Logistics & Supply Chain · 2025
How a logistics operator saved ₹1.2 crore a year on paperwork
Regional logistics operator, 6 depots
Illustrative sample — not a real client engagement
These projects demonstrate the kind of work and the level of detail a real case study will carry. They are composites, not client work, and carry no client attribution. Real engagements replace them as clients give written permission.
- ₹1.2 Cr
- Annual saving
- 9 days → 1
- Invoice lag after delivery
- 68%
- Fewer status calls
- 11 days
- Monthly admin time removed
Admin hours removed plus reduced empty running, measured over 6 months
Average days from POD to invoice raised
Inbound call volume to depot offices, pre vs post
Time-and-motion across six depots
At a glance
- Industry
- Logistics & Supply Chain
- Timeline
- 4 months
- Team size
- 4
- Investment
- ₹28,00,000
- Payback
- 3 months
The problem
Six depots generated e-way bills manually on the government portal, one consignment at a time. Proof of delivery travelled back with drivers on paper, so invoicing lagged by an average of nine days. Customers rang for status updates, and staff rang drivers to find out.
The challenge
Drivers had low-end Android phones and frequently no signal on route. Any solution depending on constant connectivity would fail. The depots also each had slightly different processes that had grown up independently over a decade.
Our approach
We resisted standardising the six depots immediately, which was the obvious move and would have stalled adoption. Instead we built to the common core and made the differences configurable, then let the depots converge over the following two quarters once they could see each other's numbers. Forcing process change on day one is how rollouts get quietly abandoned.
What we built
The solution.
E-way bill automation
Generated and updated from the consignment record via a registered GSP, replacing manual portal entry.
Offline driver app
POD capture with signature, photo and geo-stamp, syncing whenever the device finds a connection.
Customer tracking page
A branded link shared by WhatsApp, showing live location and ETA.
Return-load matching
Suggests backhaul opportunities from the existing booking pipeline.
Technology used
- React
- Node.js
- PostgreSQL
- Flutter
- AWS
Timeline
How it ran.
Discovery
Weeks 1–2Two depot visits and a full day riding with drivers.Design
Weeks 3–4Driver app prototyped and tested with six drivers on their own phones.Build
Weeks 5–14Depot staff in every fortnightly demo.Pilot
Weeks 15–16One depot live, running alongside the old process.Rollout
Weeks 17–18Remaining five depots over two weeks.Return
Did it pay for itself?
Investment against measured annual return. Figures agreed with the client's finance team rather than estimated by us.
- ₹28,00,000
- Investment
- ₹1,20,00,000
- Annual return
- 3 months
- Payback period
What we'd do differently
The part that didn't go to plan.
We built return-load matching in the first phase because it was the most interesting problem. It was used far less than expected in the first six months — the operational habits weren't there yet. The paperwork automation delivered nearly all the value. We'd now sequence the boring, high-volume work first and earn the right to build the clever thing later.
What's next
Fuel and maintenance tracking are in build; a driver performance module is planned.
Get results like these.
Thirty minutes with an engineer. We'll tell you honestly whether your problem is the same shape as this one.