A field sales process rebuilt, and sales up 3–4%
Representatives were losing selling time to paperwork and head office was reading last week's picture. We moved capture into the field. Most of the gain came before any AI was involved.
- Sector
- Pharmaceuticals, India
- Service
- Process Re-engineering
- Result
- Client reports a 3–4% increase in sales
- Notable
- The first wins required no AI
A pharmaceutical company with a large field sales team calling on doctors and pharmacies across multiple territories. The commercial model depends on visit frequency and on responding quickly to what is happening in each territory.
In practice the day worked against both. Orders were captured on paper. Activity was written up in the evening, after the calls were done. Managers assembled territory data into weekly spreadsheets, which meant head office was always looking at a picture that was several days old and partly reconstructed from memory.
Two costs came out of that. Representatives lost selling time to administration, and decisions were made on stale information. Neither was a technology problem. The process had accumulated steps that existed because of how reporting had always been done.
We redesigned the daily routine around capture-at-source: the work gets recorded once, where it happens, and reporting becomes a by-product rather than a separate task.
- 01Capture in the field, once
Orders and visit outcomes recorded on the device the representative already carries, at the point of the call — not rewritten later from notes.
- 02Evening write-up removed
Because the data was already in the system, the separate reporting task no longer had a purpose. This was a step deleted, not a step automated.
- 03Managers out of the spreadsheet business
Territory roll-ups came from the same records rather than being assembled by hand, which removed both the delay and the reconciliation arguments.
- 04Then AI, where it earned its place
Once the data was clean and current, the parts that needed judgment at volume became worth automating. That came last, deliberately.
The client attributes the gain to two things: selling time recovered from administration, and a faster response to signals at territory level now that the data arrives the same day.
On a large field team, a few percent of revenue is a material number — and it came from changing the sequence of the work rather than from a model.
If we had started with a model, we would have automated the paperwork instead of removing it
The tempting version of this project builds an assistant that helps representatives complete their evening reports faster. It would have demonstrated well and preserved the problem.
This is why every engagement starts with how the work actually runs. Automating a broken process makes it break faster, and the first improvement often needs no AI at all.
Process Re-engineering →Bring us the process everyone complains about.
A discovery session is a working conversation, not a demo. You will leave it knowing whether this is worth doing — including if the answer is no.