Unit 1: HR analytics overview
HR Analytics notes · PTU syllabus (MBA 966-26)
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Unit summary
HR analytics uses people data to make better workforce decisions and prove HR's impact on business. This unit covers the introduction and evolution of HR analytics, a data-driven HR culture, descriptive, predictive and prescriptive analytics, and aligning HR to business through analytics.
After this unit you can
- Explain the meaning and evolution of HR analytics
- Build a data-driven HR culture
- Distinguish descriptive, predictive and prescriptive HR analytics
- Align HR with business outcomes through analytics
PTU syllabus topics
- Introduction and evolution of HR analytics
- the data-driven HR culture
- descriptive/predictive/prescriptive analytics types
- aligning HR to business through analytics
- Prescriptive
What should we do?
- Predictive
Who is likely to leave?
- Descriptive
What happened?
- Operational reporting
Headcount, attrition
Topic 1
Introduction and evolution of HR analytics
- HR analytics (people analytics): collecting, analysing and reporting HR data to improve people-related decisions and organisational performance.
- 1Operational reporting
Headcount, attrition, absenteeism reports
- 2Advanced reporting
Benchmarks, dashboards, trends
- 3Strategic analytics
Root causes, segmentation, links to business outcomes
- 4Predictive and prescriptive analytics
Forecasting attrition, hiring success; recommending actions
- 5AI-driven people analytics
Real-time insights, skills intelligence, generative AI assistants
- HR metrics vs HR analytics: metrics measure (turnover rate); analytics explains and predicts (why people leave and who will leave next).
Topic 2
A data-driven HR culture
- Features: decisions based on evidence rather than intuition alone, HR business partners comfortable with data, accessible dashboards, experimentation (pilot programmes), collaboration with finance and IT, ethical use of data.
- Barriers: poor data quality, fragmented systems, lack of analytical skills in HR, privacy concerns, resistance from managers.
Topic 3
Types of HR analytics
Descriptive
What happened?
Attrition rate by department last year
Diagnostic
Why did it happen?
Exit data shows manager quality drives exits
Predictive
What will happen?
Flight-risk scores for high performers
Prescriptive
What should we do?
Recommended retention actions for each at-risk employee
Topic 4
Aligning HR to business through analytics
- Start with business questions: sales productivity, customer satisfaction, safety, innovation — then find people drivers.
- Link chain (service–profit chain): engaged employees → better customer service → loyal customers → profit.
- 1
Business objective
- 2
Critical workforce segments and capabilities
- 3
People metrics and drivers
- 4
Analysis linking people data to outcomes
- 5
HR interventions
- 6
Measured business impact
Example
A retail chain finds stores with higher staff engagement scores have 8% higher sales per square foot; it invests in manager training in low-engagement stores.
Key terms
- HR analytics
- Analysis of people data for better decisions
- HR metric
- Quantitative measure of an HR outcome
- Predictive HR analytics
- Forecasting workforce outcomes
- Flight risk
- Likelihood that an employee will leave
- Service–profit chain
- Link from employee engagement to profit
Quick revision
- Meaning; evolution from reporting to AI-driven analytics; metrics vs analytics.
- Data-driven HR culture; barriers.
- Descriptive, diagnostic, predictive, prescriptive.
- Aligning HR to business; service–profit chain.
Important exam questions
Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).
Short-answer questions
- Q1.Define HR analytics.
- Q2.Distinguish HR metrics and HR analytics.
- Q3.State two barriers to a data-driven HR culture.
- Q4.Give an example of predictive HR analytics.
- Q5.What is prescriptive HR analytics?
- Q6.What is the service–profit chain?
Long-answer questions
- Q1.Explain the meaning and evolution of HR analytics.
- Q2.Discuss how to build a data-driven HR culture.
- Q3.Explain the types of HR analytics with examples.
- Q4.Explain how HR is aligned to business through analytics.
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