Question

IN 200 WORDS OR MORE

Discuss the differences between descriptive analytics and predictive analytics. Give an example of when you may use each type

Answer 1

Descriptive Analytics: It describe 'what' happened in past. These are generally pre-canned reports, dashboards and MIS, operational reports etc. E.g. Profit per store, per region. Sales through various channels.

Predictive Analytics- It determines what might happen in 'future'. This needs larger data set expertise and tool set. e.g. : Which channels are likely to perform better in next quarter based on past data.

Descriptive Analytics describe what happened in the past.

Predictive Analytics (attempt to) describe what will happen in the future.

Descriptive Analytics risk less from over-fit as they are describing what actually happened.

Predictive Analytics risk more from over-fit as what happened, exactly, in the past under certain conditions may not happen in exactly the same way in the future as the model may not have included features that change the outcome in very material ways.

Descriptive is to Predictive as Accounting is to Economics. Seriously though, the main difference is that Predictive is centered around statistical models allowing prediction of future outcomes and is concerned about confidence in such predictions. While Descriptive is centered around data presentation, slicing&dicing, management oversight. You might say that Descriptive is to tell what is, while Predictive is to answer what if.

Descriptive Analytics: It is like laying the corpse in the mortuary bed. We just neatly dress the corpse , cover it with white blanket, ready it for postmortem.

Predictive Analytics: After many postmortems the doctor gets a pattern and concludes that excessive alcohol caused liver cirrhosis and that in turn caused death. So based on this we can predict weather the subject will get Liver Cirrhosis and die, based on the subject’s current lifestyle.

Descriptive analytics allows a reactive approach, while predictive analytics – proactive.

The best example to explain descriptive analytics are the results, that a business gets from the web server through Google Analytics tools. The outcomes help understand what actually happened in the past and validate if a promotional campaign was successful or not based on basic parameters like page views.

Prescriptive analytics if implemented properly can have a major impact on business growth. Large scale organizations use prescriptive analytics for scheduling the inventory in the supply chain, optimizing production, etc. to optimize customer experience.