Please note that throughout this response, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer. 

Call for evidence response:

1. What energy problem do you want to solve? 

There is a wide range of energy use cases identified and highlighted in IB1’s response to DESNZ’s Developing an energy smart data scheme: call for evidence (question 14). There are core principles IB1 recommends embedding. 

Smart Data becomes effective for use in AI and in decision making when it is connected

In terms of prioritisation of sector, use cases requiring cross-sector interoperability and cohesion offer the greatest immediate ability to create impact, with a manageable degree of complexity involved in rollout. 

Regardless of use case, codify a requirement to contribute to net zero

As mentioned in IB1 response to Ofgem’s AI in the energy sector guidance consultation, we acknowledge and appreciate Ofgem’s commitment to encouraging innovation while helping the UK to meet its net zero target and other associated targets. As mentioned in the IB1’s May 2024 AI consultation response, IB1 recommends that the developing AI governance landscape codifies a requirement for AI use in the energy sector to demonstrably contribute to the UK’s net zero targets and for this requirement to be open to monitoring and audit. Without codification of this principle there is a risk that AI systems are established to optimise non-environmental goals, while creating negative environmental impacts. 

IB1 acknowledges the risk of AI systems generating increases in energy and water demand. Both the impacts and the demand profile of AI use should be subject to scrutiny and appropriately governed to ensure they contribute meaningfully to the UK’s net zero targets.

2. What kind of data is needed? 

All identified IB1 use cases, detailing the value, kind, potential users, and scale of the required data, are outlined here: https://ib1.org/energy/reports/ 

3. What work is needed to create or enable a useable dataset, including making sure it can be easily combined with other datasets? 

IB1 observes that this list concentrates on technical barriers to data use, but fails to highlight legal, licensing and commercial considerations. It is very possible that cost, usage and IP conditions will hamper otherwise technically possible uses of the data. We recommend early surfacing of this information to mitigate five risks: 

1. Regulatory and compliance complexity: Data licensing must align with compliance rules around grid data, market data, and critical infrastructure. It is important to ensure data inputs to AI systems, and the outputs of the AI, remain compliant.
2. Third-party data dependencies AI models in energy often rely on weather feeds, satellite imagery, market pricing, and sensor data from multiple vendors. Each source carries its own licensing terms around permitted use, commercial exploitation, and AI training rights. Identifying these dependencies early prevents data supply chain disruptions during development, or worse, after deployment.
3. Intellectual property and model ownership: Who owns the AI model trained on licensed data? Many data providers now include clauses that restrict or claim rights over derivative works, including trained models.
4. Onward data publishing and monetisation: Energy sector companies typically want to share or sell AI-derived insights. Licensing terms set upstream can block valuable downstream opportunities. 
5. Long-term data access and continuity risk: Many foreseeable AI systems in the energy sector (e.g. predictive maintenance, load forecasting) need consistent, long-term data access. Identifying long-term data rights is critical to operational resilience.

Governance to enable usable datasets which can be combined with other datasets 

As mentioned in IB1 response to Ofgem’s AI in the energy sector guidance consultation IB1 encourages cross-sector collaboration and learning wherever possible. We recommend engaging with cross sector (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of AI guidance on different socio-economic stakeholder groups.

As described in IB1’s AI positioning statement, IB1 supports a hybrid governance model, combining robust oversight with decentralised data sharing, including smart contracts and digital identity solutions

AI must be designed to mitigate bias and discrimination, ensuring fair access to economic opportunities, financial services, and public resources. We support governance which is co-designed through processes which are adequately representative of different stakeholders or stakeholder groups, ensuring that the approach is collective rather than ‘done to’ from the top down.

To mitigate risks and enable data sharing at scale for AI use, the industry must consider more than just the dataset. For an identified use case, it needs to collectively determine:

• User needs & impact: commercial priorities, business cases, and prospective new products and services to be unlocked.
• Technical infrastructure: shared ontologies, APIs, schemas and standards to support data exchange. 
• Licensing & legal: data sharing agreements, modes of redress and liability frameworks.
• Engagement & communications: common language, stakeholder engagement and recruitment.
• Policy: alignment with corporate policy and industry regulations.

At IB1 we do this through a robust governance process and Icebreaking to drive groups of organisations to make the critical decisions required to exchange data with one another.

4. Who would the users of the dataset be? 

All identified IB1 use cases, detailing the value, kind, potential users, and scale of the required data, are outlined here: https://ib1.org/energy/reports/ 

5. What scale does the dataset need to be? 

All identified IB1 use cases, detailing the value, kind, potential users, and scale of the required data, are outlined here: https://ib1.org/energy/reports/ 

6. What would enabling AI use of this dataset unlock? 

All identified IB1 use cases, detailing the value, kind, potential users, and scale of the required data, are outlined here: https://ib1.org/energy/reports/ 

7. What would be the arrangements for ongoing maintenance, governance and curation of the dataset? 

As noted in IB1’s response to Ofgem’s AI in the energy sector guidance consultation: 

IB1 encourages cross-sector collaboration and learning wherever possible. IB1 recommends engaging with cross sector (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of AI guidance on different socio-economic stakeholder groups.

AI must be designed to mitigate bias and discrimination, ensuring fair access to economic opportunities, financial services, and public resources. IB1 advocates strongly for AI governance to integrate with developments in data governance, both within the energy sector and in the cross-economic space (e.g. Smart Data Roadmap, approaches to consent or permission). 

IB1 believes it is important for data governance to establish principles, structures, roles and responsibilities, agreed upon by market participants, that enable auditable, accurate and timely data sharing at a market-wide scale. As mentioned in the IB1’s May 2024 AI consultation response, IB1 recommends that the data ecosystem, and integration with the data governance landscape be acknowledged.

IB1 notes that in training a model it is highly likely that training datasets will contain sensitive data (it is also possible to use only anonymised data within a training dataset to retain privacy in the model itself), but it is possible to implement techniques where sensitive data is significantly better protected in the training of the model such as aggregation, pseudo-anonymising personal data. A good example of this that has been accepted by Ofgem as appropriate for maintaining privacy is the creation of datasets in energy that aggregate data down to a few households based on which properties are on different Low Voltage Feeders. If there are clear controls on the training data which datasets can and cannot be used to train AI models, then we can expect the produced AI model to be privacy preserving. If you implement data protections after an AI model has already been trained, it is harder to control. If a model has used training datasets with potentially identifiable data within them, the model may provide outputs using this data and can end up linking datasets together to make it personally identifiable

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer. 

Overall Position

We support the introduction of a new licence condition requiring improvement to connections data. However, the proposal would benefit from clearer definitions of sensitive data and a broader scope that includes both open data and shared (sensitive) data. It is important to note that capacity data is relational not static – interoperability between different data providers and datasets is essential.

A transparent user needs-led approach to data assurance would encourage data sharing, support higher data user confidence, and provide more flexibility than fixed requirements on accuracy, completeness and timeliness, for example regarding update schedules and interoperability. Data user needs must be explored and permitted to share improvement incentives to ensure design and use are aligned. It is important that shared data improvement is incentivised before the timeline for full DSI integration as there is demand for this data immediately. 

Consultation question responses:

Theme 1 – Improving visibility and accuracy of connections data 

Q1.1. Do you agree with Proposal 1.1. to introduce a new licence condition for accurate, complete and timely data? 

Yes, we agree with Proposal 1.1 to introduce a new licence condition, however, it should not be limited to open data publication (see question 1.2 below for sensitive data response). All data sharing would benefit from a clear assurance framework, which may draw from established assurance approaches such as Icebreaker One’s generic dataset assurance levels. Data that is not 100% accurate, complete or timely can still be valuable as long as the limitations are made clear. Assurance encourages publication rather than waiting for “perfect” data, which can mean that key datasets are not published due to data quality concerns. Assurance can include accuracy, completeness and timeliness but it enables more nuanced or context-specific signals about data quality, for example interoperability or provenance.

We encourage licensees to engage widely with stakeholders, particularly those outside the energy sector, to develop data assurance signals that meet specific user needs. Open Energy can facilitate this through a structured approach to design, implementation and governance of such standards within the Energy Sector Trust Framework.  

We support the requirement for data to be as close to real time as feasible, subject to security considerations (e.g. more granular data may be subject to additional access controls). Monthly updates should be considered a minimum baseline, not an indicator of best practice. More frequent (e.g. daily) data updates would be helpful to accelerate policy ambitions to speed up the connection queue. In all cases, update schedules should be published transparently as part of the assurance process.

It is vital that this condition has a consistent  approach across distribution and transmission networks to ensure data is as interoperable as possible. Increasing demand from new industrial plants and digital infrastructure reinforces the need for high-quality, frequently updated, relational connections data. Connections data requirements should apply consistently to both:

• Generation connections
• Demand connections (including large industrial loads and data centres)

Q1.2. Do you agree with Proposal 1.2. to split data into open and sensitive categories, and to use the Data Sharing Infrastructure to share sensitive data? 

No. Sensitive data is not a monolithic category, there are existing approaches (e.g. IB1 Data Sensitivity Classes) to sub-categorise which should be used in order to assess data sensitivities and place appropriate access controls/licensing. This will provide DNOs greater guidance from regulators on what should be considered sensitive data. 

DSI data sharing may not be (immediately) suitable for all use cases, it is currently unclear when and how non-regulated actors will be able to access data via the DSI and these actors constitute major customers for connections data (e.g. heavy industry, retail etc). While sensitive data may be exchanged via the DSI in future, improvements must not be put on hold until the solution is ready. Further, determining whether the DSI is used as the primary mechanism to share sensitive data should depend on the outcome of the MVP.  

Q1.3. Do you have any additional comments in relation to the decisions and proposals outlined in this theme? Do you have any additional comments related to any other aspects of this theme you think we should consider? 

Additional comments:

• Network headroom is not static at a single supply point (substation / GSP). Capacity availability is relational and influenced by:
  • Nearby supply points and how power is drawn/combined from different points
  • Connection queues and timelines
  • Reinforcement plans and timelines
  • Local and regional constraints (e.g. DNO/TNO or cross-DNO constraint interactions)
• The licence condition and associated data standards should better capture and communicate these relational dependencies.
• Greater transparency regarding capacity that has been committed but is not yet utilised (and anticipated timescale for use) may support better planning.

Lessons from relevant innovation projects (e.g. work examining relational network constraints) should inform the design of data publication and visualisation tools. In particular, lessons from the Strategic Innovation Fund REACT programme which aimed to  address current planning and future planning for generation siting may be valuable. REACT’s Alpha Phase Data accessibility and interoperability report recommendations:

• Reducing friction: To improve data assurance, reduce friction across data silos and provide forward compatibility with the Virtual Energy System, the REACT project must embrace a ‘Trust Framework’ methodology throughout its work.
• Improving data accessibility: To improve the discoverability of datasets and encourage process innovation, Transmission Owners should publish internal process diagrams that describe the workings of complicated internal processes – such as the Network Connection Request process.
• Improving prediction: To improve long-term planning for Transmission Owners and for other stakeholders, a statistical model of projects should be embraced that tracks a project’s estimated probability of success according to the best available data.
• Embracing innovation: To radically embrace innovation around processes, such as the Network Connection Request process, virtual ‘sandbox’ representations of these processes with representative data should be created. This will enable innovators to safely experiment with innovative solutions without affecting Business as Usual.

As mentioned in IB1’s Response to Ofgem Modifications to RIIO-3 consultation, with the progress of the Data Sharing Infrastructure (DSI) programme, IB1 anticipates ‘Shared Data’ sharing will evolve and will inform the evolution of data best practice (DBP) guidance. In particular, as data sharing scales, the need to standardise and harmonise legal and technical approaches will become more pressing in order not to slow innovation and add unnecessary cost. IB1 recommends that DBP should include guidance around Shared Data within the triage processes and licensing decisions, highlighting the role of Shared Data Schemes to provide definitions that aid interoperability and maximise impact.

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer. 

Consultation response:

1. Do you agree with the Workgroup’s initial view that P494 does better facilitate the Applicable BSC Objectives than the current baseline?* Please provide your rationale and, if ‘No’, please provide full details of your Alternative Modification(s) and your rationale as to why it / they better facilitate the Applicable BSC Objectives. 

