Improving academic–industry collaboration: A case study of UK distribution system operators

Most countries have net zero carbon emission targets and associated strategies to meet them.¹ Central to these strategies are the decarbonization of electricity and the electrification of transport and heat, each of which have dramatic impact on electricity networks. This is causing the grid to undergo the most rapid transformation in its entire history at the distribution level with the movement of generation to the grid edge and rapid increase in demand at the household level. An autonomous intergovernmental organization—the International Energy Agency—estimated that reaching national net zero goals would mean adding or refurbishing over 80 × 10⁶ km of grid infrastructure and cabling by 2040, which is roughly equivalent to the entire existing global grid.² 

This transformation brings a multitude of challenges and opportunities for distribution network operators (DNOs), requiring collaboration between energy sector stakeholders including developers, operators, councils, consultants, academics, government, suppliers, and the networks themselves. Additionally, such transformation to net zero brings an increased need for new professional and technical skills alongside workforce development.² This Perspective article reveals how the drive toward net zero has fostered renewed need for effective academic–industry collaboration and ultimately exposes the challenges, recommendations, and progress made so far. We hope that sharing these recommendations with the scientific community will assist academics to achieve more from their research and encourage industrial partners to better foster and benefit from collaboration.

We explore this topic through the lens of two newly formed UK Distribution System Operators (DSOs). The DSO is distinct from the long established Distribution Network Operator (DNO) model. The DNO continues to own, maintain, build, and operate power grid infrastructure to keep the lights on, and its role has traditionally been more passive—focused on maintaining sufficient capacity and safety to deliver electricity to end-users. However, with the integration of distributed energy resources and the evolving role of end-users as active participants in energy generation and management, a more dynamic approach to managing the distribution network is required. The DSO takes on this active role with a strategic objective to make better use of the existing infrastructure to enable the net zero transition for all. Statements akin to that of the IEA suggesting the need for refurbishing of the entire network sparks the need for innovation in how the existing infrastructure is used, such that no-one need wait to participate in net zero activities, e.g., electric vehicle and heat pump ownership. DSOs leverage data and insights to better forecast the needs of customers and stakeholders to ensure that network reinforcement is carried out at the right place, at the right time, ahead of need, and at the lowest cost. The standout innovation introduced by DSOs in the UK is that of local flexibility markets, and how active participation can mitigate network constraints. This approach, although established in other countries, is relatively new in the UK and potentially defers the need for reinforcement, which is a far cheaper and faster approach than reinforcement, potentially deferred in perpetuity, or until there is more certain requirement for reinforcement.

At the time of writing, the DSOs of UK Power Networks (UKPN) and Scottish and Southern Energy Networks (SSEN) have been operating for over 1 year in the UK. In the opening month of UK Power Network's DSO operations in April 2023, they received their first data and information request from an academic stakeholder.

This article uses the journey of the authors' desire for improved collaboration between distribution networks to understand how the industry–academia collaboration can be improved with recommendations for both academics and for distribution networks that represent industry. While not a brand new activity for DNOs and the newly formed DSO, the dawn of the DSO allows a fresh perspective (discussed in Sec. II). The objective is to critically analyze how these collaborations manifested, how they could be improved, and what needs to happen more broadly to succeed and be scalable in the UK. The authors are from academia and from two UK DSOs and are analyzing the barriers and solutions to their own attempts at collaboration. While this paper centers on the DSO perspective as a practical use case, the recommendations to overcome collaboration barriers are broadly applicable to the wider energy sector and even to other industries, showcasing general principles of academic–industry collaboration.

This paper begins with a brief background and context for collaboration in the UK in Sec. II. Next, we discuss the advantages arising from collaboration between industry and academia, bringing together perspectives from both sectors in Sec. III. Section IV discusses the barriers to successful collaboration between academia and industry, proposing recommendations for each stakeholder. Section V outlines current strategies to establish an effective collaborative framework, drawing insights from the perspectives of actually collaborating with a DSO.

