From behaviour change to behaviour coordination

What the transition from petro-state to electro-state means for behavioural science

“London is cooking,” warned the UN Secretary-General António Guterres, as another European heatwave gripped the continent. Europe is now the fastest-warming continent on Earth. At almost the same time, conflict in the Middle East once again exposed the fragility of the fossil fuel system, sending oil markets into turmoil and reminding governments how exposed modern economies remain to geopolitical shocks. In April this year, when Ipsos asked the UK public what should happen if the Strait of Hormuz were closed, a majority, 51%, said Britain should invest more in renewable energy rather than increase its dependence on fossil fuels.

These are often treated as separate stories: one about climate, the other about energy security. But they are becoming the same story. The age of the petro-state, where economies are built around the extraction, transport and consumption of fossil fuels, is beginning to give way to the electro-state: a system in which electricity becomes the primary organising medium of economic life, and where homes, vehicles, appliances, grids, tariffs, data systems and public policy all have to work together.

But moving from a petro-state to an electro-state is not simply a matter of replacing one source of energy with another. It requires a fundamental reorganisation of how energy is produced, distributed, stored, consumed and governed. The defining resource of the petro-state was oil. The defining capability of the electro-state is coordination.

That means coordinating generation, storage, demand, investment, infrastructure, finance, regulation and everyday behaviour. And the mechanism that makes this possible is not electricity alone, but information. More specifically, it is ‘Smart Data’. If electricity is the lifeblood of the electro-state, Smart Data is its nervous system.

This then changes what behavioural science needs to pay attention to. The challenge is not simply persuading people to buy an electric vehicle, install a heat pump, or shift their laundry to a cheaper hour. It is understanding how millions of interconnected decisions, made by households, firms, regulators, investors, network operators, technology companies and government, can be aligned into a functioning system.

That is a behavioural problem of a different order. Not behaviour change as individual persuasion, but behaviour change as system coordination.

The co-ordination challenge

The transition to clean energy changes not only how energy is generated, but how the whole system has to work. Recent energy policy and systems analysis increasingly frames clean power as a whole-system challenge involving grid expansion, flexibility, storage, demand response, digitalisation, planning reform and consumer participation

A fossil-fuel system is built around relatively centralised and dispatchable forms of generation, where supply can largely be scheduled to meet forecast demand. A renewable electricity system, by contrast uses wind and solar which are forms of variable renewable generation. They produce power when weather conditions allow, not necessarily when households, businesses or the grid most need it. This does not mean renewables are unreliable but it does mean their output is less directly controllable than fossil fuels, making timing, storage, demand management and grid flexibility much more important.

And this is what makes coordination so critical. In the old energy system, coordination mainly meant ensuring that centralised supply could meet forecast demand. In the emerging electro-state, coordination means aligning variable renewable generation, household demand, local storage, flexible tariffs, consumer data, grid constraints, institutional accountability and everyday routines. The system has to balance variable supply with increasingly variable demand.

In an electro-state society, electricity becomes the primary organising medium of economic, domestic and institutional life, and managing flows of power, data and demand becomes a core task of governance. Energy is no longer just a utility in the background but is instead a live coordination system linking homes, vehicles, appliances, tariffs, grids, suppliers, finance, data platforms and public policy.

At the same time, the role of the public changes as people are no longer simply recipients of energy. Through solar panels, batteries, electric vehicles, heat pumps, smart meters and flexible tariffs, households and small businesses can become consumers, generators, storage points, data producers and flexibility providers. A home with solar panels, a battery, an EV and a smart meter is not just a point of consumption but a node I(albeit small) in the energy system.

We can see how this might play out in the everyday life. A household might generate solar power during the day, charge an EV overnight, run a heat pump during colder periods, export surplus electricity, shift washing or dishwashing to off-peak times, and allow a third-party service to check whether its tariff still makes sense. None of those actions is especially dramatic on its own, but together they show how the household becomes woven into the operation of the system.

The coordination challenge is not only created by the variability of renewable generation. It also arises because the UK is moving towards a more mixed, distributed and institutionally complex energy system. Clean power will require wind and solar, but also complementary sources of firm or baseload power (such as nuclear) and alongside storage, grid reinforcement, demand flexibility and new local energy projects. This means the transition cannot be understood as a simple replacement of fossil fuels with renewables. It is a reorganisation of the whole energy system.