• Yes
• No 
• Neutral / No Comment 
• Other 

Rationale: Elexon is unable to fulfil the potential benefit of making the data available with its current position as Data Processor.

2. Do you agree with the Workgroup that the draft legal text in Attachment B delivers the intention of P494?

• Yes
• No 
• Neutral / No Comment 
• Other 

Rationale: 

• Data Controller is limited to “Relevant BSC Personal Data” which only applies to data about natural persons. This will exclude data protections for company data envisaged in the DUAA. It leaves a lot of heavy lifting to the SDR Rules for non-personal but commercially-sensitive company data.
• SDR Rules not sufficiently developed at this time to assess whether, in combination with the code change, they are sufficient to ensure adequate data protection under the DUAA:
  • Identifying legitimate agents
  • Identifying meter owners not covered by CCS
  • Licensing and access arrangements for commercially-sensitive but non-personal data
• The consultation notes that “The means of determining whether a data set is commercially sensitive or personal data are being explored and are outside of P494”. This leaves a lot of work for the SDR Operations Manual to cover. The SDR is described on p27 of the consultation as containing “list of all APIs and reports published as well as technical details for how SDR users can interact with the SDR”. It will need to have much more detailed governance information. There is a risk that these considerations will “fall between the stools” of the BSC modification and the SDR Operations Manual.

3. Do you agree with the Workgroup’s recommended Implementation Date?

• Yes
• No 
• Neutral / No Comment 
• Other 

4. Do you agree with the Workgroup that there are no other potential Alternative Modifications within the scope of P494 which would better facilitate the Applicable BSC Objectives?

• Yes
• No 
• Neutral / No Comment 
• Other 

5. Do you agree with the Workgroup’s assessment of the impact on the BSC Settlement Risks?

• Yes
• No 
• Neutral / No Comment 
• Other 

6. Will P494 impact your organisation?

* If it will impact, please provide a description of the impact(s) and any activities which you will need to undertake between approval and implementation (including any necessary changes to your systems, documents and processes) and any on-going operational impacts. Where applicable, please state any difference in impacts between the Workgroup’s proposed solutions. 

• High 
• Medium 
• Low
• None 
• Other 

Rationale: There is potential for P494 to affect the Perseus smart meter scheme positively, opening up a wider array of the kind of meter points used by SMEs. 

7. How much will it cost your organisation to implement P494?

* If any, please provide details of these costs, how they arise. Please also state whether it makes any difference to these costs whether implemented as part of or outside of a normal BSC Systems Release. Where applicable, please state any difference in costs between the Workgroup’s proposed solutions and if applicable, between the different roles. 

• High 
• Medium 
• Low
• None 
• Other 

Rationale: P494 does not drive any direct costs

8. What will the ongoing cost of P494 be to your organisation?

* If any, please provide details of these costs, how they arise. Please also state whether it makes any difference to these costs whether P494 is implemented as part of or outside of a normal BSC Systems Release. Where applicable, please state any difference in costs between the Workgroup’s proposed solutions and if applicable, between the different roles. 

• High 
• Medium 
• Low 
• None
• Other 

9. How long (from the point of approval) would you need to implement P494?

* Please provide an explanation of your required lead time, and which activities are the key drivers behind the timescale. Please also state whether it makes any difference to this lead time whether implemented as part of or outside of a normal BSC Systems Release. Where applicable, please state any difference in lead times between the Workgroup’s proposed solutions. 

• 0-6 months 
• 6-12 months 
• >12 months 
• Other

Rationale: P494 does not require any action from us

10. Do you agree with the Workgroup’s assessment of the consumer benefits?

• Yes 
• No 
• Neutral/No comment
• Other

11. Do you agree with the Workgroup’s assessment that P494 does impact the European Electricity Balancing Guideline (EBGL) Article 18 terms and conditions held within the BSC?

• Yes 
• No 
• Neutral/No comment
• Other

12. Do you have any comments on the impact of P494 on the EBGL objectives?

No

13. Which of the following funding options do you prefer for the recovery of SDR costs?

• Costs recovered from Suppliers based on the number of MPANs supplied (option one)
• Costs recovered from Suppliers based on their share of delivered energy volumes (option two)
• Costs recovered from Suppliers using a hybrid approach combining MPAN-based and volume-based charging (option three) 
• Costs recovered through existing BSC arrangements and borne by all BSC Trading Parties (option four) 

Rationale: No comment

14. Do you have any views on when the full review of the cost to SDR Users should occur?

• Yes 
• No 
• Neutral/No comment
• Other

15. Do you agree with the legal basis to establish and operate the SDR?

• Yes 
• No 
• Neutral/No comment
• Other

Rationale: The underlying mechanism of creating the SDR Manager and giving it Processor rights seems sound, but it is lacking detail for non-domestic users as noted in our response to Question 2

16. Do you have any views on what the de minimis aggregation level should be?

• Yes 
• No 
• Neutral/No comment
• Other

Rationale: The proposed choice of 10 MPANs is not presented with a clear evidence based rationale. If there is a more detailed rationale this should be put forward transparently. There is an opportunity to build a more nuanced context-specific decision on the appropriate level of aggregation based on factors such as geographic dispersal and existence of generation and storage capabilities that may provide a “signature” in the data. Also consider differentiating “highly aggregated” data (say 50+ MPANs) that may be widely licensed, and “minimally aggregated” data (5-10 MPANs) that may have more restrictive access and licensing to prevent abuse.

17. Do you have any further comments on P494? 

There is a considerable amount of work to be done in the SDR Operations Manual in order to achieve the goals of the SDR Trust Framework. The following are some key elements left to be defined:

1. ID & Verification for non-CCS access is not defined (and even for CCS requires that to have been established). CCS should eventually cover business meters , and hopefully this will extend to smart and AMR meters. But that may not be until 2028. Businesses are key potential beneficiaries of SDR, for both cost reduction and net-zero impact. A number of the expected SDR Users focus on services intended for business. How will SDR support businesses in the interim? How will the SDR Users be verified, their data usage controlled, and how will they provide evidence for meter data access from businesses?
2. The data sensitivity classes need more definition and clear policies for application
3. The eligibility requirements and decision-making process for executing an Access Agreement and allowing access must be defined, as well as policies/processes for ensuring SDR Users remain eligible
4. Data licensing requirements are not mentioned in the consultation. How will purposes be categorised and policed? What is permitted/not permitted for the various levels of non-open data?
5. Liability and redress are not mentioned in the consultation. What policies and processes will enable data subjects harmed by the SDR to seek redress?

Since SCR covers a wider range of legal bases and potential data users than CCS, we recommend early consideration of how governance elements such as those above may be harmonised with other data sharing initiatives. This may be achieved through identifying opportunities for common definitions around ID&V, data sensitivity, purposes (or classes of purpose), and licences. Icebreaker One and Open Energy have research and experience, drawn from wide stakeholder engagement, that can inform this work.

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org.

Consultation response:

Q1. Do you agree with our case for change and that policy intervention is needed for DNO asset registration? 

Icebreaker One (IB1) is a non-profit working on data sharing and sustainability, convening organisations and governments to design market-scale solutions to make data work harder to deliver Net Zero. IB1 creates and runs programmes to reduce barriers and costs to finding, accessing, using, and sharing data, which will ultimately reduce costs for consumers.

IB1 supports better data on assets, and data sharing between DNOs, suppliers, and other organisations who need to understand headroom capacity and demand. We note there is a need to distinguish clearly between asset type(s) and capacity at the initial phase. In future, better data on asset performance and behaviours would be helpful to ensure this initiative can be most useful – e.g. capacity is not static with flexibility assets in play.

Q2. Do you agree with our priority use cases, and are there any other use cases we should consider? 

We agree with Ofgem’s identified use cases, however, we note that the data end user within the priority (regulated entities) and further use cases may have very different needs and data sharing instruments available. As mentioned in IB1’s response to Ofgem’s Energy digitalisation governance: architectural coordination letter, we propose that an industry-independent coordination body helps coordinate a flexible energy system. Data sharing at scale requires the separation of ‘the data’ from its governance and the technology used to host and transfer it.

We encourage the inclusion of potential ‘further users’ as a part of a governance process from the outset to ensure a solution suits their needs and does not exclude the solution from expanding past the priority use cases. We advocate for starting with a use case with external (non-regulated / less digitally mature) players, then a B2B DNO focussed use case to make subsequent use cases easier and less likely to inadvertently produce blockers. Leaving local authority use cases for “later” risks local planning and investment being disconnected from the physical reality of supply. A key use case to consider is data centre energy demand, which reinforces the need to urgently prioritise local authority use cases. 

IB1 has worked on a few other relevant collaborative use cases in this area, including:

• Getting small scale assets / flex services online (Open Energy Future of heating –  Residential Property Developer use case).
• How data sharing can be used to better understand how to maintain the assets already in place. IB1, SSEN-Transmission, IBM, and Palantir on a Strategic Innovation Fund programme, NIMBUS, which focussed on granular weather data and network innovation to build for sustainability. See the Discovery Phase report and the Alpha Phase report.
• IB1 partnered with SSEN-Transmission, Olsights, Mapstand, SGN, and National Grid on a Strategic Innovation Fund programme REACT to address current planning and future planning for generation siting. See the Discovery Phase report, and the Alpha Phase report. This use case reinforces the need to know other assets on grid to aid grid capacity understanding and future planning.

Q3. Are there any other policy or industry initiatives that we should seek to align with? 

IB1 encourages seeking alignment with:

• Open Energy – run by IB1, has expertise articulating use cases, and designing and quickly implementing shared data schemes with appropriate governance – includes legal agreements, assurance and technical specifications – in collaboration with stakeholders.
• Connections end-to-end review: updated proposals and next steps​ consultation. To what extent are external entities interested in assets as opposed to capabilities?
• Consumer Consent Solution, currently being developed, designed and delivered by RECCo Ltd, as small scale asset data is in scope (unless this programme is using another lawful basis for processing, this would need to be articulated clearly).

Q4. Do you agree with the scope proposed for assets, data, entities, and data stages, should anything else be considered?

As mentioned above, there needs to be a defined governance process for considering and agreeing upon the proposed scope for assets, data, entities, and data stages. 

IB1 would highlight there is a need to identify current data uses, and to be flexible enough to incorporate new ones as they emerge, to establish both the scope and the data quality and completeness requirements for asset information. For example, there is likely to be a difference between the DNOs’ data quality requirements at the lowest end of the asset capacity scale and the data quality requirements for users like councils, planners, microgrid/heat network assessors etc. Additionally if this asset data feeds into the flex market, missing or incorrect installations could lead to financial consequences for asset owners. 

While not in scope for the initial phase of development, our suggestion for future development would be the ability to transfer data on asset profiles/behaviours. This would be incredibly useful to better understand how flexible assets actually behave and their real-life impact, for example on network capacity.

Q5. Do you agree with our enablers and dependencies, and are there any others we should consider? 

IB1 would add on the lawful basis for processing – if not using consent then clarify on what lawful basis the register operates under. It would also help to understand how any data protection risks potentially associated with the register will be managed and governed. It is not currently clear how the lawful basis distinguishes between household and business (including microbusiness/SME) assets. This will interact with the Data (Use and Access) Act for businesses and requires clarification.

Q6. Do you have any suggestions for collecting legacy data, or for integration of other datasets into DNO registers? 

No comment. 

Q7. Do you agree with the advantages and disadvantages for the proposed options, are there others or any wider aspects we should consider? 

Wider aspects to consider on Option 2:

• May require upskilling/investment by DNOs, with an opportunity to subcontract if they are lacking skills in-house. This is a low risk if data standards are agreed through a governance process.
• As mentioned in Question 2, this initiative must be mindful of restricting use cases to regulated entities first which may make it harder for other users in the future. 
• As there is demand by non-regulated users for asset data now, there may be a benefit to spinning up a scheme in the short frame which is ready to integrate with DSI but has governance to engage a wider range of end users at the start. 
• This option has the highest potential to scale as it does not bottleneck in a single database/register, and provide utility for a wide range of use cases. 

