• twenty interoperable Smart Data schemes by 2035
• £36m of Industrial Strategy investment
• cross-sector Trust Frameworks and data sharing interoperability across the economy

https://www.gov.uk/government/publications/smart-data-strategy

For IB1, this is core to our work – and features the Perseus programme. It underpins how we will help deliver our sustainable economy into a data-enabled digital-first era, building the load-bearing foundations for trust, protecting our data rights, and delivering impact.

Open Banking took a decade to get right: we can now move much, much faster. The opportunity isn’t just ‘switching’, it’s opening up new markets and connecting financial flows to real-world outcomes at scale. The time to engage is now: the schemes being shaped today will define the data infrastructure of the next decade.

The UK has a great team helping to lead this, with Samantha as co-chair, the Department for Business and Trade (Siobhan, Agnieszka, Priya, and a growing support team), and non-govt Smart Data Council members including Henk, Adam, Liz, Charlie, Marie, Chris, Ezechi, Ghela, Helen, Joe, Josh , Louise, Maria, Nicola, Stephen, Jane, Lucy, Sue and many others across industry and government now engaged.

At Icebreaker One it’s what we’ve been building with IB1 Open Energy Perseus, STREAM and our Data Infrastructure work and we will continue to lead on Open Sustainable Finance.

The Act (which covers both consumer and business data) places significant emphasis on Smart Data Schemes. These schemes, which enable secure, user-authorised data sharing between organisations, stand out as a transformative step for the UK economy.  

The benefits are far-reaching, with the potential to unlock innovation, enhance competition, and improve user control and choice. Backed by the UK Industrial Strategy’s £36 million investment in new schemes across financial services, energy, and beyond, these changes promise real-world impact. Open Finance alone is estimated to boost UK GDP by £30.5 billion each year.

Done well, the Data Act will mean:

• Data portability and control of your data 
• Better access to useful data
• Clearer rules and stronger protections for safety and fairness
• Greater empowerment and control for users to enable data sharing
• Foundations for better data sharing governance to enable real-world benefits of apps, AI and related tech services, while better addressing rights, consent and permission

This includes: 

• A statutory code on automated decision-making

Meaning the government will create a legally-recognised code of practice to guide organisations that use automated systems to make decisions. 

• Greater enforcement of the rules

More power to enforce data protection laws, making sure compliance isn’t optional and bad actors are held accountable.

• Increased emphasis on DPIAs (Data Protection Impact Assessments)

DPIAs are risk assessments that organisations must carry out before starting projects that involve high-risk processing of personal data (e.g., large-scale surveillance, sensitive health data).

• What about this whole AI thing?

Advanced software (such as AI and machine learning) is now being used to analyse data and in some cases to automate decision making. These systems are joining data together, in new ways across our economy. If we are to build and maintain trust, both voluntary and regulatory frameworks are essential to ensure they operate not only within the law, but also transparently and in the public interest. You can contribute to our conversation on this here. 

Why Smart Data Schemes matter for a Net Zero future

Smart Data Schemes aren’t just good for the economy – they are essential for our Net Zero future, because decarbonisation requires faster, smarter decisions powered by better data.

Over the past five years, we’ve been turning this vision into impact across energy, water, transport, finance and beyond. Our key learning so far? Implementation matters.

Our data infrastructure is maturing to deliver real-world impact. Initiatives like Open Energy are open, networked and verifiable to enable faster, better decisions to be made across systems. To deliver a net zero future we need data to flow as efficiently as energy itself. 

Through Open Energy, we’re creating a connected web of energy data and have already shown how better access to data delivers tangible, net zero-aligned outcomes. 

For example: 

• Our work with Scottish and Southern Electricity Networks (SSEN), shows how improved data access can better align grid capacity with EV demand. 
• On the REACT project, we found that making data more accessible helps reduce delays in connecting green energy developers to the grid, enabling Transmission Owners to deliver critical infrastructure upgrades faster.

The Act also marks a major milestone for our work on Perseus, a national smart data initiative focused on enabling green finance for SMEs. Recently featured in the Willow Report, Perseus is a live example of how to operationalise Smart Data across sectors. Provisions in the Act (e.g. smart meter data infrastructure) directly strengthen our efforts to ensure every SME can access finance for the net-zero transition.

