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Decision Modeling in Business Analytics

Decision Modeling in Business Analytics

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NYU Stern School of Business
44 West 4th Street
New York, NY 10012

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Decision Modeling in Business Analytics


PLEASE NOTE: This program is currently being taught as an In Person class.

Most firms invest time and dollars into data analytics that identify what has already happened and what might happen in the future, but this is not enough to drive success. In order to take full advantage of their data analytics, executives must know how to transform data insights into optimal, executable actions that are evaluated by their impact on key performance metrics, leading to better decision making.

This course teaches participants to harness the full potential of large quantities of data to make more informed decisions at all levels of their organizations. Participants will learn about modern decision models and machine learning tools. Through application of these tools, executives will examine data, recommend a range of actions and evaluate each action’s impact on targeted performance metrics. This course provides hands-on experience working with different models--including optimization modeling, uncertainty modeling and risk prediction--and emphasizes their application in finance, marketing and operations functions across industries.

Certificates and Credits

Upon completion of this course, participants will receive a Certificate of Achievement.

Program Takeaways

During this course, participants will:

  • Decision Models

    Learn about key decision models in analytics and their applications across a wide range of industries including healthcare, financial services, logistics and more
  • Direct Experience

    Gain hands-on experience working with data and transforming it into actionable decisions through simulation exercises
  • Value of Data

    Identify opportunities where decision models can be applied to derive value for your organization

Who Should Attend

Although there are no formal education or background requirements, this course is designed for executives who meet the criteria below. While we strongly encourage global participation, please note that all courses are taught in English. Proficiency in written and spoken English is required.

  • Years of Experience

    Designed for professionals with 5+ years of work experience
  • Job Functions

    Ideal for executives who head analytically oriented functions within their organization
  • Prerequisites

    Intended for individuals who are interested in analytics and data-driven decision making, and who already have working knowledge of analytics


The following agenda is a sample and subject to change.

9:00 am ET: Session 1: Predictive and Prescriptive Analytics

  • What is prescriptive analytics and why is it important?
  • Differences between prescriptive and predictive analytics and their roles in data-driven decision making
  • Best practices and success stories

Session 2: Machine Learning and Predictive Modeling

  • Basic classification and prediction methods
  • What is artificial neutral network and what is deep learning
  • Hands-on exercise: credit risk prediction 

12:15 - 1:15 pm ET: Lunch Break

Session 3: Framework of Optimization Modeling

  • Formulating a business decision problem: decision choices, performance measure, and constraints
  • Hands-on exercise: online dating platform

Session 4: Business Applications of Optimization Models

  • Applications in revenue management and online advertising
  • Value of optimization
  • Challenge and address model assumptions

4:30 pm ET: Day 1 Conclusion and Evaluations

    9:00 am ET: Session 5: Markdown Optimization Game

    • Combining predictive modeling and optimization modeling
    • Challenges in decision making under risk

    Session 6: Modeling Risk

    • Meaningful definition of risk
    • How to model uncertainty
    • Value of data in risk modeling

      12:15 - 1:15 pm ET: Lunch Break

      Session 7: Risk Prediction: Monte Carlo Simulation

      • Build simulation models for performance evaluation and risk prediction
      • Interpretation of results and obtaining insights
      • Hands-on exercise: retirement planning

      Session 8: Optimization under Uncertainty

      • Simulation meets optimization modeling
      • Value of strategic flexibility

      4:30 pm ET: Program Conclusion and Evaluations

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