Data Analysis & Storytelling for HR

Course Description

Duration 3 days – 21 hrs

Overview

This course equips HR professionals with practical skills to collect, analyze, interpret, and communicate workforce data effectively. Participants will learn how to transform HR metrics into meaningful insights, create clear visualizations, and develop data-driven stories that support management decisions.

The course uses common HR scenarios involving recruitment, employee turnover, absenteeism, performance, engagement, learning and development, diversity, and workforce planning. Practical exercises may be completed using Microsoft Excel and PowerPoint. Power BI may be introduced as an optional visualization tool.

Objectives

Explain the role of data analysis in strategic and operational HR decision-making.
Identify relevant HR metrics and key performance indicators.
Collect, organize, clean, and validate HR data.
Apply descriptive analysis to common HR concerns.
Interpret trends, patterns, relationships, and workforce indicators.
Select appropriate charts and visualizations for different types of HR data.
Design clear HR reports, dashboards, and executive summaries.
Transform analytical findings into structured and compelling data stories.
Present evidence-based HR recommendations to management and stakeholders.
Recognize privacy, confidentiality, ethics, and bias considerations in people analytics.

Target Audience

HR managers and supervisors
HR business partners
HR officers and specialists
Recruitment and talent acquisition professionals
Learning and development professionals
Compensation and benefits personnel
Employee relations and engagement professionals
Workforce planning and organizational development teams
HR reporting and HRIS personnel
Professionals responsible for preparing workforce reports and presentations

Prerequisites

Basic knowledge of HR processes and terminology
Basic proficiency in Microsoft Excel
Basic experience preparing reports or presentations
A laptop with Microsoft Excel and PowerPoint installed
No programming, statistics, or advanced analytics experience is required.

Course Outline

Day 1 – HR Data and Analysis Fundamentals

Module 1: Introduction to HR Data Analytics

What HR analytics is and why it matters
Moving from administrative reporting to strategic insights
Descriptive, diagnostic, predictive, and prescriptive analytics
Questions that HR data can help answer
The HR analytics process
Common challenges in using workforce data

Module 2: HR Metrics and Key Performance Indicators

Difference between data, metrics, KPIs, and insights
Selecting metrics aligned with business and HR objectives
Common HR indicators:
- Headcount and workforce composition
- Recruitment efficiency
- Time-to-fill and cost-per-hire
- Employee turnover and retention
- Absenteeism
- Learning effectiveness
- Employee performance
- Engagement and satisfaction
- Diversity and inclusion
Leading and lagging indicators
Avoiding vanity metrics and information overload
Creating an HR measurement framework

Module 3: Preparing HR Data for Analysis

Identifying internal and external HR data sources
Understanding structured and unstructured HR data
Organizing HR data in a usable format
Removing duplicates and correcting inconsistencies
Handling missing and incomplete information
Standardizing dates, categories, and employee records
Data validation and quality checks
Protecting confidential and sensitive employee information

Module 4: Essential Excel Techniques for HR Analysis

Using Excel tables, filters, and sorting
Applying essential formulas and functions
Conditional calculations and lookups
Using PivotTables and PivotCharts
Creating calculated HR metrics
Summarizing information by department, position, location, or period

Practical Exercise: Clean and summarize a sample employee dataset and calculate selected HR metrics.

Day 2 – Analyzing and Visualizing HR Data

Module 5: Descriptive Analysis for HR

Understanding totals, percentages, rates, averages, and distributions
Comparing groups and workforce segments
Trend and period-over-period analysis
Identifying patterns, changes, and anomalies
Segmenting data by department, tenure, role, age group, or location
Distinguishing correlation from causation
Avoiding misleading conclusions

Module 6: Applying Analysis to Common HR Concerns

Recruitment funnel analysis
Turnover and retention analysis
Absenteeism analysis
Employee performance analysis
Training participation and effectiveness
Engagement survey analysis
Workforce diversity analysis
Workforce capacity and planning
Converting HR questions into analytical questions

Case Activity: Analyze a workforce issue and identify its possible contributing factors.