A decade in the making; the real work starts now

This moment is the culmination of more than a decade of work. In 2012, I was appointed founding CEO of the  Open Data Institute, as the UK became a global leader in open data policy. During my tenure, I initiated what became a founding paper asking Who owns our Data Infrastructure?. 

In 2015, I was appointed co-chair of the Open Banking Working Group that created the Open Banking Standard which proved that Smart Data Schemes could move from theory to practice, creating a blueprint for sectors like energy, telecoms, and transport. And, in 2023 I joined the UK Smart Data Council as its co-chair. 

It’s been over a decade since that initial work and the UK is once again setting the bar on data infrastructure. Legislation is just the starting line: to deliver real outcomes for our economy and our environment, we must now build on this foundation at pace, with the same ambition, urgency, and collaboration that brought us here.

Example:

Given the many conversations I’m in at the moment I believe it very important to have as much debate as openly as possible, as this impacts everyone.

Here’s a question:

How should the UK implement its National Data Infrastructure so that it provides consistent control, sharing, and security for data, much like other public infrastructures such as roads and utilities?

“Everything should be as simple as it can be, but not simpler”
[often attributed to Einstein]

Having initiated ‘data as infrastructure’ at a political level in the UK in 2013, I’ve been watching and learning on this for a long time. We’ve made remarkable progress in some areas, less so in others.

Let’s explore, starting with some lessons learned.

One immediate reflection is that as over 60 countries moved to copy the Open Banking Standard, those who took only ‘parts’ of the system tended to experience less ideal outcomes (to the point that they often add them back in later to help course-correct — most notable are those who thought this was ‘just a tech problem’ and only took the open API principles).

We can look to past UK data initiatives like MiData and Open Banking and potentially infer that voluntary-only initiatives and centralisation do not work, and that the decentralised nature of Open Banking was more successful. However, these are shallow reflections.

We can point to three factors beyond centralised or voluntary which are dependent on the use case:

1. Market incentives: there must be an economic argument that policy can then amplify or mandate. If there is no financial incentive, there will be no movement (regardless of central vs decentralised, mandate or not — mandates are also often ignored). Midata was mostly tech-led, Open Banking was use-case led.
2. Removal of friction: Removing transactional friction may seem like something everyone wants, but not if your current business model relies on it. There must be “something in it” for everyone, or at least a path to cost reduction or a new business model. Removing friction can help everyone go together: this is never a ‘technology problem’ (e.g. absence of a data ontology).
3. Mandates: if the friction is ‘too high’, regulatory intervention is necessary to mandate participation and move the market. However, if the market can demonstrate self-initiation, then ‘endorsement’ from government can be sufficient to drive impact. Value creation must be visible in both cases.

I believe that we need to embrace these factors in our systems design.

We need to:

1. work out where the lines are drawn between central, pre-competitive and competitive areas;
2. ask what the role of regulation is, and at what granularity
3. query how things can be implemented in a way that humans (and machines) can and want to adopt
4. ensure those governing, operating and participating can be helped in their assessments of compatibility and interoperability
5. work out how to prioritise and create clear (and stable) roadmaps that enable investment to be made

I believe that we can build on the success of sector-specific approaches:

The Open Banking model’s success lies precisely in its sector-specific, incremental approach. It focused on the unique needs of banking, where security, standardisation, and customer trust were paramount.

Copying the Open Banking model into other sectors (e.g., energy, transport, health) isn’t about duplication but about applying tested frameworks tailored to each industry.

Without considering the market incentives for participation we risk techno-utopian thinking

Instead of trying to create a complex, overarching architecture that risks being too broad, a sectoral approach allows for flexibility and adaptation to industry-specific challenges. This carries a risk of fragmentation, and equally a potential to mandate cross-sector interoperability without defining exactly what this means in detail for everyone. The risk of push back on over-reach is material and catastrophic (in terms of adoption, if it fails). Further, market-incentives will be market-specific.

Avoiding Over-Standardisation

National Data Architecture risks over-standardisation and could stifle innovation instead of enhancing it. Different sectors have wildly varying levels of data maturity, hugely variable data governance needs and challenges, and a one-size-fits-all approach is highly likely to impose unnecessary constraints on sectors that are not as ready for them.