While a significant amount of time and energy has been invested into pipelines for collaboration between academia and industry,^3,4 this article focuses on a new area of collaboration in the energy sector, that of academia and DSOs. The British governmental Office of Gas and Electricity Markets (Ofgem)⁵ oversees and regulates energy industry groups (including DNOs and DSOs) to ensure fair treatment of consumers across Great Britain. At the time of writing, the 2024 General Election had just occurred, which resulted in a change of government. How this will impact the UK energy sector, especially in an innovation and research realm, is still to be seen and is considered outside of scope.

After various open consultations with key energy sector stakeholders (including the academics⁶), Ofgem made the determination for the establishment of DSOs in Great Britain (GB). Although the mission statement varies between the six GB distribution networks, each DSO is fundamentally setup to address the challenge of enabling the net zero transition and was launched on 1 April 2023.

Responding to the net zero transformation and how the network will be used, Ofgem expanded the representation and service of significant key stakeholders that are not necessarily represented by traditional broad measures of customer satisfaction; stakeholders that are small in number but large in impact to the net zero transformation. These stakeholders include renewable generation operators (e.g., wind farms, solar farms, and battery energy storage sites), local authorities (e.g., the local council energy planner tasked with planning the future electric vehicle strategy for a community), flexibility service providers (e.g., utility scale battery operators that respond to requests to charge during periods of generation constraint), energy startups (e.g., the software companies leveraging open data to identify the best possible network connection applications), the power system consultant (e.g., the connection specialists advising businesses on their curtailable-connection network connection offer), among many more. The stakeholder of interest for this paper is the academic.

The academic is a stakeholder of the energy system for many reasons. Principally, power systems and cross-disciplinary research often highlight the needs of the network, evaluate and recommend potential strategies, and develop solutions to the benefit of society. The academic aims to produce relevant and novel research that may 1 day be adopted by the industrial players in the energy sector to have large impact upon the world. A notable example of academia's influence can be found in the area of demand response within electricity networks. This field has been subject of extensive academic scrutiny spanning several decades, with practical applications gaining significant prominence over the past 10 years. Considering an energy sector theme such as demand side response, research can come in the form of policy based research,^7,8 experience and case study investigation,^9,10 technical and power systems based research,¹¹ which ultimately results in innovation at industry, such as Octopus Energy's “Power-ups” project,¹² launched with UK Power Networks, or the Demand Flexibility Service by National Grid Electricity System Operator.¹³ Academia also shares the responsibility of training the next generation workforce, with graduates from degree, apprenticeship, and continuing education programs.

Ofgem has found a creative and effective solution that better represents the views of the academic (and other aforementioned stakeholders) within the framework of incentives to the industry. This solution is an annual stakeholder survey that Ofgem uses to judge the success of the newly formed DSOs, whereby the stakeholders submit their scores against various metrics, e.g., data and information provision and flexibility market performance. Academics are included in the list of DSO stakeholder groups eligible to receive the survey.¹⁴ One of the primary objectives of this survey is to evaluate how responsive DSOs are to stakeholders. This has led to positive behavioral change in how networks are operated to keep the customer at the focal point of activities.

The review of the projects in the Energy Networks Association database,¹⁵ led by UKPN and SSEN since 2020, provides an overview of the current state of academic–industry collaboration. These projects were categorized based on their level of academic involvement. Among 37 innovation projects, 3 included direct university collaboration, representing approximately 8%, while 12 involved university-based research institutes, accounting for nearly 33%. Notably, collaboration has increased significantly in recent years, with 10 out of the 15 collaborative projects initiated since 2023. This trend reflects the positive impact of recent initiatives aimed at strengthening academic–industry partnerships.

Collaboration between academia and the DSO stands to yield significant benefits. The DSOs in the UK are working on difficult new innovation projects and plans to support the net zero transition. They currently face some of the more prominent challenges that research has discussed for many decades, e.g., renewable energy grid integration challenges. However, industry also has a responsibility to clearly communicate those challenges and collaborate with academia on solutions. For the DSO, academia contributes cutting-edge research, fosters innovation in power system technologies, thought leadership, and enhances the industry's knowledge base. This empowers the DSO to stay abreast of the latest advancements in fields such as data science, power system modeling, policy implementation, and more. This essential and reciprocal relationship ensures that academia continues to be informed about the latest industry situations and technologies and is able to guide the methodology for real-time problem-solving, which, in turn, could help achieve governments' net zero targets.

