# HR Analytics Training for HR Teams

> HR analytics training that teaches HR teams to clean HRIS data, build Power BI dashboards and explain attrition with evidence. Plan your program now.

- Source: https://bodhih.com/hr-analytics-training/
- Publisher: Bodhih Training (Bengaluru, India; since 2008)
- Last updated: 2026-10-15
- Contact: solutions@bodhih.com · +91 99000 11601

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This HR analytics training teaches HR teams to turn messy HRIS exports into clear answers. Participants clean data, build dashboards in Excel and Power BI, analyse attrition and hiring, and present findings that leaders can act on, without needing to code.

## At a glance

- **Duration:** Recommended: 3 days in person, or 6 x 3-hour live virtual labs, customised to your data and tools
- **Who it’s for:** HRBPs, HR operations, talent acquisition, rewards and HR MIS teams
- **Level:** Intermediate
- **Format:** In person · Live virtual · Blended
- **Track record:** Since 2008 · 2,000+ companies

HR analytics training is a hands-on program that teaches HR professionals to clean, analyse and present people data without coding. It covers core HR metrics, Excel and Power Query data cleaning, Power BI dashboards, attrition and hiring analysis, survey analytics and DPDP data privacy. Bodhih runs it over 3 days in person or six 3-hour live virtual labs.

- Recommended: 3 days in person, or 6 x 3-hour live virtual labs, customised to your data and tools
- Level: Intermediate · In person · Live virtual · Blended
- Designed with the ADDIE model and customised to your context
- Offered by Bodhih since 2008 to 2,000+ organisations across 7 regions

**Also known as:** people analytics training, HR analytics course, HR analytics workshop, HR data analysis training

**Where and how:** HR analytics training as an in-person workshop in [Bengaluru](https://bodhih.com/corporate-training-in-bangalore/), [Mumbai](https://bodhih.com/corporate-training-in-mumbai/), [Delhi NCR](https://bodhih.com/corporate-training-in-new-delhi/), [Gurugram](https://bodhih.com/corporate-training-in-gurugram/), [Hyderabad](https://bodhih.com/corporate-training-in-hyderabad/), [Chennai](https://bodhih.com/corporate-training-in-chennai/), [Pune](https://bodhih.com/corporate-training-in-pune/), [Kolkata](https://bodhih.com/corporate-training-in-kolkata/), [Ahmedabad](https://bodhih.com/corporate-training-in-ahmedabad/) and [Jaipur](https://bodhih.com/corporate-training-in-jaipur/); as a live online course; or delivered overseas in [Dubai](https://bodhih.com/corporate-training-in-dubai/), [Singapore](https://bodhih.com/corporate-training-in-singapore/) and across the Middle East, Asia and Africa.

Last reviewed 15 Oct 2026 by [Siddharthan VGJ](https://bodhih.com/siddharthan-vgj/), Founder · Bodhih Training, Bengaluru

## Why HR teams are learning analytics now

Leaders now ask HR the same questions they ask finance: what is happening, why, and what will it cost? Teams that answer with a spreadsheet dump lose the room, while teams that answer with a clear chart and a recommendation gain influence.

Data rules have also tightened. India's Digital Personal Data Protection Rules put new obligations on how employee data is handled, so hr analytics training must cover privacy alongside [Power BI](https://bodhih.com/power-bi-training/).

> India notified the DPDP Rules on 14 November 2025, with an eighteen-month period for phased compliance.

Source: [Press Information Bureau, Government of India](https://static.pib.gov.in/WriteReadData/specificdocs/documents/2025/nov/doc20251117695301.pdf)

## What participants will be able to do

### Speak in metrics

Define and calculate attrition, time to fill, offer acceptance, internal mobility and span of control consistently.

### Clean data with confidence

Use Power Query to combine and clean HRIS exports so every report starts from one trusted table.

### Build a live dashboard

Create an interactive Power BI or Excel dashboard that a business leader can read in two minutes.

### Explain attrition

Break attrition down by tenure, manager, band and location to find where and why people leave.

### Analyse surveys properly

Turn engagement and exit survey results into driver analysis and a short list of actions.

### Handle data responsibly

Apply consent, minimisation and access controls so analytics work stays aligned with privacy obligations.

