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3 min read
The One Model Team
The Only Constant in HR is Change Every year, HR leaders face a new workforce crisis. The Great Resignation, hybrid work shifts, talent shortages, return-to-office debates—the list goes on. Just when you think you've got a handle on things, a new challenge emerges, demanding fresh insights and real-time action. The problem? Too many People Analytics platforms look good on the surface but fall apart when real-world complexity hits. The Limitations of Traditional People Analytics Many platforms promise fast answers, but they often come with hidden constraints: Inflexible Data Models: Predefined frameworks make it difficult to align with your organization’s unique needs. Slow to Adapt: When a new workforce issue arises, you’re stuck waiting for vendor updates instead of getting the insights you need. Opaque Processes: If you can’t see how the numbers are built, how can you trust them? These limitations force HR teams to operate reactively, leaving them struggling to provide leadership with clear, accurate workforce insights when they need them most. Why One Model is Different One Model is designed for organizations that need flexibility, transparency, and control over their workforce data. Here’s how: Your Data, Your Way: No black-box models—One Model integrates with your unique data sources, definitions, and business logic. Full Transparency: You can see the underlying data sources and logic used to generate insights, ensuring accuracy and confidence. Flexibility Built-In: When the next workforce crisis hits, you won’t be stuck with rigid, prebuilt reports. One Model’s adaptable framework lets you build the reports you need, when you need them—with our team ready to support custom reporting as required. The Strategic Advantage of a Flexible Partner Organizations using flexible People Analytics solutions gain several advantages: Better Decision-Making: Real-time insights empower HR to take proactive action. Improved Employee Experience: Data-driven strategies help HR teams identify factors that drive engagement, satisfaction, and retention. Optimized Workforce Planning: With visibility into trends and risks, organizations can allocate resources more effectively. By leveraging these benefits, HR leaders can move from reacting to crises to staying ahead of workforce trends. Change is inevitable. Your analytics should be ready for it.
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6 min read
The One Model Team
When it comes to leveraging workforce data for strategic decision-making, organizations need tools that go beyond simple reporting. People Analytics Platforms collect, clean, and analyze data, deliver valuable insights, use predictive analytics, and integrate with other business systems. While major Human Capital Management platforms like SuccessFactors, Workday, and Oracle offer analytics capabilities, One Model stands out as a critical addition to these built-in solutions. Here’s why: Achieve More Accurate Insights with Effortless Data Integration The ability to integrate diverse data sources effortlessly is critical for gaining accurate insights. By pulling real-time data from multiple sources, organizations can make more informed decisions that directly impact their overall strategy. Workday Prism: Workday Prism aims to provide a unified analytics layer but has challenges with integrating data from third-party sources. The platform requires users to publish individual data sets, and the data preparation logic is often inconsistent. This can lead to confusion and inefficiencies, specifically for organizations that need to bring together diverse data sources. SuccessFactors Workforce Analytics: One of the major drawbacks of SAP SuccessFactors WFA is its limited data integration capabilities. While it offers workforce analytics, it primarily only works within the confines of specific SuccessFactors modules. Integrating external data from other systems or non-HR business data is either not possible or costly and cumbersome. Oracle Fusion: Similarly, Oracle’s analytics solution is tightly coupled with its HCM platform. While it provides robust tools for managing HR data, the system lacks flexibility with integrating with non-Oracle systems. This creates data silos. Additionally, Oracle’s analytics solution comes with hidden costs, such as fees for custom analytics, data storage, and specialized expertise. One Model: One Model excels at integrating all of your HR data and external business data into a cohesive platform. With pre-built connectors to popular systems like Workday, SuccessFactors, and Oracle, as well as the ability to integrate non-HR data, One Model creates a unified data warehouse that provides deeper insights