Applied research, fueled by this collaboration, allows essential know-how specific to the industry to be transferred to the academic, enriching research ideas and fostering innovation. Moreover, this collaboration brings more than intellectual benefits. It serves as an additional financial resource, facilitating the development of laboratories and offering opportunities for industry organizations and their staff to secure qualified researchers. The engagement with the industry also extends beyond the academic landscape, providing researchers with invaluable industry experience—bolstering job prospects for students and researchers. This hands-on involvement not only enhances understanding but also enables possibilities for the mentoring of students, tailoring their skills to meet industry's ever evolving needs.

While the industry holds real-time information and technological insights, it often seeks effective solutions for current and potential future problems without taking undue risks and considering the time investment required for solution discovery. Collaborating with academia becomes crucial in this context, allowing the industry to share the risk and streamline the solution-finding process, ultimately enhancing efficiency. Academia, with its focus on cutting-edge solutions and the flexibility to dedicate the necessary time to research, significantly contributes to increasing the energy industry's effectiveness. This depth of study is often a difficult learning point as industry does not often allow such deep-dives into novel—and possibly fruitless—ventures without an immediate cost benefit analysis, which is a common adjustment for many academics. Therefore, the ability to truly explore ideas, in rich and unparalleled detail, is a key opportunity afforded to academic researchers. This can manifest in outcomes such as data releases,^16,17 novel research discoveries,¹⁸ or immediate industry applicable findings.^19,20

Academia brings a wealth of knowledge from the latest developments in the literature, customizing solutions to meet the industry's evolving needs and technological advancements. This dynamic collaboration not only facilitates the industry's access to state-of-the-art solutions but also ensures a mutually beneficial relationship between academic expertise and industry requirements. Another notable advantage lies in the industry's ability to recruit new employees with practical experience, a benefit derived from the collaboration with academia. This partnership not only equips students with the necessary skills but also allows them to tailor their expertise according to industry expectations and needs, fostering a cooperative relationship between academia and the workforce. This synergy facilitates the development of robust solutions to complex problems, accelerates technology transfer, and cultivates a skilled workforce with expertise aligned to industry needs. Ultimately, the partnership promotes a more sustainable, efficient, and resilient power system, aligning academic research with the practical demands of the energy sector.

A commonality in all examples of collaboration is the exchange of data and information; whether it accesses to network models to enable independent study, visibility of relevant and pressing challenges actively facing the energy sector, or active collaboration of the various forms it may take. We look at the barriers to collaboration and present recommendations for each party alongside current DSO examples showing progress toward the common goal. We illustrate some of the recognized barriers to collaboration in Fig. 1.

Collaborating with new partners can introduce fresh perspectives and foster innovation through diverse expertise, as discussed in Sec. III. The first step in initiating a partnership among different stakeholders, especially those seeking mutual benefit rather than a mandatory relationship, is a willingness to collaborate. For our perspective, willingness refers to a genuine corporate strategy to collaborate with academia. From the outset, collaboration can be labor-intensive, as understanding each other's perspectives requires time and effort, which may be viewed as an additional workload for each partner. Over time, the success of previous collaborations builds trust and reduces perceived risk for future partnership. For example, the DSOs embed academics in positions of authority in their business model, such as Professor Goran Strbac (Professor of Electrical Energy Systems at Imperial College, London) serving on UK Power Network's DSO Supervisory Board,²¹ and Dr. Charlotte Johnson (Head of Research Programs at the Center for Sustainable Energy) and Professor Jan Webb (Professor in Social and Political Science at the University of Edinburgh, and co-director of the UK Energy Research Center) sitting on the SSEN DSO supervisory board.²² This embedding of the academic representative at the highest levels of the UK energy sector demonstrates a real willingness to bring industry and academia much closer.

