Prescriptive analytics definition 

Technology Dictionary

Datapedia

Your essential glossary of Big Data
and Artificial Intelligence terms.

What are prescriptive analytics?

This is known as the “final frontier of analytical capabilities” because it is analytics that tries to influence the future. Predictive analytics specify which actions we should learn in order to achieve certain objectives. Prescriptive analytics also does this, but also adds the interrelated effects of each option.

It seeks answers to the question “What should the business do?”

Its complexity means that, despite the value that it can offer to businesses, this type of analytics isn’t commonly used. According to Gartner, only 3% of organizations use it.

OBJECTIVE:

Predictive analytics doesn’t just anticipate what will happen and when, but it can also tell us why. Further still, it can suggest which decisions we should make in order to make the most of a future business opportunity, or mitigate a possible risk, showing the implications of each options.

IT IS BASED UPON:

It is based upon absorbing hybrid data; structured (numbers, categories) and unstructured (videos, images, sounds and text) sources. This data can come from sources internal to the company, or external (such as social networks). Statistical models are applied to this data, including those based on machine learning and natural language processing. Rules, laws, best practices and business regulations are also applied. These models can continue to collect data in order to move forward with predictions and prescriptions. Therefore, predictions become more accurate and the analytics can prescribe better decisions to the business.

EXAMPLES:

Predictive analytics software is used in decision-making processes related to discovering and producing oil and natural gas. It captures a large amount of data, creates models and images of the Earth’s structure and describes the various characteristics of the process (machinery performance, crude oil flow, reservoir temperatures, pressure etc). These techniques are used to decide where and when to drill and therefore build wells that minimize costs and reduce the company’s environmental footprint.

APPLICATION:

As well as the oil industry, prescriptive analytics is used by:

  • Health service providers:
    • In order to effectively plan future investments in equipment and infrastructure, by basing plans on economic, demographic and public health data.
    • To obtain better results in patient satisfaction surveys and to avoid patient churn.
    • To identify the most appropriate intervention models according to specific population groups.
  • Pharmaceutical companies:
    • In order to find the most appropriate patients for a clinical trial.