Can Ukraine withstand the third largest army in the world? If you asked me Thursday, I’d think the chances were low. But we’ve been told thousands of people are standing in line, old and young, to get these guns. When we heard that the government was handing out weapons to citizens who wanted them, we didn’t think anyone would get in line. I have teammates who, a few days ago, I was working with daily and are now caught up in an invasion. I tried on Twitter, but it’s such shifting ground right now. The Road Out of Kyiv (article) - I don’t know what to say about everything that is happening in Ukraine. So we can either continue to persist with what we know, or lean into our confusion and curiosity and see where it leads.Īnd often, our curiosity and confusion will lead to better answers than we could have expected. Sometimes our observations will fit into the models we have, and other times they won’t. Often we find results that are confusing or don’t fit with our view of the world (like the idea that homeopathic medicine doesn’t work). If there was ever advice for product managers, leaning into confusion would be it.

If they had, they would have learned that things like hygiene and hydration were contributing to better outcomes for patients, and could have improved outcomes for other patients, too. But medical professionals at the time decided to ignore the results because they didn’t believe in homeopathic medicine and were confused by the reported results, so didn’t pursue them further. In a story in the book, a London hospital of homeopathy had a much better record of treating patients for cholera than other hospitals at the time. We need to embrace the fact there aren’t often clear-cut answers. To be successful, we need to lean into that confusion and into the gray. Life is never black and white, but is a million shades of gray. Leaning into Confusionįinally, Galef argues we need to lean into the confusion. I feel like I’m constantly updating my thinking and processes in work and life, and you may see some of that in my writing, but I can certainly do more of it and do it more regularly. I love this idea and want to make it more a part of my regular process. They weren’t tied to specific world views and were willing to make changes based on facts rather than the way they thought things should be. And it was because the amateurs were updating their models and forecasts far more often than the professionals. In a study of superforecasters, Philip Tetlock found that amateurs regularly outperformed professionals. Rather than mistakes being fatal or calling for major contrition, mistakes can just be part of the process that call for regular updates to our mental models. This may be a big change to your mindset, to any of our mindsets, but it could be one of the best changes we make. Galef also writes in her book that we shouldn’t look at errors or mistakes as massive problems, but as ongoing updates we all make. My favorite is The Biggest Bluff by Maria Konnikova and another is Thinking in Bets by Annie Duke. There are two other books I think are excellent about this same topic. How can we do better at speaking this language and incorporating it into our processes? Wouldn’t it be better (and more accurate) to give a confidence interval of 70% confidence (or some other level) given the factors you know? And confidence will increase as you release or decrease as other factors come into play.

But is it right? How much would you wager on that outcome? A month’s salary? A year’s? And often that is what stakeholders and our businesses want to hear. We’ve done the research and have the data. How confident are we in the success of a product or feature? We may feel like it is a sure bet. This is critical for us as individuals, technologists and product people. Would you wager a week’s salary that the team can deliver by Tuesday? What about a month’s? We may initially feel very confident in an opinion (yes, we’ll make the deadline by Tuesday), but by making it more concrete with a level of confidence (an actual dollar amount or percentage), we can gauge exactly how confident we are. How confident are you with this idea? How much would you wager? A week’s salary? A month’s?īy putting something at stake, it makes a belief more real and allows us to calibrate our confidence. We should calibrate our beliefs into confidence levels. But when we’re assessing the probabilities, we need to be more nuanced than that. The ultimate outcome will be a yes or a no, one or the other, since most things are binary (they happen or don’t). And we are often overconfident, erring on the side of the positive far more often. And we often think in terms of all or nothing. We tend to be overconfident in our assessments of risk and probability.

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