The purpose of any analytics degree program in business is to prepare students for an ever-changing, complex, global business world. The curriculum nurtures students’ ability to combine the troves of internally sourced, public, and other third-party sourced data into actionable insight to improve business operations. Of the four analytics disciplines in the analytics portfolio, two — descriptive and diagnostic — provide businesses with insight into events that happened and why they occurred.
The other two analytics disciplines, predictive and prescriptive, are a step up the analytics ladder. Both give insight, and even foresight, to support business decision-making. Both predictive and prescriptive analytics incorporate statistical modeling, machine learning, and data mining to give MBA executives and MBA graduate students strategic tools and deep insight into customers and overall operations.
In addition to their similarities, it is important for analytics professionals to know the differences between predictive vs. prescriptive analytics to use both effectively and efficiently.
What Is Predictive Analytics?
It may be tempting to think of predictive analytics as a fortune-telling strategy that tells people what the future holds. It does not have that capacity, of course — no analytics method does. What it does offer is a means to use statistics and modeling techniques to make intelligently calculated predictions about future business outcomes.
The three keystones of predictive analytics are decision analysis and optimization, transactional profiling, and predictive modeling. Predictive analytics exploits patterns in transactional and historical data to identify risks and opportunities. It doesn’t guarantee positive results, but it may help make positive results more likely.
Predictive Analytics Examples
Predictive analytics’ use of decision analytics and optimization, transactional processing, and predictive modeling can provide more in-depth information about customer behavior and other similar metrics that BI cannot. An example of this can be found in the retail sector, specifically when it comes to customer behavior. While BI can inform what ZIP code a company’s most valuable customers come from, predictive analytics and its keystones can provide data that informs about how much revenue those customers can generate.
Predictive analytics can be applied in a wealth of non-retail scenarios as well. Netflix, for instance, uses predictive analytics models to curate user experiences and even develop new show concepts. In the health care sector, predictive analytics can be used to build proactive health and wellness strategies that can reduce ER visits and lower costs.
What Is Prescriptive Analytics?
Prescriptive analytics is an emerging discipline that represents a more advanced use of predictive analytics. Prescriptive analytics goes beyond simply predicting options in the predictive model. It actually suggests a range of prescribed actions and the potential outcomes of each action.
A prescriptive model can ultimately help a business create a more cohesive business strategy. It builds upon the findings gathered from a predictive analytical model by proposing strategic applications based on predicted behaviors.
Prescriptive Analytics Examples
Waymo, the autonomous car that started off as Google’s self-driving car project in 2009, is a prime example of prescriptive analytics in action. The vehicle makes millions of calculations on every trip that helps the car decide when and where to turn, whether to slow down or speed up, and when to change lanes — the same decisions a human driver makes behind the wheel.
The energy sector also provides an excellent example of the power of prescriptive analytics. Utility companies, gas producers, and pipeline companies use prescriptive analytics to identify factors affecting the price of oil and gas to secure the best terms and hedge risks. These companies are also using prescriptive analytics to improve operational safety and minimize the threat of potential environmental disasters from occurring.
Build Your Future in Business Analytics
Predictive and prescriptive analytics are co-dependent disciplines that take business intelligence to unprecedented levels. With both forms of analysis, business executives and leaders gain both insight and foresight.
Ohio University’s Online Master of Business Administration program and its business analytics concentration can help you apply these forms of analytics in ways that can make a profound impact in business. The curriculum is designed to equip you with the advanced knowledge and skills to glean actionable insight from data so effective business strategies can be created, and better business decisions can be made.
Learn how we can help prepare you to embark on a successful career.
Markets and Markets, Business Intelligence Market by Component (Solutions and Services), Solution (Dashboards and Scorecards, Data Integration and ETL), Business Function (Finance, Operation), Industry Vertical (BFSI, Telecom and IT), and Region — Global Forecast to 2025