Wider aspects to consider on Option 3:

• New databases and portals struggle to scale for a wide array of use cases as infrastructure systems are being digitalised in a decentralised and distributed way
• This option gives liability to a central entity versus distributed liability to DNOs
• May conflict with current DNO autonomy in deciding what data to publish and how to publish it, guided by DBPG. In particular may lead to a lowest-common-denominator approach that disincentivises DNOs from publishing otherwise-useful data that isn’t needed by the central register

Wider aspects to consider on Option 4:

• Operating a flexible market is a significantly different use case from the ones articulated above – expanding existing initiatives may result in a loss of focus on the original challenge it was solving
• Suggest a focus on harmonisation rather than making FMAR even more complex.

Q8. Are there any changes you would make to any of the proposed options to enhance them? 

IB1 would emphasise the need for a determination on what body would govern the standards for Option 2, and how stakeholder engagement beyond the regulated entities will be managed. There is a need to convene stakeholders within and outside the industry to ensure it is fair and accessible as well as implementable by the data holders. 

Q9. Have we missed or discounted any options that you think are suitable? In particular, for option 4 is there a preferable alternative to FMAR for expansion, and why? 

No Comment. 

Q10. Which option is your preferred option, and why?

IB1 would encourage Option 2, as it is the fastest to market and lowest cost, and can be decoupled from other initiatives, so can run in parallel and at pace. We would suggest this happens through a trial ‘scheme’ developed as and will be DSI integration ready for when DSI is ready to support asset data sharing. 

This option also has the opportunity to have the simplest governance (only DNO liabilities) – although this needs defining – as referenced in Question 8.

This is Icebreaker One’s response to Ofgem’s Energy Digitalisation Governance – Architectural Coordination letter.

Please note that throughout this consultation, Icebreaker One (IB1) uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org.

Executive summary

This response advocates for a focus on coordination of the energy sector’s data architecture and energy data governance as a fruitful starting point for architectural coordination of digitalisation governance. It emphasises that coordination is an ongoing process with human and technical components. It further works to the principle of minimisation, specifying that coordination activity must work in the leanest feasible manner, delegating to existing sector processes where possible and only acting where there are clear requirements for further intervention. We propose that the coordination challenge should be met via the appointment of an industry–independent coordination body composed of Secretariat, Research, and Monitoring functions. 

We do not propose that the coordinator should have enforcement powers, as these are most readily delivered under the existing regulatory and legislative capabilities of Ofgem and DESNZ. However, both Ofgem and DESNZ must be required to consider options from the coordination body in their determinations. 

The Secretariat should act as an independent facilitator for participatory governance processes which can adapt flexibly to evolving coordination needs and ensure accountability. 

The Research and Monitoring function should have two responsibilities:

1. mapping the domain(s) in which coordination is enacted in order to support effective participatory governance
2. monitoring and reporting on the outcomes of coordination activity to improve transparency and join-up with adjacent policy/regulatory goals (energy and cross-sector). 

We suggest that this function includes coordinating and monitoring the delivery of the sector’s digitalisation roadmap. We suggest that the body would require a small permanent staff to ensure continuity of process, with additional staffing contracted or seconded in on a short term basis for agile response to emergent needs (e.g. particular technical or domain expertise concerning a particular coordination challenge). This lightweight approach will deliver the intended benefits at a reasonable cost to the bill- or taxpayer. 

Response

Where should we focus?

Prior to addressing specific prompt questions, it is important to discuss the boundaries of the digital space and its component parts. Digitalisation is an umbrella term which can be used to refer to a wide range of different processes, technologies, activities, actors, and frameworks. Accordingly, the term is prone to some mystification as well as the drawing of false equivalences between digitalisation and technology. While we agree with Ofgem’s statement that there is an emergent need for coordination in energy sector digitalisation, we emphasise the importance of defining the boundaries of what exactly, within the wider digital space, is the target for this activity.

As discussed in IB1’s response to DBT’s Invest 2035: industrial strategy consultation, and in alignment with the National Data Strategy, the bedrock of digitalisation lies in data. In parallel, a significant proportion of industry digital activities to date involve laying the foundations for how data is governed, shared, and used within the energy sector. Accordingly, we strongly suggest that Ofgem’s architectural considerations at the present time focus on the coordination of the sector’s data architecture and associated energy data governance rather than other elements of the digital transition. Coordination in other digital arenas may well be required in future and we support future consultation accordingly. However, we do not believe that it represents value for money, nor effective prioritisation against net zero, to focus on these areas at the current time.

It is also important to draw a clear line between the valuable work currently progressing in large but focused sector-wide initiatives, such as the Data Sharing Infrastructure (DSI) or Consumer Consent Solution programmes, with the overall task of coordinating sectoral data governance. At its heart, data is not a technology, an ontology, or a standard. Rather, data is highly contextual — defined by a framework of rights-based governance, shaping how it can be gathered, shared and used, by whom, and for what purpose(s). 

Many ongoing data sharing initiatives in the sector (currently in their definition, prototype, or pilot phases) are advancing technology-led projects. These technical developments augment the sector’s capacity to collect, transport, and process data which is valuable. However, we have raised concerns in several forums that these projects risk developing in a manner which results in disjointed data governance. Coordination in the data governance arena would ensure that technology buildout will be clearly linked to user needs, meet appropriate levels of security, and promote legal interoperability supporting clear and confident data use. Without coordinating energy data governance, we risk building an environment where data exchange is improved on a technical level, but the real world use of the data remains subject to the same limitations that have been established by the research literature. 

How would coordination be achieved?

Coordination is an ongoing process between people and organisations, which will contend with ‘live’ and sensitive factors such as vested interests as well as wider factors such as the economic climate. We would anticipate a common digital architecture coordination function extending beyond a document, to capture the scale and nature of the coordination problem. The “function” of architectural coordination delivers the value – a document could describe it, but would not enact it. We believe that an independent entity is required to operationalise effective coordination. We also advocate that this should be achieved through as thin a layer of activity as possible, in order to present the best value for money and time. 

Additionally, we emphasise that our engagement with industry via the Open Energy Advisory and Working Groups has highlighted a need to think of coordination not as all organisations within the sector doing things in the same way. Rather, coordination should  focus on harmonisation and interoperability within company contexts of operation and as a common framework which aligns activities and reduces duplication. 

Open Energy

We believe that Open Energy is the only initiative currently operating within the energy sector that holds the independence, governance approach (designed in collaboration with the Institute of Directors), cross-sector experience, technical knowledge and flexible capacity to address architectural coordination of energy data governance. 

Open Energy, the competition-winning programme developed under the UKRI Modernising Energy Data Access initiative, identified and articulated the need to make it straightforward to find, access and share energy data. Open Energy was funded by £1.3m public money through three phases and is currently funded by commercial members. 

Open Energy is coordinated by the public-benefit nonprofit body, IB1, and has been specifically developed for this purpose using a combination of radically transparent methods of open working, extensive consultation with stakeholders, and the input of specific domain expertise from energy industry, academic, cybersecurity and Smart Data specialists.

Successful governance initiatives, including Open Banking, have taken the model of having an independent, non-sectoral incumbent body take on an architectural coordination role. Additionally a key recommendation from the 2021 Energy Digitalisation Taskforce Report summarises:

It is recommended that an independent, commercially disinterested body is established by Government to develop and/or incubate Public Interest Digital Assets on behalf of the sector. The Body should be given a mandate and funding to develop and deploy assets (either directly or via partners), directed by a stakeholder panel interested in the current and future needs of the energy sector. The benefit of this is that it would report to government but operate to the side of it.

As part of discussions following this letter, we appeal to Ofgem and DESNZ to enter into dialogue with Open Energy and its membership to discuss how Open Energy might be appropriately strengthened (e.g. participation or enforcement mandates) or configured (e.g. as a special purpose vehicle) to enable it to meet the required coordination function.

Our focus on governance is driven by the view that making data work harder for net zero isn’t a technology challenge. Rather than a deficit of data or technologies to manage it, it’s a deficit of effective processes for groups of organisations to come together, cooperate on and set the terms of data sharing that’s really holding us back.

In our work, governance is an ongoing process. The execution of this process produces decisions that enable data sharing to take place. In practice, this involves establishing principles, defining clear roles and responsibilities, and agreeing priorities and tasks. It also involves collaborating to create artefacts to express and enforce these decisions, such as legal agreements and technical standards.

We have a particular approach to organising data governance at IB1. We use a tiered system of Steering, Advisory and Working Groups to bring organisations together. These groups work together to agree and adopt:

• User needs & impact: commercial priorities, business cases, and prospective new products and services.
• Technical infrastructure: shared ontologies, APIs, schemas and standards to support data exchange. 
• Licensing & legal: data sharing agreements, modes of redress and liability frameworks.
• Engagement & communications: common language, stakeholder engagement and recruitment.
• Policy: alignment with corporate policy and industry regulations.

Participation in this process can be either voluntary (initiated by the market), or mandatory (demanded by regulators).

Using this collaborative process within the Open Energy programme, IB1 has designed, implemented and operates the Open Energy data search engine, the Energy Sector Trust Framework (ESTF), and within it, the Assured Open Data scheme. The ESTF is supported by IB1-developed open source Trust Services, including common technical specifications, a registry providing human- and machine-readable data sharing rules, a public directory of members and a secure portal for members to manage their information and issue digital identity certificates. These atomic, reusable services also power the cross-sector Perseus scheme that automates emissions reporting based on smart meter consumption data for UK SMEs. 

Our approach is inspired and practically informed by the UK’s Open Banking ecosystem, which enables data to be shared in new ways across banks and other financial services. It now has 15 million users and is projected to sustain a $12bn market of data-driven products and services. This change has been achieved not by building a big, centralised database of customer banking data, but by governing who should access it and how it should flow. 

Key questions:

1. Where is there a need for architectural coordination across the sector to unlock the full value of energy system digitalisation? 

As outlined above, we advocate that data governance, including the governance of data sharing, represents the clearest priority for coordination activity in the current moment. Needs are likely to change over time, so this must be regularly re-assessed in light of the wider sectoral environment (e.g. digital maturity, progress towards net zero, contextual policy challenges, economic environment etc). Additionally, we urge Ofgem to approach coordination through the lens of cross-sector interoperability and harmonisation, rather than a “one size fits all” standardisation. 

There is a need for coordination of data governance in the following arenas:

Secretariat:

• Participatory processes: An independent facilitator is needed to support the involvement of a range of participants (directly or via a representative structure) which can adapt flexibly according to coordination needs. This requires:
  • Strong governance processes – e.g. covering participant selection, means of input, minuting, reporting, and decision-making
    • Ability to offer tailored mechanisms where required – e.g. working groups to focus on specific parts of the sector, or task and finish style groups to support elements of digitalisation strategy delivery.
  • Independent Secretariat function with experienced administrators to execute governance processes and communicate expectations of timescales, plans, key decisions etc.
  • Where required, the provision of independent chairing or facilitation services
  • Dispute resolution process, linked to existing sector mechanisms and to participatory governance processes.
  • Participant accountability mechanisms (linked to enforcement – see below).
• Enforcement: we suggest that enforcement activity occurs under the umbrella of either Ofgem or DESNZ. This may include:
  • Ability to compel involvement in participatory processes (at least at some defined level) of regulated entities to ensure fair and balanced process
  • Ability to invite external stakeholders as and when required, in a transparent manner (e.g. pinned to a published methodology for a certain use case / decision / piece of research).
  • Ability to action change
• Accountability: any coordinating entity must be accountable to its stakeholders. We suggest this is supported by the following:
  • Openness policies enabling scrutiny (e.g. of methodologies, processes, minutes, reports)
  • Where required (for security purposes), clear rules defining how scrutiny will be undertaken among closed audiences
  • Defined process for dispute resolution integrated with existing sector mechanisms
  • Clear processes for change management
  • Defined avenues for external involvement in participatory processes
• Other:
  • We strongly suggest that the Secretariat is empowered to communicate across sectors in order to best learn and harmonise with digital and data sharing initiatives that cross sector boundaries.

