People Analytics Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends HR Business Partner, People Analytics Specialist and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-TPM-037

Before you join: Participants should have practical HR, talent management, workforce reporting or business analysis experience.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

People analytics turns HR, talent and workforce data into evidence for decisions on hiring, retention, performance, engagement, promotion, capability and workforce planning. Many HR teams produce regular reports but struggle to define the decision behind a metric, reconcile conflicting data sources, assess whether apparent differences are meaningful, or present findings that prompt accountable action. Poorly designed analysis can also create privacy, fairness and employee-trust risks.

This course equips participants to frame workforce questions, specify useful metrics, prepare people data, select suitable analytical methods and communicate findings to decision-makers. Participants work with HRIS, applicant tracking, learning, payroll, performance and survey data structures. They examine turnover, engagement, performance ratings, promotion rates, pay equity and talent pipeline questions using descriptive statistics, cohort analysis, regression concepts, survey analysis, adverse impact testing and dashboard design. The course also addresses data governance, ethical review, privacy-by-design and the limits of predictive models.

Teaching combines short instructor briefings with guided case work, group analysis, decision simulations and structured application planning. Cases reflect realistic people decisions, such as identifying avoidable attrition, testing performance-rating consistency, interpreting engagement results and monitoring representation in promotion pipelines. Participants leave with a people analytics project charter, metric dictionary, data-quality assessment, analysis-plan templates and an executive reporting storyboard. A certificate of completion is awarded to participants who complete the five-day course.

The course is designed for HR professionals and business partners who need to commission, conduct or interpret workforce analysis. It is also suitable for HR data specialists, talent leaders and managers who work with HR reporting teams and need clearer evidence for talent decisions.

What you will be able to do

  • Formulate decision-focused people analytics questions using hypotheses, logic models and analytic charters
  • Define workforce metrics using ISO 30414 categories, population rules and metric dictionaries
  • Prepare HR data through entity mapping, join logic, missing-data assessment and transformation logs
  • Apply descriptive statistics, cohort analysis and regression concepts to workforce questions
  • Analyse survey, attrition, performance and promotion data using suitable measures and controls
  • Evaluate people analytics work for privacy, fairness, adverse impact and ethical risks
  • Design decision-ready dashboards and executive briefings with clear uncertainty and limitations
  • Build a prioritised people analytics project plan with governance, ownership and benefit measures

Benefits of attending

For you

  • Frame workforce questions that lead to defined decisions rather than generic reporting
  • Interpret attrition, engagement and performance findings with greater statistical confidence
  • Identify data-quality, privacy and fairness issues before presenting conclusions
  • Produce clearer people metrics and executive briefs for HR and business stakeholders
  • Develop a practical project plan for an immediate workplace analytics use case

For your organisation

  • Improves the quality and consistency of workforce metrics used in talent decisions
  • Reduces reliance on anecdotal explanations for turnover, engagement and performance issues
  • Strengthens governance for employee data, sensitive reporting and access controls
  • Supports earlier identification of disparities in selection, ratings, promotion and pay
  • Creates repeatable analysis methods for HR reporting teams and business partners

Course modules

10 modules over 5 days

Participants can frame a people analytics request around a defined decision, stakeholder and measurable outcome.

  • Decision inventory linking workforce questions, decisions, owners and measurable outcomes
  • People analytics operating model: demand, data, analysis, insight and action
  • Descriptive, diagnostic, predictive and prescriptive analytics distinguished by decision use
  • Logic models connecting talent interventions to behavioural and business measures
  • Stakeholder mapping for HR, finance, legal, managers and employee representatives
  • Analytic charter defining scope, hypotheses, constraints, decisions and success criteria

Participants can define consistent workforce metrics and assess whether source data is fit for analysis.

