Building the Future of People Analytics

As Baby Boomers retire, organizations are grappling with a talent crunch, struggling to find new skills, hire frontline workers and fill leadership roles. For example, my team recently uncovered that U.S. healthcare will face a shortage of two million clinicians within three years — a challenge mirrored across other key industries.

With rising union activity, demands for flexibility and 73% of workers worried about AI, the challenges in the workplace have only increased. Factor in inflation and global economic and political instability, the “battle for talent” has become far tougher than when the term was first introduced a generation ago.

Yet, there’s no shortage of talent intelligence tech aimed at solving these talent management challenges. Platforms like Eightfold, LinkedIn, Lightcast, Visier and Draup provide precise insights into talent, salaries and skills. In theory, these tools should make HR analytics teams as impactful as finance or marketing in driving data-driven decisions — but that’s not the reality.

Our recent study reveals a sobering reality: despite years of investment in people analytics, fewer than 10% of companies can effectively correlate HR data with business metrics. The conclusion is clear and disappointing — after all this effort in tools and talent, people analytics remains the third least mature area in HR.

Can People Analytics Be Saved?

Our study at the Josh Bersin Company found that the most effective people analytics teams drive business transformation through actionable insights. These teams leverage organization-wide data integration to address critical challenges such as optimizing location strategies, closing skills gaps and enhancing productivity.

This strategic focus yields impressive ROI, as organizations at this level are:

2.9x more likely to achieve high productivity across workforce segments.
3.0x more likely to retain employees effectively.
3.0x more likely to adapt to change successfully.

Industries like technology, healthcare and pharmaceuticals lead the pack, with 20% of surveyed companies achieving high-maturity status in people analytics. Larger organizations, particularly those with more than 100,000 employees, are even more likely to excel, with 42% reaching this advanced stage.

Related Article: What 2025 Has in Store for People Analytics

What Sets High Performers Apart?

They trade perfectionism for an experimental mindset, focusing on agility and innovation. Collaboration among CHROs, CIOs, CFOs and CMOs ensures seamless data integration across the organization. They prioritize advanced software investments and align closely with business goals. AI and predictive models are central to their success, empowering teams to forecast trends and drive strategic decision-making. Most have more than a decade of experience, with 54% reporting directly to the CHRO.

The results are compelling: these leaders in people analytics are more inclusive, deliver higher customer satisfaction and adapt to change with remarkable agility. They also rank people analytics as the second most impactful driver of financial performance, outperforming traditional HR functions such as L&D and employee experience.

However, these success stories are rare. Only 10% of organizations reach this advanced level, with most still focused on basic reporting. This gap highlights a significant missed opportunity.

Our data reveals that progressing from Level 2 to Level 3 (on a maturity scale where Level 1 is the least advanced and Level 4 is the most) improves people analytics outcomes by an impressive 47%. But true transformation only happens at Level 4. To get to such heights, people analytics must transition from siloed "science projects" to what we term “systemic business analytics.” This approach integrates diverse data sources — including labor market data and internal HR metrics — to drive business decisions.

Time to Leave the Ivory Tower

To move beyond isolated analytics, organizations must become more receptive to all types of data, regardless of source or level of perfection. Systematic analysis of people trends involves tapping into various analytics, and evolving and refining strategies as you go. In fact, four of the 15 key best practices for people analytics excellence focus specifically on data.

This approach is taking root. For example, Microsoft uses data to inform its return-to-office policy, identifying key moments when in-person attendance is essential, such as onboarding and team-building events. This data-driven strategy resulted in the creation of guidelines for managers to help teams determine the best work location.

Similarly, Starbucks uses a variety of data points to identify the skills and behaviors that make branch managers successful, while also uncovering hidden talent for leadership roles. SAP, on the other hand, tracks its pay practices through advanced analytics, ensuring 99% of employees were paid fairly for equal work in 2022.

Top-performing companies also prioritize making data accessible to all employees. For instance, Panasonic and Providence Health & Services empower their line managers with data to make informed decisions about workload distribution, employee engagement and compensation.

Interactive, real-time dashboards are proving invaluable in providing these insights. Standard Bank Group, for instance, equips its 9,000 managers with dashboards to monitor leadership effectiveness and guide decision-making. This approach has resulted in significant improvements in employee retention and diversity.

The transparency factor is crucial. High-performing organizations are three times more likely to grant managers access to people data and six times more likely to share it with employees. In contrast, most organizations restrict insights to senior executives, with only 44% sharing data with line managers and just 15% sharing it with team members.

To move from siloed, ineffective people analytics to a more impactful future, organizations should:

Adopt a pragmatic, action-driven analytics approach that goes beyond traditional HR metrics, incorporating business performance, labor market trends and external benchmarks.
Integrate these data sources into a unified strategy focused not just on HR, but on addressing the organization’s key business challenges.
Embrace AI-powered technologies, predictive analytics and a culture of data-driven decision-making.

While this shift may require adjustment for people analytics professionals, seizing this opportunity could transform the role from a sidelined function to a strategic powerhouse.

Instead of getting bogged down in the micro-analytics weeds, trying to manually correlate multiple data inputs and refine the results, let AI handle much of that work. By doing so, you can pivot to a more exciting role: managing your organization’s data corpus and focusing on understanding and solving its biggest challenges — positioning you for a much more prominent role in the broader business.

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