Research and monitoring:

• Mapping: light touch, but regularly re-visited, research and documentation to understand current and emergent actors, activities, points of interaction/crossover/competition, and gap analysis – this will also help draw the boundaries around the remit of current coordination priorities and future considerations. This must:
  • Include cross-sector activities
  • Include cross-scalar activities (e.g. map devolved authorities, local etc as well as national initiatives)
  • Include identification of priority use cases / sets of use cases, particularly which require addressing via pre-competitive activity.
  • Highlighting areas where government or regulatory input may be required to meet policy goals.
  • De-mystify parts of the digital transition into clear component elements (both socio-economic and technical) with defined terminology
• Monitoring: 
  • Devising, implementing and openly publishing Monitoring, Evaluation and Learning (MEL) methodologies and reports in accordance with a transparent schedule – including ways to ensure digitalisation supports other policy goals (e.g. Net Zero, Warm Homes Plan, Flexibility development etc) and increases transparency in an area of rapid sector growth.
  • Coordinating the delivery of the sector’s digitalisation roadmap to ensure that effort is not duplicated and complexity is minimised. While we welcome NESO’s work to address sector-wide digitalisation planning, we suggest that this function should be devolved to an independent body in order to appropriately hold all actors to account. 

2. What are the constituent elements of architectural coordination of digitalisation in the energy sector?

We have interpreted this question to refer to how architectural coordination could be operationalised through a coordinating body. We suggest that the body is composed of an experienced Secretariat, which is vital to good governance processes. It must also have a small research and MEL team as outlined below. Additional elements should be flexible and responsive to the developing ecosystem. Accordingly, it may be beneficial for the body to be able to second in expert staff on a temporary basis. Across the board it is vital for the coordination body to be independent.

Secretariat component

A Secretariat coordinates and supports group meetings to ensure the programme is making effective and timely decisions and is aligned with strategic objectives. Secretariat  administrative support includes: meeting arrangements, pre-read and agenda dissemination, note-taking and drafting of formal minutes. Maintenance of an effective, experienced Secretariat requires an appropriate budget for ongoing roles.

As outlined in question 1, the Secretariat component would support participatory processes, enforcement, and accountability functions. It is vital that the Secretariat retains independence from other sector bodies in order to navigate conflicts of interest and build trust among participants.

Research and monitoring component

An effective research and monitoring function requires the maintenance of a small team with expertise in research methods, knowledge transfer, and reporting. We suggest that primary research should be participatory, bringing in experts to minimise cost and duplication. The research element of this component may require a small flexible fund to support short term targeted projects (e.g. mapping stakeholders who must be consulted when developing a specific area of pre-competitive activity). The monitoring element requires access to participation from sector authorities to define the target and frequency of monitoring activity and dialogue with the wider sector, and appropriate experts, to identify or devise appropriate methodologies. It is essential for this component to have the ability to freely publish monitoring results, with sensitivity to factors such as security when defining the appropriate level of openness. This component should provide a forum for feedback from scrutiny as and when required.

We again emphasise the importance of independence in this arena as there may be cases where the component sheds light on poor performance or emergent issues. This requires an independent entity to perform; it cannot be nested in an existing body without risking conflict of interest.

3. What value could a common digital architecture document for the energy sector provide?

Coordination is an ongoing process between people and organisations, which will contend with ‘live’ and sensitive factors such as vested interests as well as wider factors such as the economic climate. We would anticipate a common digital architecture coordination function extending beyond a document, to capture the scale and nature of the coordination problem. The “function” of architectural coordination delivers the value – a document could describe it, but would not enact it. We believe that an independent entity is required to operationalise effective coordination

Potential benefits of architectural coordination include:

• Avoiding duplication — e.g. multiple Trust Framework providers that potentially aren’t interoperable
• Learning from other sectors — lacking clear deadlines and costs. The Pensions Dashboard Programme has an estimated cost of £289m, with no released date of when the dashboard will be made available to the public
• Saving money and reducing time-to-value by providing market participants with repeatable processes and building on well-understood standards 
• Prioritisation of key use cases
• Avoid the time and financial costs of a lack of coordination, especially on urgent causes such as net zero

4. What function may be needed to deliver architectural coordination and how would it interact with functions/organisations that are delivering digital public infrastructure (DSI/NESO, Consumer Consent Solution/RECCo, Smart Metering Network/DCC, FMAR and SDR/Elexon) 

• Ability to liaise and harmonise across sectors — e.g. Smart Data schemes, DSIT, Smart Data Council
• Cross-sector thinking is required to achieve the size of impact that the Industrial Strategy and The Clean Power Plan have outlined
• Must be a non-profit dedicated to the public good to avoid distorting the market and discouraging commercial members
• A function should be judged against the criteria of:
  • How light-touch and small it can be in order to deliver the needed effect
  • How much value is gained by stakeholders from their participation

5. Is coordination an ongoing task (including monitoring), or a temporary task to deliver the elements needed (from q2)? 

We strongly encourage that coordination must be an ongoing task, including monitoring, and acknowledge that it will adapt and change as energy digitalisation evolves. Governance must be designed to assess and adapt to changes. 

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer.

Consultation response:

18. Please provide any feedback on the proposal to refine the definition of scope 2, to emphasize its role within an attributional value chain GHG inventory and clarify that scope 2 must only include emissions from electricity generation processes that are physically connected to the reporter’s value chain, excluding any emissions from unrelated sources?

This response is on behalf of the Perseus programme’s member organisations. Perseus aims to unlock access to finance that reduces emissions, by automating sustainability reporting for every SME business in the UK. Perseus operationalises one granular use case focusing on the sharing of 30-minute electricity consumption data, which is combined with corresponding 30-minute local grid carbon intensity readings to calculate assurable monthly GHG emissions (See Perseus’ emissions calculations: https://registry.core.sandbox.trust.ib1.org/scheme/perseus/process/emissions-calculations/2025-10-23). The consumption data is sourced from SMEs with either a) a single business premise and a single, unshared smart meter, or b) an account with Perseus member Energy Data Provider that can provide half-hourly electricity consumption data. 

We welcome the GHG Protocol’s efforts to update the Scope 2 guidance. As the grid decarbonises, the current annual, market-wide accounting framework is increasingly insufficient for capturing the reality and complexity of electricity consumption. Perseus is currently UK focused and requires 30-minute electricity consumption and local grid carbon intensity granularity, however, we encourage the protocol to globally require reporting organisations to use the best possible available data. 

The proposal to restrict sourcing to the same “deliverable market boundary” rightly addresses the disconnect where companies claim emission reductions from grids they do not physically use. However, boundaries must be pragmatically defined.

Perseus member companies note that restricting procurement to narrow pricing zones could strangle market liquidity and prevent companies from supporting high-impact projects in adjacent, interconnected grids where decarbonisation is necessary. The final standard should explicitly allow for procurement across recognised interconnected power pools (e.g., EU-wide) rather than strictly enforcing narrow pricing zones.

19. Please provide any feedback on the proposal to clarify the LBM definition to reflect scope 2 emissions from generation physically delivered at the times and locations of consumption, with imports included in LBM emission factor calculations where applicable? 

As Perseus uses location-based method emissions calculations, we will only comment on LBM changes. 

The proposal to refine the Location-Based Method by prioritising a hierarchy of “Local” and “Hourly” data over national annual averages is scientifically sound. It correctly identifies that grid carbon intensity varies significantly by time and place. The administrative burden of the proposals may affect different business structures in quite different ways, potentially introducing new costs to distributed business with sites that are geographically dispersed. We suggest that the potential for an element of aggregation is considered. For example, this could mirror the ESOS model where a relevant proportion of the portfolio is surveyed and information is then extrapolated to the rest of the portfolio.

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org.

Consultation response:

Regarding paragraph 3.36 in the Statutory Consultation on the RIIO-3 Licence Drafting modifications – reasons and effects document:

Generally IB1 supports a common Digitalisation Re-opener to encourage digitalisation by allowing network companies to seek funding for data and digital related projects with a broader scope than just IT hardware or software upgrades and to align with RIIO-ED2.

IB1 supports digitalisation as key for energy sector decarbonisation, and required for the investment in flex services and the coordination between sectors who rely on energy to meet their decarbonisation targets (water, transportation, built environment, industry).

IB1 supports sector-wide convening and governance to ensure digitalisation happens in a coordinated manner and can enable ‘whole system solutions,’ as promoted in RIIO-ED2 and realise the subsequent cost savings. IB1 supports Ofgem to continue to promote and finance whole system digitalisation coordination in RIIO-ED3.

As there are many ongoing data sharing and data governance initiatives e.g. consumer consent solution, flexibility services, Data Sharing Infrastructure (DSI), which are currently in progress at different stages of development (definition, prototype, or pilot). Ofgem should not expect these programmes and underlying challenges the projects aim to solve to be resolved by the end of RIIO-ED3 (2031). Data sharing and data governance needs and subsequent solutions will evolve over time as we continue to electrify and connect the UK’s grid. As mentioned above, Ofgem needs to ensure ongoing governance and sector collaboration on data and digitalisation – reinforcement of this would be welcomed in addition to specific plans to expand/evolve data governance initiatives.

With the progress of the Data Sharing Infrastructure (DSI) programme, IB1 anticipates ‘Shared Data’ sharing will evolve and will inform the evolution of data best practice (DBP) guidance. In particular, as data sharing scales, the need to standardise and harmonise legal and technical approaches will become more pressing in order not to slow innovation and add unnecessary cost. IB1 recommends that DBP should include guidance around Shared Data within the triage processes and licensing decisions, highlighting the role of Shared Data Schemes to provide definitions that aid interoperability and maximise impact.

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer.

Consultation response:

Do you agree with the proposed implementation approach? Yes.

Rationale: We appreciate that there is a governance in place to discuss and approve the proposed implementation. We would welcome further transparency on the outcomes of applications to access data via this method and suggest that a summary of cases are made openly available after a 6-12 month trial period. Ongoing avenues for scrutiny remain important.

Please provide any further comments you may have.

As we are looking holistically at the smart meter data landscape, we will continue to work with the SEC and engage as it develops on a case by case basis and impacts wider use cases.

Meeting Aims

1. Understand what members are currently working on
2. Align on comms moments for the second half of 2025 (H2)
3. Communications for the Perseus end of year report

Summary:

It was noted that:

• Four core H2 comms moments are now underway or imminent:
  
  1. Sandbox announcement (launched the week commencing 29 September).
  2. Ongoing “Perseus-ready” announcements to celebrate participants.
  3. XBRL and potential RECCo announcements to demonstrate Perseus’s integration and future-proofing.
  4. End of year Perseus 2025 report launch (December).

It was discussed that:

• The 2025 Perseus report will act both as a technical update and as a comms tool highlighting the value of Perseus, user stories, and co-creation benefits.
• Members welcomed the concept of a participation summary capturing each organisation’s contribution to Perseus during the year.
• The participation summaries should be member-driven, with IB1 providing structure and visual support.
• Distribution of the end of year report will focus on owned and partner channels (LinkedIn, newsletters, events), not earned media.

It was agreed that:

• IB1 will prepare a participation summary template and draft comms assets
• Members will identify suitable channels to help amplify the December report.
• The November AG4 meeting will finalise the comms plan and confirm each organisation’s contribution.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer.

About Icebreaker One

Icebreaker One (IB1) makes data work harder to deliver net zero. We do this by orchestrating the development of focused, decentralised Schemes that unlock data from across organisations at market scale.
Perseus, for example, enables businesses to access over $100B of green finance, by automating high-quality sustainability reporting for every SME in the UK. The Schemes we orchestrate are inspired by the architecture of the UK’s successful Open Banking ecosystem and the interventions that brought it about.

1. What issues do customers face in accessing their data held by digital markets firms and sharing that data with third parties?   

‘Digital markets’ are hard to define, given the pervasiveness of the web and related technologies. Almost all companies will use web technologies to exchange goods, services or information. 

