Veerapathra Transport · Thanjavur · Tamil Nadu
The driver who earned more — and took home less
A real per-trip P&L story from a 2-truck Indian fleet
- Window
- 7 March 2026 → 23 May 2026
- 3 P&L cycles · 40 trips
- Fleet
- 2 trucks · 2 drivers
- Tooling
- Fleetbooks per-trip P&L
- Leak identified
- ₹12,616
- over 78-day window
TL;DR
The top-earning driver produced ₹12,616 less profit than the fleet's #2 — despite higher gross revenue per trip.
The entire swing sat in one expense column — loading + unloading fees — that most owner-drivers don't line-item separately.
Sample: 40 trips (Kumar 19 + Senthil 21) over 78 days. IQR overlap shown in Figure 3 for confidence at this n.
| Driver | Kumar (vanity #1) | Senthil (profit #1) | Δ |
|---|---|---|---|
| Trips | 19 | 21 | |
| Revenue / trip | ₹36,646 ▲ | ₹35,800 | +₹846 in Kumar's favour |
| Profit / trip | ₹10,579 | ₹11,243 ▲ | −₹664 against Kumar |
| Load + unload / trip | ₹3,428 (9.4%) | ₹2,098 (5.9%) | +63% on Kumar's side |
| Profit lost in window | −₹12,616 | reference |
01 · Setup
The question every owner asks.
Two trucks. Two drivers. Same crops, same lanes, same diesel price, same bata norms.
The owner's intuition was: "Kumar runs longer trips and brings in more revenue per ticket — he's our top earner."
That's exactly the trap Fleetbooks was built to catch.
A note on language: when we say Kumar "took home less," we mean less profit for the fleet, not lower bata for the driver. Kumar's personal pay didn't change. The owner's take did.
02 · The vanity number
Revenue per trip — and where it misleads.
On revenue alone, Kumar wins. He averages ₹36,646 per trip vs Senthil's ₹35,800 — a ₹846 advantage per ticket.
If you stop here (and most fleet owners stop here), you'd hand Kumar the better routes, the better truck, maybe a bonus.
03 · The reveal
Switch to profit per trip — and the ranking flips.
- Senthil: ₹11,243 profit / trip (margin 31.4%)
- Kumar: ₹10,579 profit / trip (margin 28.9%)
A ₹664 per-trip profit gap against the supposed top earner.
04 · Cost decomposition
Line by line, on the right denominator.
The dumbbell chart below the leaderboard puts every expense column on the same axis, with the right denominator per line (₹/trip for fixed-per-event fees, ₹/km for distance-scaled costs).
Per-trip fees (₹ per event, vendor / negotiation-driven)
| Cost line | Senthil avg | Kumar avg | Δ (Kumar − Senthil) | Flag |
|---|---|---|---|---|
| Loading | ₹1,025 | ₹1,333 | +₹308 (+30%) | Kumar high |
| Unloading | ₹1,275 | ₹1,488 | +₹213 (+17%) | within ±20% |
| Other | ₹0 | ₹204 | +₹204 | within ±20% |
| RTO / Police | ₹588 | ₹450 | −₹137 (−23%) | Senthil high |
| Weighbridge | ₹50 | ₹63 | +₹13 (+25%) | Kumar high |
| Shed commission | ₹850 | ₹850 | tied |
Aggregate: load + unload alone costs Kumar ₹1,330 more per trip (₹3,428 vs ₹2,098 — a 63% gap).
Per-km running cost (scales with distance)
| Cost line | Senthil | Kumar | Δ |
|---|---|---|---|
| Diesel (sheet) | ₹27.7 / km | ₹29.6 / km | +₹1.9 / km (~7%, tied) |
| Driver bata | ₹8.4 / km | ₹9.1 / km | tied |
| Ad-Blue / Oil | ₹0.0 / km | ₹1.3 / km | small absolute |
Diesel and bata sit inside the ±20% anomaly band (Kumar +6.9% on diesel, bata effectively flat). IQRs overlap on the dumbbell at this sample size — secondary signals, not the leak.
05 · Operational diagnosis
Why this happens.
