HR Analytics Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends HR Business Partner, HR Analyst and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 7 Nov 2026 Course code SD-HM-082

Before you join: Participants should understand common HR processes such as recruitment, employee records, performance management, absence, learning or workforce planning.

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

HR teams hold data on headcount, recruitment, pay, absence, performance, learning and employee movement, yet many reports remain descriptive and disconnected from decisions. Leaders need credible answers to questions such as which roles create turnover risk, where hiring bottlenecks occur, whether retention actions work, and how workforce costs may change under different plans. This course develops the analytical discipline needed to turn people data into decision-ready evidence while protecting employee privacy and avoiding misleading conclusions.

Participants learn to frame business questions, define consistent HR metrics, assess data quality and combine data from HRIS, payroll, applicant tracking and learning systems. They calculate and interpret core workforce measures, use Excel and Power BI for analysis and reporting, apply statistical methods appropriately, and examine recruitment, retention, workforce planning, performance, learning, mobility and pay equity. The course also addresses predictive models, experimentation, fairness checks, GDPR principles and the limits of automated employment decisions.

Instructor-led sessions combine short technical briefings with realistic HR cases, guided analysis, group discussion and reporting tasks. Participants work through examples such as reducing regretted turnover in critical roles, diagnosing time-to-fill delays, assessing absence patterns and preparing workforce scenarios for a budget cycle. They leave with a reusable HR analytics toolkit containing a metric dictionary, data-quality checklist, dashboard specification, analysis templates and a 90-day application plan. A certificate of completion is issued to participants who complete the course.

The course is suited to HR professionals who already work with workforce information and need a more structured analytical approach. It is also valuable for HR business partners, people managers and analysts who must challenge reports, commission analysis or present workforce evidence to senior stakeholders.

What you will be able to do

  • Frame HR business questions using decision, metric, population and owner definitions
  • Build a controlled HR metric dictionary for headcount, turnover, absence and recruitment measures
  • Assess people-data quality using completeness, validity, consistency, timeliness and accuracy tests
  • Analyse workforce data in Excel using PivotTables, cohorts, reconciliations and segment comparisons
  • Interpret statistical findings using distributions, confidence intervals, correlations and regression outputs
  • Design Power BI dashboards that support workforce decisions without exposing sensitive data
  • Evaluate retention, recruitment, pay equity and workforce planning evidence using appropriate measures
  • Produce an insight-to-action brief with recommendations, owners, measures and review dates

Benefits of attending

For you

  • Greater confidence challenging inconsistent headcount, turnover and absence reports
  • Practical ability to translate HR requests into measurable analytical questions
  • Improved credibility when presenting workforce evidence to senior decision-makers
  • Reusable methods for identifying data-quality problems before reporting conclusions
  • A structured 90-day plan for applying people analytics to a current HR priority

For your organisation

  • More consistent workforce metrics across HR, finance and business reporting
  • Earlier identification of recruitment delays, turnover risks and absence patterns
  • Better targeted retention and workforce planning decisions
  • Reduced risk from poor-quality, biased or improperly handled employee data
  • Clearer evidence linking HR actions to operational and workforce outcomes

Course modules

10 modules over 5 days

Participants can frame HR analytics requests around defined decisions, measures, populations and accountabilities.

  • Decision-framing canvas linking business questions, workforce outcomes, metrics and owners
  • Leading and lagging indicators distinguished using practical HR measurement examples
  • Metric dictionary definitions preventing inconsistent headcount, turnover and absence reporting
  • ISO 30414 human capital disclosures mapped to internal management measures
  • Segmentation criteria for workforce, job family, location and employment type
  • Baseline targets and tolerances set before interpreting performance movement

Participants can assess whether people data is suitable, lawful and sufficiently reliable for analysis.

  • Data lineage traced from HRIS, payroll, ATS and learning systems
  • Unique employee identifiers matched across systems using controlled reconciliation rules
  • Completeness, validity, consistency, timeliness and accuracy assessed through data-quality tests
  • Missing values, duplicates and outliers treated without distorting workforce conclusions
  • GDPR purpose limitation, minimisation and retention applied to people data
  • Role-based access controls and anonymisation methods protect sensitive employee records

Participants can prepare workforce data and calculate consistent operational HR measures in Excel.

  • Excel tables and Power Query prepare repeatable employee-data refreshes
  • Headcount reconciliations separate opening balance, hires, exits, transfers and adjustments
  • Turnover rates calculated with average headcount and defined population rules
  • Absence frequency, duration and lost-time rates compared by employee segment
  • Cohort analysis tracks retention from hire date through employment milestones
  • PivotTables and conditional formatting expose patterns requiring management attention

Participants can interpret common statistical outputs without overstating what workforce data proves.

  • Distribution shape, median, mean and percentiles summarise workforce measures
  • Correlation coefficients interpreted without claiming causal relationships between HR variables
  • Confidence intervals and sample sizes tested before comparing employee groups
  • Regression outputs explain associations while controlling selected workforce characteristics
  • Statistical significance distinguished from managerial significance in people decisions
  • Bias checks identify confounding, selection effects and small-group instability

Participants can specify and assess dashboards that focus attention on workforce decisions and exceptions.

  • Dashboard audience, decisions and refresh cadence defined before visual design
  • Power BI data models connect workforce tables through controlled relationships
  • Measures use DAX calculations for headcount, turnover and absence trends
  • Chart selection matches comparisons, distributions, trends and geographic workforce patterns
  • Drill-through views preserve privacy while supporting manager-level investigation
  • Annotation and narrative hierarchy direct attention toward decisions and exceptions

Participants can analyse workforce supply, retention patterns and staffing scenarios to support planning decisions.

