Data Science: From Academia to Industry

Making Impact in the Energy Sector

Data and digitalisation have the opportunity to transform the energy sector and facilitate and accelerate the move to Net Zero. Better visibility and control of demand and generation will enable energy companies and innovators to better understand, anticipate and manage the changes on the electricity network.  

To enable this will require the utilisation of the advanced knowledge, tools and skills being developed within research institutions and universities. Unfortunately, inaccessibility to valuable data, domain expertise, and the major problems facing the industry can hinder the relevance and impact that research can make. Further to this, any insights and knowledge generated by academic institutions may be siloed in inaccessible and nonreproducible research papers, meaning the industrial companies will struggle to implement the impacts into business-as-usual and optimise the learnings produced. Further, even if the knowledge is accessible there may not be the data science and coding skills to fully implement them.  

Despite these challenges academia is valuable resource for providing the skills and innovation that is sorely needed within the energy sectors. Motivated by some of the struggles to produced academic data science impacts in industry, Energy Systems Catapult and Arenko have conducted research and interviews with experts to better understand the challenges and opportunities available through better knowledge transfer, collaboration and training between industry and academia. 

Based on these interviews we have identified key areas of impact, supporting mechanisms and recommendations which must be solved to facilitate better collaborations.  


Figure 1: Key areas of impact and supporting mechanisms to facilitate better data science collaboration between academia and industry

Major impact themes and support mechanisms

There were two major and persistent types of impact which consistently emerged in our interviews: 

  • Technical knowledge: Universities are the source of some of the most cutting-edge techniques and models. Advanced methods can help industry better optimise the applications needed to decarbonise the energy sector and help companies become leading innovators and market leaders. 
  • Technical Skills: The data science skill gap crosses all sectors but will be considerably concerning as the energy sector continues to digitalise. Universities are a valuable source of  intelligent, highly skilled and motivated individuals who can help build capacity and maximise integration of advanced algorithms and tools.  

 These two impacts are supported by four main mechanisms: 

  • Accessible and Reproducible research: If research outputs (papers, code, presentations) are not available then the advanced tools they support are unable to progress.  
  • Collaboration: Although making academic publications more accessible can help facilitate knowledge transfer some of the best ways to do this is through good quality collaborations. These can facilitate not only new tools and research relevant to the company but also provide another source of high quality graduates for recruitment. 
  • Coding Development for Academics: Although academics are highly skilled at developing sophisticated models the much needed skills within industry are proper coding skills to help develop operational models. Unfortunately there is still insufficient training within universities for this skill.  
  • Industrial Support: Academics should not be alone in their development of the latest technologies and tools. Industry can provide the strongest foundation for these advanced algorithms since they are often keepers of the data, and understand the biggest challenges and roadblocks. Innovation in the energy sector requires mutual support.  

We have developed a series of reports based on our interviews and research to investigate these impacts and support mechanisms in more detail and provide recommendations and suggestions. The main impacts and overview of the research is provided in the main report and then we include four supplementary reports for each of the mechanisms which dive deeper into each topic looking at the current state, the main challenges and what things would help facilitate better collaborations and knowledge sharing. These are by no means an exhaustive investigation but hopefully provide a useful starting point for further exploration, starting guidelines and  facilitate new solutions.  


The reports are split into one main report investigating the main impacts that academia can make in industry plus recommendations, and four supplementary reports focusing on individual supporting mechanisms.  


Figure 2: Data Science: From Academia to Industry is split into a main report and four supplementary report.

Read the Main Report

Making Impact in the Energy Sector

Supplementary Report 1

Academic and Industrial Collaborations

Supplementary Report 2

Accessible and Reproducible Research

Supplementary Report 3

Code Development for Academics entering Industry

Supplementary Report 4

Industrial Support for Academics

Energy Systems Catapult and Arenko held an online seminar to share the learnings from these reports and explore other ways to support better collaborations between Academia and industry. The following panel of experts shared their thoughts and learnings:

  1. Dr. Stephen Haben (ESC ): Intro.
  2. Dr. Sam Hinton (Arenko): Code: The missing link connecting academic publications to industry value.
  3. Dr Annette Bramley (N8 Research Partnerships): More than works: why and how what we say helps or hinders collaboration and what we can do about it.
  4. Dr Alejandro Coca-Castro (The Alan Turing Institute): The Turing Way – A collaborative guide to data science and research.
  5. Prof. Peter Grindrod CBE (University of Oxford): Energy Research: A two-way misalignment.
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Video: Data Science: From Academia to Industry report launch webinar

Next Steps

These papers suggest there is still much work to do in optimising the collaboration and knowledge sharing between academia and industry. Energy Systems Catapult will be looking to support through many of the issues including:

  • Training: To support the widening skills gap in the energy sector we must ensure that the next generation of data scientists and practitioners are equipped with the skills needed in the sector.  
  • Funding mechanisms: Not all funding options are currently aligned with the needs of developing enduring innovation within industry. Further investigation is required to understand what funding models can achieve greater impact and optimise the utilisation of academic knowledge and skills within the energy sector.  
  • Accessible and Reproducible research: Innovation is dependent on the latest state of the art learnings being openly available. Open science is essential to enable us to utilise all the tools available for us to meet Net Zero.  
  • Better Collaboration: Impact is not a one-way street. Academics and industry both have their parts to play to ensure the most is achieved through their collaborations, but they can both help each other through sharing data, knowledge, training and lessons learned. It is important to identify how real and permanent changes can be made within these organisations to ensure mutually beneficial and sustainable relationships are forged.  

If you are interesting to developing any of these areas with us, we’d be happy to help so please get in touch.   

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