New collaborations require an adaptation period for partners to familiarize themselves with each other's systems and to establish a functional interface between the partners. As a result, stakeholders can become more inclined to continue working with the same partners, potentially precluding new ones. This challenge can be a significant barrier to starting new collaborations and engaging with new partners. One other barrier to a willingness to collaborate is a perceived lack of clear link to performance requirements. Without a clear measurable benefit, such collaboration runs the risk of being crowded out by the numerous other day-to-day job priorities.

Recommendation for academia:

• Encourage early-career researchers to actively build connections with industry to strengthen collaborative links between academia and industry. While we anticipate a willingness from academics to work with industry, there is often an issue with incentivizing the fostering of links with industry. This is perhaps most important to the early-career researcher, who might not feel empowered or have the resources to network and create important links with industrial partners. Therefore leaders in academia should explicitly value industry collaboration as part of academic career frameworks,²³ fund membership of professional societies, and resource early-career researchers to attend conferences and networking activities.

• Establish interdisciplinary collaborations to blend diverse skills and mindsets, leading to high-impact, relevant research, and long-term partnerships. We believe the higher-impact, relevant research is born of interdisciplinary teams, as highlighted by team science,²⁴ which can realize long-term benefits with respect to partnerships. Interdisciplinary activities typically add greater context to challenges and problems through broader perspectives, helping industry see the bigger picture of potentially niche research. Therefore not operating in silos within academia, and blending skill sets and focus with industry, is the healthiest and most productive method to creating effective collaboration.²⁵ 

Recommendation for industry:

• Recognize the value of all forms of collaboration, from simple knowledge sharing to formal partnerships. There is a lot of opportunity for very formal collaboration already, but perhaps not enough willingness for the informal open ended collaboration. Our recommendation to industry is to embrace all kinds of collaboration, from activities as simple as knowledge sharing, thereby widening access and participation.

• Empower industry staff with academic backgrounds to engage with academia by providing the necessary time and resources for participation. Setting the expectations on staff and providing them time and funding to engage with academia is paramount to unlocking willingness, increasing awareness, and promoting mechanisms of collaboration. Through this case study, in 2023/24, DSO engagement across two afternoons directly informed 8 MSc student projects (a single MSc student project translates to an anticipated 600 h of student effort). A rigorous open data sharing strategy also lowers the time burden of informal collaborations through pre-processing of data.

The absence of clear communication channels presents a major barrier to collaboration. Within industry, there are often numerous organizations, and it can take academics months to work through generic staff and team email inboxes to find the right point of contact for further communication. The same challenge exists for industry seeking to work with academics as a single topic area is often covered across multiple disciplines, departments, research groups, and programs of study. As such, there is a not a single platform or access point to initiate academic/industry communication. This is further evidenced by the different ways in which the academic authors of this perspective each approached the DSO: an internal referral from the STEM²⁶ ambassador and networking at an academia focused energy conference.

The UK DSOs offer a valuable opportunity for engaging with academic stakeholders through their accessible Open Data Portal. The Open Data Portals^27,28 provide insight for academia and allow researchers proactive access to key datasets, creating a more self-serve environment that also benefits students seeking real-world data for their projects. It provides a great mechanism to showcase and facilitate collaboration as they are standardized across UK DSOs. They contain links to relevant data, and DSOs like UK Power Networks have already linked methods and use cases to specific data. The DSO at UK Power Networks has created a data science team responsible for the data roadmap, and there is also a well-advertised contact to feedback and request to add items onto the roadmap. This helps academia see what is on the agenda as well as speak directly to those responsible for data and information provision. As a result of this channel, academia has already invited the DSO to speak directly to the undergraduates and postgraduates, enhancing awareness of ongoing research, challenges, and data availability.

Perhaps the most poignant example of progress in this space is this perspective article itself, which represented a reflective analysis of ways to overcome these barriers effectively. The intention of this article was to begin this new journey of collaboration by offering a perspective of how it is going, and perhaps where it should go.

Recommendation for academia:

• Network at and participate in industry-focused events to establish communication with industry stakeholders. Academics are recommended to actively engage with industry events that bring together gas and electricity networks to exchange the latest developments, challenges, and future plans. Examples of this in the UK include Utility Week Live,²⁹ the All-Energy Exhibition and Conference,³⁰ and the ENA's Annual Innovation Conference.³¹ The ENA Energy Innovation Basecamp is a perfect example of an existing mechanism, where the industry presents the current challenges they are facing in an open and collaborative manner. Academics should attend this event and use the challenge statements to inform student research and teaching. All of these events are inherently free to attend and give exceptional access for any attendees to learn about the challenges facing the network.

