Companion piece: 23 ways CPOs fix underperforming sites: the remedy playbook

A charger can report 99% uptime and still turn away one driver in three.

That gap is the most useful thing to understand about charging operations right now. ChargerHelp's 2025 analysis of more than 100,000 sessions across 2,400 chargers found reported uptime running between 98.7% and 99.9%, while only 71% of charging attempts succeeded on the first try. Even more uncomfortable: 35% of those failures occurred on chargers that appeared operational. The data is American, and UK numbers will differ, but the mechanism travels. Your dashboard is green. Your driver is gone.

The same gap exists one level up. A site can look acceptable relative to your network average and still pull in half of what it should for its location.

Both gaps cost the same thing: margin. Profitability sits on every board slide in this industry now, and the cheapest route to it runs through chargers you already paid for. Getting there starts with knowing what is wrong with them, because the wrong diagnosis spends real money and moves nothing.

In our business, we speak with heads of operations and network performance of charge point operators across Europe, and with advisors who have worked on thousands of chargers. This guide sets out what those teams look at when a site slips, the five families of cause, the symptoms that separate them, and what each wrong diagnosis costs. The companion piece covers the 23 remedies that follow.

1. Define underperformance properly

A site underperforms when it pulls less than it should for its location. The average is what hides your problem. A mean built from 400 healthy sites and 40 dying ones reads as acceptable right up until the year-end margin lands. Zapmap and the Green Finance Institute found time- and energy-based utilisation rates moving within a narrow band across every power category through 2025, even as the network grew by 13% and delivered energy grew by an estimated 21%. Aggregate stability tells you nothing about the spread underneath it.

Operators who run this well score each site against an expectation built from its own context: local EV density, traffic, dwell time, competing chargers within the catchment. Then they rank by the gap. Some teams keep a worst-against-achievable list so the operations meeting opens with names rather than a dashboard.

That gap is your starting point. The rest of this guide explains what fills it.

2. The five families of cause

Demand

The hardware works. The bay is clear. There are not enough EVs within reach, or the drivers who are there have never noticed the site.

Symptom signature. Healthy success rate, low session count, flat trend with no step change. New sites show a slow ramp rather than a drop.

How to confirm. EV registration density in the surrounding postcodes against the assumption in your site case. First-time-user share at the site: if it sits near zero while repeat use holds, awareness is your problem rather than driver behaviour.

What operators tell us. Kerbside teams keep returning to housing stock. A street where most residents have no driveway behaves nothing like a street where most do, and the second one will underperform for years whatever you spend on marketing.

Cost of calling it wrong. You cut the tariff at a site with no drivers in range. You lose margin on the few sessions you had and change nothing else.

Physical site & visibility

The most common cause that never appears in a fault log is that nothing has failed.

Symptom signature. Sessions well below comparable sites nearby with similar traffic. Long unexplained availability gaps, which usually mean a blocked bay rather than a fault.

How to confirm. Photographs beat data here. Teams that drive their estates turn up payment screens bleached by sunlight that have been losing customers for months. Nobody reports it because a driver who cannot read a screen does not file a ticket, nor do they return.

Cost of calling it wrong. You run a hyperlocal campaign that successfully drives people to a bay a diesel van has occupied since Tuesday.

Technical / uptime & faults

Symptom signature. Success rate below your network norm. Sessions started well above sessions completed. Faults recurring on the same units.

How to confirm. Cut success rate by charger type, by firmware version and by site age. The comparison usually names the cause on its own. A pattern that follows hardware points at firmware or the vendor. A pattern that follows geography points at grid or comms.

Age matters more than most operators budget for. The ChargerHelp analysis found first-time success falling from 85% at new stations to below 70% by year three. Your 2023 cohort is quietly becoming your problem cohort.

Cost of calling it wrong. This is the expensive one. You market a broken site, and every new driver you attract has a failed first experience. J.D. Power's 2025 US study found 14% of EV owners visited a charger and left without charging. You paid to create those visits.

Price & competitor activity

Symptom signature. A step change, not a curve. Utilisation drops on a date. Sessions shift to a competitor while your success rate stays perfect.

How to confirm. Find the date the drop started, then find what changed in the catchment on that date. Benchmark your own tariff while you are looking: Zapmap put the weighted average pay-as-you-go price in July 2026 at 54p/kWh up to 49kW and 80p/kWh at 50kW and above. If a competitor launched a time-boxed promotion, your problem has an end date and may need no response at all. Several operators describe watching a rival run a time-boxed deal, holding their own tariff, and waiting for volume to return.

Cost of calling it wrong. Two ways to lose. You match a promotion that would have ended anyway and start a race down. Or you sit still through a permanent repricing and lose a year waiting for a recovery that never arrives. The difference between those two mistakes is knowing whether the competitor's move has an end date, so establish that before you touch your own tariff.