That reorganisation is physical as well as institutional. New generation has to connect to the grid in the right places; network capacity has to be upgraded where demand is rising; Distribution Network Operators have to manage more complex local flows; and households, communities and businesses may increasingly generate, store and shift energy themselves. GB Energy’s emphasis on co-investment, community energy and a less centralised energy system points to this wider shift: energy is becoming more distributed, more local, and more dependent on coordination between public institutions, private investors, local authorities, network operators and consumers.

This matters because the energy transition is also happening against the backdrop of a severe affordability and debt crisis. Ofgem reported that by June 2025, domestic consumer energy debt had reached £4.43bn, up 20% on the same point in 2024 and 71% since 2023, with nearly three quarters of this debt held by customers who had no repayment plan in place. Energy UK has warned that, without urgent intervention, total energy debt could rise to more than £7bn by the end of 2026.

That changes the stakes. Smart energy cannot be framed only as a future-facing optimisation agenda for confident, digitally enabled households. It also has to address the needs of people already struggling with bills, arrears and mistrust. For those households, the question is not simply whether Smart Data can help them shift demand or access better tariffs, but whether the system can make support, savings and protection visible before debt deepens further.

This is where Smart Data matters. In energy, Smart Data is not just a mechanism for sharing household energy data; it is one of the informational infrastructures through which the electro-state might become governable. It can help make distributed energy behaviour visible, connect households to better tariffs and support, enable trusted intermediaries to act, identify emerging debt risk, and align individual decisions with wider system needs. But it only becomes coordination if data is connected to governance, incentives, interfaces, consumer protection and trust.

In practice, this could mean a trusted service using smart meter and tariff data to check whether a household is on the right tariff, estimate savings from shifting usage, identify signs of debt risk earlier, support access to grants or retrofit finance, or help automate decisions such as EV charging within consumer-set boundaries. The point is not simply that more data becomes available, but that data is translated into services that reduce complexity and make better action possible.

Of course, this cannot be assumed: many households already have smart technology, especially smart meters, and many say they could shift at least some electricity use to off-peak times, yet the same polling also points to confusion around tariffs, low trust in energy companies, uncertainty about savings, and hesitation around sharing household energy data.

So the challenge is not simply awareness, nor is it simply willingness. The challenge is whether Smart Data can help make the energy transition legible and actionable to the people being asked to participate in it, including those for whom energy is already a source of financial stress rather than future-facing opportunity.

Smart technology is present, but Smart Data is not yet legible

Ipsos polling among 2,222 UK adults aged 16–75, conducted between 15 and 19 May 2026, suggests that smart technology is already present in many homes. Just over half of respondents said they had a smart meter, while a quarter said they had none of the listed smart technologies; other technologies were less common, with 17% reporting smart heating controls, 15% a smart washing machine, tumble dryer or dishwasher controlled via an app, 14% a hybrid or fully electric car or van, and 10% solar panels.

So the issue is not that the public is entirely outside the smart energy landscape, because many households already have some form of smart infrastructure. The issue is that the concept of Smart Data itself is much less settled, with 34% saying they were familiar with the concept and 35% saying they were unfamiliar.

This distinction matters because having a smart meter is not the same as understanding how household energy data might be shared, with whom, under what safeguards, and to what benefit. A smart meter may produce data, but it does not automatically create a trusted data relationship, nor does it automatically help a household make better choices.

The polling therefore points to a gap between the presence of smart devices and the understanding of the Smart Data proposition. The first coordination challenge is not installation, but a behavioural one - sensemaking: people may have the infrastructure, but not yet the mental model that allows them to understand how data-sharing connects to value, protection and control.

This matters more in an electro-state than in a traditional energy system because the household is no longer simply at the end of the pipe. As homes become sites of consumption, generation, storage and data production, the ability to understand and act within the system becomes part of the system’s functioning. If people cannot see what role they are being asked to play, the technical infrastructure may exist without becoming socially usable.

Energy anxiety creates motivation, but not automatic trust

The context for Smart Data in energy is one of widespread concern in the UK at least. Three quarters of respondents (77%) agreed that they were worried about the cost of energy, while around half also agreed that comparing suppliers and tariffs is confusing (53%) and that they do not trust energy companies to give them the best deal (52%). At the same time, around half said they felt confident they could switch to a better energy deal if they wanted to (51%) and that they were on the best energy tariff for them (50%).

