Fortune teller paradox

    In the age of information technology, expert analysts, and even predictors, have begun to appear more and more. Their task is to talk about what will happen after a while, what to look for and what trends should be expected in the foreseeable future. In the article I would like to analyze a little different types of predictions.

    50/50


    A well-known business publication is preparing a number on the trends of next year. Identifies key questions, interviews experts. Expert opinions are divided evenly from the most pessimistic to the most optimistic scenario, the most cautious make neutral forecasts.

    Such moments make me embarrassed. If we are talking about forecasting the growth of Apple shares, then in a year we will see only one solution: the price will either fall, increase, or remain the same within a certain corridor. This means that, at a minimum, ⅔ “experts” are mistaken right now in their forecasts and cannot be “experts” by definition. Nevertheless, this occurs all the time.

    50% is the probability of a blonde meeting a living dinosaur on a city street. She will either meet him or not. So you can evaluate the logic of some experts, i.e. guessed / not guessed. I note that 50% is a rather large percentage of the probability of the forecast, so with a large number of opinions you will always find someone who guesses that says nothing about his real analytical abilities.

    That is, you need to learn to distinguish expert opinion from banal guessing.

    Stable “instability”


    The principle of the maze says “always turn right.” In other words, always have the same opinion. After all, if you sit for a long time on the bank of the river, the corpse of the enemy will pass by.

    This principle is well demonstrated by the most influential economist in the world, Nuriel Roubini, who predicted the 2008 global crisis. The whole point is that, since the beginning of the 90s, Nuriel repeatedly predicted the collapse of economies, emerging markets and economic crises. Given the stable "instability" of the global economy and geopolitical processes, anyone can predict the financial crisis in such conditions.

    In such a situation, it is very important not only to predict the very fact of the occurrence of a particular event, but to identify the truereasons why this event will occur. And to do this when other “experts” will twist at your temple in front of your nose at your “forecasts”.

    Causality


    A causal relationship is a connection between phenomena in which one phenomenon, called a cause, under certain conditions gives rise to another phenomenon, called a consequence.

    One of the main problems of predictions is that very often the cause and effect are confused, or nothing is known about the real causes.

    For example, when a banking crisis occurred in Ukraine, the reason was given to citizens who collected a large number of consumer loans, which devastated banks' cash reserves. At the same time, the real reason for the cash deficit was that two years before this, banks had placed deposits at 30% (!) Per annum and distributed loans without confirming the borrower's solvency. Thus, the moment when deposit rates increased to 30% per annum was the very moment when experts had to guess about the impending financial crisis. Oh yes, you could still read the Western press, which wrote about the impending crisis at a time when we were gaining loans in large numbers.

    Process Cycle


    Another predictor trick is to make predictions based on historical events. Again, without understanding the causal relationship. This leads to incorrect conclusions.

    For example, yesterday someone wrote to me in comments on facebook that Windows Phone is waiting for failure, because I quote “I have an android and an iPhone, enough for development”. The objective situation is that even if Windows Phone is waiting for failure, this is clearly not for this reason. The presence of successful Android and iOS also does not say anything about the future situation. After all, you can immediately recall Kodak, Blackberry and the same Nokia. With this simple example, I wanted to show that the analysis of cause-effect relationships is a more time-consuming task than it might seem at first glance.

    Success and Failure Stories


    I rarely read success stories, because in 99.99% of cases they are nothing more than a successful combination of well-known factors and conditions. I also try not to read biographies of great people, moreover, I consider them fatal for the development of analytical abilities. I will not give specific names, but in the biography of each person you can find something that supposedly influenced his success (although in reality this could not be so). The main problem is that reading a biography (usually in a positive way), you can find many fictitious cause-effect relationships, and not recognize the real reasons for success. Moreover, sometimes even the person himself cannot say with certainty what exactly became the reason for success.

    But I love reading failure stories. Not in order to set yourself up for a possible file or to convince yourself that “this is normal” (as is customary in a startup hangout). No, my goal is to identify not just the moment when it became clear to everyone that everything would fly to tartarar, but the earliest moment when it was already possible to recognize the impending threat .

    When I read the opinions of experts, I try to pay attention not to conclusions (they must always be done myself), but to a chain of reasoning “cause” - “consequence 1” - “consequence 2” and how likely this chain is. From all the chains you need to choose the one whose probability is the most. Well, of course, do not forget about the “black swans”.

    So what is the predictor paradox? It consists in the fact that the longer the prediction period, the easier it is to make an accurate forecast. But to predict what will happen in a month is almost impossible.

    How can this help me?


    Project management is, first of all, an assessment of possible risks and how they can affect the course of the project. Here, an analysis of cause and effect relationships is indispensable. It is very important in the early stages to identify possible threats and simulate various scenarios. The later these problems come out, the worse it will be for you.

    And yet, analyze and draw your own conclusions, and do not get fooled by the opinions of “experts”.

    Thanks for attention!

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