Data-Driven HR
Bernard Marr · 2018
A practical guide showing HR professionals how to harness big data, analytics, AI, and connected technologies to transform every core HR function and add strategic value to their organizations.
Human resources has long been one of the most data-rich yet insight-poor functions in any organization, spending its time on administrative tasks while relying on gut instinct for people decisions. In Data-Driven HR, Bernard Marr shows how the explosion of data, the Internet of Things, machine learning, and AI are turning HR into an intelligent, strategic discipline that drives performance across the entire business. Packed with real-world examples from Google, Xerox, IBM, UPS, Marriott, and many others, the book walks readers through building a robust data strategy, sourcing and analysing HR-relevant data, and applying analytics to recruitment, employee engagement, safety and wellness, learning and development, and performance management—all while navigating privacy, ethics, and transparency. Written in a friendly, non-technical style for HR professionals who never intend to become data scientists, it is a hands-on manual for adding measurable value and preparing for the future of work.
The model it argues
A causal model in which strategic design levers (data strategy, data sourcing, analytics capability, governance, and automation) drive psychological and behavioral states in employees and HR teams (engagement, wellbeing, trust) and behavioral patterns (data-driven decision making), which in turn produce outcomes such as recruitment quality, retention, safety, learning effectiveness, and organizational performance.
Key ideas
- HR Data Strategy Alignment
- The presence and quality of a clear, focused HR data strategy that maps across the four layers of data and is directly linked to wider organizational objectives.
- HR-Relevant Data Sourcing Breadth
- The extent to which HR captures and combines the relevant internal/external and structured/unstructured data types needed to answer strategic people questions.
- HR Analytics Capability
- The organization's ability to convert data into actionable insights using a range of analytics techniques and HR-specific analytics.
- Data Governance and Transparency Quality
- The quality of privacy, consent, ethical transparency, minimization, anonymization, and security practices governing employee data.
- HR Automation and AI Adoption
- The extent to which HR uses AI, machine learning, chatbots, and intelligent assistants to automate administrative and repetitive tasks.
- Employee Trust and Buy-in
- The degree to which employees trust how their data are used and accept data-driven HR initiatives.
- Data-Driven Decision Making
- The behavioral pattern of HR and leaders basing people decisions on data and evidence rather than gut instinct.
- Employee Engagement and Satisfaction
- The extent to which employees feel happy, satisfied, engaged, and committed to the organization.