across all business functions. This flexibility ensures businesses have a complete, real-time view of their workforce and business performance. Quick Time to Value for Faster Decision-Making When speed is critical for decision-making, long implementation timelines can hinder an organization’s ability to take action. One Model’s quick deployment ensures that companies don’t have to wait months or years to start seeing value from their analytics investments. Workday Prism: Workday Prism involves an in-depth implementation and the need for specialized BI developers to maintain the system after implementation. SuccessFactors Workforce Analytics: The time to value with SuccessFactors Workforce Analytics can range from 12 to 24 months, as the system requires significant customization, data preparation, and integration efforts. Oracle Fusion: Similarly, Oracle Fusion's analytics solution requires extensive customization, and companies often face long implementation times before seeing value. One Model: One Model has the ability to deliver actionable insights in as little as 6-12 weeks. With a user-friendly platform and expert support, One Model allows organizations to experience value faster, making it the ideal choice for businesses that need rapid insights to drive strategic decision-making. With robust role-based security and pre-built, customizable HR metrics, users can access the insights they need without waiting for IT or BI teams. Empower HR Teams with a Tailored Solution to Align with Evolving Goals HR teams need to be agile and adapt their analytics strategies to meet shifting organizational priorities. Solutions that allow for easy customization can empower HR professionals to act quickly and align their insights with business needs. Workday Prism: Customizing reports and data models in Prism requires the involvement of skilled BI developers, leading to delays in decision-making. SuccessFactors Workforce Analytics: While SuccessFactors offers basic reporting capabilities, customizing reports and metrics is time-consuming and requires significant technical expertise, slowing down the ability to generate actionable insights. Additionally, the platform's rigid data architecture can make it challenging to create highly customized solutions that meet unique organizational requirements. Oracle Fusion: Oracle Fusion’s self-service capabilities are limited, and users need specialized skills to customize reports and analytics models. In contrast, One Model stands out for its ease of customization. One Model is designed to allow users to quickly create and customize dashboards and metrics in minutes. By offering a platform that simplifies customization, One Model enables HR teams to take full ownership of their analytics and ensure they are always aligned with evolving organizational goals. Understand Workforce Behaviors and Drive Efficiency with Predictive Analytics and Machine Learning As organizations continue to rely on data to shape their strategies, predictive analytics and machine learning are becoming increasingly vital for understanding and forecasting workforce behaviors. Solutions with built-in AI capabilities can provide deep insights into areas like turnover, performance, and employee satisfaction. Workday Prism: Prism offers basic reporting and visualization, but predictive capabilities are limited, and the platform is not optimized for machine learning applications. SuccessFactors Workforce Analytics: SuccessFactors lacks built-in machine learning and predictive analytics, leaving HR leaders with limited capabilities to forecast trends like attrition and performance. Oracle Fusion: Oracle’s analytics tools fall short in providing integrated predictive insights. Oracle offers a visualization layer, but predictive modelling requires significant customization. One Model: One Model sets itself apart with its powerful machine learning engine, One AI, which enables predictive insights across key HR metrics like attrition and performance. One Model offers complete transparency into its AI models, ensuring that businesses can maintain control over algorithms and stay compliant with legal and ethical standards. Why One Model is the Perfect Partner for Enhancing Your Existing HCM Solution When compared to Workday, SuccessFactors, and Oracle Fusion’s built-in analytics modules, One Model stands out as the most flexible, cost effective, and customizable solution for People Analytics. With faster time to value, data integration across multiple HR and business systems, and advanced predictive analytics, One Model helps businesses use their people data as a strategic asset. For organizations seeking fast, effective data-informed decision-making, One Model is the clear choice for enhancing your existing HCM solution.