For example, imposing the level of data governance on the industrial sector that is required in the financial sector is (today) not realistic. We are, however, on the frontline of that journey with ESG reporting today, and it highlights the complexity of that real-financial sector bridging. Incremental improvements, like extending Open Banking principles to energy or transport can allow industries to evolve organically while keeping governance controls and security as a priority.

Pragmatism of the Incremental Approach

The incremental, domain-by-domain approach may seem less ambitious, but it offers a practical pathway to innovation that can be adopted today. Trying to design a top-down, comprehensive national architecture from the outset risks paralysis by analysis and over-planning. Learning from Open Banking and rolling out smart data initiatives sector-by-sector allows for continuous improvement and responsiveness to real-world feedback, which may be more effective than a sweeping, coordinated architecture.

Interoperability Requires Industry Engagement

Interoperability relies on industry engagement. This is best fostered through practical, sector-specific initiatives like Open Banking. Imposing an overarching system from above risks of alienating key industry stakeholders, who may resist changes that threaten their business models (this happens in every sector already, today). Open Banking’s success came from the balance of regulatory oversight and industry cooperation, a formula that can be replicated in other sectors.

Market Failures Can Be Addressed Incrementally

There are (always) risks of market failures such as data hoarding (castle & moat is still the prevalent investment model for data businesses). These issues should be tackled incrementally through sector-specific mandates rather than a top-down architecture, but can be accelerated with top-down principles.

The competition fostered by Open Banking and similar initiatives already shows promise in tackling data monopolies. An incremental, practical approach allows policymakers to address market failures as they emerge, rather than trying to solve all potential problems with a one-time top-down design.

Trust is Earned, Not Imposed

Trust in data systems cannot be imposed from the top. While Open Banking was catalysed by regulation, it earned user trust through transparency, security, and gradual adoption, not through a top-down imposition. Similarly, rolling out frameworks sector by sector allows consumers, businesses and citizens to see the benefits and gradually gain confidence in the approach. Attempting to ‘mandate trust’ top-down could backfire, especially in sectors like health, where data privacy concerns are particularly sensitive.

At IB1, our Trust Frameworks are one tool (of many) that can help foster multilateral collaboration, building on Open Banking principles.

Decentralisation Encourages Innovation

The decentralised, minimised and pre-competitive nature of Open Banking has led to its adoption and innovation. A large, centralised approach would have risked locking in certain standards or technological pathways that could hinder future innovations. Allowing sectors to develop their own interoperable standards fosters a more competitive, flexible landscape, where innovations in one sector can inform developments in another, without being dictated by a single framework.

Data governance should aim to balance impact on rights and security
while minimising its own footprint and reach

While the idea of a unified, overarching data framework may sound appealing in theory, in practice it would risk being too rigid, slow to adapt, and detached from the unique needs of individual sectors. A more pragmatic approach — building on the lessons of Open Banking and extending these principles to other industries — may offer the best balance of innovation, security, and user control.

Please feel free to comment, or message me (via LinkedIn or directly)

Disclosure: I sat on the MiData energy sector board (mostly tearing my hair out on these points); co-chaired the creation of the Open Banking Standard (through which I learned so many lessons it could fill a book or two); was founding CEO of the Open Data Institute; am co-Chair of the Smart Data Council, and run this non-profit (IB1.org) working on data governance at sector and national scale.

Thanks to Chris, Frank, Paul, Hadley and others for their feedback and inputs.

Useful links

Lessons learned from Gaia-X Data Spaces https://www.sitra.fi/en/articles/eight-lessons-from-building-data-spaces/

ODI on Data Institutions 
https://theodi.org/insights/projects/rd-data-institutions/

Icebreaker One on how it implements data sharing 
https://ib1.org/what-we-do

Open Banking (implementation entity)
https://openbanking.org.uk

Additional narrative on cities
https://agentgav.medium.com/the-porous-city-92ae986cd43c

Other opinions
https://agentgav.medium.com

There was a huge amount of optimism in the room — that we are ‘at a transition moment’ where we could get this right, or miss opportunities, or create new risks.

As we are likely to do all of the above, we must to act now and work together to maximise the value for our society, our environment and our economy while addressing material risks. As I phrased it,

We can build on a critical mass, or end up in a critical mess.

