During the last years, several software have been proposing predictive analytics solutions in order to extract useful information from user data.
Let us make an example: if you have an e-commerce shop and you sell through Amazon or Ebay channels, you may have a lot of information about your activity: sales histories of your catalog, past revenues, customers behavior or your actual stock on hand.
Predictive analytics solutions are able to analyze those data in order to give you some insights, often insensitive. For example:
- how your business will evolve in next periods;
- customers A and B often buy same products;
- classical reporting activity.
On the contrary, they tell you nothing about new strategies able to increase your revenues (your company life aim).
Prescriptive analytics is the perfect candidate to fill that gap. In fact, useful insights given by the predictive analysis are simply inputs for the prescriptive block. Prescriptive tools are based on operations research and machine learning models and their goal is to give you new strategies for improving your business.
For example, let us continue with the same example of an Amazon or E-bay seller. Everyday you would like to know about next inventory replenishment points: when do you have to reorder a certain product? Moreover, what is the right quantity to be reordered for the coverage of the next months? Prescriptive tools are able to suggest you these strategies.
Furthermore, what about your inventory status? Are your products equal to each other? Probably, you need something that tells you about your inventory composition, in order to maximize your return of investment (ROI) taking into account products with better margins.
In conclusion, the prescriptive is a definitely necessary step due to their high capacity to transform numbers in right decisions.