• Value trade media to stay updated on industry developments and expert insights. Apart from actively participating in seminars and conferences, subscribing to trade media is another efficient way to stay informed about the latest industry developments and expert insights. For power systems, following technical societies such as IEEE,³² Institute of Engineering and Technology,³³ and CIGRE,³⁴ along with the Worshipful Company of Fuelers in London³⁵ as well as joining popular mailing lists like PowerSwarm³⁶ and PowerGlobe³⁷ is valuable resources.

Recommendation for industry:

• Create a dedicated section on the website for academic collaboration to improve stakeholder communication. Such a section could showcase past successful projects, inspiring new ideas and fostering further innovation. This could be coupled with existing pages that focus on past innovation projects and would also serve to reduce some of the redundancy in project requests to utilities as researchers could more clearly see the work that has already been completed on a given topic. Having this information also provides an empirical way to demonstrate value from data. Specifically, listing use cases of how datasets have been used might be the simplest method to prevent duplication of effort.

• Incorporate the academic component into existing industry innovation events to create a joint platform. While there are a number of existing industry innovation events, these events could also add an academic component, providing a joint platform for researchers to share solutions in aligned areas and help raise awareness of international best-practice. Co-location of such events can improve efficiency and minimize travel and time requirements for both audiences. A great example of such co-location can be seen in the IEEE Transmission and Distribution,³⁸ CIRED,³⁹ and IEEE Grid Edge⁴⁰ conferences that bring together thousands of industry and academic professionals each year.

Academic institutions and industry have different aims, objectives, and purpose.⁴¹ As such the motivating factors and objectives for collaboration can differ. For example, industry motivation can include improvements in network safety, operational reliability, customer service, requirements, corporate reputation, and profit, whereas academic motivation may come from contribution to knowledge, publication of findings, delivering impact, and institutional and individual reputation.

The time frames under which these partnerships develop can also present a challenge. In industry, there are often short-term objectives on the scale of 1 week to 1 year, which take priority when pursuing funding and delivery of projects (i.e., cost and budget reporting). This is often tied to annual budgets, planning cycles, or regulatory approvals. In the latter, when looking at regulatory time frames, companies are required to forecast and account for planned expenditure up to a decade in advance. As a result, with dwindling expenditure on long-term R&D, this can present a barrier to investment in academic research partnerships. On the academic side, research projects are often on the scale of months/years due to resource and funding mechanisms and the duration of postgraduate research studentships. Experience from the authors of this paper evidences of the value of collaboration across time scales through data sharing (immediate), university presentations (1 day), supporting MSc student projects (from weeks to months), internship (1 year), and alongside larger investment in research and innovation projects (from months to years). Figure 2 illustrates the relationship between the level of investment and the ease of accessibility across these collaboration scales.

Successful collaborations are those that have clear mutual objectives. New collaborations are only born should that mutuality be clear from the beginning.

Joint recommendations for academia and industry:

• Understand each other's perspectives within the context of their operating environments. To realize the benefits of collaboration, academia and industry must effectively understand and communicate the value proposition of their work within each other's operating environments. Leveraging their differences as strengths, these partnerships can address the challenge of differing time scales: enabling industry to consider on long-term objectives and academia to deliver near-term impact. The initial approach for collaboration should be accompanied by an attempt to explain the benefit of both sides.

• Embrace a range of collaboration opportunities and engage early to align objectives and co-create ideas effectively. By providing a variety of collaboration opportunities—ranging from undergraduate and postgraduate taught student projects and consultancy (weeks to months) to postgraduate research and funded research projects (months to years)—both sides can align their objectives more effectively. Moreover, early engagement is essential for co-creating ideas and meeting the multiple objectives of collaboration.

