Program Overview

Certificate in Business Analytics for Decision Makers

Predictive business analytics is a quickly growing field, but many companies struggle trying to tap into the power of available data without being overwhelmed by it. This program is geared to decision makers and leaders who need to understand the strategic value that business analytics can bring to an organization. Students will learn what analytics is and what it can and can’t do; how to build the skills to implement it; how to integrate it into other strategic processes; how to gather data across multiple sources including supply chains, POS systems, customer interactions, and market research activities; and how to make strategic decisions based on results of analysis.

This course will be offered in Spring 2018. Registration will open in February.


Program Goals

Students will learn to:

  • Describe the uses of analytics to drive business success
  • Create roadmaps to get their organization on an analytics track
  • Identify what is needed to build an analytics team
  • Develop an action plan to implement analytics at an organizational level
  • Use the intelligence generated by a company-wide data focus to get results (customers, sales, etc.)

Program Audience

All those who want to institute a culture of analytics-based decision making in their organization will benefit from the Business Analytics for Decision Makers certificate program, from small business owners to directors of units within large organizations to corporate leaders. These leaders may come from any industry, and the skills and knowledge acquired can be applied to areas as diverse as marketing, supply chain management, product development, customer service, and more. As a result of this program, students will better understand how to use analytics to make strategic decisions that promote profitability and success. 

Program Structure

The three-day seminar will be held on Northwestern's Chicago campus at Wieboldt Hall, 339 East Chicago Avenue. The seminar will be led by industry leaders with experience in developing analytic teams for major corporations. Class sessions will include lectures, the review of case studies, small group work and one-on-one consultations with the instructors. At the end of the program, students will know how analytics can be implemented in their company or organization.


The Potential of Big Data and Predictive Analytics

  • What do we mean by analytics and why is it important? 
  • What is “big data” and does it have to be big to be useful?
  • Develop an understanding of historical  vs current state vs forward looking analytics
  • Real-time usage and how it effects the enterprise
  • Harvesting the low hanging fruit of data already in the company’s systems
  • Using analytics methodologies to make better decisions
  • Using the intelligence generated by a company-wide data based decision making focus to get results (customers, sales, etc.)
  • Preparing for day two:
    • Finding the areas where analytics can be a difference maker for your business


Leadership in the Age of Big Data

  • Recognizing and overcoming limits in modeling and analytics and enhancing collaboration beyond the organization
  • Techniques used in analytic organizations:
  • Scenario planning to challenge assumptions, add context and enrich definition of questions;  
  • Mindmapping  to highlight evolving interrelationships and capture disparate views; and
  • Roadmapping to define roles, identify obstacles and lay out steps incorporating analytic results into action
  • Expectations of big data and analytics, Stakeholder/ecosystem analysis — challenges in data sharing and communication
  • Addressing gaps in common standards  critical to collaboration, data collection and analysis; defining types of standards and issues
  • Transition to day three:
    • What issues do you have in your organization today and how can we address them? (participants will apply tools to their own organizations)


Planning for and Deploying an Analytics Organization and Infrastructure

  • Building an analytic enterprise
    • People needs
    • Technology needs
    • Process and policy needs
    • Expressing support for analytics from the top down
  • Best practices for communicating the results of your analytics analyses
  • Case Studies
    • Examples of how predictive analytics are being used everyday 
  • Develop an action plan to take back to the office
    • What questions can I answer now?
    • What questions do I want to answer but can’t?
    • How do I move toward answering the questions I can’t?
    • What steps do I need to be taking to get where I want to go?
    • How can I measure progress and value?


Jeffrey Strauss

At Northwestern University for 30 years, Mr. Strauss is acting director of the Center for Technology and Innovation Management (CTIM — within the University-wide Buffet Institute for Global Studies) where he develops programs to raise attention in managers, faculty and students in multiple disciplines to underlying strategic issues not yet fully on their view screens – but which should be, and to the application of mapping and analytic tools. He is also very active in technical standards education and serves on multiple related committees.

Bryan Bennett

Mr. Bennett has more than 20 years of experience developing and implementing advanced analytical solutions for Fortune 500 companies across multiple industries. These industries include: financial services, insurance, telecommunications and healthcare. His clients have included Microsoft, State Farm Insurance, Pharmacia and Chase Bank. He is published author and a national speaker on the subjects of healthcare transformation, healthcare predictive analytics and customer behavior.

John Derwent

John Derwent is an experienced learning professional with an analytical bent and is currently managing content development for Analytics University with The Boston Consulting Group as well as being adjunct faculty and program advisor for the Certificate in Predictive Business Analytics program and adjunct faculty with the Master of Science in Predictive Analytics program at Northwestern University. After completing his graduate work, he moved into the world of corporate education and development practicing mainly in the software and technology industries. Most recently, Derwent led content and offering strategy for education services in the business analytics area with SPSS, Inc. and IBM. His main professional goal is to help people understand how mathematics can improve businesses and the world. Derwent earned his MS and PhD in Applied Mathematics from Northwestern University. 

Please note that this Certificate in Business Analytics for Decision Makers is a non-credit offering. Non-credit courses do not transfer into a degree program of any kind at Northwestern University. If you are a degree seeking student, please learn more about our Master of Science in Predictive Analytics program.

Core Courses:

  • BUS_DM 501-0 Analytics for Decision Makers