LIVE ONLINE COURSE

HUMAN RESOURCES ANALYTICS

Name: Human Resources Analytics
Rating: 5 (4 reviews)

Dates: 21 JAN 2027 -
2 MAR 2027

DURATION: 6 WEEKS
TUESDAYS & THURSDAYS
5 PM PT / 8 PM ET

This program has been pre-approved for 18 Business
recertification credit hours toward aPHR®, aPHRi™, PHR®, PHRca®, SPHR®, GPHR®, PHRi™ and SPHRi™ recertification through HR Certification Institute® (HRCI®).

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BRIAN COSTELLO
IBM

LIVE ONLINE COURSE

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Turn raw, messy HR data into a board-ready business case that proves the financial ROI of your people strategy and earns approval from the C-Suite.

Brian Costello, Manager of People Science at IBM with a PhD in Psychology, shows you how to let AI handle the statistics so you can deliver insights leadership acts on.

THIS COURSE IS FOR YOU, IF...

YOU ARE AN HR MANAGER OR BUSINESS PARTNER

You have plenty of HR data but lack the statistical confidence to prove ROI. This HR analytics course teaches hypothesis testing, KPI alignment, and descriptive stats, with an AI co-pilot doing the statistical heavy lifting for you. You'll meet the "Burden of Proof" in every C-Suite conversation and back your initiatives with numbers leadership trusts.
YOU ARE A DATA ANALYST IN HR

Your dashboards and predictive models get ignored because they miss the human context. Through the Executive Simulation workshop and hands-on data storytelling, this HR analytics training will teach you to translate statistical outputs into business language and cognitive visual design. You'll deliver analysis leadership acts on, with optional code-based extra credit assignments to push your technical skills further.
YOU ARE A TALENT ACQUISITION OR OD CONSULTANT

Gut feel and lagging metrics like time-to-fill keep you one step behind workforce problems. This HR data analytics course covers logistic regression interpretation, AI capability mapping, and the full HR analytics lifecycle through hands-on predictive workshops. You'll forecast turnover, optimize hiring funnels, and track sentiment with prescriptive analytics.

HANDS-ON AI WORKFLOWS

Every class in this human resource analytics course puts an AI co-pilot to work on real HR problems, from the AI Predictive Sandbox to a full "Frankenstein" dashboard makeover. Six assignments produce reusable assets, including a KPI tracker, a bias audit, and a Red-Team CFO defense. You'll leave with a workflow you can run on your own data right away.

INSIDE REAL PEOPLE ANALYTICS

Five case studies show what works and what backfires at scale, including Amazon's biased AI recruiting engine, IBM's attrition model, and Google's Project Oxygen. Guest speakers from Procter & Gamble, Netflix, and Nestlé share how people analytics runs inside global organizations. You'll see how leading teams win executive buy-in.

A BOARD-READY BUSINESS CASE

Your final project is a C-Suite Business Case built on a provided dataset or your own anonymized organizational data. It combines a cleaned dataset, an AI-interpreted predictive model, an interactive dashboard, and a quantified ROI report. It proves you can take a workforce challenge from raw data to boardroom approval.

BRIAN COSTELLO LinkedIn Profile

Holds a PhD in Psychology, specializing in psychometrics and advanced data science
Leads data science and analytics initiatives that connect statistical modeling to executive-level HR strategy
Pioneered the "AI Co-Pilot" methodology, moving People Analytics teams from headcount reporting to AI-augmented advisory
Presents regularly at the Society for Industrial and Organizational Psychology (SIOP) on psychometrics and validity analyses
Engineered machine learning models predicting time-to-fill, paired with time-series forecasting for attrition and hiring
Directed the end-to-end migration of dual data warehouse ecosystems supporting global data science operations

TUE (1/19), 5 PM PT/8 PM ET

Welcome Class

Meet Brian Costello, get oriented with the course structure, and preview the six assignments and final project that will shape your work over the next six weeks.

Meet your instructor
Course structure
Assignments and final project

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THU (1/21), 5 PM PT/8 PM ET

Introduction to HR Analytics & The "AI Co-Pilot"

Discover how AI levels the playing field in HR analytics as you shift from manual data puller to strategic business partner who brings human context to every calculation.

HR analytics lifecycle
The #ToolsAreNotTrends philosophy
Generative AI in HR
Bridging HR context and data mechanics
Workshop: The "Resonation vs. Evidence" Audit, using AI to challenge a VP's gut-feeling turnover theory

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TUE (1/26), 5 PM PT/8 PM ET

Key HR Metrics & Business Alignment

Learn to tie foundational HR data points directly to C-Suite goals, then automate your basic spreadsheet workflows by prompting an LLM for the exact formulas you need.

Aligning metrics with organizational goals
Retention and offer acceptance focus areas
Basic tracking in Excel and Google Sheets
AI-assisted spreadsheet building
Workshop: The AI-Prompted KPI Tracker Build in Excel

Assignment #1: The AI-Prompted KPI Tracker
Use ChatGPT or Claude to build a working 5-metric HR KPI tracker, and document the exact prompts you used to refine the AI's output.

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THU (1/28), 5 PM PT/8 PM ET

Ethical Use of HR Data & Algorithmic Bias

Develop a critical executive eye for the legal, ethical, and reputational risks of AI-augmented HR, from data privacy law to the hidden bias inside "black box" algorithms.

