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.

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Business Intelligence and Big Data

In a sentence

A scholarly synthesis arguing that organizational success in the digital age depends on building Business Intelligence and Big Data (BI&BD) capabilities to convert data into knowledge, value, and competitive advantage.

Business Intelligence and Big Data: Drivers of Organizational Success makes the case that in a turbulent, information-saturated economy, intangible resources—information and knowledge—are an organization's most strategic assets, and that the ability to intelligently process and analyze them is the key competence separating winners from losers. Drawing on resource-based and dynamic-capabilities theory, knowledge management, and decades of decision-support research, Celina Olszak walks readers through the essence and architecture of BI systems, the techniques and technologies of Big Data, concrete application domains (marketing, CRM, insurance, banking, telecommunications, energy, logistics, health care, HR), and the maturity models and critical success factors that determine whether BI&BD investments actually create business value. It is at once a textbook for students, a research agenda for scholars, and a practical handbook for managers and ICT specialists who want to know not just what BI&BD can do but what determines its successful design, implementation, and value creation.

The four lenses

Science
Statistics
Systems
Strategy

The model

A path model in which design levers (ICT/BI&BD investment, governance, technology) and contextual conditions (environmental turbulence, analytical/learning culture, human skills) drive psychological and behavioral states (analytical capability, knowledge discovery, decision quality) that in turn produce outcomes such as business value, competitive advantage, and organizational success.

BI&BD Technology Investment and Capabilitydesign lever

The organization's investment in and deployment of Business Intelligence and Big Data infrastructure, tools, and technologies (data warehouses, ETL, OLAP, mining, NoSQL, Hadoop) used to collect, integrate, and analyze data.

Environmental Turbulence and Information Flow Complexitycontextual condition

The degree of change, competition, information excess, and uncertainty in the organization's external environment that creates pressure to anticipate and respond quickly to market signals and stakeholder demands.

Fact-based Analytical and Learning Culturecontextual condition

The organizational culture, leadership support, values, and norms that encourage gathering, analyzing, sharing, and acting on information and knowledge, including openness to change, creativity, and information-based competition.

Human Analytical and Knowledge Skillsdesign lever

The technical, statistical, business, communication, and entrepreneurial skills of employees and managers that enable effective use of BI&BD, including data science competences and willingness to share knowledge.

BI&BD Governance and Strategic Alignmentdesign lever

Mechanisms for managing BI&BD resources, aligning BI&BD initiatives with business strategy, management support and sponsorship, clear vision, and a deliberate data-exploration strategy.

Analytical Capability and Knowledge Discoverypsychological state

The organization's enacted capacity to explore and exploit data—sensing opportunities, mining and analyzing data, and discovering new, previously unknown knowledge and patterns to inform action.

Decision-Making Quality and Speedbehavioral pattern

The improvement in the efficiency, timeliness, accuracy, and breadth of decisions made at operational, tactical, and strategic levels as a result of BI&BD-supported information and knowledge.

Big Data-Based Business Value Creationoutcome metric

The economic and social value derived from BI&BD use, including innovative products and services, optimized processes, improved customer relations, new business models, and risk reduction.

Organizational Success and Competitive Advantageoutcome metric

The ultimate outcome of sustained competitive advantage, organizational efficiency, profitability, and market position achieved through effective use of information, knowledge, and BI&BD.

How they connect

bibd investment → predicts analytical capability
human analytical skills → predicts analytical capability
governance strategy → predicts analytical capability
analytical learning culture → moderates analytical capability
analytical capability → predicts decision quality
decision quality → predicts business value creation
analytical capability → mediates business value creation
business value creation → predicts organizational success
environmental turbulence → moderates business value creation
governance strategy → influences business value creation

A candidate measure

Business Intelligence and Big Data — derived measurement candidates