On Tuesday, Ray Poynter, wearing his hat as Chief Research Officer of Potentiate, presented on “The Role of Brands & Insights During a Pandemic”. As part of that webinar, he discussed scenario thinking (more typically called scenario planning in the US) and built a simple model of potential scenarios.
To his mind, right now two main questions dominate regarding the virus and the economy:
- Will the virus be controlled soon, or not?
- Will the economy recover soon, or not?
While many economic experts are making predictions, these are predictions and not answers, and economists have a poor track record predicting recessions and recovery.
So Ray took these two questions, and the two results, and applied each of the questions and each of its possibilities to come up with the scenarios from the resulting permutations.
The first scenario is where the virus is controlled soon and the economy recovers soon, which is the “back to normal-ish” scenario. The people who believe they can suspend things until we get “back to normal” are betting on this. It won’t be exactly the same, but it will be mostly the same as before the virus.
The second scenario is the virus being controlled soon but the economy not recovering soon, which would result in a major recession. Already the decline is steeper than the 2008 Global Financial Crisis, but given its different causes presents its own follow-on questions regarding its length and depth.
The next scenario, where the virus is not controlled soon, but the economy does recover soon, is one Ray considers “somewhere between incredibly unlikely or incredibly inhumane.” He says, “This is the one that some of the more right-wing capitalist bankers in the United States are pushing very heavily. They say ‘The damage to the economy is worse than the deaths, and we should go back to a much more normal situation. While this would result in a million deaths instead of 100,000 in North America, it’s not much different than the number of people who die from cancer and other things in a year, so we could live with that if we kept our economy going.’ While this is a scenario we don’t like, we have to keep it in mind for the sake of preparation.”
The fourth and final scenario, “a whole new world,” is where the virus is not controlled quickly and the economy doesn’t recover soon. Ray said, “It means that we’re in lockdown, maybe for six months out of every 12 months for a couple of years. It could result in having incredible restrictions on the ability to travel, maybe to import goods, maybe most people can’t work, and we don’t have theaters and restaurants up and running again.”
The point of scenario planning is that we have no way of knowing which of these four scenarios is the most likely. The scenarios may vary geographically: “The picture in Australia may be different than the picture in Asia. The picture in the UK may be different than that in the US.” And of course these four scenarios oversimplify situations: “In fact, it likely won’t be any one of them because within each scenario are many levels of detail. It might be slightly higher or slightly lower within any scenario, but fundamentally these are the four things we’re looking at.”
You need to plan for all four scenarios and prepare to act on them. You need to go through the process so that you’re ready to work within each scenario should it arise. “We need to see a new way of doing business, and for that you need Insights. One of the things you’re going to use your insights for is to scout for signs of which scenario is happening and how is it happening, how fast is it happening, and what are the implications for your customers in your marketplace.”
You can view a recording of Ray’s presentation and also review a SlideShare of his deck.
Ray Poynter wears many hats. A Fellow of the Market Research Society, he is the founder of NewMR.org, editor of the ESOMAR book Answers to Contemporary Market Research Questions, the Managing Director of The Future Place, Chief Research Officer for Potentiate, and author of two Principles Express courses, one of which is Introduction to Data Analysis.
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