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6 min read
The One Model Team
The integration of artificial intelligence into HR practices has begun to transform how companies engage, support, and optimize their workforce. By adopting a holistic, employee-centric approach to AI deployment, organizations and People Analytics teams can foster a culture of innovation, boost productivity, and ultimately create a workplace where employees are empowered to thrive. A Strategic and Employee-Focused Approach to AI Integration Implementing AI within an HR organization demands a strategic and well-orchestrated approach. A key insight from companies successfully embracing AI is to prioritize change management for AI and employee engagement. Rolling out AI solutions shouldn’t feel like a top-down directive imposed on People Analytics teams but rather a collaborative, bottoms-up process that centers on empowering employees. When People Analytics leaders take a gradual, people-first approach, they can ease anxieties associated with AI adoption. The fear that AI will replace jobs has been pervasive, and addressing this concern upfront is essential for cultivating trust. Leaders need to clearly communicate that AI is a tool to enhance, not replace, human effort. This message must resonate throughout the HR department and company, helping employees view AI as a career-enabling partner rather than a threat. Celebrating AI Adoption as a Driver of Change Measuring initial AI adoption within the HR department is a critical first step. Successful teams have shown that fostering a culture where AI usage is celebrated can accelerate adoption. One effective strategy is creating department-wide channels where People Analytics teams can share their experiences using AI and the benefits it has brought to their workflows. Highlighting these success stories not only reinforces positive engagement but also builds momentum as teams see real examples of AI delivering tangible value. Recognition programs that reward early adopters can further stimulate interest and promote active participation. This step aligns with AI change management best practices, which emphasize that for organization transformation with AI to take hold, the individuals most affected must feel supported and valued. Key Areas of AI Implementation in HR Leading organizations have deployed AI across several HR functions to drive efficiency and enhance decision-making. Below are examples of impactful implementations of AI in HR departments: 1. Recruitment and Interview Processes Integrating AI in recruitment has revolutionized how interviews are conducted and evaluated. AI-powered tools can assist hiring managers by recording interviews, generating time-stamped notes, and linking key interview moments to questions asked. This capability alone can save managers substantial time—up to 30–40 minutes per interview—by automating note-taking and providing instant access to video highlights. 2. HR Chatbots for Employee Services Advanced, AI-powered HR chatbots are streamlining routine tasks by handling knowledge base inquiries and processing transactional requests. Integrated within platforms like Slack, these bots can facilitate actions such as submitting time-off requests or accessing benefits information, freeing up HR teams to focus on more strategic work. This integration also simplifies data access and enhances the overall employee experience. 3. AI-Enhanced Learning and Development AI’s application in L&D involves deploying intelligent tools that help curate learning content, suggest development paths, and assist employees with feedback and coaching tailored to organizational competencies and values. The introduction of AI coaches for career growth discussions or navigating difficult conversations empowers employees with customized guidance that aligns with company culture and goals. 4. Democratize People Data Across Management Teams Team leaders at any level of the organization are better leaders when they better understand the workforce under their care. Business and People Analytics teams are instrumental in that goal through building dashboards and answering big complex questions. But what happens when there are too many ad hoc manager questions across the organization for the people analytics teams to answer? Originally, that meant either questions went unanswered or people analytics teams were pulled from larger, more impactful projects to help. With solutions, like One Model, that is no longer an issue. One AI Assistant is helping companies today by giving managers the ability to ask questions on the people data they can access. HR analytics teams can have confidence in the results of One AI Assistant because it provides clear explainability and transparency of outputs. Laying the Foundation for Long-Term Success Sustainable AI integration in HR and People Analytics is not just about deploying new technologies but about embedding AI into the company culture. From day one, leaders need to ensure that the tools are intuitive, accessible, and aligned with the company’s core values. Building trust in AI begins with demonstrating how these tools support employees' roles, making HR tasks less burdensome and enabling teams to tackle more strategic initiatives. HR leaders should collaborate with engineering and data teams to customize AI solutions that fit specific organizational needs. This might involve developing unique AI assistants or prompts that streamline operations and ensure consistency across processes. For instance, internal tools that summarize interview notes or assist with coding can enhance productivity without fundamentally altering job responsibilities. Creating a Legacy of Innovation and Engagement The ultimate goal of integrating AI into HR is not just to boost efficiency but to foster an environment where employees feel excited about leveraging cutting-edge tools. Organizations that prioritize a culture of continuous learning and innovation will find that their employees are more engaged, adaptive, and capable of driving the company forward. By recognizing the transformative potential of AI and implementing it thoughtfully, HR and People Analytics leaders can elevate their people strategy with AI and position their organization as a leader in the future of work. Learn more about One AI Assistant If you would like to learn more about One AI Assistant and how other One AI tools can help your team empower your entire company with business-driving insights into their workforce, reach out. Your Data. Real Answers.
