Prescriptive Analytics – What’s a manager to do?


Course Description


Prescriptive analytics differs from descriptive and predictive analytics in that prescriptive models yield a course of action to follow. That is, the output from a prescriptive model is a plan for management to follow. Applications in business including production planning, location analysis, supply chain design, transportation, marketing/product design and financial portfolio analysis will be discussed. This module will include hands-on experience using open-source software (Open Solver) in Microsoft Excel, R for Optimization, and AMPL – algebraic modeling system.


What You’ll Learn 

In this one-day program, we will discuss prescriptive analytics including rule-based systems, heuristics and optimization, with an emphasis on optimization modeling of real business problems.

Key program takeaways include:

  • Introduce analytics techniques in the context of real-world applications
  • Improve your ability to view business processes and relationships systematically and analytically.
  • Techniques for using data to generate new ideas, experimenting with solutions, and evaluating alternatives
  • Optimization with Linear & Discrete Models
  • Business Applications of Linear Models with Open Solver, R for Optimization, and AMPL – algebraic modeling system.


Who Should Attend?


This program is designed for analysts who want to learn more about predictive, descriptive, and prescriptive analytics and how making decisions with data can be enhanced through optimization models.  This module is highly relevant for anyone seeking advanced knowledge in optimization modeling.

This course assumes prior knowledge of algebraic notation and Excel.


Course Agenda


7:45 – 8:15 Continental Breakfast
8:15 – 9:30 Introductions and agenda
What makes decision making difficult?
Analytics: Descriptive, Predictive and Prescriptive
Rule-Based Systems
9:30 – 10:15 Optimization: Business Applications of Linear Models
10:15 – 10:30 Break
10:30 – 11:30 Optimization Software
Excel Solver/ Open Solver
R for Optimization
AMPL – algebraic modeling system
11:30 – 12:00 Application of learnings to individual business challenges brought by participants
12:00 – 12:30


12:30 – 1:30 Hands-on Case Study: Linear Model
1:30 – 2:30 Optimization: Business Applications of Discrete Models
2:30 – 2:45


2:45 – 3:15

Hands-on Case Study: Discrete Model

3:15 – 4:00

Optimization: Business Applications of Nonlinear Models

4:00 – 4:45

Application of learnings to individual business challenges brought by participants

4:45 – 5:00






Jeffrey D. CammJeffrey D. Camm
Associate Dean of Business Analytics
Inmar Presidential Chair of Analytics
Wake Forest University School of Business

Jeffrey Camm is Associate Dean of Business Analytics and the Inmar Presidential Chair in Business Analytics at the Wake Forest University School of Business. His scholarship is on the application of optimization modeling to difficult decision problems in a diverse set of application areas including, operations planning and scheduling, supply chain optimization, product design, and conservation. His research has been featured in Business Week/Financial Times-ranked academic journals such as Management Science and Operations Research as well the renowned journal Science. He is coauthor of seven texts on business statistics, management science, and business analytics.


Jeff received his PhD in Management Science from Clemson University and a BS in Mathematics from Xavier University. He previously held the Joseph S. Stern Chair in Business Analytics in the Lindner College of Business at the University of Cincinnati, where he served as department head for twenty years, was awarded the life-time appointment as a Fellow of the Graduate School, and was the founding director of the UC Center for Business Analytics. He has also held positions of visiting professor of business administration at the Tuck school of Business at Dartmouth College and visiting scholar at Stanford University. He has consulted for numerous corporations including Procter and Gamble, Owens Corning, GE, Tyco, Ace Hardware, Boar’s Head, Brooks Running Shoes and Kroger among others. His work with Procter & Gamble is credited with saving P&G over $250M in their North American supply chain and was a finalist for the prestigious Edelman Award.


Program Dates


June 13, 2019

Program begins promptly at 8:30 and will wrap-up no later than 5:00.


Meeting Location


Wake Forest Innovation Quarter
Biotech Place
575 N. Patterson Ave.
Winston-Salem, NC 27101

Location and Parking




The cost of the program is $825 and includes materials, continental breakfast and lunch, and is due in full at time of registration.  Additionally, Wake Forest University alumni and faculty receive a 25% tuition discount. For more information please send an email to  or call 336-758-2239.


Program Materials


Course materials are included in the cost of tuition. Course materials will be distributed electronically in advance of the program start date. Participants must have a laptop or tablet computer to access course materials.

Registration and Payment


This is an open enrollment program. Application is not required. Course registration is complete when payment is processed. Upon registration, a representative of Wake Forest will contact you to validate the registration information and to assist in fee payment. Please click the link below to begin the registration process.


Register Now



Cancellation of Program


This course is offered contingent upon sufficient enrollment. If a course must be cancelled, all registered participants will be notified at least five (5) calendar days before the course’s start date. All registered participants will receive a 100% tuition refund. No fees will be charged for cancelled courses.


Refund Policy


Prospective participants who withdraw at least 15 days prior to the start of a course will receive a full refund of tuition paid.


For More Information


For more information or to speak with a program adviser, please send an email to  or call 336-758-2239.