Policymakers strive to establish future-focused policies that set the pathway and conditions for a better future and society. However, developing policy that effectively considers a realistic future state is often easier said than done.
Many organisations both public and private are straightjacketed by the constraints of shorter term needs and the resulting policy can fall short in achieving the visionary outcomes initially planned.
Applying Futures Thinking methodologies can support policymakers in bridging the gap between policy guesswork and realisation.
Applying Futures Thinking methodologies
As humans we are good at predicting individual events, even a series of them when linked in a linear way. Where we often fail is in predicting the future of systems, where the number of variables is almost infinite.
This is where using a Futures Thinking methodology can support our policy objectives.
Futures Thinking cannot and will not give you a definitive view of the future, nor does it focus on individual ‘things’. Instead, the OECD describes Futures Thinking as “illuminating the ways that policy, strategies and actions can promote desirable futures and help prevent those we consider undesirable.”
This is achieved using an approach that allows policymakers to examine multiple future states. Therefore, it doesn’t seek one future with one path to one objective, but multiple options. In doing so, policymakers can map out the necessary considerations before crystallising a desired future policy end state.
Futures Thinking hinges on the following:
- Signals: understanding the early indicators of change. Typically, these are not explicit and often referred to in Futures Thinking as “weak signals”.
- Drivers: What is causing the signals to broadcast? Examples of drivers are often summed up using methods such as the PESTLE analysis: Political, Economic, Social, Technological, Legal and Ethical.
- Trends: the broad direction of change, linking together drivers and signals. It includes analysis of the second and third order effects of the trend. For example, increasing urbanisation will have an impact on future transport policy, but transport policy will also reflect on urban planning. A future city may need to infill rather than spread for transport to be efficient and effective.
Even after analysing each of these, however, it is still often difficult to envisage a future state where all the proposed policy objectives are realised.
To overcome this, Futures Thinking deliberately places the subject matter on a timeline with a long but foreseeable goal date, about 30 years for example. In doing so, prospective approaches to policy can be tested, and the second, third and even fourth order impacts can be examined. Defining a set of likely future scenarios where no ideas are too extreme allows policies to be rigorously assessed before giving advice to the appropriate agency.
Futures Thinking means we have to look beyond the now, beyond the possible and proof-based suggestions to the realm of the probable.
Another benefit to Futures Thinking is that it encompasses qualitative and quantitative methods of analysis, from Relevance Trees to Structural Analysis, from scenario-based simulations to normative forecasting.
Not every approach can be applied to every problem, which is where the experts come in. Probable events and outcomes can inform how policy reforms will meet the changing environment. Similarly, scenario-based simulations add richness to how proposals are tested and iterated.
We now have the ability to move past the obvious and bring perspectives to bear on the small impacts that could have a significant ripple effect going forward.