  • ISO 30414 metrics grouped across workforce, diversity, capability and productivity
  • Metric dictionary fields: definition, formula, source, owner, frequency and caveats
  • Headcount, FTE and contingent-worker measures reconciled using clear population rules
  • Turnover metrics separated into voluntary, involuntary, regrettable and internal movement
  • Span-of-control and management-layer metrics interpreted without simplistic benchmarks
  • Data-quality profiling for completeness, validity, consistency, timeliness and uniqueness

Participants can map HR data sources and prepare an analysis-ready employee dataset.

  • HRIS, ATS, LMS, payroll and survey data mapped to entities
  • Unique employee identifiers, effective dates and slowly changing dimensions managed
  • Grain analysis prevents duplicate records and invalid employee-level comparisons
  • Join logic reconciles person, position, job, manager and organisational hierarchies
  • Missing-data mechanisms assessed using MCAR, MAR and MNAR classifications
  • Data preparation log records transformations, exclusions, assumptions and refresh controls

Participants can identify privacy, disclosure, ethical and fairness risks in people analytics work.

  • Privacy-by-design requirements applied to workforce data collection and reporting
  • Purpose limitation, minimisation and retention rules documented for each dataset
  • Role-based access controls separate analysts, managers, administrators and data custodians
  • Anonymisation, pseudonymisation and aggregation selected for appropriate disclosure risk
  • Small-cell suppression protects employees in demographic and sensitive-data reporting
  • Adverse impact ratio screens selection and performance outcomes for potential disparity
  • Ethical review questions test proportionality, transparency, contestability and employee impact

Participants can select and interpret core statistical methods for common workforce analyses.

  • Distribution tables, central tendency and dispersion summarise workforce measures
  • Cross-tabulations compare employee groups while retaining meaningful denominators
  • Confidence intervals distinguish signal from sampling variation in survey findings
  • Pearson and Spearman correlations interpreted without claiming causal relationships
  • Regression models estimate associations while controlling specified workforce variables
  • Cohort analysis traces hiring, promotion and attrition patterns over time
  • Statistical significance paired with effect size and practical decision thresholds

Participants can design, assess and interpret employee survey evidence for management action.

  • Survey constructs translated into items, response scales and scoring rules
  • Likert-scale design avoids double-barrelled, leading and ambiguous questions
  • Sampling frames and response-rate monitoring address representativeness concerns
  • Reliability assessed using Cronbach's alpha for multi-item survey scales
  • Driver analysis separates engagement correlates from actionable intervention priorities
  • Open-text coding combines thematic analysis with transparent category definitions
  • Survey reporting protects anonymity through threshold rules and careful segmentation

Participants can structure attrition analysis and interpret risk findings without deterministic employee labelling.

  • Attrition problem statement distinguishes prediction, explanation and intervention decisions
  • Event definitions establish termination dates, eligible populations and censoring rules
  • Survival analysis estimates retention probabilities across employee tenure periods
  • Logistic regression produces interpretable attrition risk estimates and feature effects
  • Model evaluation uses precision, recall, ROC-AUC and calibration measures
  • Feature selection excludes protected characteristics and inappropriate proxy variables
  • Risk segmentation directs retention conversations without labelling employees deterministically

Participants can examine performance and talent outcomes for consistency, mobility and potential disparities.

  • Performance rating distributions tested for compression, inflation and manager effects
  • Calibration analysis compares ratings across functions, levels and demographic groups
  • Nine-box grid data examined for consistency, mobility and succession implications
  • Promotion-rate analysis uses eligible populations, time windows and denominator controls
  • Pay equity analysis controls job level, location, tenure and relevant factors
  • Adverse impact testing identifies disparities requiring legal and policy review
  • Talent-review metrics linked to succession slates and development actions

Participants can communicate workforce evidence through decision-focused dashboards and executive briefs.

