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The Power of People - How Successful Organizations Use Workforce Analytics To Improve Business Performance
In a sentence
A practical, expert-informed guide to establishing, operating, and leading a workforce analytics function that uses people data to improve business performance.
The Power of People is the definitive practitioner's handbook for transforming HR from an intuition-driven, administrative function into an evidence-based, analytically powered driver of business value. Drawing on interviews with dozens of the world's leading workforce analytics practitioners, academics, and executives, the authors lay out a clear, repeatable approach to doing workforce analytics: framing business questions, building hypotheses, gathering and analyzing data, revealing insights, making recommendations, communicating through storytelling, and implementing and evaluating change. Through proprietary frameworks (the Eight Step Model for Purposeful Analytics, the Seven Forces of Demand, the Complexity-Impact Matrix, and the Six Skills for Success) and five detailed real-world case studies, the book shows how organizations can harness the latent power of their workforce data to predict outcomes, reduce attrition, grow sales, improve well-being, and increase profitability. If you want to build a workforce analytics capability that earns credibility and produces measurable impact, this book is your roadmap.
The four lenses
- Science
- Statistics
- Systems
- Strategy
Tags
The model
A causal-path model derived from the book asserting that design levers (analytics methodology, leadership, team skills, technology/data foundation, operating model, stakeholder engagement, storytelling) and contextual conditions (demand for analytics, analytical culture, resistance) shape psychological and behavioral states (analytical mindset, sponsor commitment, recommendation adoption) that produce outcomes (workforce outcomes such as retention/engagement and ultimately business performance).
Analytics Methodology Rigordesign lever
The degree to which a workforce analytics project follows a disciplined, purposeful methodology including framing business questions, building hypotheses, gathering data, conducting analyses, revealing insights, and determining recommendations.
Analytics Leadership Capabilitydesign lever
The capability of the workforce analytics leader, including business acumen, political astuteness, capacity to think, willingness to develop others, ability to inspire, and drive to achieve, as well as appropriate reporting access to the CHRO.
Team Skill Breadth (Six Skills for Success)design lever
The extent to which the analytics team has access to the six skill domains: business acumen, consulting, human resources, work psychology, data science, and communication, configured appropriately to project demands.
Data Quality and Governancedesign lever
The relevance, completeness, accuracy, currency, and governance of workforce data available for analysis, including data definitions, stewardship, and ethical/legal handling.
Technology Enablementdesign lever
The fit and capability of the technology stack (HRIS, data warehouse, reporting, statistical/machine learning, visualization, cognitive) to support the analytics vision and mission, including share/subscribe/own decisions.
Operating Model Maturitydesign lever
The degree to which the function has clear strategy alignment, governance, decision-making processes, defined roles and responsibilities, disciplined project management, and accountability mechanisms.
Stakeholder Engagementbehavioral pattern
The breadth and quality of relationships and two-way communication the analytics team maintains with served, depended-upon, and impacted stakeholders, including listening, translating, and helping them succeed.
Project Sponsor Commitmentpsychological state
The degree to which an influential, well-connected sponsor actively supports, resources, advocates for, and holds others accountable across the lifecycle of an analytics project.
Demand for Workforce Analytics (Seven Forces)contextual condition
The contextual pull for analytics arising from competitive edge, top-down requests, regulatory requirements, operational efficiency, cost pressure, humanistic concerns, and HR-for-HR needs.
Analytical Culture in HRpsychological state
The extent to which HR professionals and the broader organization embrace an analytical mindset, distributed along a spectrum from analytically savvy to willing to resistant, supported by leadership and translators.
Resistance to Workforce Analyticscontextual condition
Stakeholder skepticism, financial frugality, and HR hesitancy that impede the adoption and impact of workforce analytics.
Storytelling and Visualization Qualitybehavioral pattern
The effectiveness with which analytics insights are communicated through fact-based narrative and clear visualization tailored to audience to drive understanding and action.
Recommendation Adoption and Implementationbehavioral pattern
The degree to which insights are translated into accepted recommendations, decisions, and implemented organizational change.
Workforce Outcomesoutcome metric
Improvements in people-related outcomes such as retention/attrition, employee engagement, well-being, candidate quality, and time-to-productivity resulting from implemented analytics recommendations.
Business Performanceoutcome metric
Ultimate organizational results such as profitability, sales growth, cost reduction, and value to constituents that workforce analytics aims to improve.