This combination is revealing because people are worried, but not necessarily passive. Many feel some confidence, but that confidence exists alongside confusion and distrust; in other words, there is motivation in the system, but it is not yet converted into stable trust or action.

For Smart Data, this is crucial. A household worried about energy costs may be highly receptive to a service that helps them save money, but that same household may also be sceptical about sharing data, uncertain who is acting in their interest, and anxious about whether promised savings will actually materialise.

The energy debt context makes this even sharper. For households in arrears, or close to arrears, mistakes matter, because a confusing tariff, a badly explained data-sharing proposition, an unexpected bill, or a failed switching experience may not simply be inconvenient but financially dangerous. The more precarious the household, the more the value exchange has to be concrete, reliable and visibly protected.

This is also where the work on scarcity is useful. When people are managing debt, bills, arrears and immediate trade-offs, they have less cognitive bandwidth available for complex administrative tasks or abstract future benefits. A Smart Data service that assumes people will compare options, understand permissions, assess risks and act on recommendations may therefore be asking the most burdened households to do the most cognitive work.

For these households, good design is not about giving people more information. It is about reducing the burden of coordination. The more precarious the situation, the more the system needs to do the work: identify entitlement, simplify consent, make savings concrete, offer trusted support, and reduce the risk of costly mistakes

The polling therefore suggests that energy anxiety is not enough. People do not just need a problem that makes them motivated; they need a trustworthy route through that problem, and they need to believe that sharing data will reduce risk rather than increase it.

Flexibility exists, but it is conditional

One of the most striking findings is that many people say they could shift some electricity use to off-peak times. Eight in ten respondents said they could realistically shift at least some of their electricity use without major inconvenience, with 34% saying they could shift “some” use, around 10–30%, and 24% saying they could shift “a lot” or “most”.

This looks promising for the energy transition, because it suggests there is latent flexibility in households. But willingness is more qualified: when asked how willing they would be to shift electricity use to off-peak times to save money, 46% said they were extremely or very willing, while 27% were moderately willing, 18% slightly willing and 4% not at all willing.

That gap between ability and willingness is where the coordination problem becomes visible. Households may be able to shift energy use in principle, but practical participation depends on work patterns, family routines, trust in billing, clarity about savings and ease of action.

Among those who were not, slightly, or moderately willing to shift energy use, the leading barriers were work patterns, selected by 35%, and not knowing how much money they could save, selected by 33%. A further 19% cited lack of trust that energy companies would charge the correct rate, and 19% cited caring responsibilities or family routines.

This is not a simple motivational deficit, because it is not enough to say that “people should shift energy use”. The system has to make shifting intelligible, rewarding and low-risk, which means behaviour sits downstream of system design rather than simply upstream of it.

This is also why variable renewable generation makes coordination more important than it was in the old system. If wind and solar generate at times that do not always match demand, flexibility becomes a system resource. Households are not just being asked to save money; they are being asked, implicitly or explicitly, to help stabilise a system where timing matters more. But that only works if the terms of participation are clear enough for people to trust.

For households under financial pressure, this is especially important. Flexibility cannot just be presented as an abstract contribution to grid efficiency; it has to become a credible household benefit, with people knowing how much they might save, how the saving will be calculated, what happens if routines make shifting difficult, and whether automation can reduce the burden. Otherwise, demand flexibility risks being experienced as yet another responsibility placed on households already managing too much.

Trust is unresolved because accountability is unclear

Smart Data relies on people allowing their data to be used by others to create better services. The polling suggests some openness, but also significant hesitation: just over half of respondents (54%) said they would be comfortable for household energy data to be shared with authorised third parties, while 38% said they would not be comfortable.

The strongest levers for increasing comfort were concrete and protective. A clear financial benefit was selected by 41%, as was a guarantee that data would not be sold or shared with other companies; a trusted independent organisation checking that companies were using data properly and in consumers’ best interests was selected by 34%, and a clear explanation of what data is being used by 31%.

This tells us that people are not simply asking to be educated; they are asking for evidence of value, boundaries around use, independent assurance and clarity. They want the exchange to be worth it, but they also want to know that it will not be exploited.