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6 min read
The One Model Team
The data doesn’t lie—these are the One Model resources your peers keep coming back to. We’ve rounded up our top three most-downloaded whitepapers, plus a bonus newcomer that’s already making waves. Whether you’re searching for fresh strategies or sharpening your existing skills, these resources have proven to be invaluable to your People Analytics professionals like yourself. If you haven’t explored them yet, now’s the time to join the conversation. 1. Why Data-Informed Storytelling is the Future of HR As the field of People Analytics becomes increasingly data-savvy, this whitepaper has resonated with readers across industries, earning its place as our most downloaded resource. If you’ve struggled to tell a meaningful narrative around your data and its objective but sometimes hidden insights, data storytelling is the missing link. Stories, human anecdotes, and yes - even emotion - can help bring your data to life. It’s a powerful combo that can truly drive action for organizations. But how do you tell a meaningful data story? And why is it such a valuable skill for today’s HR teams? Download this eBook today to learn: The evolution of storytelling in HR How to craft data-informed HR stories Examples of impactful data-informed HR stories How to tell better data stories with One Model Learn how to turn raw data into compelling narratives that engage stakeholders and drive better decisions. 2. People Analytics 101 Coming in a close second in popularity, this fundamental guide is the perfect entry point for getting started in People Analytics. But even seasoned HR professionals sometimes wonder what to prioritize when establishing a strong People Analytics foundation. This content is meant for everyone, from CHROs to HR leaders looking to upskill, providing foundational knowledge that aligns your people data with your organization’s goals. Download this eBook today to learn: What People Analytics is, and why it's important How to prepare your organization for People Analytics Why employee attrition is a good starting point Steps for completing your own People Analytics projects Discover how to tailor People Analytics to your organization’s unique needs. 3. Measuring the Value of People Analytics Prove the ROI of your efforts with this comprehensive, tactical guide to measuring the tangible impact of People Analytics. A must-read for leaders seeking to align HR initiatives with business outcomes or make a business case for People Analytics. Download this whitepaper today to learn: How to redefine and measure the value of People Analytics beyond traditional ROI metrics. The three levels of People Analytics impact—direct, indirect, and induced—and how they drive better talent decisions. A practical formula for assessing the value of analytics deliverables and prioritizing resources effectively. Strategies for scaling People Analytics impact through self-service solutions and fostering a data-driven decision-making culture. Confidently calculate and articulate the impact of your HR analytics on organizational performance. Bonus: From Data to Strategy: The New Workforce Systems Leaders Transforming HR Our newest whitepaper, authored by our VP of People Analytics Strategy Richard Rosenow, recently launched to an enthusiastic reception. Clearly, it struck a chord. Focused on the emergence of a new People Analytics role that aligns the flow of data through an organization (which Richard dubbed the people data supply chain), this highly anticipated resource provides insight into the typically uncharted path of People Analytics leaders. Download this eBook today to learn: Key challenges in People Analytics (it’s not just you!) Actionable strategies for mastering the People Data Supply Chain, including an real-world example for managing attrition Who are Workforce Systems Leaders and what do they do? Get prepared to lead the next evolution of workforce management. Next steps? Contact us with your questions or to schedule a One Model Demo.
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15 min read
The One Model Team
Transcript: Hi, everyone. Let’s dive right in. Today, we’re going to talk about unlocking the power of people data platforms—what that means, how to access your data, and how to connect with it in meaningful ways to drive insights across the workforce. Introduction I’m Richard, and for those I haven’t met, it’s great to meet you. A bit about me: I started my career in nonprofits—shout out to others here with a nonprofit background! From there, I moved into HR, focusing on workforce planning at GE Capital, followed by roles at Citibank. Eventually, I discovered my passion for People Analytics, which shaped the trajectory of my career. I’ve had the privilege of working on People Analytics teams at companies like Facebook, Uber, Nike, and Argo AI. Each experience taught me something new about building scalable teams and leveraging technology to solve big challenges. For example, at Facebook (when it was still Facebook), our People Analytics team grew from 15 to 150 people. It was an exhilarating time, but not every organization can afford that kind of scale. So, when I moved to Uber, the focus was on how to scale smarter—how to build products and platforms instead of large teams. At Nike, I also helped build data foundations and worked closely with data engineering teams to develop a more robust HR data hub. When I moved to Argo AI, I worked across HR tech, People Analytics, and project management. I was heavily involved with Workday and began exploring One Model, which shaped my approach to building scalable analytics solutions. Fast forward to today: