Predictive vs. Prescriptive Analytics: What’s the Difference?

Any business analytics degree program’s main goal is to get students ready for the complicated, multifaceted, and global business environment. The program develops students’ capacity to synthesize vast amounts of data from internal, external, and third-party sources into insight that can be used to enhance corporate operations. Two of the four analytics specialties in the analytics portfolio—descriptive and diagnostic—give firms knowledge of past occurrences and their causes.

Predictive and prescriptive analytics are the other two disciplines that makeup analytics. Both provide knowledge and even foresight to help with business decisions. To provide MBA executives and MBA graduate students with strategic tools and an in-depth understanding of customers and overall operations, predictive and prescriptive analytics both include statistical modeling, machine learning, and data mining.

In addition to their commonalities, predictive and prescriptive analytics vary from one another, and analytics professionals should be aware of these variances to apply them effectively and efficiently.

Predictive analytics: What Is It?

Predictive analytics may entice one to see them as a method of informing people what the future holds. Of course, it doesn’t have the such capability; no analytics approach does. What it does provide is a way to employ modeling and statistical methods to create well-considered forecasts about future business outcomes.

Decision analysis and optimization, transactional profiling, and predictive modeling are the three pillars of predictive analytics. To find dangers and opportunities, predictive analytics uses patterns in transactional and historical data. Although it cannot ensure success, it could increase the likelihood of success.

Predictive Analytics Examples

Predictive analytics may provide deeper insights into consumer behavior and other comparable indicators than BI since it uses decision analytics and optimization, transactional processing, and predictive modeling. This is seen in the retail industry, particularly when it comes to consumer behavior. While BI can reveal which ZIP codes make up a company’s most valued clients, predictive analytics and its pillars can provide information on the potential income such customers may produce.

There are several non-retail applications for predictive analytics. Predictive analytics models are used by Netflix, for instance, to filter user experiences and even create new program ideas. Predictive analytics may be used to the health care industry to create proactive wellness and health plans that can cut down on ER visits and expenditures.

What Is Prescriptive Analytics?

Emerging as a more sophisticated use of predictive analytics is prescriptive analytics. Prescriptive analytics does more than just anticipate possible outcomes using a predictive model. In fact, it makes a number of recommendations along with possible results for each action.

A firm may finally develop a more unified business plan with the use of a prescriptive model. By putting forth tactical applications based on anticipated behaviours, it expands on the information obtained from a predictive analytical model.

Prescriptive Analytics Examples

A great example of prescriptive analytics in action is Waymo, the self-driving vehicle that was first developed as Google’s self-driving car project in 2009. Every journey, the vehicle does millions of computations that assist it in making judgments similar to those made by a human driver behind the wheel, such as when and where to turn, whether to speed up or slow down, and when to change lanes.

Another great illustration of the effectiveness of prescriptive analytics comes from the energy industry. In order to negotiate the best terms and manage risks, utility companies, gas producers, and pipeline businesses utilise prescriptive analytics to pinpoint variables influencing the price of oil and gas. Prescriptive analytics are also being used by these businesses to increase operational security and lessen the risk of environmental catastrophes.

Build Your Future in Business Analytics

The disciplines of predictive and prescriptive analytics are interdependent and raise the bar for corporate intelligence. Business executives and leaders may acquire insight and foresight by using both types of analysis.

You may use these types of analytics in ways that have a significant influence on the company by enrolling in Ohio University’s online master in business administration program with a specialization in business analytics. In order to develop successful business strategies and make better business choices, the curriculum is structured to provide you with the advanced knowledge and skills necessary.

Find out how we can assist in getting you ready to start a successful career.