Location: wrong from the first day

Symptom signature. No event explains the weakness, because there was never a strong period. The site launched flat and stayed flat.

How to confirm. Compare actual traffic and dwell time against the assumption in the original site case. This is uncomfortable work, since it audits a decision somebody in the business already made and defended.

Cost of calling it wrong. You spend three years cycling remedies through a site that no remedy reaches. Operators who run this well set a limit: after a defined set of interventions, a chronic loser gets switched off, sold, or moved, and the freed capex goes to something that can pay it back. Operators running large mixed estates describe exactly this call. Zapmap has started to see it in its own data, noting that poorly performing chargers are being taken out of public use.

3. The moves your own data can't see

Some causes hide inside your estate. Others sit entirely outside it, and those are the ones your dashboard is built to miss.

Your reporting shows your own sessions, uptime, and tariff. It shows nothing about the catchment around a site. A competitor opening two miles away. A rival cutting its pay-as-you-go rate last Tuesday. Either can pull a healthy site's volume down within days, and neither leaves a mark in the system you use to watch for trouble. The site reads fine on every internal measure. Success rate perfect, hardware green. The drivers just went somewhere cheaper or closer.

This is why a step change matters. When utilisation drops on a given date while your success rate remains steady, the cause is almost never within the unit. Something shifted in the market that day. Zapmap recorded on-street charger numbers growing 18% year on year through H1 2026, the fastest period yet, so the chance that a rival appeared in your catchment keeps climbing. Benchmark your own price while you look. Sit at or below the market rate and still lose volume, and price is not the whole story; a nearby deployment probably is.

You cannot respond to a move you never saw. Most operators learn a rival cut prices weeks later, from a sales rep or a quarterly review, long after the volume left. Watching the catchment, not just the estate, is what lets you make that call while it still matters, instead of writing it up afterwards.

4. The revenue you have already paid for

A charger's cost is fixed. The hardware, the installation and the grid connection behind it all get paid whether anybody charges or not. That single fact decides where the money leaks.

It means an empty socket is never neutral. Every session that walks to a competitor you did not spot, and every quiet hour that passes with the bay idle, is a contribution you have already paid for and did not collect. A busy site can still lose money, and a half-empty one bleeds it slowly enough that nobody flags it until the year-end margin lands.

The first leak is price. When a rival's move is real and lasting rather than a short promotion, holding your tariff out of principle just funds their growth. When it is a time-boxed deal, matching it starts a race down that nobody wins. The difference is whether the move has an end date, which is why you establish that before you touch your own price.

The second leak is time. Most sites do not underperform across the whole day. They fill at peak and sit dead in the trough, and that trough is capacity you are paying for and giving away. Time-of-day pricing pulls price-sensitive drivers into the quiet window. A fleet or depot deal contracts the dead hours to a local operator who values a guaranteed slot more than a low headline rate. Neither touches your peak margin, and both turn idle capacity into sessions. The test is simple: did off-peak volume grow without eroding what you make when the site is busy?

None of this shows up as a fault, because nothing failed. It shows up as a site that quietly earns less than the one down the road, and closing that gap is the cheapest margin you will find.

5. Where the manual version stops working

An hour per site is affordable. A thousand sites a week is not.

You cannot rank a thousand chargers by hand every Monday, hold a likely cause for each weak one in your head, and still recall six weeks later whether the tariff change at site 412 moved the number or whether the season did. So the loop degrades into a rescue: whoever shouts loudest gets attention, the same three sites get fixed twice, and the check-back disappears.

Operators with large estates describe some version of this.

The cost is not abstract. A weak site you never diagnosed keeps paying its grid connection, its maintenance contract and its capital charge while returning a fraction of the sessions it should. Multiply that across the tail of any estate, and you have the gap between the profitability number on the board slide and the one in the accounts. Diagnosis is the cheapest lever in the business, and almost nobody runs it systematically.

What we built

Dodona Network Optimisation ranks every site in your estate by the gap between what it pulls and what it should pull, then lets you quickly analyse the likely symptoms: demand, price, competitive activity, a fault, or placement.

We are opening a beta to a select group of operators in September, and several networks are already in.

Next: 23 ways CPOs fix underperforming sites: the remedy playbook

Sources

• ChargerHelp, first-time charge success rate analysis, 2025 (100,000+ sessions, 2,400 chargers)

• J.D. Power, US Electric Vehicle Experience Public Charging Study, 2025

• Zapmap and Green Finance Institute, UK charge point utilisation report, 2026

• Zapmap Price Index, July 2026

• Zapmap UK charging infrastructure statistics, H1 2026

• The Public Charge Point Regulations 2023, regulation 7

We work with charge point operators across Europe, and one pattern comes up in almost every conversation: the European charging market gets discussed as if it were a single market. It is not. An operator running sites in Rotterdam, Frankfurt and Valencia is running three different businesses with three different constraints, and the strategy that works in one will fail in the other two.

