MR Route Optimization: How AI Visit Planning Lifts Field Coverage

Ask a first-line manager where their field force loses time and the honest answer is rarely "selling." It is travel, sequencing and the quiet drift toward easy-to-reach, low-value calls. In a country where a single territory can span dozens of kilometres of unpredictable traffic, route planning is not an admin detail, it is the difference between covering your A-list doctors twice a month and missing them entirely.

The hidden cost of habit-based routing

Most MRs build their day around comfort: the clinics that are close, the doctors who are friendly, the chemists on the way home. None of that maps to prescription potential. The result is predictable, over-servicing low-decile HCPs while high-potential prescribers slip to the back of the queue. Coverage looks busy on paper and underperforms in the market.

What "optimised" actually means

A good optimisation engine balances three things at once: HCP priority score (potential × current engagement), geography (clustering calls to cut travel), and frequency rules (how often each segment should be seen). The output is not a suggestion, it is a sequenced, time-boxed day plan the MR can simply execute.

Coverage you can see and correct

The bigger unlock is visibility. When managers see a live territory map with priority scoring, coverage gaps surface before the cycle ends, not in the month-end review when it is too late to act. Redeploying effort mid-cycle is where the real gains come from.

Where Pharos RouteIQ fits

Pharos RouteIQ generates priority-scored daily call plans from HCP scoring and territory geography, with real-time maps and multi-role dashboards for MRs, ASMs and admins. It is one module of the Pharos platform, so the coverage data it produces feeds directly into prescription and pipeline intelligence elsewhere in the stack.