#34: The difficulties of not-knowing
|Vaughn Tan||Jun 24|
Last week, I talked with someone who receives the newsletter. She told me that it wasn’t clear what it is about. The fact is: I started it as a form of free self-therapy—but it has taken on a slightly different meaning because of coronavirus.
This newsletter has the same title as my book—The Uncertainty Mindset: Innovation Insights from the Frontiers of Food—which was pre-released last week. Or possibly the week before that. The precise date is apparently unknowable.
The newsletter was and still is a way to noodle in my usual half-baked way on some of the questions about uncertainty and not-knowing that I couldn’t answer (and hadn’t even come up with) in the book. Explaining what the newsletter was and is about requires explaining what the book is about.
So—in the book, I’m trying to answer three sets of questions. They’re at different levels but the levels are connected.
Level 1—What do teams do to be continually innovative?
Innovation and innovation work is inherently uncertain. This means people and organizations wanting to innovate need to work fundamentally differently.
To unpack that by way of metaphor: innovation work is about getting to an unknown destination by an unknown path. The problem is that nearly all conventional management theory is about identifying the best path to get to a known destination. (There are understandable—though not forgivable—reasons for this which I’ll write about in the future.)
So conventional management theory offers few practical solutions to the problem of how to hire people, set goals for them, and motivate them when their destination and the road to get there are both unknown.
To take just one example, most conventional hiring depends on writing up a clearly defined job specification (including tasks and required skills), looking for people who fit the specification, evaluating them through interviews and other tests, then hiring the person with the best fit. But if you’re hiring for an innovation team that doesn’t know what it will be working on or what its objectives will be, how can you write up a clearly defined job specification in the first place? The conventional solution is fundamentally unsuited to the innovation problem.
At Level 1, the book gives some solutions to innovation problems: practical ways to hire, set goals for, and motivate people doing innovation work. These solutions sound pretty out there, because they don’t sound anything like what conventional management wisdom would prescribe. If my logic holds, that’s how they should be.
Level 0—What is the general principle connecting these unusual ways of working innovatively?
Underneath concrete solutions and ways of working are general principles that lead to those ways of working. This is the second, let’s call it more fundamental, level of question the book tries to answer.
The framework here is about how organizations perceive and make sense of the world—their mindsets. Mindsets aren’t just how an organization sees and interprets the world, they also affect how it makes decisions and acts. There are many different kinds of mindsets. The idea of a mindset isn’t new, though I may be the first to argue that organizations can have mindsets.
The uncertainty mindset assumes that the future is unknown and not knowable or calculable in advance—it interprets the information it gathers about the world based on this assumption. This is in contrast with a risk mindset that assumes the future may be unknown but is fundamentally knowable and calculable. The risk mindset is behind every action chosen through precise cost-benefit analyses, every project management process based on a long-horizon budget and deliverables—it’s great for well-understood work.
Risk and uncertainty mindsets can coexist, and they should coexist when the future is partly risky and partly uncertain. (It almost always is.) The problem arises when an organization only has the risk mindset but is trying to do inherently uncertain things that aren’t well-understood—such as innovation.
Organizations with the uncertainty mindset act in ways that are more appropriate for doing innovation work—such as putting in place highly unconventional hiring methods, goal-setting processes, and motivation systems. In other words:
Mindset → Interpretation → Action. And it’s important to have an organizational mindset appropriate to the work to be done.
At Level 0, the book explains what the uncertainty mindset is and how it changes the way organizations act so they innovate better. My basic argument is that organizations should adopt the uncertainty mindset if they want to become innovative.
Level -1—Where else is the uncertainty mindset relevant?
At Level 1 and Level 0, the book is about food innovation teams and how they exemplify the uncertainty mindset. But one level down, where else is the uncertainty mindset appropriate?
At Level -1, the book argues that the uncertainty mindset is not just relevant for innovation teams—it is a way of thinking and seeing the world that is appropriate to situations where the future is unknown and at least partly unknowable.
One of those situations is innovation work, but people, teams, and organizations face many other uncertain situations.
Coronavirus has swiftly shown itself to be one such situation of great uncertainty.
Will a practicable working vaccine be developed? When will such a vaccine become widely available? Will pre-coronavirus consumer behaviour and spending patterns return after a vaccine is developed? Will there be structural changes in the economy after multiple months of lockdown? When will global routine air travel return to normal levels?
For these and many, many other policy- and business-relevant questions, we have only an incomplete idea of the possible answers. We certainly don’t have precise probabilities for all the possible answers. This means that during and after corona-time, we will face some risks but also—and primarily—tremendous true uncertainty. The future in corona-time is both risky and uncertain.
Yet though it seems pretty much indisputable that the future isn’t just risky, the risk mindset (still!) remains the default and exclusive way of thinking about and acting on the future for both individuals and organizations. Good indications that this is happening include making important decisions exclusively on the basis of cost-benefit analyses and planning major deliverables in great and inflexible detail with very long time-horizons. If you doubt that this has been happening in governments and businesses and continues to happen … well, I can’t help you there.
Since February, the questions I wanted to deal with in the newsletter have become more urgent because I live in a country where coronavirus response has been dominated by the risk mindset. (If you live in the US or Brazil, your personal situation may be analogous.)
It’s been fascinatingly horrifying to watch firsthand as theory comes to life, especially when real life confirms what theory predicted. Coronavirus response is probably the clearest example to date of the terrible consequences of applying the risk mindset to uncertain situations—and also of how the uncertainty mindset can drive responses that are appropriate to uncertain situations.
The book explains why people and organizations should adopt the uncertainty mindset right now. Personally, the most important new, unanswered, and perplexing question coming out of the last few months is: why do individuals and organizations continue to ignore indisputable evidence and avoid adopting the uncertainty mindset?
Another way to put it is: what is stopping us from admitting that we don’t have enough information to do the kind of advance planning that we normally depend on for comfort and reassurance? Yet another way to put it is: why does not-knowing seem so difficult?
It seems really urgent that we figure this out ASAP, and not just in the context for coronavirus. For the time being, this seems to be what this newsletter is about.