The following are examples of consumer markets that we think are particularly reliant on network effects, data-driven operations and multi-sided interactions: 

• Social media (such as Facebook, Twitter, TikTok, Instagram, Threads and Bluesky).
• Messaging (such as Whatsapp, Messenger, Telegram and Discord).
• Online marketplaces and retailers (such as Amazon, Temu, Shein, eBay, Gumtree, Etsy and Depop).
• Payment and transaction (such as Shopify, Klarna, Visa, PayPal and Stripe).
• Operating systems (such as Microsoft Windows, MacOS, Linux, Android and iOS).
• Web browsers (such as Chrome and Firefox). Email (such as Gmail and Outlook).
• Search (such as Google Search and Bing).
• App stores (such as Apple App Store and Google Play Store).
• Virtual assistants (such as Siri and Alexa).
• Large language models and interfaces to them (such as GPT-4, Chat-GPT, Copilot, Gemini, Claude and Perplexity).
• Cloud services (such as Google Photos, DropBox and OneDrive).
• Online courses and learning (such as Coursera and Udemy).
• Jobs (such as LinkedIn, Indeed and Adzuna).
• Loyalty schemes (such as Nectar, Clubcard and Avios).
• Gaming (such as Steam, PlayStation Network and Xbox Live).
• Gambling and betting (such as Bet365, 888 and SkyBet).
• Music streaming (such as Apple Music, and Spotify).
• Podcast streaming (such as Spotify, BBC Sounds sounds and Apple Podcasts).
• Books and audiobooks (such as Audible and Kindle).
• Video streaming (such as BBC iPlayer, Sky, Netflix, Amazon Prime and Disney+).
• News (such as Sky News, BBC News and Apple News).
• Content distribution (such as YouTube, OnlyFans and Substack).
• Travel (such as Airbnb, booking.com, Expedia and Skyscanner).
• Ticketing (such as Viagogo, StubHub and EventBrite).
• Navigation (such as Google Maps, Apple Maps and CityMapper).
• Ride hailing and food delivery (such as Uber, Bolt, Deliveroo, UberEats and JustEat).
• Gig economy (such as Upwork and TaskRabbit).
• Smart devices (such as Philips Hue and Apple Homepod).
• Health applications and wearables (such as ClassPass, Fitbit, Oura, Whoop, and Flow).

IB1 is generally involved in data sharing schemes where businesses initiate data sharing, rather than individual customers directly. However, we understand that both individual consumers and businesses can face a variety of issues in accessing their data from the services they use and sharing that data with third parties, including:

• A lack of transparency in obtaining consent, including overly legalistic wording, items hidden in small print, and a lack of clarity around the full range of partners’ data will be shared with and/or for what purpose(s).
• Lack of trust – this is key for obtaining consent. 
• Individual/household dilemma – consent for data sharing pertaining to a whole household of people is obtained from a single individual (there may also be a gender bias here if the account holders tend to be male) who may or may not actually live at that address (eg shared subscription service) – there is no mechanism to ensure household members are consulted.
• Revoking or changing consent – it is often easy to give consent (e.g. automatic pop-up) but much harder to change or revoke consent (e.g. requires a log in, hidden in a long settings menu, not available by non-digital means) – this requires much more transparency and an easy process.
• Linked services – Lack of understanding about the impacts of giving, changing, or revoking consent for services that may be linked (e.g. reliant on data flows) but potentially operated by different companies. For example, consumers may not understand the impact of rejecting access to a type of consumption data on access to smart products and services.

2. The government would like to identify where businesses are being held back by poor data access and where these data access issues could be helped through a Smart Data scheme. What use cases do you believe could be supported through a Smart Data scheme to address those issues, including types of products and services that ATPs might be able to offer, and what outcomes could this result in? 

Defining digital markets where businesses are particularly held back by poor data access is again hard to define.

In the context of this consultation – and to delineate this work from the UK Government’s existing work on Smart Data in more clearly defined, regulated markets such as energy and finance – the following can be seen as examples of business-to-business digital markets:

• Operating systems (such as Microsoft Windows, MacOS, Linux, Android and iOS).
• Cloud and compute (such as Amazon Web Services, Microsoft Azure, and Google Cloud).
• Virtual workspaces (such as Microsoft 365 and Google Workspace).
• Project management and productivity (such as Asana, monday.com and Notion).
• Instant messaging and video conferencing (such as Zoom and Slack).
• Large language models and interfaces to them (such as GPT-4, Chat-GPT, Copilot, Gemini, Claude and Perplexity).
• Financial management and accounting (such as QuickBooks, Sage and Xero).
• Customer relationship management (such as Salesforce, Hubspot and Mailchimp).
• Data science and reporting (such as Databricks and Microsoft BI).
• Content production and editing (such as Adobe, Canva and Figma).
• Social media (such as Facebook, Twitter, TikTok, Instagram, Threads and Bluesky).
• Recruitment (such as LinkedIn, Indeed and Adzuna).
• Online marketplaces and retailers (such as Amazon, Temu, Shein, eBay, Gumtree, Etsy and Depop).
• Logistics and distribution (such as SAP, Oracle and EasyShip).
• Online advertising (such as Meta Ads and Google Adsense).
• Payment and transaction (such as Shopify, Klarna, Visa, PayPal and Stripe).
• Web publishing and content management (such as WordPress, Wix and Squarespace).
• Content distribution (such as YouTube and Substack).
• Ticketing (such as Viagogo, StubHub and EventBrite).

This list is far from exhaustive; there are many further domain-specific digital markets.

At IB1, our focus is to drive the development of schemes around tightly-focused challenges or use cases related to net zero. Our flagship programme, Perseus, enables small-and-medium sized businesses to share granular emissions data from their smart meter systems with banks and other lenders. By providing lenders with the accurate and assurable data they need, the Perseus enables participating businesses to access loans and other finance to help reduce their emissions.

We urge DSIT to explore opportunities for Smart Data schemes to drive the sharing of similar energy consumption and emissions data related to these digital markets. The cloud and compute services market, for example, is responsible for a significant and increasing share of global greenhouse gas emissions. The data centers it uses consume close to 3% of the world’s electricity and global greenhouse gas emissions comparable to the airline industry. This could be achieved efficiently by developing or adapting Perseus.

3. What types of data and data holders would need to be in scope of a scheme in order to support any business models and address data access issues and use cases you have identified above? 

Data and data holders to target will depend entirely on the purpose of any Smart Data scheme. 

We believe it will be more difficult for the UK Government to establish a ‘contained’ scope for a Smart Data scheme here than in more clearly defined, regulated markets such as energy and finance. With digital markets, services are often entwined – for example, Facebook is both a social media platform and a marketplace for goods.

Open Banking was delivered through clear identification of a problem in the consumer banking market, supported by evidence. Any smart data scheme for digital markets will need a similarly thorough analysis of the market dynamics that require improved data access and intervention. 

In determining what data holders should be within scope of a Smart Data scheme for digital markets, DSIT could adopt a similar approach to the UK’s Online Safety Act and the EU’s Digital Market Act. Although imperfect – see discussion around Wikipedia’s classification under the OSA – these interventions target organisations with the power to act as gatekeepers to particular markets, primarily based on their user numbers and market position.

In determining the scope of any Smart Data scheme for digital markets, we urge DSIT to:

• Identify a very clear use case. Without this, data sharing doesn’t work. A clearly defined use case ensures there is no ambiguity around the purpose of the scheme and what it must achieve.
• Arrive at use cases and data sharing rules collaboratively. Our approach, Icebreaking, involves scheme co-creation with regulators, consumer organisations and civil society as well as industry.

4. What are your views on the feasibility to deliver a digital Smart Data scheme? Please consider any current or planned industry developments or changes that might affect delivery and highlight any key challenges.

Delivering a Smart Data scheme for digital markets is eminently feasible, even accounting for the difficulties described above. Perseus is proof of this, with banks starting to use the data to inform real loan-making.

5. Do you have an initial or provisional view on the likely impacts (positive and negative) on:

• Existing and future customers
• Data holders
• Small and micro businesses

We encourage the identification and definition of clear use cases with defined users (as mentioned in question 3) to be able to comment on likely impacts.

6. Do you have an initial or provisional view on the likely impacts (positive and negative) on:

• Innovation in the supply or provision of goods, services and digital content whether directly affected by a scheme or otherwise
• Competition in markets for goods, services and digital content affected by the regulations or other markets
• Business investment in the UK
• Economic growth

We encourage the identification and definition of clear use cases with defined users (as mentioned in question 3) to be able to comment on likely impacts.

7. What challenges and risks should we consider when developing a digital markets smart data scheme and how can we mitigate these? This might include (but is not limited to): competition; customer exclusion; data quality or data misuse; ethical, operational or technical readiness.

We see the following risks to successful delivery: 

• Developing a centralised solution. 
  • Mitigation: embrace a decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection (ensures alignment with national strategy, Open Banking has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA)).
• Not codifying the relationship and responsibilities of the smart data scheme to be in support of the UK’s net zero and climate targets. This is essential to meeting the UK’s net zero and industrial strategy goals.
  • Mitigation: Codify the relationship between a digital market smart data scheme and existing net zero goals.
• Not following a use case driven approach. The risk is trying to do too much at one time, and the programme becomes overwhelmed without a core focus point.
  • Mitigation: follow a use case driven approach 
• A chosen use case does not have a clear business impact case. If there is no financial incentive, there will be no movement.
  • Mitigation: an advisory group articulates their business case for the chosen use case. 
• Failure to implement governance from the start, and governance failure to address broader user needs, technical implementation, legal, communication / engagement and policy impacts.
  • Mitigation: robust governance from the outset. 
• Lack of cross sector collaboration. Risk of non-interoperability and not taking the learnings from other sectors.
  • Mitigation: actively engage with stakeholders from the start.
• Too much emphasis on a technical solution  – must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure a scheme is fit for purpose
  • Mitigation: understand the holistic approach required – user needs, legal, policy, and communications. https://ib1.org/sops/governance-schemes/ 
• Cultural change and industry readiness 
  • Mitigation: interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Stakeholder engagement for collective agreement across the sector
  • Mitigation: engage early, often, and formally through governance.
• A scheme is seen as a technical solution rather than a holistic solution.
  • Mitigation: a trust framework incorporates technical, communications, engagement, legal and ongoing governance arrangements.
• Unequal access to smart services if we do not address the challenges known to exist in digital markets or known barriers to access, and any other infrastructure collecting the data which will be used in the scheme. This unequal access will be baked into any smart services offered and may unintentionally miss out key beneficiaries.
  •  Mitigation: robust governance experience to reduce unintended impacts.
• Creating unintended monopolies, negative incentives, corporate capture, and data misuse
  • Mitigation: robust governance, embracing and building upon open source solutions. 

8. What are the potential implementation costs to industry of introducing a digital markets Smart Data scheme? What aspects of a scheme might be most expensive to implement?

Open Banking is a case study for engagement for Smart Data. It has over 15 million users and over 29 million transactions per month. This provides strong evidence that there is both appetite and capability for British consumers to engage with Smart Data utilising a Trust Framework approach. 

Since 2013, it has cost Open Banking £millions to achieve this success. Building on the foundations of Open Banking, the Smart Data schemes Open Energy and Perseus have been able to be in pilot phases for £3.5m. With these foundations laid, costs for smart data schemes should be reduced over time as we build on the existing investments and lessons learned through implementation.  

As a key learning from the success of Open Banking is to follow a use case driven approach, it is vital to note that identifying the user(s), their needs and developing use cases requires time, effort and resources. This can be a challenging aspect of a scheme to define but it is a core element as everything is built around the user needs. 

Another key learning from Open Banking, Open Energy, and Perseus is the importance of incorporating robust governance from the outset. Implementation costs will include secretariat functions for a governance body, relevant company time for stakeholder engagement and scoping requirements, and technical implementation. This will include team members from across an organisation, which may include innovation, technical, data, research, legal, communications/PR, and policy compliance teams. 

9. How can we build and maintain customer trust in a digital markets Smart Data scheme? For example, what responsibilities need to be considered for data owners and ATPs?

Obtaining consumer consent and customer trust is key for a digital market smart data scheme. It is important to note that the current methods for obtaining consent from a consumer may be ineffective or inefficient as laid out in our response to question 2. 

