by Principal Lecturer Harri Jalonen, Turku University of Applied Sciences

How does the refugee crisis influence European welfare societies? Is ‘big data’ a remedy for productivity challenges in healthcare or is it only one new threat to citizens’ privacy? Does the significance of investors’ ethical considerations boost the rise of socially responsible investment policies? How does climate change impact migration within and between countries and continents?

Big questions without easy answers. We don’t know what will happen in the coming years, let alone the coming decades. Although the future is always unknown, we cannot just sit and wait to see what will happen. The future may surprise us but our chances of survival depend on our readiness. We must remember that, to some extent, the future is an outcome of the choices and decisions we make today. The nexus between the present and the future also means that it is our obligation to engage in scenario planning and attempt to look at how the future can evolve from today to a future time horizon. This may sound like a cliché but “change favours only the prepared mind”.

 

The good news is that we have plenty of diverse future thinking techniques. Horizon Scanning, Weak Signal Analysis, Wild Card Analysis and the Diamond Shaped Trend Model, to name just few of them. Together with more specific foresight tools, such as Context Mapping, Progression Curves, Janus Cones, Future Users and Three Hats, it is possible to make some sense of the unknown future.

However, more important than the use of techniques and tools, is to understand the different manifestations of the unknowns. The principle is simple: different problems require different approaches. Yes, but how? Firstly, we should split the unknowns into narrower and manageable ones. Are we dealing with a lack of information on something or is there an issue which provokes conflicting interpretations? Secondly, we should carefully analyze what kind of knowledge-related challenges we are actually facing. Do we need more information about something or should we organize forums where conflicting interpretations can be discussed (even if not agreed)?
By defining the situation and analyzing its knowledge needs, we can identify four generic knowledge problems that all require different solutions.

 

Uncertainty means a lack of information about facts. Uncertainty is the gap which opens between the information required in a certain task and the information possessed by an individual or organisation. Example: How many socially excluded young people are there in a particular area?

Although uncertainty is an annoying situation, it is, however, a condition that can be easily fixed. What is needed is decent problem formulation and effective information acquisition.

 

Complexity arises from connections between situations or phenomena. Complexity refers to situations and phenomena interacting in a non-simple way. Example: How does the low-threshold family work at a child welfare clinic reduce the demand for more expensive care?  Complexity cannot be reduced by increasing information, because complexity arises from the intricacy and connectivity of various elements. Although complex problems are tricky to solve, the complexity involved is not absolute. Complexity can be simplified by increasing the organisation’s knowledge process capacity and decomposing problems.

 

Ambiguity means difficulty in interpreting a situation or phenomenon. Example: How does the internet of things enable smart healthcare? An ambiguous situation is challenging as it does not lend itself to a simple question-and-answer approach. Instead of providing an answer to an explicit question, information may stimulate several interpretations. It is essential, therefore, that an attempt is made to counter ambiguity by sensemaking – i.e. structuring the unknown and placing stimuli into some kind of framework.

 

Equivocality manifests itself as different interpretations of a situation or phenomenon. Equivocality means a situation where the actors look at the phenomenon at hand through different ‘lenses’. Example: Should private investors be able to invest in welfare? Equivocality arises from contradictory points of view. Therefore, instead of “solving” problems including equivocality, it is suggested that it should be a matter of how to encounter them by creating a trustful atmosphere and allowing a polyphony of perceptions.

 

Obviously, identifying four knowledge problems and their managerial implications is not a sufficient condition for tackling the unknown future. It is too broad to address domain-specific challenges.

However, I believe that it is a useful approach because it gives backing for individual future thinking techniques and tools. Most of all, I hope that it encourages the InnoSI project partners to think of the unknown future.