Focus on measuring what matters

Michael Mauboussin in his book Success Equation, states that success is defined by the combination of two factors skill and luck.

Everyday we are faced with a cruel random world, where the greatest contribution we can make in favor of our success is to improve our decision-making process (develop skill). If I could choose to be lucky, I would not hesitate on the option, but the reality is that this alternative is not so straightforward.

When we focus on the quality of our decisions, we can see that many of them are based on intuition. Our genetic baggage — or instinct — and experience often serve to generate rules of thumb that allow us: not to waste valuable time to solve urgent issues, or to wear ourselves out on minor issues.

It is not always necessary to kick-start our reflective system-or System Two as Daniel Kahneman and Amos Tversky would call it-to decide between eating chicken or meat, or jumping on the sidewalk to avoid being hit by a distracted cyclist. In this case the downside, or negative result, is not symmetric between the two scenarios. The point to note is that many times, the automatic response (immersed in our nature) shows up in decisions that are not life threatening, however, some of them pose great relevance and would be better off if some pondering is made beforehand.

This time we will focus on the decisions we make consciously, that is, through an analysis. The main tools that we will have at hand will be our own mental models, hypotheses, and the available information.

In this sense an anecdote comes to mind: In a park, at night, a policeman finds a man on the grass looking desperately for something under the light of a lantern. When questioning what he was looking for, the subject answered that his keys had fallen. The policeman continues to question where he had lost them, to which he replies two or three meters further back. Finally, he inquires why he was looking for the keys in this spot, to which he responds: here is where there is light …


This illustrates the availability bias, where we are inclined to search for conclusions with the easily obtainable information — where the light reaches us — which is sometimes incomplete, inconsistent, or irrelevant. Luckily, today the information is : greater, more accessible, and more relevant.

The speed at which the generation of information has advanced in recent decades is impressive, to say the least, and in fact the processing capacity of it has kept up the pace.

With more information, with better quality, and greater processing capacity, skill can be strengthened in decision-making.

The cycle between decision making, measurement of outcomes — impacted by randomness in the same way — and adjustments to our models, is increasingly shorter, allowing greater iterations and optimization in our decision-making models, in innumerable fields, ranging from agriculture, industry, health, education, finance, commerce, media, etc.

It is important to emphasize that the availability of information and state of the art tools is not everything, to illustrate it I would like to share a bit of history. During World War II, the brightest minds were focused on different areas of knowledge to get ahead of their rivals. Abraham Wald, an Austrian mathematician who emigrated to the United States, was part of a Statistical Analysis Group in New York.

One of the teams in which Wald participated oversaw aircraft’s optimization. Airplanes should be optimized considering factors such as the weight of the armor, supply of ammunition, and speed, among many others, to have an advantage over the opposing pilots. In a study, they wanted to determine where to include more armor in the body of the plane, for which they analyzed the distribution of the holes generated by the bullets received in the planes that returned from the missions. Some argued that the area showing the most damage per square feet should be reinforced, to which Wald responded. We must reinforce the areas where there are no traces of bullets … Why? Our sample considers the planes that managed to return, indicating that there are areas that, if affected, guarantee that the plane — and its pilot — will not return, that is where we should focus.


As you can see, we can have a large amount of data and process it at high speed and with pinpoint accuracy with the most sophisticated tools. And it may be that such information is accurate, consistent and accessible, but above all it must be relevant.

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