
How to get sustainable business transformation right
Sustainable corporate change is a challenging feat to pull off. Julia Binder examines the barriers and drivers of change to increase your chances of success. ...
by Arnaud Chevallier Published 3 August 2021 in Brain Circuits • 3 min read
By combining scenario planning and Bayesian thinking – in essence, using probabilistic rather than deterministic methods – executives can bolster their decision-making abilities, enabling them to move forward.
Here are some steps to promote agile decision-making that will help senior leaders make better choices in uncertain times:
Identify a broader range of possible ways the future might look six months or a year from now, from a worst-case scenario to a best-case one and some in between.
Identify the two or three forces or elements that are likely to have the most influence on the future. Then continuously monitor those forces to determine their intensity and in which direction they are pushing the future. Beware! The challenge is often not so much identifying a bunch of forces at play. What matters is identifying the two or three critical ones that will drive most of the change, as it is often difficult to monitor more than a few forces.
Develop an action plan that will enable you to be successful for different scenarios, so that you’re prepared no matter what the future might look like.
Being efficient requires only one plan to avoid wasting resources. Although this lean operations style is sensible under normal operating circumstances, it’s not appropriate when uncertainty skyrockets.
Effectiveness is being prepared for whatever might unfold; it requires thinking broadly and having plans of action for each scenario. But as the future, especially in these times, is highly uncertain, you should aim for effectiveness rather than efficiency – at least at the onset.
Move away from a Boolean worldview to a Bayesian one. In a Boolean approach, something either is or isn’t. But dealing with uncertainty, we often cannot make these black or white calls. A Bayesian perspective, on the other hand, enables shades of grey. Bayesian thinking is rooted in probability – the various versions of the future become more or less probable as events unfold, tending toward one extreme or the other.
Roll out several plans of action initially, but as more data becomes available, stop investing in these unnecessary or irrelevant action plans. By gradually narrowing down your rollout, you reintroduce efficiency in your operations.
As new evidence unfolds, update your thinking. This will require you changing your mind, which is perfectly acceptable and, in fact, the only reasonable way to act when circumstances change.
Think of it this way: decisions belong to one of two groups – some are one-way doors (irreversible), while others are two-way doors (reversible). Order your decisions so that you make the irreversible ones later, when you have acquired a better understanding of what the future will be.
Success exists even in the worst case; maybe that’s simply avoiding bankruptcy, for example, but being hit by a perfect storm doesn’t mean you’ll fail. You have a chance to shine, no matter the environment; it’s your job to recognize it and make it happen.
Professor of Strategy at IMD
Arnaud Chevallier is Professor of Strategy at IMD, Director of the Global Management Foundations program, and Co-Director of the Complex Problem Solving program. His research, teaching, and consulting on strategic thinking bridges disciplines to provide concrete tools to improve decision making and corporate problem solving. He has written two books: Strategic Thinking in Complex Problem Solving and Solvable: A Simple Solution to Complex Problems, co-authored with Albrecht Enders.
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