2023 high-impact people analytics research

People analytics has evolved from an emerging discipline to an organizational imperative.

Thinking about people analytics as an organizational imperative means approaching it like its own business. Not a science project or an adjunct piece of the human capital puzzle, but a full-fledged internal service provider that directly affects business success. Our research shows this change playing out in real time. People analytics teams are becoming more formalized—84% of all organizations surveyed in our latest research report have a clear vision and mission for their people analytics function (a 23% increase from our 2020 research).¹ And the most mature organizations are twice as likely to treat people data and analytics as core assets that create competitive advantage.

Organizations seeking to mature and scale their people analytics function to keep pace with the expanding needs of the new world of work should consider:

• Identifying key business questions and their implications.
• Investing in people analytics as an internal consulting capability.
• Establishing partnerships to build a robust offering.
• Understanding your infrastructure (and its strengths and limitations).

A data-centric culture remains the single most influential factor in driving people analytics maturity.

Deloitte’s 2020 High-Impact People Analytics research found that a data-centric culture was the single biggest driver of people analytics maturity.² Since the finding was published, we’ve seen vast improvements in technology and the ways in which we analyze and interpret data. But even as the context of a data-centric culture changes, its importance does not: Just as it was three years ago, the existence of a data-centric culture is still the most significant catalyst for people analytics maturity.

Consider the following as your organization looks to build its own data-centric culture:

• Demonstrate what data-driven decision-making looks like.
• Identify targeted interventions that encourage curiosity and creativity.
• Build data into processes and decision-making.
• Evaluate and incorporate data skills into the employee life cycle.

High-performing people analytics teams balance investments in human and technological capabilities.

Human capabilities and technology are too often developed and managed in silos. It goes without saying that there is no people analytics without people, and humans are essential to driving the value the function can deliver. The right technology is essential for performing complex analyses and distributing insights at scale. If organizations lack the tools and platforms necessary to standardize, visualize, and deliver data and insights in a meaningful way—or worse, if they attempt to use the technology at hand to completely replace the human element—even the best data will fail to yield optimal results.

Organizations looking to achieve the type of balance between humans and technology that optimizes their combined impact should look to:

• Take inventory of existing resources and capabilities.
• Look outside human resources (HR) to find needed skills and technologies.
• Manage people analytics services as a portfolio.

Integrating people and business data from a wide array of sources is central to addressing today’s workforce challenges.

Traditionally, workforce analytics started and ended with HR: HR owned the data, maintained access, and performed the analyses. But leading organizations are widening their aperture on the data that matters, and the rapid evolution of technology is helping expand our understanding of what constitutes “people data,” going beyond HR systems of record to include other business functions such as operations, finance, and sales.

Unprecedented access to new and evolving data sources affords organizations novel and tantalizing means to tackle the issues most central to the workforce. But it also presents new questions and considerations: How are larger datasets from diverse sources accessed and managed on an ongoing basis? Who is responsible for data stewardship? How does increased data access affect risk?

Organizations looking to harness the potential of people and business data should consider the following:

• Let data help define the problem.
• Be clear about ownership.
• Understand the ethical, legal, and regulatory environment.
• Shape data products to cut through the noise.

People data is business data and requires the same level of governance, quality, and investment.

Today’s organizations understand that data means business and invest accordingly. But while leading companies are prioritizing data maturity and building skills and capabilities across multiple areas of the business (for example, supply chain and finance), they are not treating people data with the same level of scrutiny and rigor. As the gap widens, the resulting lack of trust in people data threatens to undermine even rudimentary progress in people analytics.

Our 2020 research found high-performing organizations were 4.3 times more likely than their low-performing counterparts to involve HR in enterprise data governance.³ And our 2023 findings reinforce the importance of investing in HR data. Now, more organizations need to get onboard.

To build the scaffolding necessary for effective people data governance, organizations should consider:

• Focusing on where data is needed.
• Leaning on leaders to build data ownership and trust.
• Ensuring collaboration in governance processes.
• Investing in the right places.

People analytics teams face constant demands to innovate, expand offerings, and better serve customers.

For many people analytics teams, the cycle of demand in growth and expansion can make service delivery feel like a Sisyphean task. For as much as the people analytics function delivers, demand always seems one step ahead. Scaling the people analytics function’s service catalog to meet the ever-growing needs of a rapidly expanding customer base won’t happen overnight—it requires a dedicated effort across strategy, talent, technology, process, and governance.

To keep up with a constant call for innovation, people analytics leaders should:

• Know and appreciate the customer.
• Define and segment the service catalog.
• Constantly tune and maintain the operating model.