When sick-leave days spike 62% in one department, your leadership wants answers—not guesses. You'll learn why absenteeism spikes are symptoms that require systematic diagnosis, not single-cause explanations. Using fishbone diagrams in Miro, you'll classify potential causes into categories (People, Process, Policy, Environment, Tools, Management) that prevent tunnel vision and reveal hidden drivers. You'll use ChatGPT to help draft a 150-word reflection explaining why this methodology works—then verify the AI's output matches your actual analysis before sharing with stakeholders. Through realistic role plays where you diagnose a colleague's absenteeism mystery and present your findings to leadership, you'll practice the systematic problem-solving that turns HR data into actionable insights. Designed for HR professionals, people analytics practitioners, and anyone who needs to explain workforce problems without guessing. No analytics background required; access to free Miro and ChatGPT recommended.
What you'll learn
understand the principles of root-cause analysis in HR contexts
apply fishbone diagrams to categorize potential causes of absenteeism
utilize ChatGPT for drafting analytical reflections
practice diagnosing workforce problems and presenting findings
Course objectives
equip HR professionals with systematic problem-solving skills
develop data-driven approaches to understanding workforce issues