From HR operating model theory to product teams on the ground
The HR operating model most leaders inherited was built around centres of excellence, shared services, and HR business partners aligned to the business. That configuration made sense when service delivery meant standardized policies, annual performance cycles, and ticket-based support, but it now collides with agentic AI, skills-based organization design, and real-time employee experience expectations. The result is a slow-motion transformation where HR operating models quietly morph into product-centric operating systems, and people analytics either steps into product management or gets absorbed by IT.
Look closely at how leading organizations now structure HR work and you will see cross-functional product teams where a centre of excellence used to sit. At Microsoft, for example, the employee experience organization runs multidisciplinary squads that own end-to-end journeys such as onboarding, internal mobility, and manager enablement, with clear business outcomes and data-driven decision making. Those teams blend HR business partners, designers, engineers, and people analytics experts into a single unit accountable for employee experience products and measurable impact, not just policy compliance or service delivery volume.
This is the real HR operating model product teams transformation, not a slide about agile ceremonies. A modern operating model treats each major employee experience as a product, with a backlog, a roadmap, and product management disciplines that mirror customer-facing digital services. When you run HR as a product operating organization, you stop asking whether a model is “centralized or decentralized” and start asking which operating patterns best align to specific business strategy bets and the data required to prove business outcomes.
For people analytics and HR technology leaders, this shift is not abstract operating model theory. It changes where your team sits, how you prioritize work, and which leaders you serve as primary business partners inside the organization. The analytics function moves from being a shared-services reporting shop to being embedded in journey teams that own specific experiences, where data, experimentation, and model transformation are part of daily product management rituals. If your analytics team keeps optimizing dashboards while the rest of HR moves to product squads, you are effectively choosing to become a back-office service delivery function while IT builds the real-time decision-making engines.
Agentic AI accelerates this operating model shift because it automates Tier 0 and Tier 1 HR work that used to justify large shared services teams. As AI handles routine employee questions, policy navigation, and simple transactions, HR business partners are pushed toward more strategic work on workforce strategy, capability building, and organizational design. In that world, the operating model that wins is the one where product teams use data-driven experiments to improve employee experience and business outcomes, while people analytics acts as the product analytics brain rather than the historical reporting archive.
Why centres of excellence are turning into HR product teams
Traditional HR centres of excellence were designed around expertise domains such as talent management, rewards, learning, and employee relations. Those models optimized for consistency and risk management, but they rarely optimized for integrated employee experience or measurable business outcomes across the whole organization. As work becomes more digital and cross-functional, the gap between functional excellence and end-to-end experience has become a structural constraint on business strategy execution.
Product-oriented teams solve that constraint by organizing around journeys rather than functions, and by giving a single group ownership of both design and delivery. A product team for internal mobility, for example, might own the operating model for skills data, the product operating rules for internal marketplaces, and the service delivery processes that connect managers, employees, and recruiters in real time. That team uses data-driven experiments to test different models of job posting transparency, manager approvals, and learning pathways, with clear metrics on time to fill, internal move rates, and retention.
For HR business partners, this is not just a new label on the same work. In a product teams structure, the HR business partner becomes a strategic adviser to a product owner as much as to a line leader, helping translate business strategy into product backlogs and operating models that can actually ship. The HR operating model product teams transformation means that business partners now sit in cross-functional squads with engineers, designers, and people analytics experts, where decision making is based on data and rapid experimentation rather than annual planning cycles.
People analytics leaders should pay attention to how these product teams define their strategy and management rhythms. In many organizations, the analytics function is being asked to provide real-time data on employee experience, adoption, and productivity for each HR product, not just quarterly scorecards for the CHRO. That means building product management–style analytics capabilities, such as cohort analysis, funnel metrics, and A/B testing frameworks, inside HR operating models that used to focus on compliance and policy change.
This shift also redefines what “best practices” look like for HR operating models. Instead of copying another organization’s centre of excellence structure, leaders now study case study evidence from companies like Airbnb, which runs cross-functional employee experience teams, or ING, which reorganized HR into agile squads aligned to business value streams. If you want a concrete decision to act on this quarter, start by mapping your current centres of excellence to potential product teams, and identify one journey where you can pilot a product operating model with embedded analytics and clear business outcomes.
As you rethink your own role in this transformation, remember that the profession itself is evolving fast. The shift from traditional HR management to product teams and data-driven operating models is reshaping how HR careers develop, which is why many senior practitioners now frame their work as building “people products” rather than running processes, a theme explored in depth in this analysis of the evolving landscape of human resources on HR professional day and the changing HR role. The HR operating model product teams transformation is not a theoretical exercise; it is already changing how leaders hire, promote, and measure HR talent across organizations.
People analytics at the hinge of HR product operating models
People analytics sits at the hinge of this HR operating model product teams transformation, but many analytics leaders still run their function as a reporting factory. When HR becomes a product operating organization, analytics must become product analytics, with direct accountability for employee experience, retention, and productivity outcomes tied to specific HR products. If you keep your analytics team focused on static models and dashboards, you are effectively choosing irrelevance in a world of real-time, data-driven decision making.
The numbers are already pointing in that direction, and they are hard to ignore. A 2023 survey of 1,000 IT leaders by Nexthink, reported by ADP, found that 64% of respondents predict a complete HR–IT merger within five years, while 31% anticipate far more collaboration without merging, signaling that operating models for people and technology are converging into shared product teams. In parallel, Gartner’s 2023 research note “Emerging Tech: The Future of Enterprise Software Is Agentic,” based on expert analysis of enterprise software roadmaps, predicts that 33% of enterprise applications will include agentic AI within a few years, up from less than 1% recently, which means HR products will increasingly be AI-infused services that require continuous monitoring, experimentation, and risk management based on live data.
