Analytics and Predictability
Analytics and Predictability
We often read and hear that the information -the data- must be analyzed, that accumulating data without analyzing it is not useful to accumulating data without analyzing it is useless, that it is necessary to put it in context, etc. And what does it mean to put them in context? Reviewing both the content itself and the sources, to assess their importance and the possible influences that have distorted the data with respect to reality, i.e., have transformed them from information into opinion (partial information) -either by omitting part of the information or by reducing its relevance-.
This often happens, and we speak of unconscious bias (unconscious bias), among which is the availability distortion (availability bias) cuando sistemáticamente optas por soluciones o personas que te vienen inmediatamente a la cabeza. Porque son de tu círculo habitual -que termina en muchos casos provocando inconscientemente por ejemplo discriminación por género en Consejos-. El efecto generado por estos sesgos es a su vez una limitación en la capacidad de interpretar situaciones o de prever eventos con influencia en las organizaciones, por culpa de la retroalimentación de información desviada por ese sesgo y que provoca lo que se denomina Pensamiento de Grupo (“group-thinking”).
Objective analysis of information
Hence the insistence on "thinking outside the box" or "out of the box"and thus try to reduce the tunnel vision produced by being too close to the object of analysis.
And this distorting effect can also occur in relation to the numbers, and their interpretation if a certain result is sought. The expression "the numbers are there" as definitive to settle any discrepancy, is not true if the interpretation in relation to what they reflect is made by people with an interest in a particular result (even if it is, as I said before, unconsciously) or simply because they do not dare to express an opinion contrary to the majority.
The best way to avoid this groupthink and unconscious bias is to objectively analyze one's own information by comparing it with that available from the environment not only in similar situations (although there will never be certainty of similarity unless both organizations are simultaneously involved at the same level, which is difficult or impossible), but also in very different situations. In this way it is possible to analyze the consistency of the numbers/data, and to perform different analyses with very different scenarios.
The combination of these multiple analyses in various scenarios with the objective identification of trends in each sector, market, country, continent, and even any parameter of the type you want, is what leads to predictability. That is not having a crystal ball or magic but the product of a science, data science, and helps us to break the limitation that unconscious biases imply, and allows us to make decisions based on real information, not on mere intuitions or opinions.