Analytics for Decision Making

Leveraging data for business value

Overview

The ability to use data to effectively drive decisions is an integral part of modern management. In this seminar, you will learn the theoretical and practical applications of data analytics and how they apply to decision making. You will deepen your understanding of descriptive, predictive, and prescriptive analytics. You will also learn how to use that data to develop insights through a series of exercises and case studies. Finally, participants will gain a deeper understanding of how to make data-driven business decisions within their organization. This course will enable you to be an informed and empowered manager of data. You will leave with a toolkit for making sense of data and using data to make decisions.

Key Benefits and Takeaways

  • Think critically about data
  • Differentiate between good and bad data
  • Avoid data collection biases
  • Apply descriptive, predictive or prescriptive analytics
  • Understand different applications of business analytics across industries and sectors
  • Identify opportunities for creating value using business analytics
  • Properly structure data for your organization

This seminar is for managers who want to effectively translate data analytics into business value, but do not necessarily have the technical expertise to do the analysis themselves.

The registration fee includes facilitation by our highly rated faculty members, course materials, results-oriented exercises, meal service (breakfast, lunch and breaks)*, and a certificate of completion from the McGill Executive Institute.

*Meal service is included for in-person programs only.

Topics covered in this course

  • Role of data in decision making
  • Discuss different frameworks to support decision making in organizations
  • Understand the perceived value of data
  • Four V’s of data – volume, velocity, variety, and veracity
  • Forecast the future based on past trends
  • Mine data to predict customer demand and preferences
  • Assess the quality of predictions
  • Understand how to leverage data that has already been collected
  • Find the best course of action for a given situation

Course Leaders

Jui Ramaprasad

×

Jui Ramaprasad

Jui Ramaprasad is a tenured faculty member of the Desautels Faculty of Management at McGill University. She obtained her doctorate in Management, Information Systems from the Paul Merage School of Business at the University of California, Irvine. She holds a B.S. from the University of Southern California. Her research examines the impact of IT-enabled social interactions on behaviour and outcomes in two main domains: music and dating, two industries that have been transformed significantly by information technology.