The Innovation Growth Lab (IGL) has partnered with the European Innovation Council (EIC) on a one-year project to provide research and evidence-based advice on data-driven, experimental, and collaborative public sector innovation processes to support the development of the EIC’s strategic intelligence. Through this project, which harnesses the wealth of operational data generated across the EIC’s programmes and enriches it with novel data sources and methods, we are bringing together policy and academic stakeholders to share, learn, and act on how data is used to improve innovation funding across Europe.
What has happened so far
Any project aiming to make better use of data ought to start by accessing and auditing the existing data. These often non-trivial steps in organisations were also the start of our collaboration with the EIC. We have spent the first months of the project mapping the different data sources and structures of the EIC’s programmes and following all legal requirements to secure streamlined access to them. We have also met with the EIC to improve our understanding of their programmes and how the data is obtained and structured, as this often affects how it can then be pooled and exploited beyond individual programme calls. We have further explored the strategic problem spaces that the EIC is interested in gaining insights into.
In parallel, we are running a benchmarking exercise on data science and the use of data for strategic intelligence at the EIC and a growing number of other innovation agencies across Europe. In it, we are analysing their data skills and capabilities, their processes for data collection and integration, their use of analytical methods, the data use cases, and their data science pipeline. This exercise has so far led to several learnings: each agency has been individually scored and benchmarked against the others, which has been captured in individual reports to help them understand their position and potential; equally, these insights have informed the conversations with the EIC around commonalities in data problem spaces, which has influenced what is to come to help tackle these issues within the EIC and the innovation policy community.
Building on the learnings from these conversations and exercises, we have specified three experimental case studies that we will be working on over the next few months. Leveraging data from the EIC, and in collaboration with other European innovation funding agencies, we will analyse the outreach efforts to widening EU countries, examine the role of multidisciplinarity in EIC applications, and work on integrating the learnings from the benchmarking exercise into the EIC processes.
What is to come in 2024
In the new year, we will be building on the work so far to support the EIC internally and build a community of strategic data use in innovation funding.
Starting in January, we will be working on the experimental case studies with the EIC and innovation agencies to help make better use of their data in strategically relevant areas of work.
In parallel, and as a space for sharing, learning and working together to improve the use of data in innovation funding, we will be launching a series of Innovation Data Dialogues during the first half of the year, combining keynotes and structured peer-to-peer learning events addressing key issues identified in our benchmarking and problem space exploration.
We will also continue applying our benchmarking methodology to more innovation agencies, helping them better understand their strengths and their areas for improvement. These insights will equally help them obtain the most benefit from the joint activities planned.
The new year will also bring the inclusion of another group of relevant stakeholders in the exploitation of innovation funding data: the academic community. This spring, we are initiating an asynchronous datathon event, where researchers will collaborate closely with our team to conceptualise analysis ideas. They will have the opportunity to use EIC data through a secure access service, ensuring data security and compliance with privacy standards. The collaboration aims to foster a deeper understanding of available data and explore questions relevant to policy, with the potential for co-authorship opportunities with EIC researchers beyond this project.
IGL will be acting as the intermediary of the research process and framing the interactions between the policy and research communities through roundtables and individual check-ins until we all gather at the final event in September of 2024 to share insights and sketch the future of improved data use in innovation funding.
Why we are excited
This project checks all the boxes of the impact that we at IGL seek in our work. Through our mapping and exploration of the EIC’s data, we leverage data science and innovation mapping to identify meaningful problem spaces to pursue. We are then turning these problems into case studies which help the EIC become more experimental in its approach and research. Once completed, these experimental case studies will help answer operational and strategic questions which will ultimately inform EIC policy decisions by turning data into actionable evidence. Finally, the project will also lean on our strength as bridgebuilders between research and policy to help convene learning communities; this will happen by gathering innovation agencies to learn, share and work together on making better use of their data on the one hand and attracting researchers to work with EIC data to answer policy questions on the other.
With this project we are thus meaningfully contributing to the improvement of science and innovation policy, and shaping institutions, work programmes, and people to future-proof innovation funding.
Want to know more or get involved? Reach out to [email protected]!
Sara Garcia Arteagoitia
Sara García Arteagoitia joined IGL as a Senior Researcher in 2022. In her role, she helps identify experimental research opportunities with our global government partners and bring them to fruition.
Before joining IGL, Sara worked as a consultant and instructor in behavioural design with private companies and government agencies in Spain and Latin America, helping them improve their structures and programmes to achieve higher impact. Prior to that, she was the Senior Assistant Director of the Center for Decision Research at the University of Chicago, where she worked on developing partnerships and research structures to propel and promulgate experimental behavioural research.
She started her career in experimental research as a research assistant for different projects at the University of Chicago and the Max-Planck Institute for Collective Goods. Sara holds a BA in Political Science and a MA in Political Psychology from the University of Heidelberg, Germany.
David Ampudia
David is a Data Scientist at the Innovation Growth Lab (IGL).
His role at the Lab focuses on helping grow the team’s capability for using data analysis and statistics to uncover and pursue opportunities to improve the effectiveness and equity of innovation and business policy.
Prior to joining the IGL in 2022, David worked as a Research Fellow at the Data Center of the Barcelona School of Economics (BSE). His work involved the development of state-of-the-art sequential decision-making algorithms, with a particular focus on Bayesian Optimization and multi-armed bandits. He also contributed to multiple political economy projects, helping develop and implement improved methodologies using novel data sources and techniques. As a member of the Center, David has taught text-based deep learning courses at the Summer School of the BSE for several years now. Before this, David worked as an economic consultant for FocusEconomics, a macroeconomic research and forecasting institute.
David holds a one-year MSc in Data Science Methodology from the Barcelona School of Economics, and a two-year MRes in Analysis and Policy in Economics at the Paris School of Economics. He also has a BA in International Economics from the Universitat Pompeu Fabra.