is the third and final phase of analytics (BA) which also includes descriptive and predictive analytics.
Referred to as the "final frontier of analytic capabilities," prescriptive analytics entails the application of mathematical and computational sciences suggests decision options to take advantage of the results of descriptive and predictive analytics. The first stage of business analytics
is descriptive analytics, which still accounts for the majority of all business analytics today. Descriptive analytics looks at past performance and understands that performance by mining
historical data to look for the reasons behind past success or failure. Most management reporting - such as sales, marketing, operations, and finance - uses this type of post-mortem
The next phase is predictive analytics. Predictive analytics answers the question what is likely to happen. This is when historical data is combined with rules, algorithms, and occasionally external data to determine the probable
future outcome of an event or the likelihood of a situation occurring. The final phase is prescriptive analytics, which goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the implications of each decision option.
Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen. Further, prescriptive analytics suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option. Prescriptive analytics can continually take in new data to re-predict and re-prescribe, thus automatically improving prediction accuracy
and prescribing better decision options. Prescriptive analytics ingests hybrid data, a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts), and business rules
to predict what lies ahead and to prescribe how to take advantage of this predicted future without compromising other priorities.
All three phases of analytics can be performed through professional services
or technology or a combination. In order to scale, prescriptive analytics technologies need to be adaptive to take into account the growing volume, velocity, and variety of data that most mission critical
processes and their environments may produce.
of prescriptive analytics is that its distinction from predictive analytics is ill-defined and therefore ill-conceived.