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Excellence in People Analytics
Jonathan Ferrar & David Green · 2021
In a sentence
A practical, case-study-rich guide showing how organizations can use workforce data to create measurable business value through nine interconnected dimensions of people analytics excellence.
Excellence in People Analytics reframes HR analytics as a business activity rather than an HR sideshow, arguing that workforce data—when used responsibly—can unlock hundreds of millions of dollars in value while improving the lives of employees. Drawing on research with over 100 global organizations and 30 vivid case studies from companies like Microsoft, IBM, Novartis, and National Australia Bank, authors Jonathan Ferrar and David Green present the Insight222 Nine Dimensions for Excellence in People Analytics model. The book rejects rigid sequential 'maturity models' in favor of a parallel, business-first approach across foundation (governance, methodology, stakeholder management), resources (skills, technology, data), and value (workforce experiences, business outcomes, culture). It equips business leaders, CHROs, and analytics practitioners with practical frameworks, prioritization tools, and operating models to focus on the right work, improve impact, and create value at scale.
The four lenses
- Science
- Statistics
- Systems
- Strategy
Tags
The model
A causal/structural model in which design levers (governance, methodology, stakeholder management, skills, technology, data) drive psychological and behavioral states (analytical culture, stakeholder trust, data-driven decision making) that produce outcomes (workforce experience, business value, societal benefit). Grounded in the book's Nine Dimensions and supporting frameworks.
Governancedesign lever
The mechanisms, processes and procedures by which a company operates and manages risk for people analytics, including alignment to strategy, mission/brand, stewardship, accountability and ethics.
Methodologydesign lever
Processes and frameworks for repeatable, dynamic people analytics including prioritization criteria, defined analytical processes (Focus-Impact-Value), and committed sponsorship.
Stakeholder Managementdesign lever
The practice of identifying, mapping, engaging and sustaining relationships with the seven types of stakeholders to provide direction, sponsorship and enablement for people analytics work.
Skills and Operating Modeldesign lever
The capabilities of the people analytics team including the leader's skills, the operating model (Demand, Solution, Product engines), and the translator role that converts business language to analytics and back.
Technologydesign lever
All types of analytics technology needed for successful people analytics across three waves (core HR, analytics dashboards, specialist tools), including build vs buy decisions and scaling/productizing solutions.
Data Stewardship and Managementdesign lever
The stewardship, management, governance and security of people data and the leveraging of internal, external and emerging data sources to address complex business issues.
Data-Driven Analytical Culturepsychological state
The degree to which analytically willing and savvy mindsets, skills and confidence are embedded across the HR function and wider enterprise, enabling innovation and evidence-based decision making.
Stakeholder and Workforce Trustpsychological state
The level of trust held by executives, managers and employees in the people analytics function and in the ethical use of their data, enabling a fair exchange of value and data sharing.
Evidence-Based Decision Makingbehavioral pattern
The extent to which managers and executives make people-related decisions based on data, insights and recommendations rather than opinion, habit or intuition.
Workforce Experience Valueoutcome metric
The personalized, consumer-grade experiences delivered to employees, managers, executives and the workforce through people analytics outcomes.
Business Value and Outcomesoutcome metric
The measurable commercial value, risk mitigation, productivity, revenue/market growth and quantified financial impact delivered as a result of people analytics activity.
Societal Valueoutcome metric
Broader outcomes such as inclusion, equality, gender pay parity, well-being and human capital disclosure that benefit society beyond the organization.
