b. One of his major insights about decision making was triggered by this observation by Daniel Kahneman, the grandfather of Behavioural Economics. Kahneman and Miller wrote in 1986: A spectator at a weight lifting event, for example, will find it easier to imagine the same athlete lifting a different weight than to keep the achievement constant and vary the athlete’s physique. This observation basically states that bias is introduced into our thinking because the variable of choice is not random. In this example we can imagine the athlete lifting a different weight, but we don’t easily imagine a different physique; whereas both of those variables could materially influence the final outcome of the weight being lifted or not. This triggered him to think about this in the context of risk (being Distinguished Professor of Risk Engineering, New York University School of Engineering) and came to the conclusion that, in reality (not in laboratories) there are many random variables and they are all subject to variation. It seems very obvious to say this, but Taleb realised that; increasing the number of random variables compounds the number of counterfactuals and causes more extremes. And of course we all know that reality is comprised of multiple variables, so predicting an outcome in reality is really just a lottery. The practical outcome of this phenomenon are: We really don’t think straight as we think we do. (Because of an inherent bias in our thinking process, we vastly underestimate the variability of multiple variables, with catastrophic consequences – Taleb.) We foolishly cling to the notion that we can influence the universe and things happen because of us. (Price: stating the bleeding obvious.) We feel compelled to find the answers by applying rigorous rational thinking and research. If we can’t understand our own biases, research would be a good way to overcome the problem, right? Not so much. Taleb remarked that ‘scientists use statistical methods blindly and mechanistically, like cooking recipes (and) tend to make the mistake when consciously comparing two variables.’ This is very common in research and in fact so much so that I can safely say that most research is not worth the paper it is written on. I wrote that neuroscience is not all it is cracked up to be (and promptly got attacked by converted zealots.) Nieuwenhuis found in 2011 that 50 per cent of neuroscience papers (peer reviewed in prestigious journals) that compared variables got it wrong.  (I have warned about being seduced by statistics too.) We can’t rely on research to save us from sloppy thinking. The question is then, what we can do about this, because we have a life to love and a business to run? A good start would be to study and understand probability theory properly so that you can truly appreciate (for example) properties of the joint distribution of tails. But the reality is that most of us won’t be doing that, so here are some simple alternatives instead: Consciously avoid the lure of simple extrapolation. (Especially when it is so easy to do with spreadsheets.) Consciously stop and anticipate worst case scenarios. (They are more likely than you want to think.) Encourage a culture of robust questioning. (Particularly those corporate mavericks who go against the grain and sometimes seem difficult.) Actively guard against people using research as a reason to do or not do stuff. (Apple did okay without ever relying on research.) You must appreciate that any of the above could easily be abused and become a reason for never doing anything and we should be vigilant about that. But more than anything, stop being seduced by the promise of a silver bullet. Have fun. Dennis Ganador: Acquire and retain clients in the retail supply chain. PS: If you are a supplier to retail, in this post there is a little gift for you.