By utilizing data, machine learning, and various regression models, predictive analytics helps companies forecast demand, evaluate the effect of pricing strategies, anticipate customer purchasing decisions, and the like. In essence — and as the name suggests — predictive analytics helps organizations predict future outcomes.

Prescriptive analytics then goes one step further by using these predictive models along with decision rules and desired objective functions to make the best possible dynamic, automated decisions. Some examples include personalized advertising, online recommendation systems, surge pricing, promotional decisions, and stocking and fulfillment choices.

In this course, you will examine the foundational elements of prescriptive analytics, including how to use forecasts as input to build models for dynamic and automated decision making. You will then further analyze these concepts to ensure that these decisions align with and contribute positively to business goals and performance objectives.

The following courses are required to be completed before taking this course:

  • Designing Digital and Data-Driven Business Operations
  • Exploring the Fundamentals of Forecasting Demand
  • Designing Experiments in Retail and Online Businesses
 

How It Works

Course Length
2 weeks

Effort
5 to 8 hours of study per week

Format
100% online, instructor-led
  • Managers, leaders, and executives
  • Business analysts
  • Digital transformation managers
  • Consultants
  • Entrepreneurs
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