If the events of 2020 have proved anything it surely how valuable foresight is when making policy, but also how hard it is to predict the future. We have known for a while that, as a society we face some big challenges, but the COVID pandemic has brought some of these into stark relief: the future of work, the changing face of cities, loneliness, an ageing population and the environment have all become more urgent issues or been more widely appreciated as huge challenges when viewed through the lense of the pandemic. If ever there was a need for innovation in policy-making it is now, but what research on innovation in many fields shows consistently is that innovation doesn’t just happen it needs an eco-system. An ecosystem draws together a range of different actors, activities and institutions in a network of relations that facilitate innovation. The same is true for policy-making.
One key innovation in policy-making that has gathered widespread support has been the move to Evidence-Based Policy which draws heavily on the concept of evidence-based medicine and prioritises experimentation and systematic reviews of the evidence as key tools in policy-making. In the UK successive governments of different political persuasions have invested in an ecosystem to make evidence-based policy a reality, in part by building a network of What Works Centres that corral the evidence on key policy challenges. But although, evidence-based policy is important it has yet to deliver the step-change across social and economic policy-making that was seen in medicine. One of the reasons for this is the complexity of policy-making. Generating evidence for what works in medicine is undoubtedly complicated, but perhaps it is not complex in the way that working out what works in human services is. A useful analogy is the difference between sending a rocket to the moon, which is complicated, and raising a child which is complex (an analogy used by Glouberman and Zimmerman in a 2002 paper on complicated and complex systems).
This increasing complexity is one of the factors that makes greater investment in futures thinking an attractive idea. We may not be able to predict the future in an increasingly complex world, but thinking more about the future might help us prepare for many eventualities in our increasingly uncertain future. This might involve adopting a different mindset and recognizing the limitations of traditional planning and strategy processes, which tend to assume that change is linear and that what happened before is the best predictor of what is to come. One strand of thinking on better policy-making has turned to the role of technologies such as machine learning, AI and the potential of Big Data. Will these technologies help policy-makers understand complex systems and model potential future scenarios in which policy options can be tested? They certainly have much to offer, but, in the post-industrial, information economy, new models of innovation have started to break down the distinction between technologically-driven and people-driven innovation, suggesting that technologically driven, top-down models of future thinking may only be of limited use. Models of ‘open innovation’ and ‘social innovation’ for example, invert traditional models of technologically-led innovation and suggest that innovation is driven by the creation of ‘ecosystems’ made up of diverse actors who align their goals and, importantly, collaborate to co-create ‘shared value’. In other words, the value of what is created is intrinsic to the process by which it was created. It is in the coming together and sharing of knowledge and ideas that value is created. Proponents of social innovation often talk about social innovations being social both in their ends and their means. Co-creation means that instead of the citizen being seen as a recipient of innovation, in these models, citizens and in particular, the people who use services, are the drivers of innovation and work with government and services to co-create innovative solutions to meet their needs be they better financial services or more effective health services.
A report on realising the value of Futures and Foresight in policy-making, A Stitch in Time , published by the RSA, in collaboration with MetroPolis and the Policy Evaluation and Research Unit at Manchester Metropolitan University, describes futures thinking as a people-driven, multi-disciplinary project. Technology has a role to play, but so do the arts and humanities. It recognises that futures thinking is an inherently creative discipline which asks fundamental questions about what it is to be human and is necessarily values-driven. Taking this perspective leads the authors of the report to argue for the importance of encouraging all of us to make the future a greater priority and embed long-term thinking into our everyday lives. The policy-making ecosystem therefore needs to be large, inclusive and multi-disciplinary if it is to accommodate futures thinking. The report’s authors make far-reaching and radical recommendations for decision-makers and organisations across society, suggesting how this vision can be realised. We at Manchester Metropolitan University are looking forward to continuing to work with the RSA on bringing their vision to fruition.
Chris is Professor of Evaluation and Policy Analysis at Manchester Metropolitan University, where he is also Director of the Policy Evaluation and Research Unit and co-founder of MetroPolis: a university thinktank helping to embed researchers in policy and practice.