I’m now VP of People Analytics Strategy at One Model, where I get to connect with hundreds of People Analytics teams annually. This has given me a unique perspective on what’s working, what’s not, and where we’re all heading. Why is People Analytics So Hard? Let’s start with a key question I ask every time I talk about People Analytics: Why is this so hard? People Analytics as we know it is still relatively new. The modern function emerged maybe 15 years ago, and while it’s evolved a lot since then, we’re still figuring it out. There are so many names, frameworks, and definitions out there—it’s confusing for everyone. If you’re struggling to make sense of this within your organization, know that you’re not alone. From Facebook to smaller companies, everyone finds this hard. Defining People Analytics When I talk about People Analytics, I use three definitions: Community People Analytics is a community of practitioners working to create better workplaces through data. If there’s one thing you take away today, it’s this: there is a thriving People Analytics community out there. It’s full of nerdy, passionate people who love this topic. If you’re curious about data or looking to use it more effectively in your organization, find these people—they’re everywhere and eager to connect. The Act The act of People Analytics is simply using data to support workforce decisions. This isn’t just an HR responsibility—everyone in the organization, from managers to the CEO, makes workforce decisions. They should all be using data to do it. The Function The People Analytics function is the team within HR that supports this work. They build systems, provide guardrails, and help the organization use data effectively. The Invisible Work of People Analytics Leaders One challenge for People Analytics leaders is that they’re often hired for one job but end up doing another. Their job descriptions focus on descriptive, predictive, and prescriptive analytics. But once they start, they realize IT and HR haven’t spoken in years. They’re stuck cleaning data, navigating politics, and trying to get access to systems—none of which were in the job description. This invisible work is critical but goes unrecognized. If you have a People Analytics leader, send them a note and let them know you see and appreciate their effort. The "Skipped Step" in HR: People Data Here’s where the real problem lies: HR skipped a step. We went from strategy to operations to technology without fully addressing people data—the process of extracting, cleaning, and organizing data into a comprehensive HR data hub. Analytics teams are left backtracking to fix foundational issues before they can deliver insights. This skipped step creates pain for everyone. And it’s becoming even more critical now that HR data systems are feeding not just analytics but also Generative AI. The Little Red Hen Moment This brings us to what I like to call the "Little Red Hen Moment." You might remember the story: the Little Red Hen finds some corn and asks the other farm animals, "Who will help me plant the corn?" They all say no. So she plants it herself. Later, she asks, "Who will help me harvest the corn?" Again, no one helps. She does it herself. Then she bakes the bread and asks, "Who will help me eat the bread?" And, of course, suddenly everyone wants in. This is exactly what happens with People Data in many organizations. HR leaders ask, “Who will help us build the business case for People Analytics?” The data engineering team says, "Not I," because they’re busy maintaining data pipelines for sales. The IT team says, "Not I," because they’re focused on streamlining the vendor landscape. The enterprise analytics team says, "Not I," because they’re prioritizing metrics for finance. So HR is left to plant the corn, harvest it, and bake the bread on its own. We pull together data manually, build foundational systems, and lay the groundwork for analytics and insights—all while trying to establish a sustainable workforce data supply chain. But once those insights are ready—once the bread is out of the oven—everyone shows up to eat. The same teams that didn’t prioritize People Data suddenly want the insights it produces. They’re eager to see workforce metrics, predictive models, or generative AI results, but they don’t recognize the effort it took to get there. This isn’t just an HR problem; it’s a structural issue. HR has been underinvested in and systemically held back. Other business functions—like finance, marketing, and operations—have robust platforms and strong executive support. HR deserves the same level of investment to drive business outcomes. The message here is simple: it’s time for HR to demand a seat at the table and take HR data ownership People Data and build a robust HR data hub to succeed.. We need to make the case for why this work matters—not just for HR, but for the entire organization. The Framework for People Data Platforms Let’s talk about People Data platforms—which are essentially the foundation for a workforce data supply chain. A platform has two key components: The Data Foundation This is where data is extracted, modeled, and organized. It’s the backbone of everything, including generative AI. The Application Layer This is where data is visualized, analyzed, and put to use. At One Model, we’ve developed a framework that covers every stage: extract, model, store, analyze, and deliver. Each step has detailed requirements, and we provide tools to help organizations navigate them effectively. Dive deeper into the 5 Steps to Get Data Extraction Right. Conclusion People Analytics is hard, but the opportunities are enormous. By investing in People Data platforms and supporting our teams, we