## Who should attend

- HRBPs who need to bring evidence into business reviews
- HR operations and HR MIS teams who produce monthly reports
- Talent acquisition teams tracking funnels, sources and quality of hire
- Rewards and total rewards teams working with pay and benefits data
- L&D teams who want to link learning data with performance and retention
- HR leaders building a people analytics function in a GCC or large enterprise

## Program outline

Recommended design, customised to your context after a short needs analysis.

### **Foundations of people analytics**Module 1 · 2 hours

- The four levels: descriptive, diagnostic, predictive and prescriptive
- Starting from a business question rather than a data set
- Exercise: rewriting five vague requests into testable questions

### **HR metrics that matter**Module 2 · 3 hours

- Standard formulas for attrition, regretted attrition, time to fill and cost per hire
- Headcount, spans and layers, and internal mobility rates
- Building a metrics dictionary your whole HR team uses

### **Data cleaning with Excel and Power Query**Module 3 · 3 hours

- Combining HRIS, payroll and ATS exports into one model
- Fixing dates, duplicates, missing values and inconsistent job titles
- Lab: preparing a two-year employee data set for analysis

### **Dashboards in Power BI**Module 4 · 3 hours

- Data model basics, relationships and simple DAX measures
- Designing a one-page HR dashboard with filters by location and band
- Publishing and access control for sensitive views

### **Attrition and hiring deep dive**Module 5 · 3 hours

- Cohort and survival views of early attrition
- Manager-level and tenure-level patterns, plus a first look at correlation and regression
- Case exercise: explaining a spike in first-year exits at a GCC

### **Survey and text analytics**Module 6 · 2 hours

- Driver analysis on engagement and employee recommendation score results
- Using [generative AI](https://bodhih.com/generative-ai-training/) to theme open comments, with human checks
- Avoiding common traps with small samples and anonymity thresholds

### **Storytelling, ethics and privacy**Module 7 · 2 hours

- Structuring an insight: context, finding, implication and recommendation
- Privacy, consent and access principles for employee data under the DPDP framework
- Final presentation of each participant's analysis to a mock leadership panel

## Sample training plan: 3-day hands-on design

This three-day lab takes HR teams from messy exports to a dashboard and a recommendation a leader can act on. Participants work on their own laptops with a synthetic two-year employee data set built to mirror their HRIS. They agree metric definitions, clean and combine files in Power Query, build a one-page Power BI or Excel dashboard, investigate a spike in first-year exits, theme survey comments and present a real question from their own function to a mock leadership panel.

80% hands-on practice · 20.2 contact hours · Cohort: 12–20 participants, each with a laptop running Excel and Power BI Desktop · In person · Live virtual

### Day 1: Questions, metrics and clean data

Participants can frame a business question, calculate core HR metrics consistently and produce one clean analysis-ready table.

1. 09:30–10:00 · Guess the number (Energiser)
2. 10:00–11:00 · From request to question (Skill drill)
3. 11:15–11:45 · Four levels of analytics (Concept burst)
4. 11:45–13:00 · Build the metrics dictionary (Hands-on lab)
5. 13:45–14:45 · Combine the exports (Demo & practice)
6. 14:45–15:30 · Dirty data challenge (Hands-on lab)
7. 15:45–16:45 · First answers (Hands-on lab)
8. 16:45–17:30 · Data diary (Reflection)

### Day 2: Dashboards and diagnosis

Participants can build a one-page interactive dashboard and use it to explain where and why people are leaving.

1. 09:30–10:00 · Two-minute dashboard test (Energiser)
2. 10:00–11:00 · Data model and first measures (Demo & practice)
3. 11:15–13:00 · Build the one-page HR dashboard (Build sprint)
4. 13:45–15:15 · Case: the first-year exits spike (Case clinic)
5. 15:30–16:15 · Diagnosis face-off (Debate)
6. 16:15–16:45 · Secure the sensitive view (Hands-on lab)
7. 16:45–17:30 · Pick your capstone question (Reflection)

### Day 3: Surveys, privacy and the story

Participants can analyse survey results responsibly and present an analysis of their own question that ends in a clear recommendation.

