Tom Hunt | 14 April 2017
It’s not enough to just have access to a lot of data — it has to generate useful insights that tell you the what, the when and the why.
‘Data analytics’ is a term that covers a wide range of activities. Businesses can use their data to look at what has happened, why it happened and, ideally, make predictions of what might happen in the future.
Prescriptive analytics takes analysis of data a step further. This type of analysis not only anticipates what will happen and when it will happen. It also tells you why it will happen.
In a nutshell, prescriptive analytics helps businesses translate their forecasts, predictions and business information into feasible, actionable plans.
This is because it suggests options for taking advantage of a future opportunity (or mitigate a future risk) and shows the implications of each decision. Prescriptive analytics can also continually take in new data to re-predict and re-prescribe forecasts, automatically improving accuracy.
In essence, prescriptive analytics helps you make the right decision for the future. For example, a retailer may want to choose the ideal sales promotion that will appeal to the right customers at the right time. It can use prescriptive analytics to evaluate its options and get a clear understanding of how customers are likely to react to different offers and promotions.
Businesses can also use ‘what if’ simulations and models to optimise their decisions, evaluating a range of actions and their likely outcomes. As with all data science, it’s about using the information at hand to make better business decisions.
At Jarmany we regularly help our clients use prescriptive analytics to make better decisions that drive sales. Get in touch to find out more.