32 reps. 1400 pharmacies. Everyone getting exactly the same attention.

The maths was clean: 44 pharmacies per rep, visit each one monthly, move on. The results were mediocre. Equal allocation felt fair and worked like a slow leak - spreading resources evenly is not the same as spreading them intelligently, and the gap between those two things shows up in every quarterly review.

The peanut butter problem

Not all pharmacies have the same potential. A high-volume independent in a medical precinct is not the same account as a small rural pharmacy. Treating them identically treats reality as simpler than it is.

Equal allocation is also genuinely appealing. Every customer gets attention. Every rep has the same workload. The system is easy to manage and hard to argue with in a planning meeting.

It is also guaranteed to underperform.

What the data showed

When we mapped customer potential against call frequency, the pattern was stark.

High-potential pharmacies - the top 15% of the base - were visited monthly, same as everyone else. They could have absorbed twice the attention and converted it to growth. They were not getting that.

Low-potential pharmacies - the bottom 30% - were also visited monthly. Most of those visits produced nothing commercially. The relationships were pleasant. The numbers were not.

The middle 55% varied considerably. Some were growing and needed support. Some were stable and needed maintenance. Some were declining and needed a different kind of conversation altogether.

Everyone getting the same attention meant nobody getting the right attention.

The range-based call plan

We rebuilt the call plan around potential, not equality.

A-tier pharmacies (top 15%): Weekly visits. These were the growth engines. More presence meant more range conversations, more recommendations, more share.

B-tier pharmacies (next 35%): Fortnightly visits. Growing or stable accounts that needed regular but not intensive attention.

C-tier pharmacies (next 30%): Monthly visits. Maintenance accounts where presence mattered but higher frequency did not drive incremental results.

D-tier pharmacies (bottom 20%): Quarterly visits with phone support. Genuine relationships with limited commercial upside.

Same 32 reps. Same 1400 pharmacies. Completely different allocation.

The results from this engagement

Within 90 days, call productivity - measured as commercial outcomes per call, not calls per day - was up materially. The A-tier pharmacies responded to increased presence by expanding range. The attention they had been missing began converting to shelf space.

D-tier revenue held flat. The pharmacies receiving fewer visits did not buy less. They had never been buying based on visit frequency in the first place.

The reps who had been quietly frustrated by “wasted time on dead-end pharmacies” suddenly had more of that time back. Their books improved. So did their job satisfaction.

Equal attention was not serving them any more than it was serving the customers.

The fairness question

Some reps pushed back. “It’s not fair that I have to visit some customers more than others.”

The reframe: fair is not equal. Fair is proportional.

A customer with R500K potential deserves more attention than a customer with R50K potential. That is not favouritism - it is resource allocation, which is the actual job.

The discipline problem

Segmentation on paper is easy. Segmentation in practice requires something harder.

Every rep will have a C-tier pharmacy they love visiting. Nice owner. Good coffee. Easy conversation. They will want to visit more than the data suggests is warranted.

That is where management matters. The call plan is a constraint, not a suggestion. Visit frequency needs to be defended, not negotiated away over a good cup of coffee.

The productivity gain in this engagement did not come from better data alone. It came from better discipline. The data told us what to do. The discipline made us do it.

Peanut butter is for sandwiches. Not for customer allocation.