It can feel incredibly difficult to make decisions at a time like this – as individuals and organisations. Each one of us has a lot of decisions to make at home. For example, I’m currently working out how I balance work with childcare for two toddlers, how I protect vulnerable relatives, and how I can minimise frequent shopping when my boys only seem eat cheese! These kinds of questions use up ‘cognitive bandwidth’, draining the resources available for decisions in our work lives (and with pretty disastrous effects according to a range of studies).1 What’s more, we are faced by extraordinary levels of uncertainty – something most people handle pretty badly. In fact, a recent study suggests that psychologically we probably hate uncertainty more than we dislike certain calamity!
Uncertainty tends to leads to decision paralysis – which can be (literally) fatal. This is why it can be helpful to fall back on some things we know about how best to make decisions in uncertain times. Leapwise has created a lot of different tools and frameworks for better decision-making but sometimes stealing from the brilliant work of others is the way to go. This is why we often use the Cynefin framework to support organisations to think about the situations they are facing. Developed by Dave Snowden for IBM, this framework says that there are no hard and fast rules for how to make decisions, but instead we need to recognize that different types of problem call for different response types (our adaptation of this framework is shown in Figure 1).
Some decisions – which screwdriver to use for which screw, for example, are simple and can be based on rules. Here, we should in general be looking to codify rules and increasingly automate decision-making.
Other decisions are complicated. The system under examination follows clear and reasonably stable rules of cause and effect, but we need to conduct analysis to uncover these rules. This is a domain suited to analytic problem solving and the application of domain expertise – for example, working out how to price a product to get as much profit as possible.
The complex domain is where most leadership decisions occur, for example working out how to motivate employees. Social and environmental systems can be influenced by different actions, but the rules of cause and effect are unstable, non-linear and often change. Many different interventions might be helpful, but they equally will have impacts (positive or negative) elsewhere in the system. In the employee motivation example, for example, you might find that introducing bonuses gets factory workers to produce more but they become so focused on output that they stop suggesting ways to improve product quality, or cooperating with those picking up goods for distribution.
The chaotic domain is basically the one where no one really knows what’s going on. Cause and effect are very unclear and levels of complexity are so great that solutions aren’t clear. Think the immediate aftermath of a terror incident – or indeed the outbreak of an unknown virus… Here, the key is to act in any helpful way possible to start to bring more order to a situation, until it stabilizes to a level you can start to tackle more fundamental aspects of the problem. A strong action-bias is a very good thing here, because when no one knows what to do exactly, the risks of paralysis are high. Do any helpful thing you can to bring more stability to the situation.
What is clear about Coronavirus is that – like many problems – it is not exactly obvious whether the situation is chaotic or ‘simply’ complex. My sense is that it was highly chaotic until around 22nd or 23rd March, and the main critique of government, interestingly enough, was that it was insufficiently directive during that period. I’ve seen 94% approval ratings for the 23rd March announcements on restrictions and plans to use the police to enforce them, which is incredible – and does suggest that government is perhaps following rather than leading public appetite for order. Now, however, I think we are probably shifting into the complex domain. This will, I think, require a different approach – ideally, organizing the various strands of effort and activity as a series of experiments to tackle different aspects of the problem while co-ordinating activities across the different areas.
Like government, your organization will likely be making an array of decisions at the moment. And, as in government, you should be thinking about what type of situation you are in – and the decision-making style that might best fit that context. I hope this framework helps.
1. In their excellent book, Scarcity, Sendhil Mullainathan and Eldar Shafir, show just how severely anxieties and preoccupations affect decision quality