Cement Manufacturing · Sales Beat Planning

The Challenge

Beats were inherited, not planned

Sales Officers covered large rural and semi-urban territories across dealers and retail counters. The beat plan lived in personal Excel sheets and memory.

Beats built from memory

Routes passed from one SO to the next. Newly onboarded retailers rarely made it onto a beat day.

Dealer-heavy, retailer-light

Comfortable counters got repeat visits. Outer-village retailers went weeks without a call while competitors stocked them.

Kilometres, not calls

Zig-zag routes across talukas. An SO could log 110+ km in a day for eight or nine productive calls.

No line of sight

ASMs saw primary sales, not whether the beat was walked. Adherence was checked through WhatsApp check-ins.

HMC Approach

Five steps from field ride to rollout

Built with the sales team, not around it. Each phase ended with something the field could use that week.

Select a step to see what happened.

Discover · Ride the beat before redrawing it

Field rides with SOs in three territories to see how beats really run.

Audited the outlet master from DMS: duplicates, missing geo-tags, inactive counters.
Baselined coverage, km per day, productive calls and strike rate per SO.
Mapped local constraints: haat (market) days, dealer credit-collection days, monsoon access.

Deliverable: Clean, geo-tagged outlet master and a baseline scorecard.

Design · Agree the rules of a good beat

Beat rules signed off by RSMs before any model was built.

Outlet classes A / B / C by monthly potential (MT) set visit frequency: weekly, fortnightly, monthly.
Caps per beat day: outlet count, travel km, and a mandatory dealer anchor.
Clustering logic: geography first, balanced by potential so no day is all low-value calls.

Deliverable: Beat design rulebook and outlet classification.

Build · Engine in the back, Excel in the front

Python does the heavy lifting; the SO receives a beat sheet in a format they already trust.

Python clustering and route sequencing to minimise backtracking.
Power Query pipeline from DMS/SFA exports into a weekly refresh.
Excel/VBA beat sheet per SO; Power BI adherence dashboard for ASMs and RSMs.
Claude prompt pack so ASMs can ask "what if I move Begun to Thursday?" and get a revised plan with reasoning.

Deliverable: Beat engine, SO beat sheets, adherence dashboard.

Adopt · Make the new beat the easy beat

Pilot in two regions with a tight feedback loop.

15-minute weekly beat huddle per ASM, driven from the dashboard.
SO overrides logged, not blocked: swaps for haat days and dealer requests fed back into the rules.
Recognition for best-adherence SOs in the regional review.

Deliverable: Pilot results, refined rules, huddle playbook.

Scale · Hand over the engine

Region-by-region rollout with ownership moving to sales operations.

Monthly re-clustering as new retailers are onboarded.
Sales MIS team trained to run, tune and audit the engine.
Beat adherence added to the monthly sales review pack.

Deliverable: Runbook, trained owners, governance cadence.

The Solution

Territory-clustered beats, sequenced to cut backtracking

One SO territory, one six-day cycle. Toggle to compare the inherited beat with the data-built one. Hover an outlet for detail; hover a day to isolate its route.

1 SO · 64 outlets · Mon–Sat cycle · Illustrative layout

Avg travel per beat day

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Outlets on a beat

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Volume potential covered

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How the after-beat is built

Outlets grouped into six contiguous sectors around the SO's base.
Each day sequenced nearest-first, then untangled to remove crossings.
Every outlet lands on a day; large dealers anchor each route.

Impact Dashboard

More calls on fewer kilometres

Productivity rose in every region. Adherence climbed steadily once the weekly huddle took hold.

Productive calls per SO per day

By region, quarter before vs quarter after rollout

BeforeAfter

Beat adherence, weekly

% of planned outlet visits completed, pilot regions

AdherenceTarget 85%

Figures indicative; validated metrics available on request.

Before vs After

What changed on the ground

Dimension	Before	After
Beat creation	SO's own Excel, carried over year to year	Clustered by geography and outlet potential, refreshed monthly
Outlet priority	Relationship-driven	A / B / C class sets visit frequency
Route sequence	Town by town, frequent backtracking	Sequenced nearest-first; haat days respected
Coverage visibility	Monthly, inferred from primary sales	Weekly adherence by SO, beat and outlet in Power BI
Beat review	Only at territory change	15-min weekly huddle with Claude-assisted what-ifs
Planning effort	~6 hrs per SO per week	~40 min per SO per week

Key Takeaways

What transfers to any field sales team

Fix the outlet master first

Geo-tags and outlet classes decided most of the outcome. A clean master beat a clever algorithm.

Plan for potential, not just proximity

Visit frequency by outlet class kept clusters commercially honest. Short routes alone can still miss the volume.

Ship in the format the field trusts

An Excel beat sheet and a 15-minute weekly huddle drove adoption faster than a new app would have.

Sales Beat Planning