How they connect
- governance → influences stakeholder trust
- methodology → predicts business value
- stakeholder management → influences stakeholder trust
- stakeholder management → predicts business value
- skills → predicts business value
- technology → influences workforce experience
- technology → influences business value
- data → influences business value
- data → influences stakeholder trust
- stakeholder trust → mediates workforce experience
- analytical culture → predicts evidence based decision making
- skills → influences analytical culture
- evidence based decision making → predicts business value
- business value → influences analytical culture
- business value → correlates societal value
- governance → moderates business value
A candidate measure
Excellence in People Analytics — derived measurement candidates
Governance
Presence/quality score of governance artifacts; % projects aligned to strategy; Number of governance bodies active
self-report suitability: medium
Methodology
% projects scored on Complexity-Impact Matrix; % projects with documented sponsor; Process adherence rate
self-report suitability: medium
Stakeholder Management
Number of stakeholder meetings; Stakeholder relationship status distribution; Coverage of stakeholder types
self-report suitability: high
Skills and Operating Model
Reporting line level (CHRO, CHRO-1, etc.); Number of role types present; Skills coverage score
self-report suitability: high
Technology
% adoption per wave; Number of productized solutions deployed
self-report suitability: medium
Data Stewardship and Management
Data quality score; Number of data sources integrated; Presence of data steward role
self-report suitability: medium
Data-Driven Analytical Culture
% HR using platform; Training completion rates; Confidence/willingness survey scores
self-report suitability: high
Stakeholder and Workforce Trust
% employees open to data analysis; Survey response rates; Trust survey scores
self-report suitability: high
Evidence-Based Decision Making
Dashboard usage logs; Number of decisions changed by data; Self-service adoption rate
self-report suitability: medium
Workforce Experience Value
eNPS score; Offering adoption/usage rates; Text/sentiment analysis scores
self-report suitability: high
Business Value and Outcomes
ROI/IRR/NPV figures; Cost avoidance amounts; Productivity indices
self-report suitability: low
Societal Value
Representation metrics; Gender pay gap %; Well-being survey scores; Human capital disclosures
self-report suitability: medium
The story
The reader A CHRO, business leader, or people analytics practitioner who wants to use workforce data to create measurable business value and improve the lives of their people.
External problem
Their organization collects vast amounts of workforce data but struggles to turn it into focused, impactful, value-creating insights.
Internal problem
They feel uncertain about what to focus on, fear overpromising and underdelivering, and worry their function lacks credibility.
Philosophical problem
It is just plain wrong to make people-related decisions based on opinion, habit, or 'the highest paid person's opinion' when evidence-based alternatives exist.
The plan
- Connect with business stakeholders to understand their challenges.
- Prioritize work to find high-value 'Quick Wins' and 'Big Bets'.
- Define the ambition, mission and brand of people analytics.
- Build solid foundations across governance, methodology and stakeholder management.
- Resource the function with the right skills, technology and data.
- Deliver and scale value through workforce experiences, business outcomes and culture.
Success
- People analytics delivers quantifiable commercial value and is embedded in business operations.
- Employees experience personalized, valued workforce experiences and a fair exchange of value.
- HR becomes a strategic, data-literate, credible business partner.
- The organization reaches 'Age of Excellence'—value at scale, repeatedly, globally.
At stake
- People analytics remains stuck in a low-value reporting role and fails to add real value.
- Wasted investment, lost employee trust, reputational and regulatory risk (e.g., GDPR fines).
- HR loses relevance and the opportunity of $3.1 trillion of untapped workforce value is missed.
Chapter by chapter
ch02The business value of people analytics
This chapter explores the essential role of people analytics in organizations, revealing how data-driven decisions can enhance workforce engagement and productivity while highlighting potential pitfalls.
- People analytics is no longer optional; it is a fundamental pillar for organizations seeking competitive advantage.
- The effective use of people analytics correlates with higher employee engagement and satisfaction, ultimately translating into enhanced business performance.
- Data overload can debilitate decision-making; a focused and structured approach is essential.
- Transparency and communication around analytics can foster trust among employees and bolster engagement.
ch03Stakeholder Management
In an environment where success hinges on collaborative networks, effective stakeholder management emerges as a critical skill for professionals striving to drive impact and gain strategic advantage.
ch04Workforce Experiences
This chapter explores the multifaceted nature of workforce experiences, emphasizing how individual perceptions shape workplace dynamics and influencing overall organizational effectiveness.
- Employee perceptions and experiences are critical to understanding overall workplace engagement.
- Organizations must actively listen to employee feedback in order to foster more positive workforce experiences.
- Higher emotional intelligence within teams correlates with better workplace interactions and outcomes.
- Addressing workforce experiences is not just a human resources issue; it is a strategic priority for organizational success.
ch06Culture
This chapter examines the pivotal role of organizational culture in shaping employee engagement and performance, arguing that culture is not merely a backdrop but a dynamic entity that requires intentional cultivation.
ch09Concluding remarks
The chapter encapsulates foundational insights about the pivotal role of people analytics in transforming organizations, underscoring its value in driving business performance and future advancements.
- People analytics is not merely a trend but a foundational element for driving enterprise performance and value.
- Engaging executives and stakeholders from the outset is crucial for the success of any analytics initiative.
- A data-driven culture supports innovation while creating more impactful employee experiences and business outcomes.