Even with a common understanding of the problems faced by industry, failure to understand differences in focus across technology readiness can inhibit collaboration. This effect is so pronounced that the transition from research to impact is often referred to as the “valley of death”.⁴² The DSO faces the responsibility of ensuring the reliability, security, and efficiency of the network, and embracing innovative solutions involves risks when compared to existing, verified solutions with a proven track record. When the DSO evaluates its responsibilities and assesses the risks associated with new solutions or approaches, a more cautious or conservative approach is often adopted. This can be at odds with academic research, which seeks to push the boundaries of efficiency, optimization, and of knowledge rather than implement existing solutions. While aiming to secure their safety and reliability of their networks and their trust and customer service to their customers, UK DSOs release a set of annual reports. These reports enable academics to learn about current technological readiness and potential future problems that DSOs face. One such example where UK Power Network's DSO has highlighted this is their Forward Plan⁴³ that encourages active participation from external stakeholders (inclusive of academics) to provide their input to shape the active plans. SSEN has shared their Action Plan⁴⁴ to inform stakeholders about their long term and short-term plans for ensuring a reliable network and improving operational efficiency.

Recommendation for academia:

• Identify the technology readiness level of research, considering its applicability within the industry. Technology Readiness Levels (TRLs)⁴⁵ are used to evaluate the maturity of technologies, with each level and its explanation shown in Fig. 3. Academics should be able to articulate the stage of technology readiness of their research and the intended audience. While clear in industry and commercially minded academics, better exposure to TRL should be provided to early-career researchers and students to build an understanding of the end-to-end process of research. In this manner, academics should be able to not only identify the aimed advancements in knowledge but also work with industry to understand the pathway to application of their work at the outset. It is worth noting that novel research need not have high TRL, but having a grasp on this commercially minded terminology is beneficial.

• Conduct realistic testing to build confidence in transitioning research to practical applications. If applicable to the collaboration, building confidence in the ability to transition from research to application requires realistic testing of the research. Examples of this can be seen internationally with Pacific Northwest National Laboratories (PNNLs), which have developed an open source platform for researchers to develop and deploy Advanced Distribution Management System (ADMS) applications (GridAPPS-D).⁴⁶ This provides a means to evaluate new algorithms and control strategies in a safe but realistic environment. With the growing amount of real power system data available, researchers should also test their approaches on real historical data where possible, further validating the approach and providing confidence to industry of its applicability.

Recommendation for industry:

• Take strategic steps ahead of need by recognizing the importance of innovation at lower TRLs. Industry is encouraged to engage with academics to foster forward thinking by recognizing the need and risks associated with innovation at lower TRL. This proactive approach should lead to strategic investments ahead of need, addressing emerging issues and integrating innovation into strategic road-maps.

Insufficient commitment of time, money, and availability of data presents a barrier to effective collaboration. From a time perspective, collaboration can be placed at a lower priority than core business objectives and is often done in addition to other job responsibilities. This barrier is further compounded by a common discrepancy between the amount companies would spend on external consultancy and their willingness to commit similar resources to research; though countered by the fact that a consultancy purely serves a business function, it need not prevent more open ended projects that befit a research perspective.

Beyond finance, academic studies demand data to model power system behaviors and test proposed solutions. Concurrently, the ascent of artificial intelligence algorithms has led academia to increasingly adopt data-hungry approaches. However, the data regularly face potential challenges of not being stored for an extended period, lacking high resolution, and encountering issues such as missing measurements, questionable quality, which is a common challenge faced by the industry. The required data may not be measured in real-time due to concerns about cost, and the networks are always audit ready by regulators against any inefficiencies. Additionally, industry may encounter restrictions in sharing specific data due to privacy concerns and is obligated to adhere to regulations, such as General Data Protection Regulations, anti-competitiveness behavior law, license conditions, or the Utilities Act 2000 section 105.1b.⁴⁷ 

To comply with these regulations, sensitive data are often aggregated to broader time intervals or averaged across customer categories to protect privacy, with direct identifiers removed to prevent re-identification. While these techniques can limit accessibility and may require researchers to make assumptions based on aggregated data, they maintain a careful balance between data accessibility and privacy.

