Every CPO conference has that one slide. The one where someone claims their network is “the fastest-growing” or “most reliable.” Bold claims, usually backed by press releases and not much else.
We wanted something testable. A single number that answers: controlling for location quality, how much charging does this operator actually attract?
We call it the execution score. We’ve computed it for every fast-charging operator in the Nordics, using 12 months of data. As our data series mature across more European markets, the score will extend to additional countries over the coming months. But even in the Nordics alone, the spread between the best and worst is enormous — and not always where you’d expect.
What the execution score measures
Start with every fast-charging station in a given market. Measure how much actual charging happens there each month. Then divide out the location score — our model that captures how good the spot is based on traffic, road network, population, amenities, and competitive density.
What’s left is the operator. Their pricing, uptime, brand pull, charger reliability, amenities — everything that determines whether a driver picks their station or drives past it.
The execution score isolates the operator’s contribution by stripping out location effects. 1.0x means the operator performs at the market median for that country. Higher is better.
Scores are computed per country, per month. An operator needs at least five qualifying fast-charge stations in a market to be scored. Confidence levels — high (30+ stations), medium (10–29), or low (5–9) — tell you how much weight to put on the number.
The chicken and the egg
There’s a problem. To measure operator quality, you need to control for location quality. But to measure location quality, you need to control for operator quality. A Tesla Supercharger at a highway interchange looks great — but is that the location or the brand?
We solve this with an expectation-maximization loop. The model alternates: estimate location scores given current operator factors, then re-estimate operator factors given updated location scores. Each pass strips away another layer of confounding. After roughly 20 iterations, both estimates converge.
What comes out is a clean separation — how much of each station’s performance comes from where it is versus who runs it.
Operators with fewer than 10 stations get their score shrunk toward 1.0x. That’s a statistical safeguard. If you’ve got six stations and they all happen to sit next to a Tesla factory, we won’t crown you the best CPO in Europe. Not yet.
Norway: the most competitive market
Norway has the world’s highest EV penetration and most mature fast-charging market. It’s also where we have the deepest data. Here’s every scored operator, June 2026.
The chart splits neatly into two groups, and the dividing line isn’t random. It’s retail DNA.
Tesla (1.70x) and Ionity (1.67x) sit at the top. No surprise once you think about what execution actually is. Both are deeply embedded in in-car navigation — their stations surface as first-choice options before a driver even thinks about alternatives. Tesla has vertical integration and brand loyalty that borders on religious. Ionity has the OEM consortium behind it, with Plug & Charge removing every possible friction point. Add competitive pricing and high reliability, and you get 70% more utilization than the market median.
Uno-X (1.64x) and Circle K (1.41x) are fuel retailers — companies that have been selling stuff to drivers for decades. They know how convenience retail works. They have existing fuel card infrastructure, payment terminals that just work, and locations where people already stop. The transition from selling diesel to selling electrons turns out to be easier than building a charging brand from scratch.
Below the 1.0x line, the pattern flips. Mer (0.93x, 256 stations), Kople (0.87x, 166 stations), and Recharge (0.65x, 263 stations) are all traditionally asset-focused operators. They hail from utility or infrastructure fund ownership — organisations that know how to deploy capital and build physical networks, but whose core competence has never been consumer-facing retail. Great at picking locations and pouring concrete. Less practiced at the pricing, branding, and user experience that makes a driver choose your station over the one across the road.
That’s exactly what the execution score captures. The location score already gives these operators credit for their asset base — and many of them score well on location. What’s left is the retail execution: converting footfall into sessions. And there, the gap is stark.
Same brand, different markets
A single execution score hides something important: the same operator can excel in one market and struggle in another. Per-country scores — each relative to that country’s own market median — reveal the variation.
Every operator on this chart scores higher in Sweden than in Norway. That’s not because they’re better in Sweden — it’s because Sweden’s market median is lower. Norway’s extreme EV penetration means the bar for “average” is higher there.
Tesla and Ionity both cross 2.0x in Sweden — double the local market median. Circle K outperforms in both markets but with a bigger edge in Sweden (1.61x vs 1.41x).
Mer is almost perfectly average in both countries: 0.93x in Norway, 0.93x in Sweden. Consistent, but consistently middling.
Recharge underperforms in both: 0.65x in Norway, 0.70x in Sweden. More stations at below-average utilization is a volume play, not an execution play.
The execution score strips away location noise to reveal what operators actually control: in-car navigation presence, brand pull, pricing, uptime, and user experience. In Norway, the best operator (1.70x) generates nearly three times the utilization of the worst mainstream network (0.65x) — at locations of equal quality. That’s the difference between a profitable network and a stranded asset. And it maps almost perfectly to whether the operator’s heritage is retail or infrastructure.
See execution scores for every operator on the CPO Benchmark, or explore individual company profiles in ChargiPedia. Every score is updated monthly with 12 months of trend data.
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