How they connect
- demand for analytics → influences analytics methodology rigor
- analytics leadership capability → influences team skill breadth
- analytics leadership capability → predicts stakeholder engagement
- team skill breadth → predicts analytics methodology rigor
- data quality and governance → influences analytics methodology rigor
- technology enablement → influences analytics methodology rigor
- operating model maturity → influences analytics methodology rigor
- analytics methodology rigor → predicts recommendation adoption
- storytelling and visualization → predicts recommendation adoption
- stakeholder engagement → mediates recommendation adoption
- sponsor commitment → moderates recommendation adoption
- analytical culture → influences recommendation adoption
- resistance to analytics − moderates recommendation adoption
- recommendation adoption → predicts workforce outcomes
- workforce outcomes → predicts business performance
- analytical culture − influences resistance to analytics
A candidate measure
The Power of People - How Successful Organizations Use Workforce Analytics To Improve Business Performance — derived measurement candidates
Analytics Methodology Rigor
eight-step adherence audit score; percent of projects with sponsor-signed business question; percent of projects evaluated post-implementation
self-report suitability: medium
Analytics Leadership Capability
360-degree competency ratings; reporting-line proximity to CHRO; sponsorship secured per project
self-report suitability: medium
Team Skill Breadth (Six Skills for Success)
skills inventory coverage percentage; gap analysis results; ratio of specialists to project demand
self-report suitability: medium
Data Quality and Governance
percent missing values; outlier counts; data dictionary completeness; governance audit score
self-report suitability: low
Technology Enablement
technology capability checklist score; required vs available capability gap
self-report suitability: low
Operating Model Maturity
maturity rubric score; presence of governance framework; percent projects with business cases
self-report suitability: medium
Stakeholder Engagement
stakeholder engagement survey scores; communications plan completion rate; stakeholder attitude shift over time
self-report suitability: high
Project Sponsor Commitment
sponsorship behavior checklist; sponsor availability frequency; resources secured
self-report suitability: high
Demand for Workforce Analytics (Seven Forces)
count and emphasis of active forces; number of project requests by force
self-report suitability: medium
Analytical Culture in HR
distribution across savvy/willing/resistant categories; capability scan scores; attitude survey index
self-report suitability: high
Resistance to Workforce Analytics
resistance type/source assessment; count of blocked projects; skepticism survey items
self-report suitability: medium
Storytelling and Visualization Quality
audience comprehension test results; artifact quality rubric score; principle adherence (educate/enlighten/convince)
self-report suitability: medium
Recommendation Adoption and Implementation
percent recommendations accepted; percent implemented; time-to-implementation
self-report suitability: medium
Workforce Outcomes
voluntary attrition rate; engagement index; well-being incident rate; time-to-productivity
self-report suitability: medium
Business Performance
profitability percentage; revenue/sales growth; cost avoidance; project ROI
self-report suitability: none
The story
The reader An HR or business leader (or aspiring workforce analytics leader) who wants to improve business performance by using workforce data and analytics.
External problem
People decisions are made on intuition rather than evidence, and HR struggles to demonstrate measurable contribution to business outcomes.
Internal problem
The reader feels uncertain about where to start, lacks confidence in data and analytical methods, and fears being seen as non-strategic or non-analytical.
Philosophical problem
In a data-rich world, it is simply wrong to manage the organization's largest investment—its people—without rigorous, evidence-based analysis.
The plan
- Understand why workforce analytics matters and clarify what the function is called and where it reports.
- Set your direction by finding sponsors, identifying demand, and creating a vision and mission.
- Apply the Eight Step Model to run purposeful analytics projects with strong research design.
- Get a quick win, then build capability in data, technology, team skills, partners, and an operating model.
- Establish an analytics culture through enablement, overcoming resistance, and storytelling.
- Implement, evaluate, and continually communicate impact to drive lasting change.
Success
- HR makes evidence-based people decisions that demonstrably improve business performance.
- The analytics function earns credibility, secures sponsorship, and grows in scope and impact.
- The organization reduces attrition, grows sales, improves well-being, and increases profitability through people analytics.
- An analytical mindset becomes embedded across HR and the wider business.
At stake
- People decisions remain based on gut feel, leading to costly mistakes and missed opportunities.
- HR continues to be perceived as administrative and non-strategic, losing relevance.
- Competitors who embrace workforce analytics gain a sustained advantage.
- Analytics projects stall, lose sponsorship, and fail to drive any organizational change.
