In the face of uncertainty, what can you control?

Uncertainty is anxiety-provoking in many ways, and often with good reason. Defined as the absence of information about a given phenomenon, it often means that we don’t know what to expect, leaving the door open to unpleasant surprises – loss of job, illness, accident, war, etc. – and leaving us helpless. Because the main fear linked to uncertainty is that of loss of control, where we can no longer foresee or plan. But this fear is based on a belief that only prediction allows control. This is not necessarily the case, and the two notions can be dissociated, with important consequences for management.

Management research has known this for a long time, and one of my colleagues regularly conducts the exercise with a group of executives: the greater the uncertainty we feel, the more we tend to reinforce the use of predictive logic. But the great lesson of history, and not only of the last two years, is that we are almost incapable of predicting. The more uncertain the situation, the more difficult the prediction. The biggest changes have rarely been predicted, and the predicted changes rarely happened. This is true on a smaller scale, as many corporate executives spend weeks making their annual forecasts, which are then often contradicted by the facts. Reinforcing a predictive posture in the face of uncertainty is, in a way, a managerial version of The Animal Farm: when our system doesn’t work, we try to “work harder”.

Prediction is not control, but the illusion of control

But the problem goes deeper than an inherent inability to predict. Only prediction, it seems, can control, but control what? It is never clear. In any case, one does not control the creation of the future. It’s a bit like in the movie theater: you can choose your seat, but you won’t have any impact on the movie itself. When we make a prediction, we assume – without often being aware of it – that the future is, in a way, already written, and that we cannot influence it. The only possibility is to predict it as well as possible and, once this is done, to trace the best path between now and this future. This is the purpose of the business plan. If I sell toothbrushes, I need to “know” where the toothbrush market is going. I discover trends, I anticipate evolutions, I predict market sizes. I consider all the aspects I can predict (market evolution, technological changes, regulatory changes, changes in consumer behavior, etc.). Implicitly, I recognize that I have no real power to influence what will happen. I am a “taker” of the future that will happen. Then I ask myself the question: how can I best benefit, through my actions, from what is going to happen? In essence, my approach is: what is the best thing I can do to take advantage of a future that I do not control. Here, the action is about the predictable aspects of a future that we cannot control. Prediction therefore does not give control, but the impression – or illusion – of control.

Let’s take back control (Caspar David Friedrich – Wanderer above the sea of fog, source: Wikipedia)

Prediction and control: a link to be redefined

The link between prediction and control is fortunately richer than a simple causality. This is illustrated by an example from an article written by Rob Wiltbank and colleagues in 2006. Imagine you are a startup that has just developed a new, highly innovative product. Let’s say a green metal chair, for which you predict a very large market. You go and present it to a potential customer. The customer, after listening to you, says: “Great, but I would prefer it in wood and red. What do you do? You have four options. The first is to adapt. After all, the customer is king! You thought the future was green metal chairs, but your customer tells you it’s actually red wooden chairs. The second option is to forget about this potential customer and find another one, remaining in your predictive paradigm. You don’t change your vision of the future, you just change the customer; this is called segmentation. The third option is to persist and try to convince the customer that he is wrong, and that the future is indeed green metal chairs. You stay in a predictive paradigm, but you also try to make your prediction come true. You add a dimension of control to your prediction; it’s the visionary paradigm. The fourth option is to sit down with the customer to discuss the chair and define the type of chair you could create together. After all, neither you nor he knows what the future of chairs is made of. The agreement is simply to define what is acceptable to you and to him for the chair you will make together. The agreement is only about that chair. It does not presuppose anything about the future of chairs in general. It is therefore an agreement about a very short term, about the “next move,” and totally non-predictive. Once the chair is made, you can co-create a new chair with the same customer, or take the same approach with another one. In this way, you will co-create the future from short term to short term. In other words, by co-creating with a stakeholder, you acquire a capacity of control over the very short term, which therefore dispenses with the need to predict the long term. To move forward in the uncertainty of the chair world, you no longer need to predict, you just need to agree with someone. So we see with this example that we can perfectly decouple prediction and control. If I am in control, on the next move, I no longer need to predict.

The inability to predict the future is therefore not bad news, on the contrary. The absence of long-term prediction not only avoids misdirection but also leaves open the possibility of unexpected opportunities. The history of innovation is full of examples of surprises. It is therefore not a question of giving up prediction by falling back on an inferior approach, but of realizing that predicting is not only unnecessary, but can be counterproductive. It locks the innovator into a kind of innovation tunnel, conceived as a big bet where it’s a “hit or miss”. A non-predictive approach with a step-by-step control, where the whole is rethought at each step, is much more robust and creative.

Uncertainty, the key to innovation

This notion of control, and in particular when it is based on co-creation, i.e. when it includes a social dimension, highlights another facet of uncertainty as an anxiety-provoking situation, that of uncertainty as a source of opportunity and innovation. Associating the notion of control with that of creativity is not as paradoxical as it sounds: it is a matter of identifying a small space where you can act concretely rather than dreaming of a large space where your only hope is that those who created it will leave you a small space. In the face of uncertainty, the right question is not “what will happen?” but “what can I do right now?” and more importantly “with whom can I do it?”.

One response to “In the face of uncertainty, what can you control?

  1. Pingback: Challenging Cassandra – The two risks of prediction for the decision-maker | Philippe Silberzahn

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