Data privacy and protection (GDPR/CCPA)
Data security in an AI-driven world
Mitigating bias in "black box" algorithms
Ethical dilemmas like productivity tracking
Case study: Amazon's AI recruiting engine
Workshop: The "Black Box" Bias Audit of a flawed resume screening output

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TUE (2/2), 5 PM PT/8 PM ET

Data Governance & Navigating HR Data Siloes

Master the groundwork of safe analysis by learning to source, standardize, and govern messy, siloed organizational data so every insight you deliver rests on data you can trust.

Fragmented HR tech stacks
Data governance basics
Access protocols at scale
Preparing raw HR data for analysis
Workshop: Messy Data Triage, writing a standardization rule-set for a siloed HR CSV

Assignment #2: The Data Governance & Bias Audit
Audit a flawed dataset from a mock AI resume screening tool, pinpoint the data silos and bias, and recommend a privacy fix before it scales.

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THU (2/4), 5 PM PT/8 PM ET

Core Analytical Concepts (Without the Math Anxiety)

Explore when to apply each statistical test and how to meet the "Burden of Proof," with AI handling the calculations while you focus on what the results mean for the business.

Descriptive statistics
Hypothesis testing with ANOVA and t-tests
Correlation vs. causation
Translating statistical significance into business risk
Workshop: The "Burden of Proof" Translation into a jargon-free executive summary

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TUE (2/9), 5 PM PT/8 PM ET

Workshop: The Executive Simulation

Practice translating complex statistical findings into a clear business case as you test a panicked VP's gut-feel turnover theory on a mini-dataset and draft a recommendation live.

Framing an executive HR crisis
Running statistical tests with an AI co-pilot
Interpreting raw data outputs
Drafting strategic recommendations
Case study: Google's Project Oxygen
Demo: AI output validation

Assignment #3: The "Burden of Proof" Executive Memo
Run an ANOVA or t-test on engagement data with an AI co-pilot, then translate the result into a 1-page plain-English memo for a skeptical VP.

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THU (2/11), 5 PM PT/8 PM ET

Predictive Analytics in HR

Understand the business mechanics of forecasting workforce challenges, using regression and leading indicators to spot costly issues early and frame predictive ROI for the board.

Linear vs. logistic regression
Leading vs. lagging indicators
Predicting turnover risk and hiring outcomes
Framing predictive ROI for the board
Workshop: Leading vs. Lagging Indicator Mapping for 90-day onboarding failure

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TUE (2/16), 5 PM PT/8 PM ET

Workshop: The AI Predictive Sandbox

Execute and interpret a complex predictive model entirely through AI prompting, then put your energy into the strategic HR intervention your strongest predictors point toward.

Prompting for logistic regression
Extracting feature importance
Formulating an intervention plan
Peer review of intervention strategies
Case study: IBM's proactive attrition model
Workshop: The AI Predictive Sandbox with an onboarding retention dataset

Assignment #4: The Predictive Intervention Plan
Run a logistic regression on an onboarding retention dataset with your AI co-pilot, and build an intervention plan around the top 3 predictors.

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THU (2/18), 5 PM PT/8 PM ET

Visualizing HR Data Effectively + Guest Speaker

Design streamlined, tool-agnostic dashboards that cut the jargon and tell a single business story, choosing the right visual for each executive stakeholder you need to win over.

Cognitive visual design principles
Choosing visuals for executive stakeholders
Reducing dashboard clutter
AI-enhanced insights with Power BI Copilot
Case study: Microsoft Viva Insights
Workshop: The Cognitive Design Tear-Down of a "Frankenstein" dashboard

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TUE (2/23), 5 PM PT/8 PM ET

Workshop: Dashboard Buildout & Storytelling

Build an interactive, executive-ready dashboard by rebuilding a "Frankenstein" dashboard in Excel, Power BI, or Tableau, then use AI to draft the manager briefing that goes with it.

Step-by-step dashboard makeover
Filters and visual hierarchies
AI-drafted manager briefings
Live peer critique
Workshop: Dashboard Makeover Build

Assignment #5: The Cognitive Dashboard Makeover
Rebuild a cluttered HR dashboard in Power BI, Excel, or Tableau into a streamlined executive version that tells one cohesive business story.

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THU (2/25), 5 PM PT/8 PM ET

AI Capability Mapping & Scale

Gain a C-Suite framework for deciding when a free AI tool will do the job and when a multi-million-dollar enterprise HR system is worth the investment.

Mapping AI capabilities to the HR lifecycle
The "Build vs. Buy / Scale" framework
Enterprise AI tools like HireVue and Eightfold vs. localized LLMs
Mitigating large-scale implementation risks
Case study: Unilever's digitized recruitment pipeline
Workshop: The "Build vs. Buy" Debate on an AI sentiment analysis vendor pitch

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TUE (3/2), 5 PM PT/8 PM ET

Communicating Insights & Career Reverse-Engineering

Finalize your C-Suite Business Case, defend it against executive pushback, and walk away with the exact playbook hiring managers use to select analytics leaders.

AI as an adversarial "Red Team" CFO
Presenting final project ROI cases
Interview reverse-engineering
Personal branding in the AI era
Group discussion: Winning stakeholder buy-in for people analytics
Workshop: The "Red-Team" CFO Defense

Assignment #6: The "Red-Team" CFO Defense
Prompt an AI to play a cynical CFO against your final project recommendation, then build a data-backed defense to its top 3 objections.

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