Strategic Foresight and Warning Methodology

Our Foresights and Insights

Mapping risk and uncertainty is the second step of a proper process to correctly anticipate and manage risks and uncertainties. This stage starts with building a model, which, once completed, will describe and explain the issue or question at hand, while allowing for anticipation or foresight. In other words, with the end of the first step, you have selected a risk, an uncertainty, or a series of risks and uncertainties, or an issue of concern, with its proper time frame and scope, for example, what are the risks and uncertainties to my investment portfolio within the next 18 months to 3 years, or what will be the future of the emerging artificial intelligence world over the next twenty years, or what are the risks and uncertainties to my activity within the next fiver years as a result of China’s rise.

Once this initial question is defined, the second stage is about constructing our underlying model for understanding, i.e. mapping our risk or issue.

As Professor Joshua Epstein underlines, constructing a model – i.e. modeling – is nothing more, actually, than making explicit the hidden, implicit, model we, as human beings, are using when thinking. Epstein lists 16 advantages that result from this explicit modeling, to which we can add a couple more. Among these, we can notably highlight that, in terms of intelligence and anticipation analysis, making the model explicit will help identifying various cognitive, normative and emotional biases, thus allowing for their mitigation. Thanks to this modeling we can think out of the box and overcome silos. Then, the model and its construction will help defining areas of uncertain understanding, which can then be marked for further study, inquiry and research. Meanwhile, an explicit model will also help us working collaboratively, while communication will be greatly eased and enhanced, notably by using tools developed for big data analytics.

How are we thus to transform our inner implicit and imperfect model about the risk and uncertainty of concern into a proper and efficient explicit model to assess correctly risks and uncertainties, design critical responses and communicate about both risks and the decisions taken to manage them?

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In many foresight methods, once you have identified the main factors or variables and reach the moment to develop the narrative for the scenarios, you are left with no guidance regarding the way to accomplish this step, beyond something along the line of “flesh out the scenario and develop the story.”*

Here, we shall do otherwise and provide a straightforward and easy method to write the scenario. We shall use the dynamic network we constructed for Everstate – or for another issue – and the feature called “Ego Network” that is available in social network analysis and visualisation software to guide the development and writing of the narrative.

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Variables, Values and Consistency in Dynamic Networks

In this article we explain and discuss the methodological background that allows us to set the criteria for Everstate – or for any country or issue chosen – as exemplified in the post “Everstate’s characteristics.” Meanwhile, we also address the problem of consistency.

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Revisiting influence analysis

Once variables (also called factors and drivers according to authors) have been identified – and in our case mapped, most foresight methodologies aim at reducing their number, i.e. keeping only a few of those variables.

Indeed, considering cognitive limitations, as well as finite resources, one tries obtaining a number of variables that can be easily and relatively quickly combined by the human brain.

The problem we here face methodologically is how to reduce this number of variables at best, making sure we do not reintroduce biases or/and simplify our model so much it becomes useless or suboptimal.

Furthermore, considering also the potential adverse reactions of practitioners to complex models, being able to present a properly simplified or reduced model (however remaining faithful to the initial one) is most often necessary.

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Go back to Part 1

Actually, any SF&W model as it primarily deals with time should be a dynamic network. How can we expect obtaining any potential outline for the future if our model for understanding is static?

Our map thus aims at representing the potential dynamics of polities. We shall notably use Ertman’s work on past state-building, but making it adaptable to present and future conditions.

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