HR Analytics Using Advanced Excel Training Course

Duration 5 days 10 modules · 33 contact hours
Level Advanced Certificate on completion
Who attends HR Analysts, HR Business Partners and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-HM-133

Before you join: Participants should be confident Excel users who can work with worksheets, tables, common formulas, filters, charts and PivotTables.

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, pay, recruitment, absence, performance and employee movement, yet reporting often depends on manual spreadsheets, inconsistent definitions and static charts. This makes it difficult to identify attrition risks, recruitment bottlenecks, pay patterns or workforce cost drivers with confidence. Senior stakeholders need clear measures that reconcile to source records and support decisions on hiring, retention, organisation design and people investment.

This advanced course develops the Excel methods used to turn HR data into controlled analysis and decision-ready reporting. Participants build data models from HRIS, payroll and recruitment extracts; clean and combine records with Power Query; create reusable measures with Excel formulas, Power Pivot and DAX; and calculate workforce metrics accurately. The syllabus covers headcount, turnover, absence, recruitment funnel performance, compensation, diversity indicators, workforce planning and statistical testing. Participants also learn when conclusions are supported by data and when further investigation is required.

Instruction combines short technical briefings with HR cases drawn from payroll, recruitment, employee movement and workforce planning scenarios. Participants work through data-quality checks, metric definitions, PivotTable analysis, dashboard design and statistical interpretation, then translate findings into management actions. They leave with a reusable HR analytics workbook structure, metric dictionary, dashboard specification, data-quality checklist and an application plan for improving one live HR report or analytical process.

The course suits experienced HR professionals, HR analysts and people managers who already use Excel and need stronger analytical methods for workforce decisions. It is also relevant to finance, payroll and business planning professionals who contribute to workforce reporting.

What you will be able to do

  • Build refreshable HR data models from HRIS, payroll and recruitment extracts
  • Clean and combine workforce datasets using Power Query transformations and validated join keys
  • Calculate headcount, turnover, absence, recruitment and compensation metrics using controlled Excel formulas
  • Create Power Pivot data models and DAX measures for repeatable workforce reporting
  • Analyse recruitment, attrition, diversity and pay patterns using segmentation and statistical techniques
  • Apply regression, confidence intervals and hypothesis tests to appropriate people-data questions
  • Design interactive Excel dashboards that distinguish management indicators from diagnostic measures
  • Govern HR analytics through data-quality controls, privacy safeguards and documented metric definitions

Benefits of attending

For you

  • Produce HR reports that reconcile to defined source data and approved metrics
  • Diagnose turnover, recruitment and absence patterns with defensible analytical methods
  • Build refreshable Excel models rather than repeating manual monthly calculations
  • Present workforce findings in decision-ready dashboards for senior stakeholders
  • Apply privacy, fairness and statistical caution to sensitive employee-data analysis

For your organisation

  • Reduce manual effort and formula risk in recurring workforce reporting
  • Establish consistent definitions for headcount, turnover, vacancy and recruitment measures
  • Identify attrition, hiring and absence issues earlier through segmented analysis
  • Improve workforce planning decisions with transparent cost, demand and scenario models
  • Strengthen controls over employee data, reporting access and analytical assumptions

Course modules

10 modules over 5 days

Participants can define controlled HR data inputs, metric definitions and quality checks before analysis begins.

  • HRIS extracts, payroll files and recruitment records mapped to a data dictionary
  • Define grain, primary keys and reporting periods before combining workforce tables
  • Assess data completeness, validity, consistency, timeliness and uniqueness using quality rules
  • Classify personally identifiable information and restrict fields by analytical purpose
  • Reconcile headcount totals against payroll control reports and HRIS snapshots
  • Document metric owners, refresh frequency and approved source-system definitions

Participants can prepare repeatable, analysis-ready HR datasets using Power Query.

  • Power Query imports CSV, workbook and folder extracts through repeatable query steps
  • Standardise employee identifiers, dates, job codes and organisational hierarchies
  • Merge employee and event tables using validated join keys
  • Unpivot monthly columns into analysis-ready transaction records for time-series reporting
  • Handle missing values, duplicates and outliers with documented treatment rules
  • Build refreshable staging tables separate from reporting outputs and source files

Participants can create auditable formula models for recurring workforce calculations.

  • Structured references and Excel Tables create auditable workforce calculation models
  • XLOOKUP, INDEX-MATCH and XMATCH retrieve controlled employee attributes
  • SUMIFS, COUNTIFS and AVERAGEIFS calculate period-specific HR metrics
  • LET and LAMBDA functions reduce repeated logic in metric definitions
  • Dynamic arrays with FILTER, UNIQUE and SORT generate controlled report views
  • IFERROR and validation checks identify formula exceptions before publication

Participants can build relational HR data models and reusable DAX workforce measures.

  • Relational Data Model connects employee, position, requisition and exit tables
  • Star schema separates fact tables from conformed workforce dimensions
  • Power Pivot relationships prevent duplicate counts across one-to-many HR records
  • Calendar tables support month-end headcount and rolling twelve-month measures
  • DAX measures distinguish headcount, events and distinct employee populations
  • CALCULATE, DIVIDE and time-intelligence functions produce reusable HR measures

Participants can calculate and interpret workforce movement measures using agreed definitions.

  • Headcount, FTE and vacancy measures reconciled to agreed workforce definitions
  • Joiners, leavers and internal moves calculated from effective-dated records
  • Annualised turnover, regretted attrition and retention rates compared correctly
  • Span of control, management layers and internal mobility indicators calculated
  • Absence frequency, duration and Bradford Factor interpreted with policy context
  • Cost per hire, time to fill and offer acceptance metrics calculated

Participants can analyse recruitment pipeline performance and identify hiring-process bottlenecks.

