Learn the Difference Between Prescriptive Versus Predictive Analytics With an MBA Degree

Business analytics (BA) is the process of collecting, assessing and utilizing data to understand and improve business functions and capabilities. BA involves the use of statistical and quantitative analysis techniques to identify patterns, trends and insights that inform decision-making and drive organizational success. Many organizations leverage the four primary forms of analytics in every function to improve decision-making and business outcomes: descriptive, diagnostic, predictive and prescriptive.

Descriptive analytics summarizes raw data and performance metrics that provide an easy-to-understand overview of what is happening in a business. Diagnostic analytics compares coexisting variables and uncovers correlations. On the other hand, predictive and prescriptive analytics are more complex, taking descriptive and diagnostic data and transforming them into insights, predictions and actionable information.

Business professionals must have a firm understanding of these four forms of analytics. Radford University’s online Master of Business Administration (MBA) program equips graduates with rounded knowledge in the analytics space. This article delves into the similarities and differences between predictive and prescriptive analytics and how professionals can use each to make informed and effective decisions.

What Is Predictive Analytics?

Predictive analytics is a sophisticated type of analytics that enables forecasting future trends or events. It entails constructing statistical models to detect and interpret patterns and trends within extensive data sets. Predictive analytics applies current data, historical data and statistics to predict future scenarios, usually providing a timeframe and the level of certainty associated with the outcome. In short, it answers the question, “What may happen in the future?” Companies benefit from using predictive analytics to gain insight into potential outcomes and the consequences of their decisions.

A good example of predictive analytics is the analysis of customer behavior and purchasing patterns to identify customers at risk of churn. By utilizing data such as purchase history, engagement with marketing campaigns and customer service interactions, marketing professionals can develop predictive models that identify customers likely to leave and target them with personalized retention offers or interventions before they defect.

What Is Prescriptive Analytics?

Prescriptive analytics is advanced analytics that goes beyond predicting what might happen in the future to suggest possible actions to achieve the desired outcome. Instead, it looks at future scenarios using complicated mathematical algorithms, artificial intelligence, machine learning and business rules to look deeper into the “what” and “why” of a potential outcome. Prescriptive analytics can also help a company see multiple options and possible results.

As more data comes in, prescriptive analytics can alter its predictions and suggestions accordingly, identifying a range of actions an organization can take in response to a given predictive analytics forecast. It can then attempt to determine likely outcomes based on advised actions.

An example on a manufacturing job is the optimization of production scheduling to minimize downtime, maximize throughput and reduce costs. Using prescriptive analytics, a shop can analyze historical data, current capacity and customer demand to determine the best sequence of production runs, considering factors such as machine and material availability and delivery dates. By simulating different scenarios and evaluating the impact of various decisions, prescriptive analytics can recommend the optimal production schedule to meet customer demand and minimize production costs.

Understanding the Similarities and Differences

Just a few years back, predictive and prescriptive analytics were limited to large-scale enterprises, as they were the only organizations with the financial resources to collect, organize and analyze massive amounts of data from multiple sources. However, with the rise of software-as-a-service (SaaS) providers and CRM analytics, even midsize and small businesses can now access valuable BA tools and apply these complex forms of analytics. Both are commonly used in conjunction and share significant similarities, as Career Foundry outlines.


  • Both inform business strategies based on collected data.
  • Both often apply machine learning methods and systems.
  • Both can address a wide range of applications and problems.
  • Both are tools for turning descriptive and diagnostic analytics into insights and decisions.
  • A combination of both is needed to create the best possible outcomes.
  • Together, MicroStrategy reveals that the forms of BA lead to improved efficiency (64%), better financial performance (51%), identification of new revenue sources (46%), improved customer acquisition and retention (46%), improved customer experiences (44%) and competitive advantage (43%).


  • According to CareerFoundry, prescriptive analytics often involves optimizing complex business processes, such as production scheduling or resource allocation, while predictive analytics focuses more on identifying trends and patterns in data.
  • Predictive analytics predicts potential future outcomes based on historical data and statistical models, whereas prescriptive analytics provides specific recommendations to achieve desired results.
  • Prescriptive analytics is more complex and involves evaluating multiple possible actions and their impact on the outcome.

Develop Your Expertise in Business Analytics in the MBA Online Program

Radford University’s MBA online program equips students with proficiency and success in business analytics throughout the curriculum, mainly through the following courses:

  • Business Analytics Foundations covers BA, including exploratory and predictive models used to provide fact-based recommendations to optimize business decisions and outcomes.
  • Predictive Analytics and Data Mining explores the application of predictive analytics and data mining techniques to solve strategic business problems.
  • Prescriptive Analytics and Modeling enhances your ability to obtain actionable decisions in business employing mathematical modeling and simulation.

Learning business analytics allows you to make data-driven decisions and stay competitive in today’s business world. The Radford University online MBA program’s emphasis on BA ensures that graduates are ready to analyze data and derive insights that drive organizational success.

Learn more about Radford University’s online MBA program.

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