The unresolved question is where trust should sit. When respondents were asked who they would most trust to check whether they were on the best tariff using smart meter energy data, 27% selected their energy supplier, 16% selected a price comparison website, 15% a government-backed or certified service, and 9% Citizens Advice or a consumer charity. But 11% said “no one” and 14% said “don’t know”.

This is not just a supplier reputation problem, but a governance problem. If a quarter of the public either trusts no one or does not know who to trust, the system has not yet made accountability visible.

There is also an incentive question sitting beneath the trust question. Consumers are being asked to allow data to move through a system in which different actors may not benefit in the same way: a household may want lower bills, a supplier may worry about lost revenue, a third party may seek a new commercial relationship, and the system may need demand to shift for grid reasons. Smart Data therefore has to make the alignment of interests visible, because if people cannot see who benefits, who is accountable, and how errors are corrected, data-sharing may feel less like empowerment and more like exposure.

This is also a question of fairness. Smart Data may create value for the energy system by making demand more visible, enabling flexibility, reducing pressure on the grid, improving targeting of support, and helping suppliers or third parties design better services. But consumers will only participate if they believe that value accrues to them as well.

This is not just a commercial issue. It is a psychological one. People are highly sensitive to distributive justice: who gets what, who benefits, and who loses out. As Milton Friedman argued, even market societies depend on people believing that the distribution of rewards is broadly legitimate. If the gains from Smart Data appear to sit mainly with suppliers, platforms, aggregators or the system operator, while households are asked to provide data, change routines and accept automated decisions, the exchange may well feel extractive rather than fair.

Procedural justice matters too. People may accept unequal outcomes if they believe the process is transparent, accountable and governed by rules they can understand. But if the process feels opaque, if it is unclear who benefits, or if consumers cannot see how errors are corrected, then even technically useful services may face resistance. This is especially true where energy costs are central to people’s sense of security and standard of living. In those circumstances, an unfavourable outcome is not experienced as a minor inconvenience. It feels personal.

For Smart Data to feel legitimate, consumers need to see a fair return: lower bills, clearer tariffs, easier access to support, reduced administrative burden, stronger protections, or more control over how their household participates in the energy system. The value created by household data and flexibility cannot simply disappear upwards into the system. It has to be visibly shared.

A functioning Smart Data system will therefore need more than authorised data flows. It will need a visible trust architecture: certification, redress, auditability, clear consent, independent oversight and simple explanations of who is acting in whose interest.

This is particularly important in a debt-heavy energy market. When many households are already behind on bills, trust is likely not a soft factor, but a condition of participation. Consumers need to believe that data-enabled services will not worsen their position, expose them to disadvantage, or make it easier for providers to optimise against them. For Smart Data to support affordability, the public must be able to see not just the technology, but the protections around it.

Smart Data has to coordinate production, demand and protection

The promise of Smart Data is often presented in terms of better services: easier tariff comparison, smoother switching, more personalised advice, improved account management, or better support for green home upgrades. Those are all important, but in energy the deeper issue is that Smart Data has to sit across three forms of coordination at once.

First, it has to help coordinate the physical system, where variable renewable generation, local generation, household demand, storage and grid constraints have to be balanced over time. Second, it has to help coordinate the market system, where suppliers, third parties, price comparison services, regulators and consumers need clear rules about data access, value creation and accountability. Third, it has to help coordinate the social system, where people need to feel that participation is understandable, beneficial and safe, especially when many are already worried about bills or carrying energy debt.

This is why Smart Data cannot be treated as a consumer-facing add-on to the energy transition. It is one of the ways the emerging electro-state tries to see and organise itself. It can make demand more visible, make flexibility easier to locate, allow trusted services to act on behalf of consumers, and connect individual household decisions to wider system needs. But visibility is not the same as coordination. Data only becomes coordination when it is translated into services, incentives, protections and decisions that different actors can rely on.

This also changes what “consumer engagement” means. In the old model, engagement might have meant understanding a bill, switching supplier, or reducing consumption. In the electro-state, engagement may mean allowing an EV to charge at a certain time, letting a third party assess tariff suitability, using household data to access support, responding to a flexibility incentive, exporting solar power, or accepting automated optimisation within boundaries the consumer can understand and control.

