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 2-day seminar, you will learn both the theoretical as well as practical applications of data analytics and how they apply to decision-making. You will deepen your understanding of descriptive, predictive and prescriptive analytics. Next, you will 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 that allows you to make sense of data and how to make decisions using it.
Key Benefits & Takeaways
- Think critically about data
- Differentiate between good and bad data
- Avoiding data collection biases
- When to use 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 analytics themselves.
The registration fee includes facilitation by our highly-rated faculty members, a comprehensive workbook, results-oriented exercises, seminar supplies, meal service (breakfast, lunch and breaks) and a certificate of completion from the McGill Executive Institute.
Topics covered during the program
- What is the role of data in decision making
- Discuss different frameworks to support decision-making in organizations
- Understand the perceived value of data
- 4 V’s of data: volume, velocity, variety and veracity
What is good data and how do you structure it
- Forecasting the future based on past trends
- Mining data to predict customer demand and preferences
- Assessing the quality of predictions
- Understand how to leverage data that has already been collected
- Find the best course of action for a given situation
Prescriptive Analytics
CPD Hours
This program has been approved for 13 CPD hours under Section A of the Continuing Professional Development (CPD) Log of the Human Resource Professionals Association (HRPA).
Programs to Consider
Upcoming Sessions
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Location
6th floor
Montreal, QC H3A 1G5
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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 behavior and outcomes in two main domains: music and dating, two industries that have been transformed significantly by information technology.