Future is noisy. There are so many signals of potential future developments that it is hard to hear anything important amidst it. New technologies join the clank of the engine that drives the hype machine. Multiple voices tell the stories and anecdotes about shifts in behaviour, politics and priorities. Facts, ideas and opinions form a cacophony of sound seeking your attention. And megatrends provide the underlying hum to it all.
How to make sense of all this noise? In the Platform Value Now project we have been developing the use of the multi-level perspective as a filter and frame to screen and position all the signals of future developments. I will give a more scientific presentation about this research in progress next wednesday at the EU-SPRI conference in Lund, but here is the basic idea.
The first step in structuring signals of future developments is to take a step back and think what kind of change is in question. Our case was about the impact of platform economy on work and employment, which means that the change will probably be pretty drastic. In addition, the main drivers are technologixal developments, such as digitalisation, and social developments such as demographic changes. Therefore we decided to approach our theme as a socio-technical transition.
The next step is to do an initial scan with a fairly wide scope, collecting signals from scientific and news articles, blog posts, projects, and social media feeds. The signals are then positioned to the multi-level perspective as shown below. On the landscape level are the usual suspects, the easy to spot things such as megatrends. On the niche level are examples of interesting solutions that might scale up to form the new dominant modes of operating in the regime. The most interesting stuff is on the regime level, between the assumptions about the current state and the descriptions of preferred image of the future. This is where the not so obvious factors driving change are positioned as well as all the minor changes themselves, which form larger pathways or narratives of the transition taking place.
In practice the result of the initial scan is not of course as neat a picture as it sounds, but rather a mess of all kinds of signals. But based on what kinds of pathways seem to emerge, the picture can be clarified in the next rounds of scanning. The multi-level perspective thus forms a guiding structure to which the results of an iterative process can be positioned. What is especially useful, especially in topic as value-laden as the future of work, is making a difference between what is assumed about the present, what kinds of changes are anticipated and what is seen as a preferable future. This makes the argument about what needs to be done now more easy to understand and debate.
The process is still very much on-going, but what is clear already is that the transition paths differ not only in their focus themes, but also on the amount of existing structures they challenge. On a very superficial level there is the disruption platform thinking has created in human relations and job search via services such as LinkedIn. On a more profound level, platform thinking challenges the way of working (via enabling microwork and new forms of organisation), the structures of industries (via enhancing the effects of artificial intelligence), and eventually also the very notion of what a job means by shifting the focus from capability management to asset management (e.g. earning a living via Airbnb). More on these in a later post.