As mentioned in IB1’s Developing an energy smart data scheme: call for evidence response, please find our recommendations to build and maintain trust with core principles below:

• Governance mechanism is built to function flexibly: As digitalisation of the wider economy accelerates it is essential that governance adapts with a shifting technical landscape. There will be a continual balance between addressing user needs and potential threats, necessitating robust governance to be participatory and responsive to a full spectrum of social and environmental considerations shaping the operational landscape, for example including capacity to respond to forthcoming Net Zero 2030 milestones. 
• Simple and Low Friction: IB1 recommends a simple and low friction option which builds on previous implementation in other industries, for example Open Banking which has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA), to ensure an energy smart data scheme is aligned with national strategy.
• Interoperable IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. IB1 suggests the solution defines relationships with cross-sector bodies to enable cross-sector interoperability.
• Agile, Flexible, and Scalable: IB1 suggests introducing a clear process for change management in this principle. As governance needs will likely change with time. This may include indication of how the list of permitted data use purposes will be maintained with additions and removals
• Transparent and Informative: IB1 strongly recommends that documentation is published openly, along with any accompanying processes, methodologies, financial, legal, operations and governance processes, as also suggested in our DSI consultation response. 
  • Clear and consistent use of definitions and communications surrounding data. IB1 uses the data spectrum to communicate the definitions and differences between Open, Shared, and Closed data. 
• Inclusive by Design: IB1 urges the defined user journeys, messaging, terms, and customer support to be easy to use, transparent, and explained in a way that someone with a low technical reading comprehension can engage with. IB1 recommends building on open source, if not incorporated, there is a risk of inadvertently creating a monopoly.

• Secure by Design: IB1 encourages working with the National Protective Security Authority (NPSA) and National Cyber Security Centre (NCSC). IB1 would also recommend an adversarial analysis to be performed to see where security gaps may occur, and may affect the proposed architecture. A Smart Data scheme must avoid creating large targets for hackers where a compromise affects many consumers. Data required for investment must undergo a thorough assessment of risks, benefits, security measures, and potential international standards as there may be implications for data transfer and use across the UK and international borders. 
• IB1 recommends a focus on data rights: the same data will be used for many purposes. This means there will be multiple rights, based on purpose, carrying different legal, liability and related conditions. 

10. What common principles are needed to support the development of a digital markets smart data scheme and why?

We have recently introduced NOVA. A ‘NOVA-compliant’ solution embodies a coordinated structure of interoperable rules, governance, and infrastructure that connects actors across sectors while ensuring data flows are lawful, rights-based, and fit-for-purpose. NOVA stands for:

Networked

Data infrastructure must support modular, federated and interoperable participation across organisations, sectors, and jurisdictions.

• Modular: embody what is needed in a repeatable, cohesive and scalable manner
• Federated: support the coexistence of multiple platforms, protocols, and providers
• Interoperable: systems (not just technical, but also legal and operational) must be able to interact with low cost and friction, with harmonised approaches

Open

Data infrastructure must be grounded in open standards, API-enabled access, and transparent governance.

• Open standards: standards which are openly accessible and usable by anyone
• Open APIs: a web-addressable interface that enables machine-enabled data exchange
• Transparent governance: clear, accurate, and timely disclosure of policies, decisions, performance and impact

Verifiable

Data infrastructure and data access, usage, and governance must be assurable, rights-based and permissioned.

• Assurable: that the process of joining as a member, and of enabling data transfer and use can be audited, tracked and held to account
• Rights-based: data sharing is based on legal and related rights, codified in a contract, and enabled between assured members
• Permissioned: where relevant, or required by law, that permission or consent is given from the business or consumer, or that pre-authorised permission is determined by contract

Architecture

Data infrastructure must optimise for market access while enabling adaptive governance, whether market participants are data providers or data users, to ensure an open market.

• Market access: enable any Verifiable actor to enter the market
• Adaptive governance: define, iterate at market-relevant pace, enable, and facilitate scalable enforcement of, the rules
• Open market: ensure private sector, public-benefit, and national interests are addressed

11. Are there any tensions, overlaps, gaps or other features of the regulatory landscape in digital markets that the government should take into consideration?

As noted in IB1’s response to the Department for Science, Innovation, and Technology’s Technology Adoption Review, IB1 notes a key barrier to digital market and technology adoption, investment, and participation is a lack of a consistency in vision and policy which is vital for the decision makers in the organisations and companies to de-risk technical and innovation investments. Having a cohesive, consistent vision with clear actions allows for stakeholders to incorporate data sharing and data access at the core of their decisions.

As the data sharing economy develops in a manner which is increasingly fluid and cross-sector there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

Additionally, it is essential to have consistency within sectors and to consider cross-sector interactions of digital market Smart Data schemes, especially across the pinchpoints where sectors meet and/or markets are increasingly ‘coupled’ (i.e. energy and transport; energy and water; energy and manufacturing). It is essential that a smart data scheme promotes interoperability and consistency across sectors, promoting a whole-system approach to digitalisation and net zero.

12. What data sharing initiatives already exist in digital markets that the government should be aware of when evaluating a Smart Data scheme in digital markets?

Open Banking

The Open Banking Standard, which is now implemented in over 95 jurisdictions and a £20B open market, placing the UK at the forefront of data sharing innovation. It uses financial-grade APIs within a strong, neutral governance framework to address data policy, licensing, privacy, liability and technical standards. 

Perseus

Icebreaker One’s Perseus Scheme (the ‘rule book’ defining how data is governed) is aiming to facilitate trusted, standardised, permissioned and secure data sharing across sectors. It addresses key challenges in data interoperability and trust by linking data systems through a cohesive Trust Framework, streamlining the process of collecting and reporting emissions data. By enabling interoperability between members, it enables SMEs to minimise their manual effort in measuring and reporting their GHG footprint, and matching their profile to green finance. 

It is being developed by a group including commercial businesses (incumbents and challengers), non-profits, public bodies and trade associations, with support from the UK Government.

Open Energy

Icebreaker One’s (IB1) UKRI Modernising Energy Data Access competition-winning programme Open Energy has identified and articulated the need to make it straightforward to find, access and share energy data. IB1 established an energy sector data sharing programme through sector engagement (convening 100s of organisations and 500+ public webinar attendees) and governance processes (80+ Steering and Advisory Groups members) to develop operational services for search and access control. These are are now live and market-facing through the Energy Sector Trust Framework and Schemes, IB1 created, designed and developed Open Energy https://ib1.org/energy/ to provide three services:

1. Community: an expert network of professionals – the IB1 Constellation
2. Governance: co-design of data sharing Schemes using our Icebreaking process
3. Trust Services: An Energy Sector Trust Framework for Scheme implementation, covering Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent. In addition, Trust Services deliver search and assurability services. 

Our approach helps drive the design, implementation and adoption of open standards to create assurable data flows between organisations. This enables assurable Open Data and pre-authorised Shared Data and ultimately builds confidence across the ecosystem.

As noted in IB1’s Developing an energy smart data scheme: call for evidence response,international examples of data sharing initiatives include (not all smart data schemes):

• India: https://indiastack.org/
• Government scale (not energy system) Taiwan – https://digi.taiwan.gov.tw/ MyData – https://www.ndc.gov.tw/en/nc_8455_34364 
• COVID tracking – data governance: https://academic.oup.com/policyandsociety/article/41/1/129/6513795
• See for examples of data ecosystems and learnings: https://cris.vtt.fi/en/publications/guidebook-data-ecosystems-for-smart-sustainable-cities 

13. What lessons should we bear in mind from Open Banking that would be helpful to consider when developing a digital markets Smart Data scheme?

It is essential that Open Banking is viewed holistically – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution.

IB1’s foundational work on Open Energy, Open Net Zero and approach to data sharing is based on the foundations of Open Banking. IB1 practises this through:

• Decentralised architecture implementation
• Advocating for common secure web standards (i.e. FAPI)
• Openly published rules and clear governance structure 
• Openly list service providers are available
• Providing member services 

As mentioned above, a key learning from the success of Open Banking is to follow a use case driven approach.

General lessons from national and international data sharing initiatives: 

• Incorporate governance at the outset. It is difficult to retroactively implement robust governance.
• Ensure governance is robust, participatory and responsive. It will be required to adapt to a full spectrum of social and environmental considerations shaping the operational landscape. A governance model must reflect the socio-technical nature of the energy sector, not just the technical side.
• Avoid putting too much emphasis on a technical solution  – An energy smart data scheme must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure the solution is fit for purpose.
• Complexity and collective agreement across the industry – an initiative must recognise the complexity and changing nature of the energy industry.
• Cultural change and industry readiness – must understand and interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Appropriately defining and governing the roles and responsibilities.
• Appropriate legal support and resourcing – a mechanism must develop the applicable data licences, and needs to be appropriately resourced to be able to do so. 

14. What lessons should the government bear in mind from the EU DMA and other Smart Data schemes in other jurisdictions including the establishment of Open Banking schemes around the world?

Icebreaker One Founder & CEO, Gavin Starks, co-chaired the development of the Open Banking Standard, co-chaired the UK Smart Data Council, and was founding CEO of the Open Data Institute. Since then Gavin has advised New Zealand and Canada on their implementation of Open Banking in their jurisdictions. 

In New Zealand in particular, the initial implementation of Open Banking was sector-led by Payments NZ. In 2017 and 2019, former Ministers of Commerce and Consumer Affairs wrote to New Zealand’s banks to encourage them to advance sector-led initiatives for open banking. From 29 August to 10 October 2024, the Ministry of Business, Innovation, and Employment consulted on policy settings for banking regulations under the Customer and Product Data Act, the regulations for which were then drafted in 2025. This shows the importance of both industry collaboration and regulatory mandate to drive sector-wide adoption.

15. Do you have any additional comments on any aspect of developing a digital markets Smart Data scheme that has not been covered elsewhere in this call for evidence?

None.

Co-chaired by Icebreaker One and NWL, the group’s primary function is to help provide leadership and market signalling. Oversight of, and endorsement from, this group will establish a lasting set of robust governance measures to ensure data is shared safely and with the correct regulations.

Meeting Aims:

1. Introduction to the Cunliffe Review in preparation for aligning on responses in the next meeting 
2. Conduct vote to endorse setting up Data Standards Water Quality Monitoring 
3. Conduct vote to confirm endorsement by members of the Innovate UK bid 

Summary:

Q3 outcomes update and engagement overview

• It was noted that:
  • Work is progressing as planned, with only one item in the technology pillar at risk of not being completed.
  • An engagement sheet has been created to track all activities in Stream and to identify gaps, especially around voting.
  • Improvements are being made to address barriers to engagement, such as adding links to chaser emails and increasing visibility of upcoming work.

Cunliffe review framing

• It was noted that:
  • Ofwat will be replaced by a new regulator following the Cunliffe Review
  • Individual meetings will be arranged during October between Ofwat and water companies to discuss open data progress and future plans.
  • 37 review recommendations relevant to Stream will be reviewed at the next SG meeting.
  • Members were asked to review recommendations and prepare for discussion on Stream’s future role.

Data standards for continuous water quality monitoring (CWQM)

• It was noted that:
  • Section 82 of the Environment Act mandates continuous monitoring of discharges with near real-time data publication in a common format.
  • Alignment with regulatory obligations, transparency, and open publication are key drivers.
  • Implementation timelines vary across companies.
  • Stream’s role may require coordination with Water UK or other bodies for broader sector inclusion.
• It was discussed that no definition has yet been given for the “common format,” creating both a challenge and an opportunity to define standards early, to ensure that fragmented approaches seen previously (e.g., NSOH) are avoided.
• The English WaSCs agreed that:
  • There is a need for a CWQM data standard.
  • They supported  Stream convening WaSCs to define this standard.
  • They supported Stream leading consistent near real-time publication.
  • They are willing to participate in a follow-up session.
• It was noted that additional companies want to take advantage of being involved in the data standardisation discussion.
• It was noted that the next step would be to gain consensus on the plan to create and publish a standard and co-ordinate the open publication of the data.

Costing Working Group update

• It was noted that:
  • The Costing Working Group (WG) has met several times and proposed a draft set of commercial principles to guide work beyond core running costs.
  • The principles aim to safeguard Stream’s open data mission while enabling aligned commercial work; members were asked to consider their appropriateness.
  • The model supports Stream’s independence from NWL, working towards a not-for-profit structure post-project phase.
• It was discussed that:
  • A freemium model is being considered, with open use cases remaining free and optional commercial services layered above.
  • Lessons from NSOH show the importance of securing parallel resourcing to avoid diverting core teams.
• It was noted that early feedback supported the approach, including a desire to avoid increased subscription fees while leveraging co-funding opportunities such as the Ofwat Innovation Fund.