To improve data accessibility and address stakeholder needs, UK DSOs regularly publish their digitalization strategies and action plans, outlining current and planned data services.⁴⁸ UK Power Networks has implemented data governance processes for curating, triaging, and classifying data to comply with regulatory requirements. Data are categorized and tagged based on access levels—such as public, private, or self-registration—to facilitate sharing within appropriate privacy and security boundaries.⁴⁹ Additionally, UK DSOs have created Open Data portals that contain triage of past data requests. This helps to raise awareness and avoid duplicate effort by either party where a particular request has already been considered or is under consideration. GB Networks have invested heavily in data and digitalization strategies to bring networks into the modern age. These strategies have a focus on data provenance from source to destination, preserving data quality and completeness.

UK Power Networks has additionally created a dedicated Data Science and Software Development team to capitalize on the potential afforded by these high-skilled resources; many of which come from academic backgrounds. This new hyper-focus on data competencies and capabilities within distribution networks poses ripe opportunity for academics today.

Recommendation for academia:

• Highlight the value of data in requests to assist industry in justifying its provision. Academics are well positioned to understand the landscape of where industry data could enable research from a different part of the world to be applied within a specific context. As such, academics should accompany data requests with a statement of the value of data to support industry in making the business justification for its provision.

• Make informed, unique data requests. It is important for academics to review triage processes and company documentation to avoid redundant data requests, enabling industry to focus on supplying high-quality data. When requesting data, academics can cite examples where similar data sharing practices have benefited industry stakeholders in other countries or regions. This approach facilitates engagement with the business development team for effective collaboration.

Recommendation for industry:

• Allocate the necessary resources to foster internal innovation and effective collaboration. Time and budget are the two main concerns with resource availability. Both can always be allocated against direct outcome expectation, so it is well recommended to have a clear understanding of the benefits of collaboration so that appropriate resource can be allocated. Allowing resource for innovation amongst staff and encourage collaboration with academia in this process will strive toward the benefits, but it should be systematic. Examples of “individual learning/professional development” time has proven to improve staff satisfaction and enhance innovation in the tech sector.⁵⁰ 

Each ongoing relationship requires time investment for it to yield fruitful outcomes. As the number of potential collaborative partners increases, the time available to invest with each partner decreases. At some point, the teams that manage collaborations will become saturated, and further collaboration would adversely impact existing work. As a result, this can result in “preferred” partnerships based on longevity of the organizational collaborations, reputation, and precedent.

This is for good reason as it takes time to demonstrate competence, trust, and exchange knowledge. However, over time, as entities evolve, the original benefits of the partnership may no longer be present, while being a blocker to new partnerships forming. If formed on the basis of a relationship between individuals, partnerships can dissolve as quickly as they were formed if either party leaves an institution or even changes role within the same organization. There needs to be continuous and cyclical outputs to justify the investment from a long-term perspective. Through the aspect of short-term collaborative horizons, however, the net should be cast far and wide to facilitate broad audience of academic collaborators with industry.

Recommendation for academia:

• Value aligning research objectives with industrial perspectives and needs. Work to align research with business objectives rather than the needs of an individual by seeking greater understanding of the motivation of the industrial partner. By considering broader industrial challenges, constraints, and needs, research gains an industry perspective and becomes more grounded in real-world conditions, helping to create a foundation for sustainable collaboration. In this way, even if organizations and individuals are shuffled, the value proposition of the work remains clear and strategic. An example would be gleaning perspectives beyond a single individual through participation in wider academic-industry activities such as the Supergen energy networks community.⁵¹ 

• Leverage available resources to improve the efficiency of collaboration efforts. For shorter term collaborations, follow the aforementioned guidance to explore what is already available from industry, such as data on open data portals; these products are ready made and can be used “off-the-shelf,” in that the burden and resource requirement on industry is substantially less should existing products be leveraged. Also, student research projects can provide natural ways for more informal partnership and deliver effective value to all involved.

Recommendation for industry:

• Integrate research into the organization to strengthen the long-term sustainability of the collaboration. Embed the research within the target organization from the start so that the contribution to strategic objectives of the organization is evident.⁵² This way, even if individuals change positions, the relationship can continue. However, for this approach to be successful, each party must invest from an organizational perspective rather than individual perspectives, and the true test of longevity comes following departure of former lead contacts. Use of customer relationship management (CRM) systems to track these relationships can also increase the resilience of these relationships over time to the departure of any single employee.