1. 09:30–10:00 · Privacy spot check (Energiser)
2. 10:00–11:00 · Engagement driver analysis (Hands-on lab)
3. 11:15–12:00 · Theming open comments with AI (Demo & practice)
4. 12:00–13:00 · Capstone build, part one (Build sprint)
5. 13:45–14:30 · Context, finding, implication, recommendation (Skill drill)
6. 14:30–15:30 · Capstone: the leadership panel (Presentation)
7. 15:45–16:30 · Gallery of dashboards (Gallery walk)
8. 16:30–17:30 · My 90-day analytics plan (Action planning)

Recommended: 3 days in person (09:30–17:30), or 6 × 3-hour live virtual labs over three weeks, using anonymised data shaped around your HRIS, plus 30- and 60-day dashboard reviews. A sample design: every Bodhih program is customised after a short needs analysis.

### How long is HR analytics training?

The recommended design is three days in person, from 09:30 to 17:30, or six live virtual labs of three hours each over three weeks. A two-day foundations version suits HR teams new to data. Dashboard reviews at 30 and 60 days help teams put the work into regular use.

### What activities are included in HR analytics training?

It is lab-based from start to finish. Participants build a shared metrics dictionary, clean four messy HR exports in Power Query, build and user-test a Power BI dashboard, diagnose a spike in first-year exits at a GCC and present their own analysis to a mock leadership panel.

## How we deliver it

### Your questions, safe data

We build anonymised or synthetic data sets that mirror your HRIS fields, so labs feel real without exposing personal data.

### Lab-first design

Every concept is followed straight away by a hands-on exercise in Excel or Power BI on the participant's own laptop.

### Tool-agnostic thinking

Examples use exports from common HRIS platforms, and the logic transfers to whichever system your team uses.

### Capstone analysis

Participants finish with a real analysis on a question from their own function, reviewed by the trainer and peers.

## Tailored versions

### HR analytics foundations

A two-day version for HR teams new to data, focused on metrics, Excel and simple visual reports.

### For GCC people analytics teams

An advanced track covering Power BI data models, predictive attrition concepts and global reporting standards across regions.

## How we measure impact

Following the Evaluate phase of ADDIE, participants take a pre and post data skills assessment on AssessAll covering metrics, Excel and interpretation. We review each capstone dashboard against a clear rubric and check at 30 and 60 days whether it is in regular use. At 90 days we ask HR leaders which decisions the analysis supported and share a short impact summary with the program sponsor.

AA

Pair this program with [AssessAll](https://assessall.com), Bodhih’s AI assessment platform, for pre- and post-program skill measurement.

## Frequently asked questions

### What is HR analytics?

HR analytics is the practice of using people data to understand and improve workforce decisions. It ranges from basic reporting on headcount and attrition to diagnosing why problems occur and forecasting future needs. Good analytics always starts with a business question and ends with a recommendation that a leader can act on.

### What tools are used in HR analytics?

Most HR teams start with Excel and Power Query, then move to Power BI or Tableau for dashboards. Data usually comes from an HRIS, payroll system, applicant tracking system and survey tools. More advanced teams use [Python](https://bodhih.com/python-for-data-analysis-training/) or R for modelling. Our HR analytics training focuses on Excel and Power BI because they are widely available.

### Can HR professionals learn analytics without coding?

Yes. Most day-to-day HR analytics needs no coding. With Excel, Power Query and Power BI, HR professionals can clean data, calculate metrics, build dashboards and run simple statistical checks. We introduce Python only in the advanced track, for teams that want to go further into modelling and automation.

### How do you calculate attrition rate?

A common method divides the number of exits in a period by the average headcount for that period, then multiplies by 100. Many organisations also track voluntary, regretted and first-year attrition separately. The key is to agree one definition across HR, which is why the program includes building a shared metrics dictionary.

### Do participants need their own laptops and software?

Yes. Participants need a laptop with Excel, and ideally Power BI Desktop, which can be installed free on Windows. We share setup instructions and practice data before the program. For [live virtual](https://bodhih.com/live-virtual-classes/) batches, we recommend two screens so participants can watch the demo and work at the same time.

### How do you handle confidentiality of employee data?

We never ask for identifiable employee data. Labs use anonymised or synthetic data sets built to mirror your HRIS fields. The program also teaches privacy principles such as purpose limitation, minimisation and access control, so participants handle real data responsibly when they return to work.

### Can HR analytics training use our own HRIS reports?

Yes, in a safe way. During the Analyse phase we review the structure of your HRIS and payroll exports, then build anonymised practice files with the same fields and quirks. Participants learn on data that looks like theirs, so they can apply the same Power Query steps and dashboards to live reports the following week.