Breakout group 1 feedback:

• It was agreed that Stream must maintain a foundational, business-as-usual programme focused on publishing, updating, and maintaining core open data services.
• It was discussed that:
  • There are outstanding governance questions, including whether thresholds could be introduced to streamline approval for smaller projects.
  • The distinction between commercial and non-commercial activities may challenge existing principles, and a sub-committee or working group could be established to manage these complexities.
  • Publishing third-party data raises considerations around data security, SLAs, and service expectations, particularly under commercial agreements.
  • Clear value demonstration is essential for stakeholder support, including defining impact metrics and understanding Stream’s addressable market within public-good versus private sector boundaries.
• It was noted that financial thresholds could be introduced to distinguish between minor and major projects requiring SG oversight.

Breakout group 2 feedback

• It was noted that:
  • The group broadly supported the proposed commercial principles, recognising the viability of an open and premium model.
  • Public bodies may face constraints in engaging with commercialised data models.
  • The group supported further refinement and wordsmithing of the draft commercial principles.
• It was discussed that maintaining alignment with Stream’s vision and avoiding dilution of its public-good mission is essential.
• It was suggested that a governance committee could be established to manage commercial decision-making and mitigate against mission drift.

Innovate UK Bid – Water ontology and AI workshop

• It was noted that:
  • A visioning workshop is planned for 10 September to explore the use of AI in accelerating development of a water sector ontology, supported by UCL, the Future Water Association and Visioning Lab.
  • The initiative aims to address the lack of a common ontology across the water sector and determine how AI might assist in resolving that gap.
  • No costs are associated with the initial workshop, and at least two water companies are required to support the Innovate UK bid.
  • Stream’s involvement was seen as positive for ensuring sector-wide alignment and engagement, including access to shared datasets and structured workshops.
  • The scope will likely need to narrow over time due to the complexity of the challenge.
  • Stream members were asked to vote to indicate their willingness to participate in the Innovate UK bid, which they passed in favour
• It was discussed that data protection and vendor lock-in were key concerns; participants requested assurances about non-functional requirements, such as secure environments and ring-fenced data

Meeting Aims

1. Group is prepared for comms moments in H2
2. Gather feedback on end-of-year report comms and engagement

Summary:

• It was noted that:
  • AG1 approved and the SG discussed and positively received, that Perseus will shift the strategic narrative from “financing green” (focused on a small subset of green-linked loans) to “greening finance” (using Perseus data across FSP solutions) both to broaden impact, the total addressable market, and address shifts in language in the market (e.g. transition finance, efficiency, cost reduction, improved productivity, and enhanced business resilience). 
  • 2026 upcoming activities will focus on making the scheme operational at scale with product enhancements, scope on greening finance, adding gas as a data category, a focus on comms and engagement, and investigation of future scope expansion (e.g. Orion).
  • Perseus will be mentioned within UK Business Climate Hub’s 2025 UK Net Zero Business Census Report – being published 21 October, and will aim to be mentioned in the BBB SME Vertical Report – publication date TBC
• It was agreed that:
  • To showcase the 2025 Perseus report content, IB1 will pull out short form content to highlight Perseus’ users, their story and their benefits
• It was discussed that:
  • The shift to “greening finance” is a strategic shift for Perseus, with the best forum for discussion in AG1, however, it will require a messaging shift to ensure Perseus continues to highlight the benefits for different groups of stakeholders 
  • Upcoming comms moments will include:
    • The sandbox launch announcement focussed on the benefits of engaging,  who is engaging to become ‘Perseus-ready.’ 
    • XBRL integration announcement, highlighting how the alignment with them means Perseus speaks common business reporting language & disclosures
    • Perseus report launch, which will include 2025 progress and the 2026 plan.

Meeting Aims

1. Shared understanding and alignment of business model and how it will be leveraged
2. Align on language and positioning for financing green vs greening finance

Summary:

• An AG1 vote approved and the SG discussed and positively received, that Perseus shift the strategic narrative from “financing green” (focused on a small subset of green-linked loans) to “greening finance” (using Perseus data across FSP solutions) both to broaden impact, the total addressable market, and address shifts in language in the market (e.g. transition finance, efficiency, cost reduction, improved productivity, and enhanced business resilience). 
• It was discussed that the new Proposed Voluntary SME Sustainability Reporting Standard developed by B4NZ and the Broadway Initiative will be implemented by IB1 as Project Orion. It will connect and build upon Perseus with independent funding and governance that will be designed in 2025. 
• The 2026 business model for Perseus was presented and discussed:
  • Perseus will retain a multi-tiered membership model, with the aim to increase the number of members to drive down individual membership fees
  • The plan is to make the scheme operational at scale with product enhancements, scope on greening finance, adding gas as a data category, a focus on comms and engagement, and investigation of future scope expansion (e.g. Orion).
• The Advisory Group updates noted that:
  • AG1 will now focus on a long-term vision of greening finance, targeting high-impact SMEs, and reframing language to improve engagement. The group endorsed sharing information to aid the estimation of the Total Addressable Market (TAM), discuss potential corporation tax incentives with HMT, and support the greening finance vision.
  • AG2 is transitioning from pilot to sandbox and production phases. AG2 members agreed a revised, simpler approach for technical security certificates better suited to cloud environments, and this will be used in both sandbox and production systems.
  • AG4 has updated the core narrative and language in the customisable media pack (https://ib1.org/perseus/media-pack). Upcoming plans include communications for the sandbox launch and highlighting XBRL integration to demonstrate alignment with standard business reporting.
  • AG3 & AG5 are due to hold workshops in September and AG meetings in October
• The Delivery Oversight Committee (DOC) noted that
  • They are comfortable with the continued management of the project by the IB1 team, and broadly satisfied with Perseus’ financial situation, management, cash flows, risk management, and budgets
  • New risks include:
    • successful mitigation of the risk of dissipation of resources and focus due to the arrival of Project Orion, 
    • monitoring risks that could arise with broadening of the project’s scope from ‘financing green’ to ‘greening finance’.
  • Increased risks include:
    • volatile policy environment, including potential pushback against climate and environmental initiatives
    • managing challenges associated with payment schedules from large companies (and cashflow)
  • J Geldart will be temporarily stepping down as Chair of the DoC. The SG acknowledged his material effort and support to the programme. T Greenham will take up the interim Chair of the DOC for 2025.

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer.

Consultation response:

Icebreaker One (IB1) is a public-benefit non-profit working on data sharing and sustainability, convening organisations and governments to design market-scale solutions to make data work harder to deliver Net Zero. It creates and runs programmes to reduce barriers and costs to finding, accessing, using, and sharing data, which will ultimately reduce costs for consumers. Through the UKRI Modernising Energy Data Access competition, in collaboration with over 400 industry stakeholders, IB1 developed Open Energy which identified and articulated the need to make it straightforward to find, access and share energy data. Given IB1’s focus, we have responded to a number of the questions in the consultation. 

IB1 supports RIIO-ED3’s goals of moving away from gas infrastructure, toward renewables, and a more resilient grid. It is essential to have a joined-up approach and cross-sector thinking to achieve the size of impact outlined in the Industrial Strategy and The Clean Power 2030 Action Plan and unlock the widest range of potential benefits.

OVQ36. Do you agree with our position of not changing the Digitalisation licence condition?

IB1 supports digitalisation as key for energy sector decarbonisation, and required for the investment in flex services and the coordination between sectors who rely on energy to meet their decarbonisation targets (water, transportation, built environment, industry).

IB1 supports sector-wide convening and governance to ensure digitalisation happens in a coordinated manner and can enable ‘whole system solutions,’ as promoted in RIIO-ED2 and realise the subsequent cost savings. IB1 supports Ofgem to continue to promote and finance whole system digitalisation coordination in RIIO-ED3.

As there are many ongoing data sharing and data governance initiatives e.g. consumer consent solution, flexibility services, Data Sharing Infrastructure (DSI), which are currently in progress at different stages of development (definition, prototype, or pilot). Ofgem should not expect these programmes and underlying challenges the projects aim to solve to be resolved by the end of RIIO-ED3 (2031). Data sharing and data governance needs and subsequent solutions will evolve over time as we continue to electrify and connect the UK’s grid. As mentioned above, Ofgem needs to ensure ongoing governance and sector collaboration on data and digitalisation – reinforcement of this would be welcomed in addition to specific plans to expand/evolve data governance initiatives.

With the progress of the Data Sharing Infrastructure (DSI) programme, IB1 anticipates ‘Shared Data’ sharing will evolve and will inform the evolution of data best practice (DBP) guidance. In particular, as data sharing scales, the need to standardise and harmonise legal and technical approaches will become more pressing in order not to slow innovation and add unnecessary cost. IB1 recommends that DBP should include guidance around Shared Data within the triage processes and licensing decisions, highlighting the role of Shared Data Schemes (see OVQ37) to provide definitions that aid interoperability and maximise impact.  

OVQ37. Do you agree with our proposed approach to the DSI licence condition?

IB1 welcomes the energy industry collaborating and agreeing on data sharing. Through IB1’s Open Energy programme, we have co-designed the Energy Sector Trust Framework with sector stakeholders, including DNOs. Members are currently in the process of assuring their open data publication using the Assured Open Data Scheme governed by Open Energy. IB1 will continue to bring Open Energy learnings into the DSI development process. 

We encourage more clarity on what DSI ‘participation’ entails, including anticipated associated costs and funding. As mentioned in IB1’s response to DESNZ energy smart data scheme call for evidence, it is essential that a Trust Framework is viewed holistically – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution. IB1 would recommend ‘participation’ in DSI is defined as being broader than operating data sharing nodes, including:

• In collaboration with stakeholders within and outside the energy sector:
  • Identifying and developing use cases
  • Designing technically- and legally- interoperable schemes
  • Agreeing, implementing and governing operational policies
  • Keeping in step with emerging trusted data approaches in other sectors of the economy, at home and abroad
• Articulating the amount of technical and non-technical work required for a Trust Framework 
• Articulating the role of consent and permissioning aligned with the 2025 Data (Use and Access) Act.
• Setting out the expected amount of resourcing including external and internal communications, executive support, legal resource, and skilled involvement in data governance and technical implementation

Our experience is based on establishing an energy sector data sharing programme through sector engagement (convening 100s of organisations and 500+ public webinar attendees) and governance processes (80+ Steering and Advisory Groups members) to develop operational services for search and access control. These are are now live and market-facing through the Energy Sector Trust Framework and Schemes, IB1 created, designed and developed Open Energy https://ib1.org/energy/ to provide three services:

1. Community: an expert network of professionals – the IB1 Constellation

2. Governance: co-design of data sharing Schemes using our Icebreaking process

3. Trust Services: An Energy Sector Trust Framework for Scheme implementation, covering Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent. In addition, Trust Services deliver search and assurability services. 

We recommend drawing upon this experience to both clearly and tightly define expectations for the DSI licence condition, and the roles of actors in the ecosystem (e.g. what is within the remit of regulators and code bodies, what could/should be precompetitive and what is open to commercial market competition).

Meeting Aims 

1. What’s the next best step to take within the analytics space? 
2. Understanding the challenges and pain points within the Stream platform 

Summary:

• Outcomes:
  • It was noted that:
    • The session focused on analytics, with the aim of identifying next steps and user needs.
    • Operations and technology workstreams are progressing, though minor blockers remain (e.g., Teams accounts for IB1).
    • No immediate support is required, but risks were raised for awareness.
• Definition of analytics
  • It was discussed that:
    • Analytics should support understanding of user engagement, platform usability, and dataset value.
    • Analytics requirements differ by user group (e.g., Product Team vs water company members and their Boards), necessitating tailored approaches.
    • Developing analytics as a product backlog using user stories would aid iteration.
  • It was noted that:
    • Two core categories exist: platform experience analytics and data consumption analytics.
• Sector examples:
  • It was noted that:
    • Members seek better tools to assess data usage trends and engagement over time.
    • User account systems could improve attribution but may conflict with open access principles.
    • Reservoir dataset engagement provided a strong narrative, aligning with public search trends.
    • A member company’s NSOH API received over 5 million queries, with estimates suggesting polling activity by 50–100 organisations at 5–15 minute intervals. While precise use cases are unknown, this indicates sustained external interest and engagement with the data.
    • Tracking the impact of social media activity, such as LinkedIn posts promoting datasets, could help assess whether such communications drive greater user engagement with data.
  • It was discussed that:
    • Current analytics are insufficiently granular and fragmented across sources.
    • Tools like Google Analytics provide partial solutions without requiring logins.
    • Incorporating prompts during the user journey, asking users to indicate the purpose of their data download or map use, could improve understanding of dataset value and inform analytics.
    • Real usage insight helps validate our platform’s impact and guide future dataset priorities.

