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Descriptive, predictive and prescriptive analytics


The fact that companies are already analysing their own database to guide strategic decisions is a reality nowadays. Truly, it is more prevalent in large companies, but as Thiermann (2015) stated, this habit has begun to spread among small (18%) and medium enterprises (57%), principally due to three reasons:

Until very recently, the analytic was purely descriptive. It was analyzed based on historical company data, and tried to draw statistical conclusions from past actions that could defend a particular strategic decision with a high degree of confidence. However, in recent years, thanks to the work of technicians, statisticians and mathematicians, new models of analytics have been developed. This new models, based on statistical algorithms and mathematical rules, do not only analyze the historical enterprise, but they seek to predict future hypothetical scenarios, and have the ability to modify different indicators and analyze their direct impact on major decisions to make the right decision.
There is always been doubts about the differences between predictive and prescriptive analytics, and Lafuente (2013) posits this clear distinction between both of them:

Predictive and prescriptive analytics, and BI tools mostly seek to facilitate their own use to small businesses with some limitations (not so specialized, regardless of the specific knowledge of their employees, their budget, or any department which wants to use them).
At the end, your company objective has to be the fact of not needing technical profiles to incorporate Business Intelligence in your company, but to make it accessible to all your employees.



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