We heard from digital identity providers about the huge growth and opportunities in the sector, from private sector companies that have seen ‘misuse’ of legal precedents to try and stop them adding value to consumers and workers, the scale of benefit to getting data interoperability right, and the risks that if we do not seize this moment to get data governance right then we are exposing ourselves, our economy and our country to systemic risks.

I wanted to summarise some of the key points from across the day, with a particular focus on the policy landscape, and what this means for us. The Government panel included a great cross-section of the ecosystem.

My main take-aways from the day are:

1. We need to take a bold and broad view of data’s role in our economy, as part of our industrial strategy
2. There are material opportunities to drive economic growth and improve market outcomes
3. There is a critical need for a coherent policy approach to data
4. Collaboration and coordination is essential, across government departments and with industry
5. There are many government initiatives: Digital Information and Smart Data Bill, National Data Library and AI Action Plan (and more) that need to be connected
6. Smart data policy is focusing on both customer and business data and we must align them, while letting each address their own needs
7. The upcoming smart data bill will give government powers to introduce smart data schemes in any sector
8. There is need to support strategy development with new ministers, and input is being actively sought now
9. Initiatives should be impact and value-led with a focus on user needs, not ‘tech-led’
10. Without robust, scalable and flexible data governance we will create new risks (especially with AI)
11. Smart data schemes are important for both consumer empowerment and market competition
12. Open Banking continues to be an exemplar
13. We must address the regulatory foundations, costs and incentives in the development of any Schemes
14. We must balance data protection with data access and innovation
15. Trust is central to development and investment is needed in capacity and capabilities
16. We must coordinate and collaborate with international initiatives, some of which are very well funded (e.g. the EU has invested €1B in Data Spaces)

Everyone in the room sees the potential of smart data initiatives to drive innovation and economic growth. There was also good acknowledgement of the complexities and challenges in implementing such schemes effectively. For example, there are material economic and societal risks of ‘corporate capture’ (e.g. castle-moat behaviours) and that it’s not a ‘technology problem’ (we have the tech today).

The design principles that we put in place now must:
1. Act to provide clarity (e.g. roadmaps) so everyone can plan
2. Act now: the time for theory is over
3. Address the (timely, material) risks of known unknowns

My policy view is that the UK has:

1. A comprehensive approach. It is cross-departmental and recognises the value of policy and regulation as catalysts to economic growth, service improvements, and legal protections.
2. A foundational legislative framework. Primary and secondary legislation will provide powers to introduce smart data schemes across sectors and create a foundation for data schemes across the economy.
3. An emergent approach to balancing priorities of data protection and security with the innovation and economic growth. The development of Trust Frameworks and Schemes, done well, should increase data access and portability while addressing risks of many forms.
4. A sector-based approach. It recognises that different sectors must own and shape their own destinies, while enforcing cohesion and interoperability across the legislative spectrum.
5. An understanding of the need for public-private action. Smart Data Schemes are powerful tools that can enforce these and must include:
   • Mandated participation
   • Mandatory interoperability between schemes
   • Regulatory oversight
   • Clarification on costs
   • Clarification on incentives (positive and negative)
   • Flexibility to adapt to market changes

There was general acknowledgement of the scale of the task ahead: multi-stakeholder engagement, alignment on language, building skills and capabilities, the articulation of material benefits, and the demonstration of impact to build trust, systemically and carefully, over time.

There is a growing public expectation of data portability, and we must align policy and their implementation with this culture change.

The foundation of open markets is transparency. The foundation of a digitally-enabled economy is interoperability. As such we must base our approach on open systems, and design for open.

The UK has led the world with initiatives such as Open Banking. It has, in some opinions, fallen behind over subsequent years. My opinion is the UK is ‘connected’ enough that it can rapidly redress this and, once again, accelerate to a leadership position. It has exceptional skills that can navigate the complex landscape of data rights and technological change to deliver economic, environmental and social benefits.

We must address the market architecture for an open (digitally-enabled) economy.

From a business perspective, I believe business leaders must now address data sharing at board level. Data isn’t ‘a technology’ — it makes markets.

I’ve long advocated that data increases in value the more it is connected. The imperative is, therefore, to reduce the friction to such connections. Smart Data Schemes can enable this at market-wide scale.