Chapter by chapter
ch08p01Engage with Stakeholders (part 1/2)
This chapter discusses the critical role of stakeholder engagement in workforce analytics, emphasizing how involving the right stakeholders can enhance project success and drive actionable insights.
- Stakeholder engagement is not just beneficial; it is essential for the success of workforce analytics projects.
- Strong project sponsors can provide essential resources and remove barriers, which is critical for project viability.
- Clear communication creates alignment between analytics initiatives and stakeholder expectations—this is fundamental to earning their trust and input.
- Engaging stakeholders early in the process helps ensure that analytics objectives align with business needs and strategic goals.
ch08p02Engage with Stakeholders (part 2/2)
Effective engagement with stakeholders is crucial in analytics projects; without it, even the best analyses can fail to drive actionable outcomes.
- Engagement with stakeholders is not just a formality; it is essential to the success of analytics projects.
- Effective storytelling and clear visualizations are vital for ensuring that insights lead to organizational buy-in and action.
- A strong partnership with the right sponsors can propel analytics projects forward and enhance their impact.
- Anticipating common project pitfalls can significantly increase the likelihood of successful analytics implementations.
ch11Get a Quick Win
In establishing workforce analytics within an organization, choosing a first project that delivers high impact with manageable complexity is crucial for credibility and future success.
ch16p01Establish an Operating Model (part 1/2)
This chapter argues that establishing an effective operating model for workforce analytics hinges on understanding and managing data imperfections while promoting a culture of continuous learning and improvement within organizations.
- High data quality is crucial, but the aspiration for complete perfection can lead to paralysis—progress should be valued over inaction.
- The phrase 'garbage in, garbage out' highlights the importance of assessing data quality before analysis, revealing the need for foundational data practices.
- An iterative approach to analytics encourages adaptability and fosters resilience in the face of data challenges.
- Collaborating with subject matter experts enhances the understanding of data relevance and context, driving more informed analyses.
ch16p02Establish an Operating Model (part 2/2)
This chapter explores the strategic options for staffing a workforce analytics team, outlining in-house, in-source, and outsource frameworks while assessing their respective advantages and disadvantages.
ch17Establish an Operating Model
This chapter elucidates the critical need for a structured operating model in workforce analytics, asserting the importance of aligning analytics practices with organizational strategy for enhanced decision-making and business performance.
- A well-defined operating model for workforce analytics allows organizations to focus on strategic business decisions rather than reactive problem-solving.
- Governance structures and ethical guidelines are essential for ensuring responsible use of HR data, maintaining trust within the organization.
- Regularly validating the vision and mission of the analytics team ensures continued alignment with evolving organizational goals and stakeholder expectations.
- The integration of diverse perspectives in decision-making processes leads to superior outcomes and enhances team accountability.
ch20Communicate with Storytelling and Visualization
This chapter argues that effective communication relies on the use of storytelling and visualization, engaging audiences in a manner that traditional methods cannot.
- Stories have the unique ability to engage audiences at an emotional level, making them more memorable and impactful than traditional information alone.
- The effectiveness of visual communication increases significantly when it supports rather than detracts from the narrative being presented.
- Professionals must view communication as an art that intertwines storytelling and visualization to foster genuine audience connection.
- A well-structured narrative can inspire action, turning passive listeners into engaged stakeholders.
ch21p01The Road Ahead (part 1/2)
The chapter foresees the future of workforce analytics, detailing anticipated technological advancements, emerging data sources, and the evolving structure of analytics functions within organizations.
- Workforce analytics represents a seismic shift in how organizations approach human capital management, providing opportunities for strategic insights that were previously unavailable.
- The integration of emerging data sources and technologies will redefine HR practices, making them faster, more efficient, and more responsive to employee needs.
- While the risks associated with new data sources are significant, the potential benefits of doing so can position organizations as leaders in talent management.
- An evolving workforce analytics function must include close alignment with other business areas, enhancing the overall strategic capabilities of HR.
ch21p02The Road Ahead (part 2/2)
As workforce analytics continue to evolve, the integration of diverse data sources and collaboration across functions will be pivotal for organizations to effectively utilize people data and drive business performance.
- Workforce analytics is rapidly evolving, and professionals must adapt to emerging technologies and methodologies to remain effective.
- Collaboration across business functions is essential for maximizing the impact of workforce analytics on organizational performance.
- Rigidly following established analytics maturity models may impede an organization’s ability to respond effectively to current business challenges.
- Continuous learning is a fundamental requirement for workforce analytics professionals in navigating the complexities of modern data landscapes.
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