Module 7: Principles of HR Data Visualization

Purpose of data visualization
Matching chart types to analytical questions
Using bar, line, column, pie, scatter, and combination charts
Showing comparisons, trends, composition, and relationships
Applying appropriate titles, labels, colors, and annotations
Reducing clutter and unnecessary decoration
Designing accessible and management-friendly visuals
Common charting mistakes and misleading presentations

Module 8: Designing HR Dashboards and Reports

Identifying the dashboard’s purpose and audience
Selecting the most important KPIs
Organizing dashboard information logically
Using filters and categories effectively
Creating executive, operational, and analytical views
Highlighting exceptions and areas requiring action
Introduction to Excel dashboards
Optional introduction to Power BI for HR reporting

Practical Exercise: Create a one-page HR dashboard using a sample dataset.

Day 3 – Data Storytelling and Presentation

Module 9: Fundamentals of Data Storytelling

Difference between reporting data and telling a data story
Combining data, narrative, and visuals
Understanding the audience and decision context
Identifying the central message
Separating important insights from supporting details
Building credibility through evidence
Balancing accuracy, clarity, and persuasion

Module 10: Structuring an HR Data Story

Establishing the HR or business context
Presenting the key question or workforce problem
Showing relevant evidence and findings
Explaining the meaning and implications
Developing actionable recommendations
Structuring the story using:
- Situation
- Insight
- Impact
- Recommendation
Creating an executive summary
Developing an effective call to action

Module 11: Presenting HR Insights to Stakeholders

Adapting the message for executives, managers, and employees
Communicating technical findings in plain language
Connecting HR findings to business outcomes
Presenting sensitive or unfavorable results objectively
Using annotations and emphasis to guide attention
Responding to questions and challenges
Communicating limitations and assumptions
Building confidence when presenting data

Module 12: Ethics, Privacy, and Responsible People Analytics

Employee privacy and confidentiality
Responsible handling of personal and sensitive information
Data minimization and appropriate access
Recognizing bias in data and analysis
Ethical use of employee information
Avoiding discriminatory interpretations
Transparency and accountability in HR analytics

Capstone Workshop: HR Data Story Presentation

Analyze a sample HR dataset.
Identify a significant workforce issue or opportunity.
Select relevant metrics and supporting evidence.
Create appropriate data visualizations.
Develop an HR data story.
Present insights and recommendations to the group.
Receive feedback based on clarity, accuracy, relevance, and actionability.

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Compare picking strategies based on order characteristics and operational requirements.
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Target Audience

Warehouse supervisors, team leaders, and managers.
Inventory controllers and stock control personnel.
Logistics and distribution supervisors.
Internal auditors and operational compliance personnel.
Supply chain and operations professionals.
Personnel responsible for reviewing warehouse controls and performance.

Prerequisites

Basic familiarity with warehouse, logistics, or inventory activities.
General understanding of business processes and operational documentation.
Basic numerical skills, including percentages and simple calculations.
Basic spreadsheet skills are helpful.
No prior experience with a specific Warehouse Management System (WMS) is required.

Course Outline

Day 1: Warehouse Processes, Layout, and Storage Controls Module 1: Warehouse Operations and Process Controls

Warehouse roles within the supply chain.
End-to-end flow: receiving, put-away, storage, replenishment, picking, packing, and dispatch.
Physical stock movement and corresponding system transactions.
Responsibilities, authorization, and segregation of duties.
Common operational weaknesses and audit evidence.

Module 2: Warehouse Layout and Storage Systems

Functional zones, movement paths, and space utilization.
Receiving, storage, picking, staging, and dispatch areas.
Storage options: floor stacking, shelving, pallet racking, and bin storage.
Fixed and dynamic location systems.
Product slotting based on movement, size, handling needs, and compatibility.
Layout bottlenecks and their effects on productivity and inventory control.

