Instinct and goodwill no longer cut it. For HR leaders aiming to steer their organisations with precision, the compass must be data—and the map, a robust set of analytics capabilities.

With every keystroke and interaction generating data, the concept of "data ubiquity"—highlighted in the Baromètre RH 2024 by OpinionWay for Kelio—is fast becoming reality. Data isn’t just influencing decisions; it’s embedded in every process. Yet, despite the buzz around predictive analytics and AI, many HR teams remain stuck in a loop of reactive reporting. Even with 2025 hailed as a tipping point for AI integration, progress is patchy, often held back by skill gaps, legacy systems, and a shortage of data-savvy professionals.

Consider this: in early 2024, a study of 301 HR professionals in France found that while 28% were using AI daily, 60% still resisted adoption—though that resistance had dropped by 16 points from the previous year. Momentum is building, particularly in mid-sized firms, where 34% of HR managers are already leaning into AI tools. Meanwhile, 91% of global tech decision-makers reported plans to boost IT spend in 2024, underscoring the urgency to invest not just in technology, but in the people and skills that make it work.

But all the AI in the world won’t make a dent unless the humans behind the screens can harness it. HR is becoming a domain of creators, analysts, and consultants—people who not only ask the right questions, but also know what to do with the answers.

Why people analytics is indispensable in today's HR function

Analytics shifts HR decision-making from gut feel to evidence-based rigour. Here's why.

Data-driven decision making: Analytics brings objectivity. It helps HR justify programmes, reduce bias, and tailor strategies based on hard facts. For instance, data can highlight which sourcing channels yield the best candidates, or where a training investment is delivering returns.

Optimised talent acquisition: Predictive models now help HR teams anticipate candidate success, track cost-per-hire, and forecast future hiring needs—making the recruitment funnel leaner and more effective.

Boosted engagement and retention: Data from surveys, feedback tools, and HRIS platforms allows HR to spot flight risks and engagement dips early, tailoring interventions for greater impact.

Sharper performance management: Rather than relying on anecdotal manager feedback, data-driven reviews help identify performance gaps and evaluate the ROI of development initiatives.

Strategic workforce planning: HR can use analytics to map future skill needs, align hiring with business goals, and manage labour costs with foresight.

Measuring HR’s ROI: Perhaps most critically, analytics lets HR show its value in terms leaders understand—impact on revenue, profitability, and customer experience.

Eight essential skills for people analytics success

To make data sing—and influence action—HR professionals must develop a blend of technical, strategic, and interpersonal skills. These eight capabilities are key:

1. Data analytics and technical expertise

At the heart of people analytics is the ability to collect, clean, analyse, and interpret data. Proficiency with tools like Power BI, Tableau, SPSS, or even Python and R enables HR to move beyond spreadsheets into meaningful, real-time insights. Understanding statistical models and data wrangling techniques is like learning a new language—it’s the foundation for everything else.

2. Work psychology and behavioural science

Numbers alone can’t tell you why turnover is spiking or engagement is dipping. That’s where psychology enters. Professionals with a grounding in behavioural science can decode what motivates people, how teams function under pressure, and which interventions are most likely to succeed. It’s a way to connect the dots between data trends and human truths.

3. Business and HR acumen

Great analytics won’t go far if they’re disconnected from business reality. HR professionals need to understand shareholder priorities, competitive dynamics, and how different business functions operate. At the same time, they must stay fluent in HR operations, from compliance and performance management to global mobility. This dual lens ensures that data insights are both strategic and actionable.

4. Communication and storytelling

Raw data rarely speaks for itself. The ability to translate complex findings into clear, engaging narratives is essential. Whether it’s a dashboard that speaks volumes or a well-framed pitch to the executive team, storytelling turns information into influence. Think of it as marketing your insights—drawing leaders in and giving them the confidence to act.

5. Consulting and stakeholder management

People analytics often sits in a political hot zone—navigating competing priorities, sceptical stakeholders, and evolving business demands. The most effective professionals act like internal consultants: listening deeply, reframing problems, and guiding teams toward data-led solutions. Stakeholder influence, not just insight, is often the game-changer.

6. Integration and cross-functional alignment

No data lives in a vacuum. Successful analytics work requires pulling insights across silos—HR, finance, IT, marketing—and weaving them into a unified view. This calls for systems thinking, API fluency, and a clear understanding of cloud-based architecture and data governance. The goal? Build a seamless, trusted data ecosystem.

7. "Translator" capability

One of the most underrated but critical roles is that of the translator—the bridge between data scientists and decision-makers. These professionals don’t just understand numbers; they understand people. They turn technical jargon into strategic value, ensuring the data tells a story that business leaders can act on. Without them, insights risk getting lost in translation.

8. Curiosity, innovation, and continuous learning

The best teams cultivate a growth mindset—experimenting with new tools, piloting fresh approaches, and staying ahead of the curve. Whether it's learning about reusable data products or exploring the next frontier of generative AI, staying curious is non-negotiable.

The AI shift: changing the shape of HR

AI has already redefined what’s possible in HR. From scanning CVs to onboarding workflows, and even predicting turnover with up to 87% accuracy, machine learning tools are stepping into territory once considered exclusively human. Recruitment software can cut hiring costs by 30%, while new platforms are enabling data lineage tracking and repeatable analytics models.

According to AIHR’s HR Trends Report 2025, HR teams are no longer just service providers—they’re creators, developers, and strategic consultants. Companies like IBM have even automated entire HR functions, redeploying human talent to higher-value roles in product, sales, and leadership. But even here, the success of these transformations hinges on human skill.