Businesses should understand that:

• Smart Data schemes will open up new opportunities for innovation and market entry
• preparation is needed for upcoming regulations and potential costs of scheme participation
• there is huge potential for cross-sector data applications and new product/service development
• that customer data portability and security will increase in importance
• there is a value in engaging with policymakers and investing in technologies to leverage smart data initiatives

The room was under no illusion that there are many material challenges. There will be a process of ‘creative destruction’, new threat vectors and many incumbent interests that will not want to address this systems change.

However, the ship is now leaving the port, the time for theory is over: time to act is now.

If you’d like to get in touch or follow progress, please connect on LinkedIn: Icebreaker One or directly with me, or join our mailing list.

Introduced by the EU in 2007, EPCs provide information on a property’s energy usage, using a ranking system of A – (the most energy efficient) to G – (the least energy efficient) as well as suggesting methods to improve energy efficiency. To paint a picture of the task at hand, 71 percent of UK homes do not meet EPC standard C, the minimum requirement to bring buildings in line with net zero.

Open data and accuracy

While EPC data could prove to be a useful instrument in framing policy ideas centred around a green economic recovery, we should first assess the potential flaws in this data. According to a report by Spec, around 2.5 million EPCs could be wrong because of errors in measurement standards and practices. What’s more, the Property Technology solution states that 90 percent of EPCs lodged use simple averages or standardised values rather than actual measurements.

Another seemingly glaring error is the depth of inspection. If an assessor is unable to see the use of energy efficient measures, such as loft insulation, then the software used assumes an insulation level in line with when the property was built. Meaning, that for a house built over 100 years ago, zero insulation will be assumed, providing an inaccurate portrayal of housing efficiency.

EPC data is publicly available in England and Wales under a UK Open Government license v3.0 with the exception of address data which is provided under a Royal Mail Copyright Notice. Open data access to real-time EPC datasets can improve functionality and enable interoperability between other government owned databases as well as providing value to academia and businesses. The UK government’s ‘Action Plan’ released in September 2020, lays out plans for the creation of a new EPC register by the end of 2020, addressing issues of accuracy and openness while also moving towards EPC ratings that are more reflective of actual household energy use, an important move given the increased number of people working remotely.

A tool for framing policy

Across Europe, EPC data is being utilised for policy making and monitoring. Bulgaria, for example, set its national recovery strategy using EPC data. And, in a pilot scheme run by the Energy Efficient Mortgages Initiative, lenders will be offering lower interest rates on mortgages for both new build homes and renovations based on EPCs. KfW’s Environmental and Energy Efficiency Programme provides subsidies to building owners, including long-term loans with low interest rates and grants. The German development bank uses EPCs to determine the efficiency level of a household, rewarding higher efficiency levels with higher funding.

EPC data can be a critical metric in forming policy and shaping green initiatives. And, with domestic homes alone accounting for around 15 percent of UK’s greenhouse gas emissions, the data provides both public and private owners and tenants with vital information, legal certainty and incentives to improve their household energy efficiency. But, in order for the government to meet its commitment to net-zero by 2050, EPC data needs to be more accurate, reliable and open. 

Find out more

On Monday 16 November 2020, our team will be hosting a session to discuss how policy interventions can help local governments, cities and regions accelerate innovation and drive toward a net-zero economic recovery from Covid-19 at London Climate Action Week 2020. Their remarks will draw on the preliminary findings of our net-zero Covid-19 recovery programme, Project Cygnus. To find out more about the findings which will touch on some of the content elaborated above, sign up for free here.

Judging by the UK government’s first announcement on how to make the economic recovery from Covid as green as possible, we may have to scale down our immediate expectations. On July 22nd, a joint announcement between Number 10, the Department for Transport and the Department for Business, Energy and Industrial Strategy was made, laying out the government’s £350 million plan to “cut emissions in heavy industry and drive economic recovery from coronavirus” (GOV.UK). Upon investigation, there are several things wrong with the plan.

The first one is obvious and doesn’t require any further digging: £350 million is absolutely nothing. The Lib Dems have laid out a £150 billion green Covid recovery package, and while it is light on specific details, the overall figure is a lot closer to what it will take to get this moving in the right direction. A £350 million pound plan might as well be a zero pound plan in the grand scheme of things.

