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An IoT loss-control system for heavy industry, piloted at a major steel producer

At an industrial site, diesel leaves the tank in ways nobody can see, so nobody can price it. This is how the product was scoped at the nozzle and the tank, and why the saving was the only metric that counted.

Role
Product Manager, FuelBuddy
Setting
A major steel producer, India
Type
IoT, industrial SaaS, 0→1

Problem

At an industrial site, diesel leaves the tank through loss, theft and spillage that nobody can see, so nobody can price it. The plant knew its monthly consumption; it did not know how much of it was waste.

Evidence

Site walks at the plant, with the people who dispense fuel as well as the people who buy it. The gaps were at the nozzle and the tank, so the product had to live there: automatic tank gauges, dispensers, flow meters, RFID nozzle tags and tank sensors, 100+ requirements in all.

Decision

A six-month pilot measured against the site's own baseline, with the saving as the metric. The buyer could verify the saving at the meter, which is what makes a hardware-linked product sellable.

Result

Savings did not arrive in month one. As the controls and site behaviour settled, the six-month pilot cut loss, theft and spillage by about 20 paise per litre against the site's own baseline, a run-rate of ~₹4 lakh a month by months 5–6.

What I'd do differently

Set the expectation of a ramp in the contract. A saving that climbs over six months reads as a miss in month two unless the buyer was shown the curve first.

Related work

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Commercial terms stay private. Figures are rounded.

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