For a people analytics leader, the strategic question is simple and uncomfortable. Do you want your team to be the business partner that designs the data layer, experimentation framework, and model transformation roadmap for HR products, or do you want IT to own product management while you maintain legacy reports? The organizations that treat people analytics as a core part of product teams are already using data-driven insights to tune service delivery, optimize shared services staffing, and refine operating models based on employee behavior rather than policy intent.
That requires a different operating model for analytics itself, one that looks more like a product team than a traditional centre of excellence. Your analytics group should include product management skills, engineers who can instrument HR systems for event-level data, and analysts who can run experiments on employee experience flows, not just build static models. In a skills-based organization, which is explored in this analysis of what actually shipped versus what stayed in the slide deck on skills based organization design, people analytics becomes the engine that connects skills data, work design, and business outcomes across product teams.
There is also a governance angle that analytics leaders cannot ignore as HR products become more AI enabled. Regulatory pressure on HR AI is rising, and the European Union has already given CHROs extra time on HR AI compliance, a reprieve that is analyzed in depth in this piece on how to use the additional months for HR AI compliance. In a product operating model, people analytics must own the data governance, monitoring, and risk metrics for AI-infused HR products, ensuring that model transformation and change management are grounded in transparent data rather than vendor promises.
If you want a concrete move this quarter, embed at least one analytics professional directly into a cross-functional HR product team and give them joint accountability for a business outcome, such as reducing time to productivity for new hires by a specific percentage. Treat that person not as a report builder but as a product analytics lead, responsible for instrumenting data, running experiments, and informing decision making on backlog priorities. That is how you start shifting from analytics as a shared-services function to analytics as a core part of the HR operating model product teams transformation.
Designing agile HR product teams for measurable business outcomes
Agile HR is not about copying Scrum ceremonies into HR meetings; it is about designing HR product teams that can ship meaningful change in short cycles and measure impact with hard data. In an agile HR operating model, each product team owns a clear slice of the employee experience, such as performance, learning, or internal mobility, and aligns its backlog to explicit business strategy outcomes. That means leaders must define what success looks like in terms of employee behavior, productivity, and retention, not just policy compliance or engagement survey scores.
To make that real, you need to rethink how you structure work, roles, and governance inside HR. A high-performing HR product team is cross-functional by design, blending HR specialists, people analytics experts, engineers, designers, and operations staff into a single team with shared accountability for service delivery and business outcomes. That team uses agile product management practices such as sprint planning, backlog refinement, and regular retrospectives, but it also uses data-driven experiments to test different operating models, communication strategies, and change interventions.
For example, imagine a product team focused on manager effectiveness as a lever for employee experience and performance. That team might run a project product initiative to redesign feedback conversations, using real-time data from collaboration tools, learning platforms, and performance systems to track how managers adopt new behaviors. The people analytics members of the team would build models to predict which managers are at risk of low employee engagement or high attrition, while HR business partners would use those insights to target coaching and support where it matters most.
Agile HR product teams also change how you think about shared services and service delivery. Instead of treating shared services as a separate operating model focused only on efficiency, you can treat it as a platform product that serves other HR products with standardized capabilities such as case management, knowledge bases, and workflow automation. In that setup, people analytics provides the data layer that allows each product team to see how changes in shared services processes affect employee experience, resolution times, and overall business outcomes across the organization.
The risk of inaction is clear and already visible in many organizations. If HR leaders do not redesign their operating models around product teams and data-driven decision making, IT will step in and build digital employee experience platforms where HR becomes just another stakeholder. When that happens, the analytics function is often fully absorbed into IT, and HR loses its ability to shape how data, models, and AI systems define the future of work for its own people.
For senior people analytics and HR technology leaders, the decision this quarter is straightforward. Start treating your analytics roadmap as a product portfolio aligned to HR operating model product teams transformation, with clear business partners, defined business outcomes, and explicit model transformation milestones. Measure your success not by the number of dashboards delivered, but by the number of product teams that can make better decisions in real time because your data, models, and insights are embedded directly into their daily work, not engagement scores, but stay signals.
Key figures on HR product teams and people analytics
- 64% of IT leaders predict a complete HR–IT merger within five years, while 31% expect much deeper collaboration without a formal merger, indicating that HR and IT operating models are converging into shared product teams (Nexthink survey of 1,000 IT leaders across North America and Europe, reported by ADP in 2023; online quantitative survey with stratified sampling by company size).
- Gartner estimates that 33% of enterprise software will include agentic AI within a few years, up from less than 1% recently, which means most HR products will soon require continuous monitoring and data-driven governance by people analytics teams (Gartner, “Emerging Tech: The Future of Enterprise Software Is Agentic,” 2023; based on analyst review of vendor roadmaps and client inquiries).
- A survey of 150 CHROs by the CHRO Association and the University of South Carolina found that 91% cite AI and workplace digitization as their most immediate concern, yet 47% have not established clear productivity measurements for AI initiatives, exposing a major gap that people analytics and HR product teams must close (CHRO Association & USC, “The CHRO’s Role in the Age of AI,” 2023; mixed-method study combining an online survey and follow-up interviews).
- Organizations that adopt agile, cross-functional product teams for HR services report up to 30% faster delivery of new HR capabilities and significantly higher employee satisfaction with HR solutions, according to a 2021 McKinsey case study on agile HR transformations in large financial institutions (McKinsey analysis of three global banks using before-and-after performance metrics and qualitative interviews).
- Companies that embed people analytics into HR product teams are more than twice as likely to report strong business outcomes from HR technology investments, including measurable gains in retention, time to productivity, and manager effectiveness, based on longitudinal research by the Josh Bersin Company (“The Global HR Capability Project,” 2022; multi-year benchmarking study of several hundred organizations worldwide).