Predictive Analytics vs. Prescriptive Analytics | Jeremy Robertson

Abstract ideologies such as those based on what happened in the past or are speculatively happening are insufficient data that cannot support decision-making in a business. To overcome these limitations, business persons should integrate predictive and prescriptive analytics. Predictive analytics is a statistical and modeling strategy used to determine futuristic events. On the other hand, prescriptive analytics identifies what is likely to happen and recommends the best business options to employ. This technique creates a model and validates it against the present and past events to establish the best criteria to be followed.

Prescriptive and predictive analytics are essential in running a business; however, according to Gartner’s analytics, prescriptive analytics is superior to predictive analytics. This said the latter does not offer guidance on what to do with the data obtained. Predictive analytics is best suited when carrying out forecasts, modeling specific aspects of a business, optimizing one function at the expense of another, and situations where outputs are non-actionable. In addition to prescriptive analytics models, the entire enterprise provides foundational measurable advantages, recommends specific guidance, and accounts for inputs, results, and variables.

These two techniques are not meant to work separately or in isolation; there is space for each in an organization. Predictive analysis is used for short-to-medium-term challenges such as short-term insurance risk analysis, profitability issues, customer churn, etc. In comparison, prescriptive analytics caters to the bigger picture by establishing optimal manufacturing strategies for producing companies, optimizing opportunities to increase profitability, meeting customer requirements, etc.

While both techniques have tangible advantages, prescriptive analytics offers more superior results. Predictive analytics tend to be more rewarding for short-term risk analysis promising huge returns by limiting risk. Prescriptive analytics provides the same magnitude of returns but over a more extended period. Prescriptive analytics is more expensive but guarantees an increased annual revenue.

The critical difference between predictive and prescriptive techniques is that the former provides short-term outlooks with necessarily no measure of cost and no metric in profitability. The latter offers a calibrated tangible information taking into account all inputs, processes, and outputs to maximize profits and minimize cost.

Several businesspersons have seen the importance of incorporating both of these analytics tools. As predictive analytics identifies the challenges, prescriptive analytics ascertains the best way to counter them. These techniques achieve individual needs catering to both reactive and proactive requirements.

Article originally published on JeremyRobertsonPredictiveAnalytics.com