What is prescriptive analytics?

Prescriptive analytics focuses on finding the best course of action in a scenario, given the available data. It’s related to both descriptive analytics and predictive analytics, but emphasizes actionable insights instead of data monitoring.

Descriptive analytics offers BI insights into what has happened, and predictive analytics focuses on forecasting possible outcomes, prescriptive analytics aims to find the best solution given a variety of choices. Additionally, the field also empowers companies to make decisions based on optimizing the result of future events or risks, and provides a model to study them.

See how AI turns data into action:

Read the paper

Prescriptive analytics gathers data from a variety of both descriptive and predictive sources for its models and applies them to the process of decision-making. This includes combining existing conditions and considering the consequences of each decision to determine how the future would be impacted. Moreover, it can measure the repercussions of a decision based on different possible future scenarios.

The field borrows heavily from mathematics and computer science, using a variety of statistical methods. The process creates and re-creates possible decision patterns that could affect an organization in different ways. Prescriptive analytics is the final step of business analytics.

How can I use prescriptive analytics?

Most modern BI tools have built-in prescriptive analytics to provide users with actionable results that empower them to make better decisions. One of the more interesting applications of prescriptive analytics is in oil and gas management, where prices constantly fluctuate based on ever-changing political, environmental, and demand conditions.

See it in action:

For manufacturers, the ability to model prices on a variety of factors allows them to make better decisions about production, storage, and new discoveries. Furthermore, both prescriptive and predictive analytics is useful for managing equipment and maintenance in manufacturing, as well as making better decisions regarding drilling and exploration locations.

In healthcare business intelligence, prescriptive analytics is applied across the industry, both in patient care and healthcare administration. For practitioners and care providers, prescriptive analytics helps improve clinical care and provide more satisfactory service to patients.

Insurers use prescriptive analytics in their risk assessment models to provide pricing and premium information for clients. For pharmaceutical companies, prescriptive analytics helps identify the best testing and patient cohorts for clinical trials. This reduces the costs of testing to eventually help expedite drug development and possible approval.

See how AI turns data into action:

Read the paper
Back to Glossary