Worse than that, some of the specific items in the £350 million plan have a very Dominic Cummings vibe about them. For instance, £15 million of the project is dedicated to a “New National Space Innovation Programme” which will “monitor climate change across the globe” and will look to protect local areas from the impacts of extreme weather by identifying changes in the environment. Often the government’s green Covid recovery package has the feel of something played around with in Number 10 and then hastily chucked out; a Special Advisor’s toy to have fun with as opposed to a serious plan for reaching difficult emissions targets.

Trying to be positive about some aspects of the green recovery plan, there is a large chunk set aside for Carbon Capture and Storage that could lead to something positive in the coming years. There is also part of the £350 million set aside for construction tech, which given retrofitting houses to make them more energy efficient needs to be part of any UK green recovery plan, is welcome. The money in there for R&D around electric cars is comforting. Yet again, one has to come back to the paltry amounts we’re talking about here: £10 million for the construction tech and £10 million for electric cars R&D are simply not serious amounts of investment in either important area.

One can try and be as forgiving as possible here and say that the £350 million plan announced in July is simply the government’s starter for ten, and much more will be coming down the pipeline. They will do more thinking and put more resource towards this once the UK-EU trade negotiations are no longer in the way, surely. I can only hope that this is the case.

Reference: Australian policy consultation — Energy Rules Framework

Icebreaker One Response — August 2020

Executive Summary

We welcome the publication of this consultation document and fully support consumer control over their energy data through the Consumer Data Right (CDR). We believe this is an inflection point that will enable a thriving ecosystem of private service providers, new entrants and existing energy stakeholders, expanding to provide the innovation the whole system requires to meet its goals. Access to data will clarify inefficiencies and identify opportunities, bringing considerable efficiency gains and savings as digitalisation, decentralisation and decarbonisation accelerate.

To achieve this, the use of energy data must be characterised by strong governance, standards and architectural agility. We hold an ambitious view for the future energy system: one which is highly innovative, delivering strong environmental, economic and societal benefits by fostering a decentralised data ecosystem, enabling widespread machine-to-machine data exchange and the ability to address privacy challenges. This will require additional consumer protections and enhanced rights. We advocate the principles of consumer primacy, control of consent throughout the provisioning chain, and greater emphasis on liability and redress. 

We recently published relevant reports through our associated company, Dgen, for the UK Government on consent, liability and redress. These are pertinent to your consultation and you can find them here:

https://www.gov.uk/government/publications/smart-data-research-on-consent-liability-and-authentication

Overview of Icebreaker One 

Icebreaker One is an independent, non-partisan, global non-profit. Our vision is to develop the data infrastructure to deliver a demonstrably net-zero future. We connect private and public sector leaders to help reduce risk and grasp the opportunity to transform the climate crisis into economic innovation.

We understand that every asset, system, organisation and network in energy (and beyond) will be producers and consumers of data. These systems will increase in complexity: they are not only being digitalised, they are becoming data-driven. The growth in data connections will be exponential as the market matures. 

We believe the energy ecosystem must implement a data architecture which can scale in data-type, volume and connectivity, across use-cases, organisational and logistical boundaries, sectors and jurisdictions. It must deliver this in a secure, safe, robust and adaptable environment with trusted governance. 

Responses to Consultation Questions

We have responded to questions 1, 2, 3, 4, 20, 22, 24, 26, 34, 35 where we believe Icebreaker One (IB1) expertise and experience will be helpful. 

Consultation questions: an approach to data sets in energy rules

1. Do you agree with our proposed approach to data sets in the energy rules? Why or why not?

We recommend that all data sets and assets should include descriptive metadata. The approach adopted should enable the ability to “crawl” energy metadata for both open and shared data. This approach enables searchable energy datasets and assets and understands relationships and meaning. Furthermore, it will enable links to be created between related assets and datasets e.g. metadata about a dataset linking to metadata about the physical asset from which the dataset was recorded.  

2. Considering the above discussion about potentially sensitive information, what data, if any, should be subject to specific arrangements (for example, during the consent process)? Should any particular sensitive data be explicitly excluded from the proposed data sets?

We agree that hardship details and concession details be separately categorised to allow ADRs to clearly explain the purpose and benefit of a consumer consenting to the sharing of these data sets. This confirms research in the UK by the Money & Mental Health Policy Institute which considered how firms might use data which suggests a consumer may be vulnerable. A key recommendation from this was for government to create a shared space for regulators, firms and consumer groups to consider how such data can be used appropriately. Ethical use of data must be a key focus of regulation and should ensure that those consumers choosing not to share such sensitive data do not face prejudice.

