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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.

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Constructing Grounded Theory

Kathy Charmaz · 2014

In a sentence

A practical guide for qualitative researchers on how to use constructivist grounded theory methods to systematically analyze data and construct original theories from the ground up.

For researchers and students drowning in qualitative data, "Constructing Grounded Theory" offers a clear, practical, and systematic journey from data collection to a finished theoretical analysis. Author Kathy Charmaz, a leading voice in the field, demystifies the research process by providing flexible, step-by-step guidelines for coding, memo-writing, theoretical sampling, and integrating a final theory. Moving beyond the original objectivist approach, this book champions a constructivist perspective, teaching you not just to discover theory but to actively construct it through your engagement with the data. Filled with concrete examples and practical strategies, this guide empowers you to move beyond mere description, manage your analytic process with confidence, and produce an original, insightful, and credible contribution to your field.

The four lenses

Science
Statistics
Systems
Strategy

The model

This model represents the core process of constructing a grounded theory as described by Charmaz. It posits that the application of specific Grounded Theory Practices leads to a state of Analytic Abstraction, which in turn determines the quality of the final theoretical product. The practices are the procedural levers, the abstraction is the key mediating process, and quality is the ultimate outcome.

Application of Grounded Theory Practicesdesign lever

The systematic and flexible application of core grounded theory methods, including the iterative cycle of data collection and analysis, the constant comparative method, and strategic theoretical sampling to achieve saturation of categories.

Analytic Abstractionpsychological state

The researcher's cognitive and behavioral process of moving from concrete data to abstract concepts. This is achieved through the practices of initial and focused coding to fracture and categorize data, and memo-writing to explore, develop, and integrate these categories into a coherent conceptual framework.

Grounded Theory Qualityoutcome metric

The degree to which the final constructed theory meets the criteria of Credibility (fit with the data, strong evidence), Originality (fresh insights, new conceptualization), Resonance (portrayal of the experience, makes sense to participants), and Usefulness (applicability, sparks further research, contributes to knowledge).

How they connect

grounded theory practices → influences analytic abstraction
analytic abstraction → predicts grounded theory quality

The story

The reader A qualitative researcher (student or professional) who has gathered rich data and wants to produce a rigorous, insightful, and original theoretical analysis, rather than just a simple description.

External problem

The researcher faces a mountain of qualitative data (interviews, field notes, texts) and lacks a clear, systematic process for analyzing it to develop a coherent, defensible theory.

Internal problem

They feel overwhelmed, uncertain, and anxious about the analytic process, fearing their work will be seen as impressionistic, unsystematic, or superficial, and that they will fail to produce a significant contribution.

Philosophical problem

It's wrong that researchers with valuable data should be stuck in descriptive summaries or forced to impose pre-existing theories because they lack practical guidance for developing their own original, data-driven theories.

The plan

Gather Rich Data: Learn to collect detailed and full data through methods like intensive interviewing and ethnography.
Code the Data: Master the systematic practices of initial and focused coding to break down and conceptualize the data.
Write Analytic Memos: Use memo-writing as a pivotal step to develop ideas, explore categories, and build the analysis.
Sample, Saturate, and Sort: Employ theoretical sampling to refine categories until they are saturated, then sort memos to integrate the theory.
Reconstruct and Write the Theory: Learn to move from analysis to writing the final draft, including constructing arguments and positioning the work.

Success

The researcher transforms their raw data into a coherent, insightful, and original grounded theory.
They feel confident, competent, and in control of their analytic process.
Their work is recognized as a rigorous and significant contribution to their field.

At stake

The researcher remains stuck with descriptive, unsystematic analysis, and their project feels overwhelming and directionless.
They produce a superficial report that fails to realize the potential of their data.
Their work makes little impact and is seen as impressionistic rather than theoretically robust.

Questions this book answers

How can qualitative researchers systematically analyze their data to develop an original, data-driven theory?
What are the practical, step-by-step practices of grounded theory, from gathering rich data to writing the final draft?
How does a constructivist approach to grounded theory, which sees theory as co-created by the researcher, differ from traditional, objectivist versions?
What are the core techniques of coding (initial and focused), memo-writing, and theoretical sampling, and how do they work together to build an analysis?
How can a researcher move from concrete data and descriptive summaries to an abstract, integrated, and compelling theoretical framework?

Glossary

Application of Grounded Theory Practices: The systematic and flexible application of core grounded theory methods, including the iterative cycle of data collection and analysis, the constant comparative method, and strategic theoretical sampling to achieve saturation of categories.
Analytic Abstraction: The researcher's cognitive and behavioral process of moving from concrete data to abstract concepts. This is achieved through the practices of initial and focused coding to fracture and categorize data, and memo-writing to explore, develop, and integrate these categories into a coherent conceptual framework.
Grounded Theory Quality: The degree to which the final constructed theory meets the criteria of Credibility (fit with the data, strong evidence), Originality (fresh insights, new conceptualization), Resonance (portrayal of the experience, makes sense to participants), and Usefulness (applicability, sparks further research, contributes to knowledge).

Tools these methods power