• Invest in a long-term pipeline of collaboration. Often “extra” activities like conference attendance, travel budgets and other related expenses are seen as lower priority during times of fiscal conservatism. However, it is important to view these activities within the lens of a longer-term investment into sustainable talent, knowledge, and innovation pipelines. It is essential that industry continues to invest in these areas so that the sector is resourced to tackle the wider societal challenges.

Noteworthy studies have analyzed the dynamics of collaboration in terms of their mutual benefits,^53,54 success factors for evaluation,⁵⁵ and barriers to collaboration.⁵⁶ They highlighted the need for a more intentional approach. It is underscored that, when industry and academia engage in collaborative efforts, a harmonious relationship unfolds, contributing significantly to the development of both industrial and academic benefits.⁵⁷ 

There is a gap for the more informal collaboration to quickly get a steer on a project, get a new dataset released, or get access to expertise on a topic, with no cost overhead or expectation of outcome. The establishment of DSOs has sparked a fresh attempt to foster more academic collaboration as Ofgem has empowered the data enquirer formally as a stakeholder. The outlook is for DSOs to foster more intentional informal collaboration that is perhaps more befitting the label “data enquirer.” By contrast, the formal routes to long-term, competitive, and well funded collaboration continue to exist through governmental incentive, and their scope and data needs are well communicated at application, with little speculative data needs. Therefore, we anticipate a growth in greater engagement with academics and students in the early phase of their academic journey. In the 2023/24 reg year, UK Power Networks released 31 new datasets onto its Open Data Portal²⁷ in response to customer requests, six of which originated from academic data collaborations. That same year, UK Power Network's DSO had three enquiries for academic collaborations following the described informal collaboration (in that there was no grant or financial agreement associated with the interactions), for example, engaging with the cohort of Electrical Power Systems Master's students at the University of Birmingham. This provides examples of how intentionality from the DSOs can benefit student projects and shape the trajectory of wider academic research.

It is estimated that the green energy transition will create 500 000 jobs and require up- and re-skilling of four × 10⁶ workers in the UK alone by 2030.⁵⁸ It is perhaps befitting that the trajectory of DSOs in the UK appears to be that of engaging and arming the early career academic with the data, network, and skills needed to enter this fascinating new chapter in the energy industry. When considering existing mechanisms for early-career academic collaboration potential in the UK, there are great examples including Centers for Doctoral Training (CDT) and the Institute of Engineering and Technology (IET) Power Academy. These approaches fill a much needed space in the partnership, but a more extensive pipeline will be necessary to sustain the described workforce and innovation needed for the energy transition. Rather than placing the emphasis on larger R&D investment, there are clear opportunities to leverage the existing processes more effectively to facilitate collaboration at scale, widening participation and expanding the pool of talent engaged in tackling the challenges DSOs face.

This perspective article considered collaboration and applied it to the DSO landscape in the UK. The core theme is that real intention is required to succeed. We hope that the recommendations in willingness, communication, objectivity, understanding, resources, and outcomes will help improve the academia–industry collaborative future and hopefully benefit the energy sector and its transition to the low carbon future.

The work of Hilal Ozdemir was supported by the EPSRC (Grant Reference No. EP/W524542/1).

The authors have no conflicts to disclose.

Jamie M. Bright: Conceptualization (lead); Investigation (lead); Methodology (equal); Project administration (lead); Writing – original draft (lead); Writing – review & editing (equal). Hilal Ozdemir: Conceptualization (supporting); Investigation (equal); Methodology (equal); Visualization (lead); Writing – original draft (equal); Writing – review & editing (equal). Daniel L. Donaldson: Investigation (equal); Methodology (lead); Writing – original draft (equal); Writing – review & editing (equal). Rosabella F. Robertson: Investigation (supporting); Methodology (supporting); Writing – original draft (supporting); Writing – review & editing (supporting).

Data sharing is not applicable to this article as no new data were created or analyzed in this study.