Editorial
Data is the currency of strategic decision-making. Nowhere is this truer than in human resources where data can change a People function from a cost center into a value driver. Yet, for many Chief People Officers (CPOs), the journey from data collection to strategic impact is fraught with challenges. To build a truly data-driven People function, one must begin with the basics: clean, reliable data.
AI Starts with Clean Data
Every data-driven function begins with data integrity. Without clean data, even the most sophisticated analytics could lead to flawed insights. HR leaders must first ensure their data is accurate, complete and up-to-date. This is the bedrock upon which everything else is built — from job architecture to rewards programs, strategic workforce planning, talent development and more.
Clean data is not merely a technical necessity; data hygiene affects your credibility with the executive team and the Board. Nothing undermines trust faster than presenting analytics only to discover that the underlying data is riddled with errors. Worse, poor data can lead to misguided decisions such as over-investing in talent initiatives that do not drive business performance.
Beyond its immediate applications, clean data is also essential for embedding predictive analytics and artificial intelligence (AI) into HR processes. Machine learning models trained on erroneous data are, at best, ineffective and, at worst, actively misleading.
Establishing Strong Data Governance
Having clean data is necessary but insufficient without proper governance. This means implementing a Human Resources Information System for all employee data, but it also means implementing processes to keep that data accurate over time. Scrubbing the data once but failing to install processes to maintain data integrity is like cleaning your house once and expecting it to stay clean forever.
Governance is about accountability, meaning defining who is responsible for data quality, setting standards and ensuring compliance. To make governance easier, prioritize automation. Manual data entry is a wellspring of errors. CPOs should explore automation options such as data parsing tools, integration with other HR and business systems or even using AI to maintain data accuracy.
Regular data audits should be scheduled to catch inconsistencies before they become systemic problems. Conducting audits helps data remain accurate, complete and compliant with evolving regulations. They allow HR leaders to address issues before they affect decision-making.
Compliance is another important ingredient for building data-driven People teams and processes. From the California Privacy Act to the EU AI Act and GDPR, compliance is a legal obligation as well as the right thing to do. HR leaders must stay updated on global data privacy laws and ensure that both internal policies and external vendor practices align with these regulations. Noncompliance can lead to financial damage, and worse, reputational damage to the organization’s employer brand.
Beyond compliance, data governance is about building trust. When employees know their data is handled responsibly, they are more likely to participate in engagement surveys, provide candid feedback and support other data-driven initiatives.
Using HR Data for Storytelling
Numbers alone do not inspire action. The best CPOs know how to transform raw data into compelling stories that inform and persuade. This begins with understanding that data answers the "what" question: what is happening, where and to whom. Strong storytelling, however, goes beyond these questions.
The next layer is the "so what." This is where context is added, linking data to business outcomes. Rising turnover rates are not just numbers; they may be symptoms of leadership gaps, cultural misalignment or a lack of growth opportunities. For instance, if data reveals that high-potential talent is leaving more quickly, the story is not just about attrition; it is about the business’s ability to maintain its competitive edge and deliver on strategic priorities. By looking at data this way, HR leaders move beyond reporting and become strategic advisors.
Finally, there is the "now what." This is where data becomes actionable. Recommendations must be clear, specific, tied to business objectives and accompanied by a strong business case. Should leadership invest more in upskilling? Should employee benefits be restructured to enhance retention? Or perhaps it is time to revisit leadership development initiatives to better equip managers for an AI-powered future.
Distinguishing Between Leading and Lagging HR Indicators
One of the most common pitfalls for HR leaders is over-indexing on lagging indicators. For example, turnover and absenteeism are important metrics, but they are reactive. It is helpful and necessary to analyze turnover by department, geography, tenure and other data views. By the time issues such as turnover surface in your data, however, the underlying problem has likely been festering.
Leading indicators such as employee engagement scores, internal mobility rates or stay interview feedback serve as early warning signs. They help HR leaders proactively address emerging issues. Organizations that track sentiment data from employee surveys can often predict turnover or performance gaps months in advance.
Leading indicators also enable proactive talent management. For example, if engagement data shows declining engagement in an important department, HR can partner with the functional leader to take corrective actions before those employees begin leaving. This predictive approach changes HR from a reactive function to a proactive, strategic partner.
Why HR Needs to Invest in Analytics
As organizations grow, so too must their analytical sophistication, which starts with building people analytics capabilities within the People team. For smaller companies, this may be an analytics expert who is retained in a fractional or consulting capacity.
Alternatively, this work can sit under the Total Rewards or Employee Experience function. For larger organizations, a full-fledged people analytics team can bring value through predictive modeling and other more sophisticated capabilities. Investing in training is also essential; HR professionals who can interpret data and translate insights into strategic action become invaluable.
Every HR professional from recruiters to HR business partners and DEI leaders should have baseline knowledge of data analytics and data-oriented storytelling. Programs that blend analytics with strategic storytelling help build this competency internally.
CPOs must also consider investing in data science resources for their teams. This investment can take several forms. It may involve hiring a dedicated data scientist, sharing a resource with another department or partnering with an external provider. As predictive analytics and AI become more ingrained in HR practices, data science professionals bring a unique blend of skills, helping bridge the gap between numbers and human behavior. This capability transforms the People function from being seen as focused on the 'soft stuff' to being a critical driver of enterprise value.
Finally, HR leaders must collaborate with other functions such as finance, IT and operations to gain an holistic view of workforce data. This cross-functional approach means HR is not operating in a silo but is a fully integrated partner in business decision-making.
A Data-Driven HR Culture: The Ultimate Goal
Building a data-driven People function is about more than just technology or analytics talent. It is about fostering a culture where data-driven recommendations are an expectation, and continuous improvement is the norm. CPOs must model this mindset by regularly challenging their teams to question assumptions, validate insights and refine recommendations.
Data and analytics help CPOs understand workforce potential, identify and invest in high-potential talent and make decisions that align with business strategy. Ultimately, it is not about collecting data but about using it to tell a story, make predictions and drive action. For CPOs, mastering this capability can be a great way to earn trust and credibility with their CEO and board.
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Editor's Note: Read more tips on making people analytics work for you:
- What 2025 Has in Store for People Analytics — People analytics is a powerful space that can transform organizations. But knowing how to use it remains key to success.
- Generative AI Is Shaking Up People Analytics. 4 Use Cases — Generative AI promises to shake up HR. Some of its early use cases are turning up in the world of people analytics.
- HR Data Analytics Skills Are in Demand: 4 Ways to Upskill — Research finds HR teams are lacking data analytics skills to make smarter decisions faster. Here is why — and how — you can upskill to seize the future of HR.
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