Moreover, it is essential that consumers are fully informed when making decisions and are asked to consent. From a consumer perspective ‘consent’ is often not clear because to access a product or service consumers must understand and agree the company Terms and Conditions as well as the way in which their data will be used. This is a lot of information to absorb and is often poorly presented. This raises the risk that consumers do not genuinely understand what they are agreeing to, and the potential consequences of their actions. 

We, therefore, recommend that a Standard for consent that requires ADRs to put the interests of consumers first. This should be implemented as a codified approach with a common set of parameters and values that is presented to the consumer in an easily understood way. For example, such a standard should include:

• The purpose of data sharing (with a clear explanation of the value exchange)
• Other organisations involved in the data sharing, if this is the case
• What data items will be shared
• Draw attention to any sensitive data
• Access and individual rights of the consumer
• Information governance arrangements (such as accuracy of data, the deletion of data, termination of data sharing and complaints management)
• End date and review periods for the agreement

This should be developed from the consumer perspective, with an emphasis on comprehension and user experience, and allowing for the interconnected nature of the data provisioning chain.  We note that such a Standard would enable the development of an API specification and associated metadata that enables the detail of the consent to be checked by other parties in any provisioning chain or carried alongside the consumer’s data in an API payload. This requirement is not unique to the energy sector and should be applied to any sector where personal data is shared. We trust that these aspects of the consent approach and process are included in the scope of the planned work on authentication and authorisation. 

Consultation questions: approach to the Rules, standards and privacy safeguards to accommodate the gateway data access model

3. Do you consider the proposed approach to the gateway rules, standards and privacy safeguards appropriate for CDR in energy?

We are concerned that the proposed approach may limit the potential for the use of energy data in Australia. While noting the rationale behind the original decision and extensive stakeholder engagement, we are encouraged at the inclusion of a 3-year review of the gateway approach as in the longer-term this approach:

• Will create a single point of failure;
• May prove to be costly and inefficient to ensure consistent, reliable real-time access to the data required in use-cases that will become widely adopted;
• Adds a layer of complexity in the development of the CDR rules and data standards to ensure interoperability with the broader CDR ecosystem, potentially hindering the emergence of cross-sector services; 
• Is not the favoured option for innovative technology companies that will be critical in the drive to decarbonise;
• Does not, in our view, take into account the powerful mitigating impact in the economy-wide model of Technology Service Providers, which have emerged in the data-sharing ecosystem to provide integration, implementation and aggregation services, as well as consent management services.

Our experience through extensive stakeholder engagement in the UK energy sector repeatedly emphasised that there cannot be a ‘single platform’ in which ‘all data is put’ to address ‘all use cases’. Energy data is highly diverse and is evolving too rapidly for any central, proprietary IT system to keep up.

4. If not, which aspects of the approach should be reconsidered or amended, and why?

We favour a fully decentralised approach – akin to the economy-wide model considered – in which data and metadata is distributed, always up-to-date, and managed real-time on data holders’ servers.

We acknowledge that decentralised data and asset search is challenging and existing datasets are not strongly linked. However, search and discovery technology offers a solution to this problem.

Data should be searchable, accessible and available to agreed standards. This approach can provide the common rules, controls and processes needed for access, discovery, security, commercial applications, privacy and regulatory compliance. This will enable an energy data ecosystem to develop, which will lead to greater innovation that brings both direct consumer benefits and will support solutions that enable more rapid decarbonisation.

Consultation questions: dashboards

20. Of the three options for data holder dashboards, which do you prefer and why? 

We welcome the inclusion of dashboards as a tool to enable authorisation and consent management. However, we recommend that an alternative approach is considered, enabling new approaches and entities for consumers to manage their consents. It will be insufficient to consider just the retailer or AEMO, as we fully expect a thriving ecosystem of third party service providers to develop innovative, value-adding solutions as the market develops. This will lead to complexity in the provisioning chains as data will necessarily be shared with other parties. This means that consumers may be faced with managing many consents, some of which is likely to relate to data drawn from multiple sectors.

