How CHROs Can Power Up Their People Analytics

Despite growing pressure to make faster, data-driven decisions, most HR leaders admit they’re not especially confident in their people analytics capabilities. In fact, 74% of CHROs said their HR analytics capabilities are basic or descriptive only, while only 18% believe their organizations consistently use data analytics to drive better business decisions, according to a new Korn Ferry survey of 750 global HR leaders. 

When organizations truly focus on the capacity and maturity of their people analytics, it affects the entire employee life cycle. The Korn Ferry survey found that talent acquisition and retention (cited by 66% of CHROs), employee engagement and productivity (60%), and workplace agility and planning (47%) are the practices most impacted by people analytics capabilities. 

Indeed, according to SHRM research, the most common current application of people analytics is in the area of retention and turnover (used by 82% of organizations). In addition, 72% of HR executives using people analytics said that this approach adds the most value to their organization by enabling them to make more effective decisions, improve the employee experience, and impact the bottom line. 

It’s clear that fully powered people analytics has the potential to provide more insight into key stops along the employee life cycle while helping drive business goals. So, how do HR leaders take their people analytics from descriptive and basic to consistent and effective? Consider these roadblocks and what HR leaders can do to break through them. 

Roadblocks on the Path to Powerful People Analytics 

Several common barriers prevent organizations and their HR teams from fully leveraging data analytics to drive better decision-making. 

“The main obstacles are data availability and the skills to be able to interpret and apply data insights,” said Kenny Pyle, SHRM’s lead HR technology analyst. “But also, a lack of connection or buy-in from end users of the data and how the talent analytics team makes data available are real problems. Then there is a larger change management issue of getting people to stop making decisions without data and start using it before familiar questions are automatically answered.”

Here are the biggest roadblocks that HR leaders should address to unlock the full strategic value of their data: 

• Poor Data Quality. Incomplete, inaccurate, or inconsistent data limits reliability. Disconnected systems lead to fragmented or siloed data, such as if your human resource information system (HRIS), applicant tracking system (ATS), and learning management system (LMS) are not integrated. Lack of standard definitions can also hinder data quality (e.g., inconsistent definitions of “turnover” or “headcount”).

• Lack of Analytical Skills. HR and business users often lack data literacy or statistical training. Too few data analysts and data scientists are embedded in HR and functional teams. And organizations typically overrely on IT or external consultants, which can slow agility and ownership. 

• Weak Data Governance. When your organization has no centralized ownership or has unclear roles around data stewardship, quality and consistency break down. Security, privacy, and compliance concerns may also block data sharing or collection, while fear of ethical misuse of employee data can hinder its application.

• Culture and Resistance to Change. When leaders view analytics as methods to track people rather than help them, it can lead to data distrust. And if leaders or employees don’t trust data or feel threatened by what it reveals, it can lead to decision-making based on intuition or tradition rather than evidence. Plus, a lack of executive sponsorship or vision for data-driven transformation can seriously hinder progress, especially when leadership views analytics as a side project, not a core driver of competitive advantage. 

• Lack of Clear Business Questions. Data has to be backed up with strategy. Analytics efforts often lack focus because the leaders have no strategic questions or goals. And data teams may analyze what’s easy to measure — not what’s most impactful.

• Underinvestment in Tools and Technology. Relying on legacy systems makes integration and automation difficult. By limiting access to modern intelligence platforms or predictive tools and only relying on centralized reporting, an organization’s analytics can’t mature.  

• Slow Operationalization of Insights. It’s one thing to generate insights and another to translate them into action. With no feedback loops to measure if changes based on analytics improved outcomes, the resulting insights might end up too high-level or not timely enough to influence decisions.

6 Ways to Access the Full Power of Data 

HR leaders can pave the way for better people analytics through several strategic actions. But according to Pyle, this starts with accessibility and upskilling.  

“HR needs to upskill everyone in the function in data literacy, data storytelling, and statistical thinking,” he said. “Further, many organizations use multiple technologies to capture relevant data, but they don’t spend resources and time to properly manage all data assets as part of a broader ‘data lake.’ This makes it impossible to address anything beyond simple, narrow questions.” 

Above all, people need to care, Pyle said.  

“People are busy and won’t take the time to use the data to enhance their decision-making process unless they care.” he said. “A little bit of UX [user experience] research and thinking could help significantly.”  

Here are seven concrete steps HR leaders can take to strengthen their technical capabilities and embed analytics more strategically across their organizations: 

  1. Build a Strong Data Foundation.

• Ensure data integrity. Clean, complete, and reliable data is essential. 

• Centralize data. Consolidate sources (such as HRISs, ATSs, and LMSs) into a single data lake or platform. 

• Standardize definitions and align metrics across the organization. For example, define “turnover” or “high-performer” consistently. 

2. Upgrade Skill Sets.

• Upskill HR teams in data literacy, storytelling with data, and statistical thinking. 

• Hire or partner with data scientists who understand workforce and organizational behavior. 

• Encourage cross-functional collaboration with IT, finance, and operations analytics teams. 

3. Tie Analytics to Business Outcomes.

• Focus on strategic questions. For example, “What drives high sales performance?” or “What’s the return on investment on leadership programs?” 

• Link people data to business key performance indicators, including productivity, customer satisfaction, and profit per full-time equivalent. 

4. Operationalize Insights.

• Build dashboards and scorecards that are embedded into business rhythms (such as quarterly reviews or talent planning). 

• Create feedback loops to measure the impact of HR interventions (e.g., did new manager training reduce attrition?). 

• Promote self-service analytics for business leaders with user-friendly tools. 

5. Foster a Culture of Evidence-Based HR.

• Make data a regular part of HR decision-making. 

• Reward data-informed decisions. 

• Train leaders and HR business partners to ask better questions and interpret results. 

6. Ensure Ethics and Privacy.

• Develop data governance policies for consent, bias mitigation, and usage limits. 

• Be transparent with employees about how their data is used.