What is PeopleAnalyst?

PeopleAnalyst is the front door for people-analytics research: 205+ works indexed and profiled, 40+ citation-grade findings extracted, and peer-reviewed behavioral science translated from academic to actionable — the missing manual for the people analytics you always meant to do.

What is people analytics?

People analytics is not a dashboard. It is behavioral science and statistical inference applied to workforce decisions — a discipline with its own methodology, spanning measurement, organizational design, talent, leadership, and analytics craft.

Why does AI in HR need measurement science?

AI is being deployed in high-stakes people decisions — hiring, performance, attrition — without the measurement science to evaluate whether it works or whom it harms. Construct validity, effect sizes, and criterion validity are the vocabulary for asking an AI vendor the right questions.

How is the research made accessible?

The evidence is indexed and searchable: 205+ works, 40+ citation-grade insight cards, and 8 research arcs, so the right finding reaches the right decision at the right time.

What separates good people measurement from assertion?

Good measurement has a method: construct validity, reliability, and effect-size interpretation are not optional — they are what separates evidence from assertion.

library / lib0fa999301038ed7d

The basic principle of people analytics learn how to use hr data to drive better outcomes for your business and employees

Erik van Vulpen · 2016

In a sentence

A practical primer that demystifies people analytics and shows HR professionals how to use workforce data to make better, evidence-based decisions that drive business and employee outcomes.

The Basic Principles of People Analytics is an accessible, example-rich introduction to applying data science to HR. Erik van Vulpen strips away the theory-heavy jargon that intimidates HR professionals and instead walks readers through what people analytics is, why it matters, and how to actually do it. Grounded in stories like Google's discovery that its interviews didn't predict performance and Credit Suisse saving up to $100 million by reducing turnover, the book lays out a maturity model, the multidisciplinary team skillsets required, and a five-step analytics process cycle—from asking the right business question to interpreting and executing on results. It is the ideal starting point for anyone looking to move HR beyond static reporting toward a fact-based discipline that finally quantifies its impact and earns a strategic seat at the table.

The four lenses

Science
Statistics
Systems
Strategy

The model

A framework linking the design levers and conditions of a people analytics capability (business alignment, team skillsets, data quality, maturity) to intermediate analytical and decision states, and ultimately to organizational outcomes such as better decisions, business impact, and HR strategic influence.

Business Priority Alignmentdesign lever

The degree to which a people analytics effort is connected to one of the organization's top strategic business priorities rather than to interesting but irrelevant HR topics.

Team Skillset Completenessdesign lever

The extent to which the analytics team possesses the five required capability contexts—business, marketing, HR, data analytics, and IT—needed to select, analyze, communicate, and act on people data effectively.

Data Qualitycontextual condition

The validity, reliability, completeness, and cleanliness of the HR data used for analysis, including consistency of labels, absence of duplicates, up-to-date records, and freedom from bias and outliers.

Analytics Maturity Levelcontextual condition

The organization's developmental stage of people analytics capability, ranging from operational reporting to advanced reporting, statistical analytics, and predictive/prescriptive modeling.

Analytical Capabilitypsychological state

The organization's practical ability to combine data from multiple systems and apply appropriate descriptive, predictive, and prescriptive techniques to generate valid, decision-relevant insights.

Actionable Insight Communicationbehavioral pattern

The extent to which analytical results are translated, visualized, and marketed into simple, actionable recommendations delivered in a way that prompts managers to take action.

Reduced Human Bias in Decisionspsychological state

The degree to which decision-making relies on evidence and structured data rather than gut feeling, unconscious bias, self-fulfilling prophecies, and the fundamental attribution error.

Decision Qualityoutcome metric

The accuracy and effectiveness of people-related decisions made by the organization, such as hiring, retention, compensation, and workforce planning choices.

Business Impactoutcome metric

The tangible organizational value created by people analytics, including cost savings, reduced turnover and absenteeism, improved performance, and competitive advantage.

HR Strategic Influenceoutcome metric

The extent to which HR is recognized as a strategic business partner with a seat at the decision-making table, able to influence business decisions using data.

How they connect

business priority alignment → predicts business impact
team skillset completeness → predicts analytical capability
data quality → influences analytical capability
analytics maturity → predicts analytical capability
analytical capability → predicts decision quality
reduced human bias → predicts decision quality
analytical capability → influences reduced human bias
actionable insight communication → mediates business impact
analytical capability → predicts actionable insight communication
decision quality → predicts business impact
business impact → predicts hr strategic influence
business priority alignment → moderates actionable insight communication

The story

The reader An HR professional or leader who wants to move beyond static reporting and use workforce data to make better decisions and earn a strategic seat at the table.

External problem

HR holds valuable people data but lacks the process, skills, and confidence to turn it into evidence-based decisions that impact the business.

Internal problem

They feel confused about where to start, intimidated by statistics, and afraid HR will remain a low-impact support function.

Philosophical problem

People are a company's most valuable and most expensive asset, so it is just plain wrong to manage them on gut feeling while every other department runs on data.

The plan

Understand what people analytics is and why it matters.
Assess your organization's analytics maturity level.
Assemble a team with the five required skillsets or partner for missing capabilities.
Ask the right question tied to a top business priority.
Select, clean, and analyze the relevant data.
Interpret results in context and execute with well-communicated, actionable recommendations.
Repeat the cycle, securing quick wins along the way.

Success

HR becomes a data-driven, strategic business partner that quantifies and proves its impact.
Better hiring, retention, and people decisions save money and build competitive advantage.
Work is made better for employees through fairer, evidence-based policies.

At stake

HR remains a low-impact support function seen as a fee burner.
Expensive decisions are made on biased gut feeling, wasting time and money.
Analytics efforts become an irrelevant, short-lived fad that adds no business value.

Questions this book answers

What is people analytics and how does it differ from traditional HR?
Why is people analytics important for HR and the business?
What skills and team capabilities are required to do analytics in HR?
How mature is my organization's analytics capability and how do I advance it?
What is the step-by-step process for running a people analytics project?

Glossary

Business Priority Alignment: The degree to which a people analytics initiative is tied to one of the organization's top strategic business priorities rather than an interesting but irrelevant topic.
Team Skillset Completeness: The extent to which an analytics team collectively holds the five capability contexts required for effective people analytics.
Data Quality: The validity, reliability, completeness, and cleanliness of the HR data used in analysis.
Analytics Maturity Level: The developmental stage of an organization's people analytics capability across a four-level model.
Analytical Capability: The practical ability to combine data and apply appropriate techniques to generate valid, decision-relevant insights.
Actionable Insight Communication: The extent to which analytical results are translated, visualized, and marketed into simple, actionable recommendations that prompt action.
Reduced Human Bias in Decisions: The degree to which decisions rely on evidence rather than gut feeling and cognitive biases.
Decision Quality: The accuracy and effectiveness of people-related decisions the organization makes.

Related in the library

Tools these methods power

Answers grounded in this book

What is the step-by-step people analytics process?The consistent first move across the practitioner primers is counterintuitive: start with a business priority or a hypothesis, not with the data (van Vulpen). Then choose data appropriate to the level of analysis and the context, rely on evidence over gut feeling to reduce bias, and never read correlation as causation without weighing context. Fitz-enz's four-phase frame — scan, plan, produce, predict — puts the same discipline in motion: anticipate tomorrow's questions today, and build an integrated measurement system that links leading indicators such as engagement and leadership to operational and financial outcomes rather than reporting metrics in isolation. The process is a loop from question to decision, not a pipeline from data to chart.

All evidence-based answers →