Value Added Analytics

Introduction

Please note that this is a preliminary course description. The final version will be published in June 2027.

In today’s data-driven business environment, organizations increasingly rely on analytics not just to explore data but to deliver value. Many projects are initiated but never get into production where they can deliver value.

Value Added Analytics is a capstone course designed to bridge the gap between analytics theory and the practical implementation and evaluation of analytics projects, in order to increase the number of projects that get into production and deliver value. This course equips students with the critical tools, frameworks, and perspectives needed to assess the maturity of analytics capabilities, define project scope effectively, and guide organizations through the analytics lifecycle with a focus on value creation.

This course combines asynchronous modules and live webinars, along with industry engagement—featuring guest lecturers from commerce - to provide a comprehensive and applied learning experience.

Course content

1. Defining, Scoping and presenting a Business Problem (Asynchronous)
   • Framing business problems for analytics
   • Stakeholder identification and expectation management
   • Translating strategy into analytical questions
   • Presenting problems and solutions to relevant stakeholders
2. Evaluating an Analytics Project (Asynchronous)
   • Criteria for success in analytics projects
   • ROI, feasibility, and impact assessment frameworks
   • Case studies of evaluation success and failure
3. Analytics Maturity (Webinar & Guest Lectures)
   • Maturity models and diagnostic tools
   • Insights from the International Institute for Analytics (IIA)
   • Organizational capability building
4. Analytics Canvas (Webinar)
   • Structure and purpose of the canvas
   • Applying the canvas to real and hypothetical projects
   • Integration with business models and strategy
5. Analytics Lifecycle (Webinar)
   • End-to-end project phases from ideation to operationalization
   • Common pitfalls and best practices
   • Governance and continuous improvement