Introducing IGL's Data and Technology Unit

Summary

IGL has launched a Data Science and Technology Unit. The Unit will develop data-driven tools for decision making, use those methods to create new policy insights and support the adoption of such methods across institutions. Our work will combine with IGL’s existing work on experimentation and developing experimental organisations to realise a vision of next-generation innovation and productivity policies augmented by data.

Data and technology powered policy

When it comes to designing policies about how to orient science, innovation, entrepreneurship and business activities that can orient our economy towards things that matter - productivity, inclusivity, sustainability - we are data rich and information poor.

Policymakers are often unable to fully benefit from the wealth of relevant data that exist due a range of issues, including fragmentation of data and knowledge, a lack of suitable tools, heterogenous skills and capabilities, and poor integration of data within institutional processes.

When used effectively, data science and data powered technologies can be used across a range of policy problems such as detecting emerging innovation trends, benchmarking new funding programmes, evaluating the impact of past policies and identifying areas of innovation to support. Data can be used in conjunction with experimental methods, for example to design hypotheses or track novel outcome measures, while new technologies can provide opportunities for testing experimental approaches to policy implementation. There is huge potential.

What will IGL's Data and Technology Unit do?

So, what do we think it is going to take for the innovation agencies and policymakers of the 21st century to use data-driven methods to drive strategic decision making, and shape science and innovation?

Our vision is for the Unit to act as a collaborator and partner with institutions across three streams of work designed to address major challenge areas.

Connect - Bridging the gaps between people, knowledge and organisations

Through supporting organisations to develop experimental approaches to policy making, IGL has learned that barriers often occur not because of a lack of technical capacity, but because of internal structural barriers.

The Unit will help organisations unlock the full value of the data and relevant skills with the right processes, examples and experience. We will support organisations to assess their data capabilities, develop programmes on data management and governance, design impactful data projects and offer guidance on the expansion and design of data science teams for strategic policy aims.

In addition, we will foster networks of researchers, analysts and decision makers to create dialogues and learning communities, and to join up potential collaborators.

Build - Developing tools, platforms and infrastructure needed by innovation agencies and policy makers

In many cases, organisations across research and innovation policy share common needs and problems when it comes to the use of data and technology. Instead of individual organisations developing unvalidated, idiosyncratic solutions we envision tools, processes and standards being developed that can be adopted across multiple institutions.

The Unit will translate useful analysis methods or datasets created within academic research groups into open source software packages which internal analysts can use more readily.

In other cases, we will prototype entirely new technology applications. We might create a tool to identify science and innovation trends, a system that allows funders to take a data-driven approach to portfolio management, or a platform that allows policy makers to synthesise evidence on productivity challenges.

Apply - Putting data and methods into action to create evidence and drive critical policy decisions

As well as creating tools and translating methods for the ecosystem, the Lab will have a team of data scientists, supported by designers and researchers, that will act as a delivery partner for organisations. This team will focus on producing actionable, data-driven insights and infrastructure for policy and do R&D for organisations.

From mission driven policy, to metascience, to disruptive innovations, our data science research team will produce findings that map ecosystem activities, investigate impacts of programmes and measure the effectiveness of policy levers. We will do this by leveraging big data, machine learning, AI and causal analysis methods, as well as integrating our methods with IGL’s existing strengths on experimentation to trial policy interventions.

We aim to provide policy notes and working papers on important topics and make original and collaborative contributions to relevant academic research fields.

From launchpad to escape velocity

IGL’s Data and Tech Unit has already started to deliver a new programme of projects, building directly on the work and legacy of Nesta’s Innovation Mapping team. 

We have developed methods to taxonomise research and innovation outputs in collaboration with ARIA. Now, we are finalising a year-long project with the European Innovation Council which has assessed the data capabilities of nine innovation funding agencies, uncovered 14 questions through ‘Innovation Data Dialogues’ and examined pathways for strategic data-driven decision making. In the coming months, we will be releasing a study on the impact of a significant AI technology on scientific research as well as sharing more of our vision.

As a non-profit, IGL’s role is to develop public goods and support organisations to develop their own capabilities for data driven innovation and productivity policy.

We are interested in partnering on new research and applied projects and then scaling their impact. Realising the ambitious vision for the Unit will also mean going beyond project-by-project progression. It will require the support of people and institutions that recognise the importance of this mission and want to work with us to grow the team and make it happen.

If you found this interesting or have an idea to discuss, book in time for a chat or send an email to the Data and Technology Unit.