This eight-week self-study programme is designed for senior HR and People leaders who want structured, rigorous grounding in People Analytics, applied directly to real-world challenges.
Each module combines core conceptual frameworks, a curated reading list of freely accessible resources, and a hands-on practical exercise that produces a tangible, interview-ready artefact.
Developed by Lee C. Stonehouse FCIPD, architect of the People Risk Intelligence Framework (PRIF). The PRIF is referenced throughout as primary applied evidence, particularly in the Week 8 capstone.
Draw a stakeholder map for your current or most recent organisation. For each key decision-maker (CEO, CFO, Board, line managers), define: the people question they are trying to answer, the data that would answer it, and the format that would make it credible to them. Identify which questions can be answered with data you already have, and which require new collection. This becomes your first analytics priority list.
Using your own organisation's data or a mock dataset, identify your top eight operational HR KPIs. For each: state the formula, the data source, the reporting frequency, and the threshold that would trigger action. Then sketch a single-page executive dashboard showing all eight without clutter. Apply the principle: one number, one trend line, one traffic light per KPI.
Pick a real workforce problem you have encountered. Build a full fishbone diagram identifying all plausible causes across six categories: People, Process, Policy, Management, Environment, and Data. Apply the 5 Whys to the two most likely causes. Write a one-page problem statement suitable for CEO decision-making.
Design a People Analytics experiment for one of: (a) structured 30-day onboarding vs 90-day retention, (b) weekly manager check-ins vs absence rates, or (c) pay transparency vs internal promotion applications. Write a one-page design covering hypothesis, treatment group, control group, success metric, timeline, and confounder controls. Identify ethical risks and mitigations.
Map out the selection process for a senior People leadership hire. For each stage, identify: what it measures, the evidence base for its predictive validity, and whether it carries adverse impact risk against any protected characteristic. Redesign the process to maximise validity and minimise bias. Prepare a one-page hiring manager briefing.
Using your Power BI dataset or any HR dataset with 30+ records, run a correlation analysis between two variables: e.g. tenure vs absence rate, team size vs ER incident rate, or manager tenure vs engagement score. Interpret the r value, plot the scatterplot, and write a three-sentence executive summary. Identify at least two confounders that could explain the relationship.
Design a conceptual predictive model for voluntary turnover risk. Identify eight+ input variables covering demographic, behavioural, and engagement data. For each: state the data source, collection method, and hypothesised direction of effect. Then write a one-page model governance brief for a Board Risk Committee covering decision use, output visibility, and safeguards against discriminatory application.
Write a board-ready business case for implementing a People Analytics function in a 500-person, Series C fintech. Cover: current state gap, proposed architecture (data sources, tools, governance), investment required, expected ROI with three measurable outcomes, and a 12-month implementation roadmap. No more than four pages. Reference specific tools, methodologies, and metrics from all eight modules. This is your interview-ready artefact.
You have completed the eight-week programme. Your capstone business case is your primary evidence of analytical capability. Download the PDF version to share with colleagues or use as a CPD record.
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