Module 3: Receiving and Put-Away

Purchase orders, delivery documents, and expected receipts.
Quantity, condition, and item identification checks.
Recording shortages, overages, damage, and discrepancies.
Controls for acceptance, quarantine, and release.
Put-away rules and location confirmation.
Traceability through labels, barcodes, lot numbers, and serial numbers.
Timely recording of receipts and stock movements.

Module 4: Storage, Stock Rotation, and Replenishment

Storage discipline and location integrity.
FIFO and FEFO principles, applications, and limitations.
Batch, lot, and expiry-date management.
Controls for slow-moving, obsolete, damaged, and expired stock.
Replenishment of picking locations.
Supervision and review of stock rotation compliance.

Day 2: Order Fulfillment and Inventory Accuracy Module 5: Picking Strategies and Order Fulfillment

Discrete, batch, zone, and wave picking.
Selecting picking strategies for different order profiles.
Pick paths, location sequencing, and travel reduction.
Replenishment coordination and stock availability.
Picking verification and error prevention.
Packing, staging, and dispatch confirmation.
Handling short picks, substitutions, cancellations, and returns.

Module 6: Inventory Records and Accuracy Controls

Item master data, units of measure, and location records.
On-hand, available, allocated, and quarantined stock.
Transaction controls for receipts, transfers, issues, returns, and adjustments.
Common causes of physical and system stock mismatches.
Barcode scanning and WMS control points.
Inventory reconciliation and supporting documentation.
Measuring inventory accuracy and interpreting discrepancies.

Module 7: Cycle Counting and Physical Inventory

Cycle counting versus full physical inventory.
ABC classification and risk-based count priorities.
Count frequency based on value, movement, and discrepancy history.
Count preparation, blind counting, and movement controls.
Recounts, variance investigation, and adjustment approval.
Root cause analysis and corrective action follow-up.
Reviewing the effectiveness of the counting program.

Module 8: Shrinkage Reduction and Inventory Protection

Sources of shrinkage: loss, damage, theft, misplacement, and recording errors.
Access controls and accountability for stock movements.
Controls for high-value and sensitive inventory.
Returns, write-offs, scrap, and disposal controls.
Exception reporting and unusual transaction patterns.
Investigating recurring losses and unexplained adjustments.
Preventive and detective controls for shrinkage reduction.

Day 3: Performance Management, Process Review, and Improvement Module 9: Warehouse Productivity and Inventory KPIs

Receiving productivity and dock-to-stock time.
Put-away productivity and replenishment performance.
Picking productivity and order accuracy.
Inventory accuracy and cycle count variance.
Space utilization and storage capacity.
Shrinkage, damage, and expiry indicators.
Defining KPI formulas, data sources, and reporting boundaries.
Interpreting trends while balancing speed, accuracy, and service.

Module 10: Supervising and Auditing Warehouse Processes

Process mapping and identification of critical control points.
Reviewing procedures against actual warehouse practices.
Tracing transactions from documents to systems and physical stock.
Reviewing approvals, access rights, and segregation of duties.
Identifying control gaps and recurring process exceptions.
Documenting findings with clear supporting evidence.
Prioritizing corrective actions and tracking closure.

Module 11: Warehouse Improvement Planning

Identifying bottlenecks, unnecessary movement, and rework.
Improving layout, slotting, and picking arrangements.
Addressing inventory discrepancy root causes.
Standardizing transaction recording and exception handling.
Assigning improvement owners and measurable targets.
Monitoring results and sustaining operational improvements.

Module 12: Capstone — Warehouse Operations and Inventory Improvement Plan

Review a warehouse scenario containing layout, transaction, inventory, and performance information.
Identify weaknesses across receiving, put-away, storage, picking, and dispatch.
Recommend appropriate FIFO or FEFO controls.
Develop a cycle counting and inventory reconciliation plan.
Propose controls to reduce shrinkage and improve traceability.
Select relevant KPIs and define their calculation and reporting requirements.
Produce a prioritized improvement plan with responsibilities and expected outcomes.

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