  • Workforce supply-demand model compares required capacity with current talent inventory
  • Scenario planning tests hiring freezes, growth assumptions and attrition changes
  • Flight-risk indicators prioritise retention conversations without automated employment decisions
  • Survival analysis estimates tenure-based likelihood of employee departure
  • Exit interview coding combines qualitative themes with turnover patterns
  • Retention interventions evaluated using segment-specific baseline and follow-up measures

Participants can assess recruitment efficiency, representation patterns and pay equity evidence using defensible measures.

  • Recruitment funnel conversion measures source quality, speed and offer acceptance
  • Time-to-fill decomposed into requisition approval, sourcing, selection and notice periods
  • Adverse impact ratios screen selection outcomes across protected-group comparisons
  • Pay equity analysis compares like-for-like roles using regression controls
  • Representation and progression metrics identify barriers across career stages
  • Fairness review documents human oversight, model limits and escalation routes

Participants can connect performance, learning and organisational design data to workforce improvement questions.

  • Performance rating distributions examined for calibration patterns and manager effects
  • Learning evaluation links participation, skill evidence, behaviour and business results
  • Kirkpatrick levels distinguish attendance measures from transfer and outcome evidence
  • Internal mobility flows reveal career pathways, bottlenecks and succession risk
  • Span-of-control and layer analysis test organisational design assumptions
  • Productivity measures paired with workload and wellbeing indicators to avoid distortion

Participants can assess predictive models and intervention evidence with appropriate controls and safeguards.

  • CRISP-DM stages structure a people-analytics project from question to deployment
  • Classification models predict defined outcomes using training and test datasets
  • Precision, recall and false-positive rates guide model performance assessment
  • Cross-validation reduces overfitting before any workforce model is adopted
  • A/B tests and quasi-experiments assess whether HR interventions caused change
  • Model cards record purpose, inputs, limitations, fairness checks and owners

Participants can present HR findings as accountable actions and plan a practical analytics initiative.

  • Executive narrative connects workforce evidence, operational risk and recommended action
  • Insight-to-action briefs state decision, owner, timing, cost and success measure
  • Stakeholder maps identify sponsors, data custodians, managers and employee representatives
  • Analytics operating model assigns intake, governance, delivery and review responsibilities
  • Benefits realisation plan tracks adoption, outcomes and unintended consequences
  • Personal 90-day application plan sequences a defined workplace analytics initiative

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

What you take back to work

  1. HR metric dictionary template
  2. People-data quality assessment checklist
  3. Workforce dashboard specification
  4. Retention and attrition analysis model
  5. Insight-to-action briefing template
  6. 90-day HR analytics application plan

Who should attend

  • HR Business Partner — needs evidence to advise leaders on workforce priorities
  • HR Analyst — needs structured methods for analysing and reporting people data
  • People Analytics Specialist — needs consistent measures, governance and stakeholder reporting methods
  • HR Manager — needs to interpret workforce evidence and direct improvement actions
  • Talent Acquisition Manager — needs funnel, source and time-to-fill analysis for hiring decisions
  • Learning and Development Manager — needs to assess learning participation, transfer and outcomes

Skills and tools covered

HR metrics designPeople-data governanceWorkforce data analysisStatistical interpretationHR dashboard designEvidence-based recommendations

Tools and standards

ISO 30414, CRISP-DM, Microsoft Excel, Microsoft Power BI

How the course runs

Training methodology

The course uses short instructor briefings to introduce methods, followed by guided case analysis, group exercises and individual reporting tasks. Participants work with realistic workforce datasets covering headcount, turnover, recruitment, absence and performance. They calculate measures, test data quality, interpret charts and statistical outputs, and discuss how findings should influence HR decisions. Scenarios include workforce planning, attrition diagnosis, hiring funnel analysis and pay equity review. Each participant develops an application plan for a defined workplace analytics priority.

Requirements and prerequisites

Participants should understand common HR processes such as recruitment, employee records, performance management, absence, learning or workforce planning. Experience using Excel for sorting, filtering and basic formulas is expected, as participants will work with workforce-data examples. Familiarity with HRIS, payroll or applicant tracking data is helpful but not essential. The course does not require advanced statistics, programming, data science experience or prior use of Power BI. Participants do not need to bring live employee data; realistic course datasets are provided.

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

You should understand standard HR processes and be comfortable with basic Excel tasks such as sorting, filtering and simple formulas. Advanced statistics, programming and prior Power BI experience are not required.

Bring a laptop with Excel installed if possible, plus examples of HR reporting questions you need to address. Do not bring identifiable employee data unless your organisation has approved its use and handling.

The course suits HR analysts, HR business partners, HR managers, people analytics specialists and functional HR leads. It is designed for professionals who need to create, interpret or act on workforce analysis.

This course starts with the HR decision and the quality of the underlying data, rather than treating reporting as a technical task. Power BI and Excel are used as supporting tools alongside workforce metrics, statistical interpretation, privacy and action planning.

Participants leave with templates for defining metrics, checking data quality, specifying dashboards and presenting recommendations. The final module produces a 90-day plan based on a workplace issue such as attrition, recruitment delays or absence.

The five days provide approximately 32.5 contact hours, normally from 08:30 to 16:30 each day. Time is divided between instructor input, data analysis, case work, group discussion, reporting tasks 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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