That is a much more demanding relationship between citizen and energy system. It requires more than information. It requires confidence that the system is coherent, and that the value created by household participation does not simply disappear upwards into institutional or platform advantage.

Visibility is not the same as agency

There is also a property and tenure problem. Many households cannot act as energy participants in the way policy rhetoric sometimes assumes. Renters may not be able to install solar panels, batteries, heat pumps or EV chargers, leaseholders may depend on building-level decisions and lower-income households may lack the capital to benefit from technologies that create flexibility in the first place. This means that whilst Smart Data can make opportunities more visible, visibility is not the same as agency. If the system identifies better options that people cannot practically take up, it may expose constraint rather than resolve it.

This matters because the risk is not only that people do not adopt Smart Data but that Smart Data becomes an optimisation layer for the already-capable and a value-capture mechanism for institutions: people with EVs, solar panels, batteries, flexible routines, digital confidence and spare attention benefit most, while suppliers, platforms and intermediaries capture new commercial value from household data and flexibility. Meanwhile, those in debt, rented housing, unstable work or low-trust relationships with suppliers may be left with fewer gains, more exposure and a stronger sense that the system is being optimised around them rather than for them.

This is the political challenge of the Smart Data agenda. Whilst it could help democratise access to better tariffs, better advice and earlier support, it could also sharpen existing inequalities if the system is designed around the needs of those already best placed to act. In that sense, the challenge is not simply adoption but distribution: who can benefit, who carries risk, who captures value, and who gets left managing complexity without the assets required to turn information into action.

Familiarity matters, but the deeper issue is system legibility

The Ipsos polling suggests that familiarity with Smart Data is associated with greater confidence around tariffs, switching and shifting usage. Those familiar with Smart Data appear more likely to say they could shift at least some energy use (89% versus 77% of those unfamiliar), and more comfortable sharing data (72% of those familiar versus 46% of those unfamiliar).

This pattern is important, because familiarity may matter not simply because people have heard the phrase “Smart Data”, but because familiarity gives people a stronger sense of how the system works. They can imagine the connection between data-sharing, tariff comparison, savings and control, which makes the proposition feel less abstract and more usable.

The practical task is therefore not just awareness-raising. It is making the system ‘legible’.

People need to understand what data is being used, who receives it, what service it enables, what benefit they can expect, what protections apply, and who is accountable if something goes wrong. Without that, Smart Data risks becoming another opaque market mechanism in a sector many already find confusing.

This also reframes the energy debt issue. Households in or near arrears are not simply a vulnerable group to be protected at the margins, but central to the legitimacy of the whole system. If Smart Data only works for confident, affluent, digitally enabled households, it will deepen the perception that the energy transition is something done for the already-capable. If it can help identify risk earlier, route people to support, make savings tangible, and reduce the administrative burden of managing energy costs, then it becomes part of a fairer transition.

Smart Data as coordination infrastructure

The transition to an electro-state ultimately asks a different question of behavioural science. For decades, the field has excelled at understanding individual decision-making: how people respond to incentives, defaults, information, norms and choice architecture. Those insights remain valuable, but they are no longer sufficient.

The defining behavioural challenge of the energy transition is not persuading individuals to make better choices in isolation. It is enabling millions of interconnected decisions, made by households, suppliers, regulators, network operators, investors, technology companies and government, to reinforce rather than undermine one another. In other words, the challenge is no longer behaviour change as individual persuasion, but behaviour change as system coordination.

This demands a shift in perspective. Rather than asking how we encourage people to adopt heat pumps or electric vehicles, we should ask how we design systems that make those choices easier, fairer and more rewarding. Rather than treating Smart Data as another digital service, we should see it as coordination infrastructure: a way of helping distributed actors see one another, align incentives, reduce friction and build trust across an increasingly complex energy system.

Success, therefore, will not be measured simply by how much data is shared or how many households sign up to new services. It will be measured by whether the system itself becomes easier to navigate, whether the benefits of participation are distributed fairly, and whether the burden of coordination shifts from individuals to institutions capable of carrying it.

Perhaps that is the deeper lesson of the electro-state. The transition to Net Zero is not simply an engineering challenge, nor even an energy challenge. It is a behavioural coordination challenge. And if that is true, then the future of behavioural science lies not only in understanding how people make decisions, but in understanding how societies make systems work.