We picked these three countries deliberately. Each one clearly represents a different problem that the whole continent will face at some point. The Netherlands shows what happens when a mature market runs out of grid. Germany shows what a massive, state-driven buildout does to everyone's site economics. Spain illustrates the risks of an early market in which infrastructure outpaces the drivers. Wherever you operate, at least one of these is either your market's future, your current situation, or a phase you have already worked through yourself.

Here is what each one is dealing with in 2026, what they can learn from each other, and where we fit in.

Netherlands: the grid has become the market

The Dutch charging market served as Europe's showcase for a decade. Over 40% of new cars sold in 2025 were electric. The public network passed 200,000 charging points, the densest coverage in the world. Then the grid ran out.

The scale of the problem is hard to overstate. Regional grid operators hold more than 14,000 open requests for offtake capacity, totalling around 9 GW. TenneT's national queue holds a further 38 GW. Stedin has declared parts of the Utrecht network closed to new capacity indefinitely, with no reopening date. Businesses seeking new connections or expansions report waiting up to 10 years. The congestion has now reached households too: Liander placed 7,300 homes on a waiting list this year, some facing three-year delays for a heavier connection, largely driven by heat pumps and home chargers.

The government's response tells you where this is heading. The grid congestion campaign announced in February 2026 contains eight measures, and almost none of them involve building faster. Instead: flexibility tenders from every major grid operator this year, an extra €500 million per year for contracting flexible capacity, subsidies for flexibility scans, and new rules from the consumer authority arriving in July. The official position is explicit: grid capacity will stay scarce in the new energy system, and flexible use of what exists must become standard practice.

For a CPO, this entirely rewrites site selection. In most markets, the question is whether a location has the demand. In the Netherlands, the first question is whether a location can be energised at all, and getting that answer wrong costs years, not weeks. A site with perfect traffic, strong footfall and no grid access is worth nothing. At the same time, locations with available capacity have become the scarcest and most contested assets in the market, and the operator who identifies them first wins them.

Three things follow for anyone operating there. When one of those rare connectable opportunities does surface, the operator who can assess it fastest and with the most conviction takes it. Speed alone is not the whole game, though, because scarcity inflates prices, and a contested asset is exactly the kind you overpay for in the heat of a negotiation. The operators who come out of this period healthy will be the ones who modelled precisely what each site is worth to them and how far they can and will go before the bidding starts, so that conviction arrives with a ceiling built into it. And with expansion constrained, the network you already run becomes the growth engine, which makes it essential to know how each of your sites performs against nearby competitors and, where a site underperforms, whether the cause is low footfall, the wrong charger mix, new competition or something else entirely. Each of those has a different fix, and in a market where you cannot simply build your way out, fixing what you have is the strategy.

Dodona helps you understand how your network is performing and why, so you can optimise based on recent trends.

Germany: nine thousand new fast chargers are about to test everyone's demand assumptions

Germany's problem is the opposite one. The Deutschlandnetz programme plans to deliver around 9,000 high-power charging points across more than 1,000 locations by the end of 2026, each rated at 300 kW or higher, with locations based on a government needs analysis rather than on operator site selection. AFIR adds mandatory fast charging every 60 km on main routes. In May, the Federal Ministry of Transport opened a €1 billion programme for heavy-duty charging, paying €500 per installed kilowatt for depot and public projects. The first funding calls opened on 26 May with a 7 July deadline, and further calls will follow over the programme's four-year term. The Masterplan Ladeinfrastruktur 2030 targets one million public points by the end of the decade.

Two consequences follow, and both punish slow analysis. The first is competitive. A site that pencilled last year may not pencil next year once a subsidised 300 kW hub opens a few kilometres away. German operators now need to underwrite every location against a charging map that is redrawing itself monthly, which means knowing exactly where competitors and Deutschlandnetz sites are landing, and what that does to each site's numbers. Commercial sites in Germany need roughly 20-25 sessions per day to cover their tariff structures after accounting for grid costs. Plenty of new capacity will fall short of that, and the difference between winners and casualties will come down to who read the local competitive picture correctly before committing capital.

The second consequence is speed. The funding programmes run on fixed windows and competitive selection, so the operator who can assess a large portfolio in days rather than months gets to bid on more of them, with better numbers. This is exactly the kind of situation Dodona was built for. Operators import candidate sites in bulk, and the platform scores each site against traffic, competition, demographics, and dozens of other data layers, delivering ranked results in minutes. One team used it to evaluate 238 locations over a weekend and submit a competitive tender by Monday morning. When funding rounds have deadlines and the competitive map changes monthly, that turnaround is not a convenience. It determines how much of the German buildout you can participate in.