Meeting aims:

1. To prepare members for the next use case prioritisation conversation (next AG) 

2. Co-create the Open October event 

Summary:

• Outcomes review:
  • It was noted that:
    • that outcomes for Q3 are progressing as planned. The APR dataset was published on 1 August, with work underway on data quality and the DWQ dataset.
    • that ecosystem pillar items are also in progress, with no concerns raised.
• Use case prioritisation:
  • It was noted that:
    • Six AMP8 priorities were confirmed: water efficiencies, protecting the environment, health and safety, customer experience, net zero, and infrastructure/resilience.
    • CReDO will be prioritised for discovery in Q4, while other use cases remain in the backlog or blocked due to external constraints.
    • Tagging each use case with AMP8 priorities would strengthen future prioritisation discussions.
• It was discussed that overlaps between priorities mean a single use case could address multiple areas.
• It was agreed that members should provide additional input and new use case ideas ahead of the next Advisory Group at the end of September.
• Cross-sector use case: CReDO
  • It was noted that:
    • CReDO 2, focused on climate adaptation and cross-sector resilience, will begin discovery in September, with Connected Places Catapult, Edinburgh University, and Northumberland among the partners.
    • CReDO is considered a high-profile use case and a significant opportunity for Stream to demonstrate impact.
  • It was discussed that:
    • Questions remain on the granularity of probabilistic asset failure analysis, which will be clarified in future sessions.
• Open October planning
  • It was noted that Open October will run 13–16 October with a hybrid hackathon and in-person event, themed around systems thinking.
  • It was discussed that Leeds, Wales, and Yorkshire have offered to host, while an East region location is still being explored, however, the event may be condensed to one location depending on availability.
• Group 1: Hackathon challenge focus
  • It was discussed that potential hackathon themes include Cleaning Up the UK’s Rivers, Lakes and Seas, storm overflows, lead in drinking water, water scarcity, per capita consumption, leakage ratios, and energy-water resilience.
  • It was noted that:
    • Some data gaps may limit feasibility (e.g. reservoir levels).
    • Aligning this hackathon with learnings from the year’s previous hackathons may provide continuity, with water scarcity and drinking water quality framed as possible themes for the following year.
• Group 2 – In-person event design
  • It was noted that engagement and communication remain a challenge, and members endorsed using the event to demonstrate Stream’s alignment with AMP8 priorities and to showcase successes.
  • It was discussed that:
    • Tangible open data examples (APR, NSOH) would help secure internal support for attendance.
    • Togetherness and cross-company engagement were key benefits of one in-person meetup.
    • A session on data sharing models/infrastructure should be considered to support progress toward shared data.
    • Water companies wish to see a clear three-year roadmap with defined expectations of involvement.
    • A presentation on digital twins and discussion of Section 82 delivery would be valuable.

Meeting Aims:

1. Update AG1 members on recent workshops
2. Vote on proposed directions
3. Update members on plans for the next quarter

Summary:

• It was noted that:
  • Since the last AG1 meeting, we held two Total Addressable Market (TAM) focussed workshops to:
    • determine the TAM
    • discuss the change of vision to be ‘greening finance’ from financing green to expand the financial offerings Perseus is able to impact 
    • Shaping a message for the Net Zero Council 
• It was voted that a quorate of attendees:
  • would be happy to supply UK Finance (or similar) with information (anonymised if required) to help them estimate the TAM.
  • Supported the Perseus Steering Group (and Delivery Oversight Committee) to approach/discuss tax incentive approaches with HM Treasury.
  • Agreed with the long-term vision to transition to “Greening Finance” as a more expansive approach encompassing all business accounts rather than “Financing Green” focusing only on green lending.
• It was noted that:
  • More case studies demonstrating the value and impact of using Perseus with financial products are essential
  • Progress is being made to include gas, with only minor amendments to the existing process being required
  • IB1 is in conversation to implement the Proposed Voluntary SME Sustainability Reporting Standard (codename: Project Orion)

Meeting Aims

1. Highlight an issue which risks slowing down the progress to data sharing and the amount of value it could bring
2. Alignment on approach and definitions
3. Alignment on market architecture proposal

Summary:

Definitions, roles and responsibilities in the market around data sharing

• It was noted that:
  • Inconsistent use of key terms such as “Schemes” and “Trust Frameworks,” have contributed to causing wider confusion across the industry, hindering decision-making and alignment. 
  • Future data sharing frameworks are likely to involve multiple, independently governed trust frameworks, making coordination and interoperability essential.
  • The forthcoming DEZNZ and Ofgem flexibility roadmap and response on Data Schemes are expected to acknowledge sector-wide fragmentation and coordination challenges, and may provide further clarity on roles, responsibilities, and implementation expectations.
• It was discussed that, while some participants identified the absence of a central coordinating orchestrator as contributing to delays and duplicative costs, others questioned whether such a role is essential, proposing that clearer implementation responsibilities and project-level accountability might be sufficient. However, concerns were still raised around the “grey areas” of overlap or lack of clarity.
  • It was noted that:
    • Coordination is particularly important in the context of any move towards cross-sector as opposed to within sector alignment.
    • There is some apprehension around cross-sector coordination, which could be mitigated by exploring different pilot projects to see where the value drivers, risks and potential funding sources are, ensuring that practical problems are addressed.
• It was agreed that:
  • Open Energy should explore initiating and/or support sector-wide dialogue to unify terminology and framework design.

The value question: market architecture proposal

• It was noted that
  • Existing estimates, such as £20bn from the Smart Data Forum and £7bn delivered by Open Banking, suggest significant but potentially understated economic value.
  • There is intra-organisational disjointment, making it even harder to achieve inter-organisational collaboration.
• It was discussed that:
  • Determining what is pre-competitive infrastructure (e.g. Schemes, Trust Frameworks) versus competitive innovation space, is key to unlocking participation from a wide range of actors.
  • A collectively developed model could help engage government stakeholders and clarify implementation pathways, moving the proposal from conceptual to operational.
• It was agreed that a credible valuation of a joined up approach to data infrastructure is essential to building momentum, and that both top-down and bottom-up estimation approaches have limitations, and that Open Energy should continue to explore this proposal. 
• However, it is currently not the right time to proceed with it, instead we should all consider what comes out of the Flexibility Roadmap publication, and the Government response on developing a data scheme in the energy sector (these were both published the day after the SG, on 23 July 2025, along with a Call for Evidence on improving the visibility of Distributed Energy Assets and a Consultation on the best way to engage consumers on consumer led flexibility).

Co-chaired by Icebreaker One and NWL, the group’s primary function is to help provide leadership and market signalling. Oversight of, and endorsement from, this group will establish a lasting set of robust governance measures to ensure data is shared safely and with the correct regulations.

Meeting Aims:

1. Sentiment and comments on end of phase report 

2. Decision around revisiting the use case 

3. Impact and outcomes

Summary:

• It was noted that members should be working towards a position where their votes are formal endorsements on behalf of their organisation.
  • In addition, it was noted that in any vote, there is an option to delegate responsibility.
• It was noted that there were a couple of OKRs that did not progress from last quarter, including one regarding the engagement of legal representatives from water companies. This OKR was put on hold due to not getting a full list of names nor a tangible use case for legal teams to dig in as a reference point.
• It was noted that public interest and search on the Stream platform for the reservoir dataset has increased.
  • It was discussed that it would be worth revisiting this dataset now that demand is there, particularly during a dry period, to help drive behavioural changes.
  • It was noted that in order to understand the true impact of the data, we need to engage with users to find out how they are using the data, which could be done via a short survey or blog post that notes Stream’s response to reservoir concern and how we are responding to it.
• It was noted that Stream’s LinkedIn lead magnet and  external newsletters have been well received, with a strong open rate and subscriber list.
• It was noted that internal newsletters are not performing as well currently, particularly click through rate, which is being addressed by trialling a few different features.
• It was noted that an end of phase report has been written and shared with members to incite feedback and to ensure there was a general consensus on the benefits articulated.
• It was noted that
  • Stream has elevated the importance of open data within organisations, enabling increased executive engagement and supporting internal project advancement.
  • the foundational infrastructure established through Stream enabled the delivery of projects such as the National Storm Overflow Hub.
  • the attraction of additional funding validates the credibility of Stream.
• It was discussed that
  • Stream facilitates sector-wide conversations that individual companies may not be well-positioned to initiate, particularly with external stakeholders who are critical of the water sector.
  • external testimonials from users and organisations that have benefited from Stream would strengthen the evidence of impact.
• It was noted that
  • the report was well received, with Stream’s role in improving transparency and APR data quality highlighted as key achievements.
  • there is good consensus amongst members that it’s hard to bring a complex set of organisations together and maintain activity.
  • the report should also acknowledge the challenges that have been faced, highlighting where the initiative has had to pivot during implementation.
  • outcome metrics and public benefit assessments are considered to support external communication and more effective stakeholder engagement.
• It was discussed that
  • the value of data should be recognised across its full lifecycle, not only when converted into insight or wisdom
  • third-party and indirect reuse of Stream data (e.g. sewage mapping tools) may extend its reach beyond what is currently measured.
• It was noted that two new working groups are in need of member support: Open October Planning and Technology Tool Stack Framework, and a registration form was provided for expressions of interest.

Meeting Aims 

1. Members to review and refine the end of phase report findings 
2. Members to shape the impact and outcomes into playback for their senior stakeholders 

Summary:

• It was noted that this quarter is about prepping for the next phase of funding.
• It was noted that activities for this quarter include things like finalising team structure, tooling, as well as the analytics work that has been carried over.
  • It was discussed that the analytics work last quarter focused on what we need and this quarter is making decisions around those needs.
• It was noted that a final version of the Phase 2 report will be submitted on 25th July after review by the Steering Group. 

End of Phase Report – Group 1 feedback:

• It was noted that approximately £1.2 million in duplicated project costs have been avoided through shared efforts under Stream.
• It was noted that several companies avoided consultancy costs of £140–150k by discontinuing plans for separate open data portals and opting to publish via Stream.
• It was noted that the NSOH data standard was agreed efficiently in just three sessions, attributed to Stream’s facilitation and process maturity.
• It was discussed that the second year of APR reporting was significantly easier than the first, reducing resource burden and improving staff well-being.
• It was noted that APIs have enabled real-time regulatory compliance tracking, helping companies replicate Ofwat’s processes and address site-level issues.
• It was noted that Stream’s joint and individual risk assessments provide layered protection against data breaches, with learnings taken from the energy sector.

End of Phase Report – Group 2:

• It was noted that Stream provides governance benefits, particularly in making participation straightforward and cost-efficient.
• It was discussed that the programme has strengthened internal governance and encouraged better data-sharing practices across organisations.
• It was noted that the platform and support team enable water companies to engage with open data in a way that may not have been possible without Stream.
• It was suggested that stronger evidence of external impact, such as testimonials from third-party data users, would further demonstrate value.
• It was noted that Stream fosters a culture of trust and collaboration, supporting wider industry engagement and innovation.

Sharing the report within organisations:

• It was noted that Stream outcomes and benefits should be shared internally to raise awareness and reinforce the programme’s value.
• It was discussed that tailored materials are needed:
  • A concise one-slide summary of key benefits for executive engagement.
  • A fuller slide deck to support team discussions and address concerns around data sharing and risk.
• It was noted that modular, reusable content would help water companies present Stream’s work effectively at forums such as board or risk committees.
• It was noted that content should highlight Stream’s achievements, sector benefits, and risk management, e.g., the rivers/aquifers example resonated well.
• It was noted that having a clear route to access presentation materials would support internal communication efforts.