- The value generated from well-implemented analytics will not only enhance organizational performance but also promote employee satisfaction and engagement.
ch10Governance
This chapter emphasizes the critical role of robust governance in people analytics, illustrating how proper alignment with corporate strategy, a distinct mission, and ethical stewardship can significantly enhance organizational effectiveness.
- Effective governance in people analytics is foundational to accountability, transparency, and delivering value.
- Aligning analytics efforts with corporate strategy can significantly enhance credibility and usability within the organization.
- Establishing a distinct mission and brand elevates the visibility and impact of people analytics functions.
- Failing to invest in governance can lead to misalignment, ineffective projects, and reputational damage.
ch11Methodology
This chapter delves into critical methodologies for effective people analytics, emphasizing prioritization, structured processes, and the value of committed sponsorship to drive measurable business impact.
- Prioritization in people analytics must align directly with business needs and employee expectations.
- Effective stakeholder engagement is a critical driver of success in analytics efforts.
- The Complexity-Impact Matrix helps in categorizing projects to focus on those that will drive significant business value.
- Analytics leaders should pursue a values-based approach, aiming for impactful initiatives that benefit employees and the organization.
ch12Workforce Experiences
This chapter underscores the critical role of various stakeholders in the effective implementation of people analytics, emphasizing the necessity of engaging employees and business leaders to enhance workplace outcomes.
- Stakeholder engagement is crucial for enhancing the relevance of people analytics, as diverse insights can directly shape effective strategies.
- Employees must perceive a fair exchange of value tied to their contribution of data, as outlined by Accenture's ‘trust dividend’ concept, to ensure participation.
- Mapping stakeholders helps visualize the importance of different voices and enables more effective prioritization in analytic initiatives.
- Listening is a vital skill for analytics leaders, allowing them to gather nuanced insights that inform strategic decisions.
ch13Skills
This chapter delves into the essential skills needed for leaders in people analytics, emphasizing the roles of the leader, the translator, and the operating model that can drive organizational success.
ch14Technology
This chapter examines the pivotal role technology plays in advancing people analytics, addressing the critical decision of whether to build or buy analytics solutions, and the transformation necessary to scale analytics across organizations.
ch15p01Data (part 1/2)
This chapter argues that the people analytics leader should assume the role of the chief data officer in HR, emphasizing the critical aspects of data management and the potential of leveraging internal and external data sources to drive business outcomes.
- People analytics can only reach its full potential by coupling data management with ethical governance.
- Trust in data usage is paramount; organizations must prioritize transparency to foster employee confidence in how their data is handled.
- High-quality data stewardship leads to improved analytics outcomes and deeper business insights, which are essential for effective HR strategies.
- The integration of the chief data officer role within HR enhances the capacity for data utilization across the organization.
ch15p02Data (part 2/2)
This chapter argues for the democratization of people analytics, emphasizing its vital role in empowering managers and executives with actionable insights to foster a data-driven culture within organizations.
- Data democratization empowers managers and executives with the ability to act on insights directly, improving decision-making agility.
- Organizations that successfully implement data democratization enhance their culture of trust, collaboration, and performance.
- Training and user-friendly design are critical to ensuring data tools are adopted and utilized effectively across all tiers of management.
- Case studies show that successful data integration produces tangible benefits that resonate across organizational functions.
ch16Culture
This chapter argues for the importance of developing a data-driven culture within human resources, highlighting the need for both analytical skills training and psychological safety to foster engagement with people analytics.
- A robust data-driven culture in HR not only enhances decision-making but creates tangible business value; 84% of HR professionals now recognize this importance.
- The 'Culture Pyramid' is essential for building a sustained analytics framework, consisting of demonstrating value, developing capability, creating structure, and building confidence.
- Employees’ confidence in their analytical abilities can be significantly improved through structured training initiatives and by fostering a supportive environment.
- Merck KGaA's transformation highlights that scaling people analytics requires a multi-year commitment and a clear vision iteratively realized.
ch17The next steps for people analytics
This chapter argues for a business-first approach in people analytics, emphasizing the necessity of stakeholder engagement and strategic prioritization to drive meaningful organizational outcomes.
- Building relationships with business executives is the foundational step in transforming people analytics into a strategic asset for organizations.
- A dynamic prioritization model ensures that analytics teams focus on projects with the highest impact and relevance to business goals.
- Clear articulation of the analytics function's mission and objectives fosters greater engagement and support from stakeholders.
- Transparency in the prioritization process cultivates trust and collaborative ownership among all stakeholders in the analytics journey.
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