To illustrate the impact competitors have on a portfolio you are assessing, we conducted a case study. The following are 4 snapshots from our platform showing an example portfolio over a 3-month period. The first shows all the sites, and the following shows the number of sites where competition deployed a charger in the vicinity since the beginning of observation.

Spain: the chargers exist, the demand map does not

Spain's numbers look healthy at a distance. The public network is approaching 50,000 charging points. Corridor operators like Zunder, Repsol and Iberdrola are investing heavily in ultra-fast highway sites; Plenitude plans to achieve full coverage of its Spanish service areas by the end of 2026, and EU money continues to flow through AFIR obligations and EIB financing.

Up close, the picture fractures. AEDIVE reports persistent problems with territorial distribution and administrative activation, meaning a meaningful share of installed chargers sit waiting for grid connection or paperwork, built but not selling a single kilowatt hour. Permitting varies across seventeen autonomous communities, each with its own set of rules, so a project timeline in Madrid tells you nothing about one in Extremadura. Deployment is concentrated in Madrid, Catalonia, and the Basque Country, while other regions barely move. And underneath all of it, electrified vehicles still make up under 2% of the national parc, even as registrations grow at double-digit rates. Spain is building infrastructure ahead of the drivers, which makes every placement decision carry more risk than it would in a mature market.

In a market this thin, intuition fails. The demand that exists is concentrated: around specific corridors, specific urban zones under low-emission pressure, and specific pockets of EV ownership. A charger a few kilometres off that concentration is a stranded asset for years, and Spain already has enough of those. What a Spanish operator needs is a way to see where the real demand signals sit: EV registration density, traffic volumes, points of interest, existing competition and more, before capital is committed and long permitting clocks start running.

Dodona answers that in both directions. Operators can score any candidate location against all the demand signals, and, where no pipeline exists yet, flip to outbound mode: define the criteria that matter, such as traffic thresholds, proximity to specific point-of-interest categories, distance from existing competition, etc., and let the platform generate candidate locations from scratch. And because every score breaks down into the underlying data, an operator can walk a landowner, a municipality, or an internal investment committee through the reasoning live rather than present a black-box recommendation. In a market where permitting runs through seventeen administrations, showing the data tends to move conversations faster than asserting a conclusion.

Dodona allows you to find greenfield locations that are specific to your charging scenario. e.g., on-the-go charging (close to motorways, away from competitors, and convenient to stop), destination charging (looking for convenient 1-2-hour dwell-time locations without competition), or public on-street residential (in residential areas away from competitors).

What each market can learn from the others

The three stories read as separate national problems. When put side by side, they become lessons that travel.

The Netherlands is a warning to Germany and Spain about timing. Grid scarcity did not arrive as a crisis announcement; it crept in behind a success story, and by the time it was undeniable, the queues were a decade long. Operators in markets where connections still feel routine should treat that as a window, not a permanent condition. A grid connection secured today is an asset your competitors may not be able to replicate in five years, and the cost of over-securing capacity now is trivial compared to the cost of queueing for it later.

Germany is a warning about static assumptions. A location assessment is a snapshot, and in a market where subsidised capacity lands by the thousands, snapshots age fast. The lesson carries to Spain's corridors, where several operators are racing to cover the same highways: the site that looks uncontested in this quarter's analysis may have two competitors breaking ground next quarter. Underwriting needs to account for where the market is heading, not just where it stands.

Spain is a reminder that the mature markets have half forgotten: deployment counts are not a business. Chargers waiting on paperwork, chargers placed for coverage optics, chargers a few kilometres off the real demand- all of it shows up eventually as utilisation that never arrives. Dutch and German operators planning their next phase would do well to hold on to the discipline Spain is being forced to learn early, because in every market, the money eventually stops rewarding installation and starts asking about revenue per site.

And one lesson holds everywhere: the operators coming out ahead in all three markets are those who understood each location in precise detail before committing, rather than finding out afterwards.

Where we fit in

Dodona is a charge point planning platform, and the way it helps maps directly onto the three problems above.

When opportunities are scarce and contested, as in the Netherlands, speed and precision on each one matter. Operators can score any candidate location within minutes and see how existing sites perform against nearby competitors, including the diagnostic behind an underperforming site: low footfall, too many chargers relative to demand, or a competitor that opened recently. Each cause points to a different fix.

When the pipeline is large, and the clock is running, as in Germany, operators import sites in bulk and get a ranked list scored against traffic, competition, demographics and dozens of other data layers in minutes instead of weeks, fast enough to fit inside a funding window.

When no pipeline exists yet, as in much of Spain, outbound mode generates candidate locations from the criteria that matter to your business. And wherever a decision needs defending, in front of a landowner, a municipality or an investment committee, every score opens up into the individual data behind it, so the conversation runs on evidence rather than on a black box.

If you operate charging infrastructure in any of these markets and want to see how your pipeline scores against the data, we should talk.