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Strategic Foresight for Corporations

The Art of Imagining the Future

“[…] the economists are at this moment called upon to say how to extricate the free world from the serious threat of accelerating inflation which, it must be admitted, has been brought about by policies which the majority of economists recommended and even urged governments to pursue. We have indeed at the moment little cause for pride: as a profession we have made a mess of things.”

This direct quote from the economist Friedrich von Hayek’s Nobel Prize Lecture highlights the inherent limitations of relying on economic forecasts for strategic decision-making (his highly engaging lecture is strongly recommended reading here). 

Despite the growing number of available forecasts, there is increasing evidence of their poor performance. One study indicates that although professional forecasters are quite confident in the reliability of their predictions (53%), their accuracy is significantly lower, with only 23% of forecasts proving correct. As expected, forecast performance further declines as the time horizon lengthens—meaning the accuracy of economic predictions is even lower for longer-term forecasts.

The latter issue becomes especially problematic when corporations rely on economic forecasts for strategic decision-making. An enterprise’s success hinges on how effectively it integrates future developments of its business environment into its strategy. Because of delays in the implementation and their natural long-term reach, an optimal strategy requires clarity on economic and political trends over extended periods. As such, basing corporate decision-making on forecasts that are known to be inaccurate much of the time does not appear to be a very attractive proposition. 

There are several reasons why long-term economic forecasts are often wrong. The two most significant factors are the world increased complexity and projection bias. 

First, not only is the world becoming more complex but also, crucially, more interconnected. While, in theory, greater connectivity could make events more predictable—by establishing feedback and impact/response relationships between variables that can be modelled), it proves problematic in practice. In economics, the factors that influence events are rooted in the collective behaviour of many individuals, each with unique preferences and utility functions. Even worse, those could be swayed by random influences—weather, waking mood and other stochastic effects.  When these individual behaviours are aggregated, so too are the errors we commit to using them to forecast the future. And these errors tend to compound rather than cancel out because of common biases (it is proven, for example, that economic forecasts are inherently prone to over-optimism). Hence, the more we aggregate different factors (reproducing the complexification of the world), the larger the forecasting error (see here).

Projection bias is an even more serious flaw in strategic decision-making informed by economic forecasts. This bias stems from the assumption that people have stable preferences and beliefs. In business decision-making, this bias results in companies being better prepared for a future that resembles the present. In practice the similarity between the present and the future –sometimes modelled as a ‘geometric Brownian motion’, where the expected value of a variable is its current state) may hold much of the time, projection bias leaves enterprises ill-prepared to capture the value (or mitigate the pitfalls) in regime switch. It is at the tail of the probability distribution of future events that lay the most uncertainty but also where the most value can be created. 

So, what is the alternative if using forecasts is not good for corporations?

Over more than fifteen years of professional experience, I’ve found that amore effective approach is Strategic Foresight. While the web offers many definitions, I describe Strategic Foresight as fundamentally different from forecasting: where the latter tries to guess the future, the former imagines it.  

There are several key differences between these two approaches to inform strategic decision-making. The following three are the most relevant. 

First, forecasting is quantitative: we forecast a number—inflation rate in the next four years or GDP growth—using statistical methods. In contrast, Strategic Foresight is largely qualitative.  Though it relies on rigorous methodologies, its outcome is typically a narrative—a story or, more often, multiple stories. Much has been written on the power of storytelling. By engaging our senses and emotions, narratives create lasting impressions that shape our beliefs, attitudes, and behaviours. Strategic Foresight is based on the idea that this power can prepare the organisation for a range of possible future (while forecasting projects a single future).

Second, Strategic Foresight deals with the future in a much freer way. It typically imagines a futures that are much different from the present, thus escaping projection bias. Consider one of the principal methods in Strategic Foresight: Scenario Planning (refer to this excellent article for the origins and the main principles of this technique). Each scenario practitioner develops their own methods; for me, one of the most critical features of a scenario planning exercise is its internal consistency. 

In a typical scenario, the end state—the future world, country, or enterprise—results from concatenating several events. Working backwards, each event in the chain is the most logical consequence of the event that immediately precedes it. ‘Most logical’ is crucial here: each link in the chain should be easily explained and understood. Yet, the magic of scenario planning lies in how the most logical sequence (in probability) can lead to a future state of the world that can be vastly different from the present. The end state, viewed from the present perspective, often appears quite improbable.

As such, Scenario Planning is not designed to forecast the future. In fact, scenario exercises typically produce two or more scenarios, each considered equally plausible. Its contribution to decision-making is to stretch the thinking of corporate management. By envisioning seemingly unlikely future states, leaders prepare the corporation for the ‘contingency’ of different future situations. Through Scenario Planning, the corporation develops greater organisational agility and cultivates a positive attitude towards uncertainty: a source of potential value rather than a risk to be avoided.

Finally, Strategic Foresight often employs a technique called Systems Thinking. This is becoming increasingly popular, and it has many different definitions. Like Scenario Planning, the greatest value of Systems Thinking in strategic decision-making lies in its methodology rather than its outcome. It is the time we spend designing the system that underpins one event—mapping the web of cause-effect-feedback loops that shape the state of a variable—that truly matters. 

Systems thinking not only leads to a deeper understanding of a process but also embraces their complexity. In other words, it thrives on the intricacies of the process, quite the opposite of forecasting, which tends to simplify (or flatten) stochastic processes to fit into more manageable mathematics.

Luca Silipo, Chief Economist, Sustainability and Supply Chain Leader at Finisterre Solutions