Fleet-wide electrification screen
Every truck scored for electrification suitability against its own measured duty cycle, producing a ranked shortlist rather than an opinion about which vehicles feel suitable.
Feasibility study · 2026
Electrification and solar, waste-collection operator
Fleet screen and conversion plan
Fifteen trucks, nineteen routes and close to fifteen hundred customer stops, with a single month of fuel card data to work from, extended into a combined energy-transition case.
15
trucks screened across 19 routes
~1,500
customer stops in the route data
847k
DKK annual saving on the combined case
142
tonnes CO2 per year avoided
The brief
A waste and recycling transport business wanted to know which of its trucks could be electrified and in what order. The available evidence was thin: one month of fuel card data, route records and a partial picture of what each vehicle actually does in a day.
The study was later extended beyond the fleet into a combined case that put rooftop solar alongside the vehicles, because the same depot that charges the trucks has a roof doing nothing.
Deliverables
What was handed over.
Five-year conversion plan
A sequenced plan naming the first movers and the deferrals, which went on to support a funding application.
Combined energy transition case
Electrification and a 100 kWp rooftop solar installation modelled together and separately, so the decision on one does not depend on the other. Combined: roughly DKK 7.15M of capital after grants against DKK 847k a year and an 8.4 year payback.
Management briefing
A sixteen-slide briefing delivered to management, with measured data and benchmark data visually distinguished on every slide that mixed them.
Actions
What I did.
- Derived each vehicle's daily distance two independent ways from the available data and checked one derivation against the other, because a single derivation from one month of fuel cards is a guess with a decimal point.
- Scored every truck for suitability and identified the two depot-return urban vehicles as first movers.
- Deferred the long-haul vehicle by twelve to twenty-four months on three separate counts and said which: range on two days in five, no charger at its overnight stop, and a body weight that leaves too little payload once a battery is added.
- Modelled the solar installation on its own economics so it could be approved or dropped independently.
- Closed out an eight-item data list with the client to move the case from directional to decision-grade.
Problems and solutions
What went wrong, and what was done about it.
Every project has these. They are more informative than the finished result, so they are on the page.
Problem
One month of fuel card data cannot carry a five-year investment decision, but it was what existed.
Solution
The study carried its own reliability grade on its face: the data reached only the lowest tier, and the document said so in the opening rather than in a footnote. Every figure was tagged as measured, calculated or estimated. Being explicit about what was borrowed from benchmarks mattered more here than in any other study I have run, because the alternative was a confident number with nothing underneath it.
Problem
The client's instinct was to electrify the biggest, most visible truck first, which is also the one that produces the best-looking CO2 headline.
Solution
The screen put it last, with the three specific reasons written out. Range, charging and payload each independently disqualify it today, and none of the three is fixed by wanting it more. The two quiet urban trucks that nobody had nominated went first.
Problem
Combining vehicles and solar into one number would have made the case look stronger and made it impossible to act on partially.
Solution
Modelled all three ways: vehicles alone at a 7.3 year payback, solar alone at 8.8 years, and combined at 8.4. A client that can only fund one half can still see which half to fund.
Outcome
A ranked, sequenced conversion plan that supported a funding application, and a combined case putting roughly DKK 847k a year and 142 tonnes of CO2 against DKK 7.15M of capital after grants. The pilot was positioned as the programme's public reference story for the quarter.
What it took
Fleet screening and scoringDuty-cycle analysisSolar PV business caseData quality gradingExcel financial modelsPower BI dashboards