Loading & unloading fees in Tamil Nadu lorry ops are negotiated trip-by-trip with the hamali / shed crew. Rates vary by:
- Crop (rice gunnies vs loose paddy vs cement)
- Crew of the day (regular crew = lower; replacement crew = higher)
- Time of day (after-hours premium)
- Whether the driver pushes back
Kumar's pattern over 19 trips suggests he's accepting whatever the crew quotes; Senthil's lower numbers suggest he's bargaining or working with cheaper regulars. There's no procurement contract for these vendors — pricing is purely driver-discretionary.
This is why the leak hides:
- Trip-sheet totals show only one line:
finalAmount(the EBITDA proxy) - Aggregated monthly P&L bundles load + unload into "operating costs"
- Per-driver, per-cost-line view requires breaking the totals open
- Most accountants don't categorise hamali charges per driver
Fleetbooks computes this per trip and surfaces the anomaly badge once a driver's average on any line deviates ≥ 20% from peer median.
06 · The fix
What the owner actually did.
01
Rate card
Owner asked Senthil to share his typical hamali quotes by route. Built an informal rate-card sheet kept in both trucks.
02
Driver awareness
Showed Kumar his own per-trip profit number (not revenue). Once he saw the personal P&L, the negotiation pushback started naturally.
03
Weekly review
The leaderboard now gets a 5-min review every Sunday — anomaly badges are the agenda.
No vendor was changed. No truck was reassigned. No bata was cut. The fix was visibility, not procurement — once Kumar saw his own per-trip profit line (not just revenue), the pushback at the shed crew started naturally. The next cycle's data isn't in this case study yet; we'll publish a follow-up once cycle 4 closes.
07 · Product takeaway
Spreadsheet vs Fleetbooks.
This case study is the canonical demo of what Fleetbooks does that a normal spreadsheet doesn't:
| Source you'd use today | What it shows | What Fleetbooks shows |
|---|---|---|
| Spreadsheet / WhatsApp ledger | Monthly revenue per truck | Per-trip revenue and profit per driver |
| Spreadsheet / WhatsApp ledger | Total expenses by category | Each expense column on the right denominator (₹/km vs ₹/trip) |
| Spreadsheet / WhatsApp ledger | P&L statement at month-end | Live leaderboard with anomalies auto-flagged ≥ 20% vs peer median |
| Spreadsheet / WhatsApp ledger | Diesel and bata (because they're big) | Every fee column, including the ones owners forget |
| GPS-tracker SaaS (BlackBuck, Fr8, WheelsEye) | Truck position, ePOD, freight matching, fuel pings | Per-trip P&L, per-driver cost decomposition, anomaly badges — once the load is booked, we run the back office |
In hard numbers, for this fleet: ₹12,616 visible over 78 days on a fleet that grossed ~₹14.5L in the same window. That's ~0.9% of revenue — small as a percentage, large in absolute terms for an owner-operator running on EMI. Linear extrapolation: ~₹59K per year leaking on one cost line between two drivers.
Scaling math (route-mix similar, same loading-fee dispersion): a 5-truck fleet on the same lanes carries roughly 2.5× the annual leak → ~₹1.5L / year. A 20-truck fleet → ~₹6L. The gap compounds with driver count, not revenue scale — which is why mid-fleet owners (5–25 trucks) feel this hardest: they have enough drivers to leak, not enough margin to absorb it.
08 · Methodology
Numbers and method, audited.
- Source
trip_sheetstable, joined withexpensestable per trip- EBITDA basis
- Revenue − trip-sheet expenses − Direct operating − Repairs & maintenance − Insurance & taxes − Other operating
- Profit / trip
- (revenue − all expenses) / trip count
- Anomaly threshold
- ≥ 20% deviation from peer median and ≥ ₹100 absolute impact per trip — the absolute floor prevents tiny-base lines (e.g. weighbridge ₹13 / +25%) triggering noise badges. Basis is per-km for variable costs, per-trip for fixed-per-event fees.
- Cycle convention
- VPT P&L runs 7th → 6th of next month (not calendar)
- Sample size (n)
- 19 trips (Kumar) + 21 trips (Senthil) over 78 days
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