questions from the sales managers to analyze cause for decline in prescription patterns at a physician and territory level. However, we realized that more often than not, the analysis from trends observed in the dashboard was post-facto and did not provide the sales and marketing team with enough time and details to influence and retain physicians who were at risk. Mu Sigma brainstormed with the client to explore using market factors such as change in managed care access, disruptions in the form of a new sales rep calling on a certain physician and leading indicators of prescription patterns to proactively identify physicians who needed to be targeted for retention.

 

The Approach - Modeling physician behavior

Mu Sigma used historical trends observed from the dashboards and insights from the ad-hoc analysis done over the last couple of years to list down all potential leading indicators of decline in physician prescription patterns. Proactive identi­fication of physicians at risk was enabled by:

  • Developing an algorithm to highlight signifi­cant upward/downward trends in prescription patterns early in the cycle using statistical control limits to pro-actively flag physicians at risk

  • Reducing instances of false alerts by factoring in relevant physician profi­le attributes and business/market events that could explain the trends

As the sales team gained increasing confi­dence on the accuracy of identifying at-risk physicians, actionability was enabled by building an intelligent self-learning system that could:

  • Identify drivers of physician behavior using response models to recommend best possible actions to arrest decline

  • Predict the future propensity of a physician to prescribe a competitor drug

 

The Outcome - Real time actionable alerts

  • Recognized early trends in physician behavior and identifi­ed physicians who warranted attention

  • Provided real-time actionable alerts on physician performance, which helped sales force take proactive measures

  • In a rollout to the sales force for the client’s leading brand, representatives with access to the solution had 40% fewer physicians with declining sales and 9% higher goal attainment against their target

 

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