Given the complexity of managing ongoing consents, and the proliferation of consent and access management across those sectors opening up to the data-sharing ecosystem, it would be useful to consider early how this could be managed most effectively for the consumer and market alike so that they have the tools and a good understanding of the way in which these tools can be used. Alternative models should therefore be explored.

22. What other options should we consider? 

We recommend consideration of new models such as companies or entities that undertake the management of the consumer’s consents on their behalf across all sectors covered by the CDR. This can be achieved using a common consent standard, API specifications and associated metadata. 

24. What consumer experience factors should we take into account with respect to how dashboards should be presented to CDR consumers?

We strongly recommend a common set of language, with common terminology applicable across sectors wherever possible.  From the consumer’s perspective, easily comprehensible words and phrases must be widely used that are easy to read and well understood. This will encourage wider acceptance, trust and adoption of services.

We also recommend that dashboards should be considered as tools which enable consumers to view which data has been received into the firm, as well as data which the firm has shared with other participants (data ‘in’ and data ‘out’). 

Dashboards should include:

• The recognisable consumer brand with whom a consumer has shared their data, and any party to whom data has been onward shared.
• The specific data clusters/types being accessed, clearly explained.
• Why the data is needed – the purpose, so that this can be easily understood.
• What specifically it is used for – the processing activities and any sharing with other parties in a provisioning chain.
• The duration that access to the data is granted for.
• Their rights, and the way in which they can manage their data should be clearly explained.
• The ability to revoke consent and notification that this has taken place and how data collected previously will be dealt with (e.g. ‘put out of use’/’deleted’)
• Consents should be sortable and clearly outline those which are active, expired or cancelled

Additionally, the introduction of a recognised approach to the provision of consent management tools, and potentially a guarantee or certification will help consumer trust. The location of the dashboard should be easy to find from the main menu. You may also wish to make requirements about the accuracy and timeliness of the data held on the dashboard (for instance, the dashboard should update in real-time to avoid any miscommunication).

Consultation questions: internal dispute resolution

26. How important do you consider consistency of IDR approaches across sectors at this stage of the CDR regime? 

We observe that, as a proxy measure, the UK Open Banking initiative has undergone a rapid evolution in the way in which products and services are provided to consumers, through complex provisioning chains. We believe that this will become a characteristic across all markets and sectors. We observe new risks associated with opening up data as well as the risks which are exacerbated by the intelligence afforded by data. Data risks are often interlinked so that a mistake at a data holder creates risks downstream, not just for the ADR but for other parties involved in the provisioning chain. 

Furthermore, data will be used in services which cross regulatory/sector perimeters, meaning that there must be a consistent approach so that consumers can always feel confident and trust that if anything goes wrong, they know how to have things put right. In particular, consideration should be given to the assessment of liability and apportionment of redress both in the energy sector in and cross-sector, cross regulatory cases, which will prove to be complex.

We, therefore, recommend that early attention is given to the creation of a single, accessible dispute resolution system for problem resolution, that facilitates effective inter-organisational communication and has common rules and processes. This will require consistency between regulatory approaches across different sectors.

Internal Dispute Resolution will be greatly improved where data is more easily traceable. We, therefore, recommend that metadata attaches to consent. This aids discussions about liability and dispute resolution.

We also recommend that consideration is given to how consumers may access redress which is simple, free and timely without recourse to the courts. This work includes understanding the value of energy data, how it may be used by nefarious actors (e.g. isolating when a family are at home and when the house is empty for instance), and what the value associated with privacy, were this data to be breached. This includes consideration of the use of energy data outside the energy sector by other third parties and the jurisdiction of any ombudsmen. 

Consultation questions: issues relating to accreditation

Energy data

34. Do you agree that energy data sets are less sensitive than banking data sets?

We agree with this statement at present, but advise that this situation will change. As energy generation decentralises and decarbonises, with wider use of DERs, data originating at the household level (including personal data) will become more widely used. Therefore, the sensitivity of this data will increase. Moreover, the combination of energy data with data from other sectors will enable greater levels of analysis and inference.

35. Should any energy data sets, or subsets of those data sets, be treated with a higher degree of security (due to potential sensitivities), similar to banking data?

Any data originating at household-level, or where individuals and their behaviour are identifiable, should be treated with a higher degree of security. We see a range of use cases, such as home energy management or localised/community resource management where such data will be critical.