  • Recruitment funnel conversion calculated from applicant, interview and offer stages
  • Time-to-fill decomposed into requisition approval, sourcing and acceptance intervals
  • Source-of-hire quality assessed through retention and performance outcome links
  • Recruiter workload and requisition ageing segmented by function and location
  • Cohort analysis compares hiring outcomes across recruitment months
  • PivotTables and slicers expose bottlenecks without changing base calculations

Participants can analyse pay and representation data while applying appropriate disclosure controls.

  • Pay distributions compared by grade, job family, location and tenure
  • Compa-ratio and range penetration calculated against approved salary structures
  • Gender representation and promotion rates segmented with disclosure controls
  • Four-fifths rule screens selection-rate differences requiring further review
  • Median and mean pay gaps distinguished from equal-pay analysis
  • Regression controls introduced for pay-equity exploratory analysis
  • Small-cell suppression protects individuals from identification in demographic reporting

Participants can select and interpret appropriate statistical methods for HR questions.

  • Descriptive statistics summarise central tendency, dispersion and distribution shape
  • Correlation matrices distinguish association from causal claims in people data
  • Confidence intervals express uncertainty around survey and attrition estimates
  • t-tests compare group means while checking assumptions and sample sizes
  • Chi-square tests assess associations between categorical workforce variables
  • Linear regression estimates relationships while testing residual patterns and multicollinearity
  • Interpret p-values, effect sizes and practical significance for HR decisions

Participants can design interactive Excel dashboards that support specific workforce decisions.

  • Audience, decision and action defined before dashboard measures are selected
  • Executive scorecards separate strategic indicators from operational diagnostic measures
  • PivotCharts, slicers and timelines create controlled interactive reporting views
  • Variance analysis compares actual, target, prior-period and benchmark results
  • Conditional formatting highlights exceptions without overstating insignificant movement
  • Dashboard layout applies preattentive attributes, hierarchy and accessible colour choices
  • Protect formulas, document assumptions and publish version-controlled management packs

Participants can apply governance controls and plan a targeted improvement to HR analytics reporting.

  • GDPR principles of purpose limitation, minimisation and retention applied to HR data
  • Role-based access and aggregation thresholds reduce re-identification risks
  • Audit trail records source, transformation, metric definition and approval
  • Data ethics review tests fairness, transparency and foreseeable employee impacts
  • Scenario models quantify workforce cost, hiring demand and attrition assumptions
  • Application plan prioritises one reporting improvement, owner, milestones and controls

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

What you take back to work

  1. HR analytics data dictionary template
  2. Power Query workforce data-preparation workflow
  3. Excel HR metrics calculation model
  4. Power Pivot and DAX measure library
  5. Executive HR dashboard specification
  6. HR analytics governance and application plan

Who should attend

  • HR Analysts — build reliable workforce reports and investigate people-data patterns
  • HR Business Partners — translate workforce measures into actions for business leaders
  • People Analytics Specialists — strengthen Excel-based analysis before specialist platform investment
  • Talent Acquisition Managers — diagnose funnel conversion, hiring speed and source performance
  • Compensation and Benefits Analysts — analyse pay distributions, ranges and representation indicators
  • Workforce Planning Managers — model headcount demand, attrition assumptions and workforce cost

Skills and tools covered

HR data modellingWorkforce metric designPower Query transformationDAX measure creationPeople analytics statisticsHR dashboard reporting

Tools and standards

Microsoft Excel Power Query, Microsoft Excel Power Pivot, DAX, GDPR

How the course runs

Training methodology

The course uses short instructor briefings followed by guided work with realistic HR datasets, including employee master data, payroll extracts, recruitment funnels and exit records. Participants apply Excel functions, Power Query, Power Pivot, DAX, PivotTables and statistical methods to structured cases. Small-group discussion tests metric definitions, dashboard choices and the limits of conclusions drawn from people data. Instructor feedback focuses on auditability, decision relevance and privacy. Each participant finishes with an application plan for a priority HR reporting or analytics improvement.

Requirements and prerequisites

Participants should be confident Excel users who can work with worksheets, tables, common formulas, filters, charts and PivotTables. Experience with HR reporting, HRIS extracts, payroll records, recruitment data or workforce planning is expected, although participants do not need to work in a dedicated analytics role. Familiarity with headcount, turnover and basic HR measures is useful. Prior Power Query, Power Pivot, DAX, regression or statistical testing experience is not required. No programming, database administration or specialist people analytics software knowledge is required.

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 should already be comfortable with formulas, tables, filters, charts and PivotTables. The course teaches Power Query, Power Pivot, DAX and statistical methods from a practical HR reporting starting point.

Bring a laptop with a current desktop version of Microsoft Excel that includes Power Query and Power Pivot. Participants may also bring an anonymised HR reporting challenge, metric definition or sample structure for application planning.

It is designed for experienced HR analysts, HR business partners, people analytics specialists, talent acquisition managers, compensation analysts and workforce planners. Finance, payroll and business planning staff involved in workforce reporting will also benefit.

General Excel courses focus on spreadsheet features, while this course applies advanced Excel methods to HR data structures, workforce metrics and management reporting. It also covers HR-specific issues such as effective-dated records, privacy, representation measures and sensitive-data interpretation.

Participants can use the templates and methods to improve a monthly headcount pack, turnover analysis, recruitment dashboard, absence report or workforce planning model. The application plan identifies a priority improvement, accountable owner, milestones and controls.

The five days provide about 32.5 contact hours, delivered from 08:30 to 16:30 each day. Time is divided across ten modules covering data preparation, advanced Excel modelling, HR measures, statistical analysis, dashboards and governance.

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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