As the history of big data shows, we try to understand how the business or the world around us behaves by analyzing the available data. Any business have long been involved in the analysis on how they performed over time.
While in the past, this used to be merely descriptive analytics to answers the question “what happened in the past with the business?”
Now, with the availability of big-data we entered the new era of predictive analytics, which focuses on answering the question: “what is probably going to happen in the future?”
However, the real advantage of analytics comes with the final stage of analytics: prescriptive analytics. This type of analytics tries to answer the question: “Now what?” It tries to give a recommendation for key decisions based on future outcomes. What is the difference between these three “Descriptive, Predictive, and Prescriptive” and how do they affect your business?

Descriptive Analytics is About the Past
Descriptive analytics helps companies understand what happened in the past. The past in this context can be from one minute ago to a few years back.
Descriptive analytics help to understand the relationship between customers and products and the objective is to gain an understanding of what approach to take in the future: learn from past behaviour to influence future outcomes.
Netflix, for example, uses descriptive analytics to find correlations among different movies that subscribers rent and to improve their recommendation engine they used historic sales and customer data.
Predictive Analytics is About the Future
Predictive analytics provides companies with actionable insights based on data. It provides an estimation regarding the likelihood of a future outcome. To do this, a variety of techniques are used, such as machine learning, data mining, modelling and game theory. Predictive analytics can, for example, help to identify any risks or opportunities in the future. From predicting customer behaviour in sales and marketing, to forecasting demand for operations or determining risk profiles for finance. As example of predictive analytics is forecasting the demand for a certain region or customer segment and adjusting production based on the forecast.
Prescriptive Analytics Provides Advice Based on Predictions
Prescriptive analytics is the final stage in understanding your business, Prescriptive analytics not only foresees what will happen and when it will happen but also why it will happen and provides recommendations on how to act upon it to take advantage of the predictions.
It uses a combination of many different techniques and tools such as mathematical sciences, business rule algorithms, machine learning and computational modelling techniques.
Prescriptive analytics could affect any industry and any business and help them become more effective and efficient.
For example, prescriptive analytics can optimize your scheduling, production, and inventory to deliver the right products in the right amount in the most optimized way for the right customers on time.
Keep in mind, these three types of analytics should co-exist. One is not better than the other, they are just different in nature, but all of them are necessary to obtain a complete overview of your business. In fact, all of them contribute to the objective of improving decision-making.
With descriptive, predictive and prescriptive analytics understanding, your business will become easier, effective and better-informed for decisions that can be made taking into account future outcomes.