  • Dashboard design starts with user decisions, metric hierarchy and alert thresholds
  • KPI trees connect workforce measures to talent and operating outcomes
  • Time-series charts, cohorts and funnels selected for accurate pattern interpretation
  • Control charts distinguish common-cause variation from special-cause signals
  • Data storytelling states finding, evidence, implication, limitation and recommended action
  • Executive briefings present uncertainty, trade-offs and decisions without technical overload
  • Self-service dashboard governance assigns definitions, permissions and refresh responsibilities

Participants can plan a governed people analytics project from prioritisation through benefit tracking.

  • CRISP-DM stages adapted for people analytics projects and decision checkpoints
  • Use-case prioritisation scores value, feasibility, risk, sponsorship and data readiness
  • Minimum viable analysis defines scope, measures, decision owner and timeline
  • RACI matrix assigns accountability for data, analysis, action and monitoring
  • Benefit tracking separates realised outcomes from assumptions and external influences
  • Implementation roadmap sequences pilot, review, scale-up and governance activities
  • Personal application plan specifies a workplace question and first deliverables

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. People analytics project charter
  2. Workforce metric dictionary and data-quality assessment
  3. Attrition analysis model specification
  4. Employee survey design and analysis plan
  5. Performance and talent equity diagnostic
  6. Executive dashboard storyboard and decision brief

Who should attend

  • HR Business Partner — needs evidence to challenge assumptions and advise business leaders
  • People Analytics Specialist — needs structured methods for workforce data and stakeholder decisions
  • Talent Management Manager — needs insight into performance, succession, mobility and retention
  • HR Reporting Analyst — needs to progress from recurring reports to decision-focused analysis
  • Learning and Development Manager — needs evidence on capability needs and learning outcomes
  • HR Director — needs governance and meaningful workforce measures for strategic oversight

Skills and tools covered

Workforce metric designHR data preparationStatistical interpretationTalent analyticsEthical data governanceExecutive data storytelling

Tools and standards

ISO 30414, CRISP-DM, RACI matrix, Adverse impact ratio

How the course runs

Training methodology

The course uses short briefings to introduce methods, followed by guided case work using realistic workforce datasets and decision scenarios. Participants interpret metrics, test assumptions, assess data quality and prepare findings for HR and business audiences. Group exercises examine attrition, survey results, performance ratings and promotion patterns; decision simulations test how evidence should inform action. Instructor feedback focuses on method selection, interpretation, privacy and fairness. Each participant completes structured application planning for a workplace people analytics question.

Requirements and prerequisites

Participants should have practical HR, talent management, workforce reporting or business analysis experience. They should be comfortable reading tables, percentages, averages and basic charts, and should understand common HR processes such as recruitment, performance review, employee surveys or turnover reporting. Familiarity with Excel or a similar spreadsheet tool is helpful. The course does not require coding, advanced mathematics, data science experience, statistical software knowledge or responsibility for an HR information system. Participants do not need access to employer data during the course.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants need practical familiarity with HR, talent management, workforce reporting or business analysis, plus confidence with basic percentages and charts. Advanced statistics, programming and data science experience are not required.

Participants should bring a laptop if attending in person, although course materials and case datasets are supplied. Bringing a real workplace question, such as turnover in a critical group or survey follow-up, will help with application planning.

The course suits HR business partners, people analytics specialists, HR reporting analysts, talent managers, learning leaders and HR directors. It is intended for professionals who need to create, commission or interpret people analysis.

HR reporting courses focus mainly on producing recurring measures, while this course links analysis to talent and workforce decisions. Data science courses typically give greater attention to coding and advanced modelling; this course concentrates on sound HR questions, interpretable methods, governance and action.

Participants leave with templates for defining metrics, assessing data quality, structuring analyses and presenting findings. The final module converts a workplace question into a prioritised project plan with owners, measures and first deliverables.

The course runs from 08:30 to 16:30 each day, providing about 6.5 contact hours daily. Ten modules provide approximately 30 contact hours, with remaining contact time used for case discussions, analysis activities, feedback and application planning.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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