Data-Informed Decision Making
Strengthen your ability to make business decisions supported by relevant evidence. This case-based course introduces the Problem–Data–Option–Decision framework, helping learners distinguish useful information from noise, compare alternatives and assess risks and trade-offs. Through group exercises based on departmental business cases, participants develop a Decision Brief and practise explaining and defending their recommendations.
Course at a Glance
| Description | Detail |
|---|---|
| Duration | 1 day · 6 hours |
| Format | Classroom · Case-based workshop |
| Prerequisites | Completion of Data Insight Discovery |
| Course Output | Decision Brief outlining the problem, evidence, options and recommendation |
Learning Objectives
By the end of the course, participants will be able to:
- Apply the Problem–Data–Option–Decision framework to a business case.
- Distinguish relevant evidence from information that does not support the decision.
- Compare options and assess their risks and trade-offs.
- Prepare a Decision Brief with a clear, evidence-supported recommendation.
- Present a recommendation and respond to questions that challenge its reasoning.
Course Outline
Module 1 — A Framework for Business Decisions
Explore the Problem–Data–Option–Decision framework and learn how to connect a business problem with evidence, alternatives and a recommendation.
Module 2 — Relevant Evidence vs Noise
Practise identifying information that matters to a decision using sample cases, and distinguish it from distracting or irrelevant data.
Module 3 — Business Case Workshop & Decision Brief
Work in groups to analyse a real departmental case, assess options and trade-offs, and draft a Decision Brief supported by evidence.
Module 4 — Decision Pitch & Peer Challenge
Present your recommendation and respond to challenges from peers and the instructor to test and strengthen your reasoning.
Who Should Attend
Professionals who use data to analyse departmental problems, compare options and recommend business actions.