Tevfik Tolga Kavun

Human-in-the-Loop AI for Pharmaceutical Field Force Management: From Predictive Signals to Managerial Decisions

Abstract:

Pharmaceutical field organizations generate large amounts of sales and activity data, but having more data does not necessarily make managerial decisions easier. One of the practical challenges for commercial leaders is identifying which performance signals require attention and then understanding what is actually behind them.

This talk explores a human-in-the-loop approach to AI-supported pharmaceutical field force management, drawing on more than two decades of commercial leadership experience across Kazakhstan and Azerbaijan. It considers how AI can help managers identify unusual patterns in sales performance, target achievement, account coverage, order quality, and field activity, while leaving the interpretation of context and consequential decisions to experienced managers.

A field case from Kazakhstan will be used to illustrate why poor performance should be treated as a signal rather than an immediate diagnosis. The presentation also discusses situations in which mathematically sound recommendations may not lead to good managerial decisions, particularly in target allocation and people management.

The central argument is that the most useful role for AI in field leadership is not to replace managerial judgment, but to help leaders focus their attention earlier and more effectively.

Profile:

Tevfik Tolga Kavun has more than two decades of commercial leadership experience in the pharmaceutical industry, including senior roles across Kazakhstan and Azerbaijan. His background covers pharmaceutical sales, field force management, commercial strategy, performance management, sales planning, and the development of large field organizations.

During his career, he has managed multi-level commercial teams and worked extensively with regional managers and medical representatives on sales performance, coaching, territory development, and field execution.

His current professional work and research interests include the practical use of artificial intelligence in pharmaceutical commercial leadership, particularly predictive coaching, exception-based decision support, adaptive territory management, and human-in-the-loop approaches to managerial decision-making.