What if? That is often the decisive question before any strategic decision in a company, government, or policy field. Unfortunately, so far, answers to this question can only be found by looking deep into the famous „crystal ball“ (mostly designed and owned by politicians, consultants, or scientists).

How could it be otherwise? After all, it is not (yet) possible to briefly visit the future and check whether the proposed change to a governance process or public policy will have the desired consequences. This lack of knowledge, this sense of unease about the unintended consequences of one’s actions, paralyzes people and organizations. They remain still because only the bravest dare to walk in the dark.

And this is precisely where a major problem lies for sustainable and positive change within our regions, industries, and the world we live in. Because the world – as everyone is well aware by now – is complex. Countless interdependencies, feedback loops, tipping points, and adaptations make the world in which we have to make decisions an extremely confusing place.

And if you are not even sure where you are at the moment, how can you imagine what the future might look like? Just as evolution does not follow a plan, we can expect little consistency and reliability from the world itself.

Using governance simulation to navigate a complex world

But after all, we are not completely helpless in this complex world. We have methods and tools that we can use to look into possible futures (plural!). Strategic foresight is a good example. Formerly a rather linear discipline that naively inferred the future from the past, it has greatly improved in recent years and has made room for contingency thinking.

Rapidly advancing technological development, especially with regard to computing power, has brought more attention to a field of computational simulation that has long been explored but has not yet been used to its full potential.

You have probably heard of computer-based simulations within climate research. Recently, the successful computer-based simulation of protein folding has also made headlines in the field of biology. Now, widely used terms such as AI and machine learning are often used interchangeably with computer-based modeling and simulation.

Modeling and simulation have become an integral part of the social sciences as well. After all, this approach makes it possible to conduct experiments that would hardly be possible in non-artificial environments, in the so-called „real world.“ You can’t stop societies, fast-forward them, or multiply them to unfold in different directions. With artificial societies, however, you can!

And this is why this framework is particularly effective for management, organizational, and political science. In these fields, the aforementioned problems of counterfactual conditions are even more valid. Not least for ethical reasons, it is not easy to conduct large-scale experiments with governance or public policies in particular.

Too much is at stake. Thus, one hesitates to, as Otto Neurath put it, rebuild the ship on the open sea and in stormy weather. The citizen as sovereign and taxpayer also has little sympathy for grand social designs created on the drawing board.

However, there is no doubt that our society faces enormous challenges and that changes are needed, particularly in the area of governance, to address these wicked problems.

If we are to mitigate climate change, stop species extinction, or tackle global inequalities while maintaining prosperity and competitiveness, we need new and more effective forms of public governance and inter-organizational collaboration.

Governance simulation aims to explore and test precisely such alternative steering and collaboration approaches by using systems thinking, computational modeling, and simulation.