can create better workplaces and drive smarter decisions. Q&A Q1: During the modeling phase, are you prioritizing data? Is all of it being stored, or are you storing it in multiple places? Are you saying, “This is the most useful for dashboards,” and keeping other data as a backup in case it’s needed for KPIs later? What does that look like? A: That’s a really good question. Here’s how it typically works: You have data that sits in your core HR tools, the data you extract from those tools, and the modeled data you use for analytics. Along the way, you need to maintain copies—raw files, for example—for audits. But it’s the modeled data that should be driving your business decisions. What often happens in HR is that we’re told, “Just pick what you need,” because we aren’t given the resources to extract and store everything. This is one of the things One Model addresses—we create a single, unified data model where all your data is combined and accessible in one spot. This approach is becoming the norm for mature People Analytics teams. They no longer accept being limited to a single report from Workday or any other system. Instead, they demand full access and make sure their data is modeled and ready for any use case. And this is important because features in your data can play into your models in surprising ways. For instance, data from internal communications platforms like FirstUp can be remarkably effective for attrition prediction, but it’s often difficult to get access to that data. Q2: So, you’re doing predictive modeling as well. Can you use the same scripts or frameworks and apply them to different datasets? A: That’s a great question. Another key point to understand here is the difference between data extracts for reporting and data extracts for data science. For example, Workday provides daily snapshots of data. That works fine for reporting, but for predictive modeling, you need data over time. HR data is especially time-sensitive—more so than in many other functions—because of how events like transfers, exits, and tenure affect workforce insights. You can’t have someone transferring after they’ve already quit. The sequence of events really matters. This is where taking raw file snapshots and turning them into analytical feeds becomes critical. The ability to extract data for machine learning and predictive modeling is fundamentally different from extracting data for reporting. It’s something HR teams need to be aware of and push their IT teams to support because I’ve seen too many teams pressured into settling for reporting-level extracts, and it’s just not enough. Q3: When working with highly customized platforms like Workday or your ATS system, you often can’t—or don’t—make changes. For example, adding regrettable versus non-regrettable turnover as a data point can require defining those terms and assigning someone to audit that information. What advice do you have for making the business case for these changes? A: That’s an excellent question. Two things come to mind. Bring the stakeholder’s pain with you Let’s say you have a stakeholder downstream who’s really feeling the pain from a lack of data, like not knowing whether turnover is regrettable or not. Often, HR tries to solve this issue internally, on behalf of the stakeholder, by negotiating changes with upstream teams like HR tech. The problem is, the tech team doesn’t feel that pain firsthand, so they don’t prioritize the change. Instead, bring the stakeholder along with you to these discussions. Let them articulate their challenge directly to the HR tech team. When the tech team sees how their choices—or lack of action—are impacting the business, they’re more likely to respond. Create a new umbrella function The other solution I’ve seen gaining traction is hiring a leader to oversee People Analytics, HR technology, HR strategy, and operations as a single function. We call this the “workforce systems leader.” About 40 Fortune 50 companies have already started building roles like this. This umbrella leader can help navigate the politics and make tough decisions more efficiently. For instance, they can prevent unnecessary internal friction, like the head of People Analytics clashing with the head of HR tech. Instead, this leader would coordinate those efforts to drive progress forward. Q4: How do you recommend building a relationship with IT so they understand HR’s needs without seeing it as interference with data governance? A: That’s a fantastic question. I’ll give you two approaches—one "nice" and one a little more assertive. The nice way A lot of times, IT leaders (and finance leaders too) don’t fully understand HR’s technical needs. But they do understand their role as people leaders. So, start by framing the conversation in terms they’ll relate to. For example, you might say, “You’re leading a 400-person organization. Do you have visibility into what’s happening in your own team? Do you know where your pain points are?” This can help them see how better data access benefits not just HR but also their own leadership. The assertive way Here’s the reality: Other functions, like IT or finance, have no problem saying "no" to HR. But when they need something—like hiring 50 new project managers—they come to us, and we almost always say "yes." HR is often the ultimate team player, taking on more than its share of the load. While that’s great in theory, it can sometimes weaken our bargaining position. To build a stronger relationship with IT, we need to be more assertive about our needs. For example, we might say, “If you want to continue working the way you are, we’re going to need support from you. Let’s come to the table and figure this out together.” In short, it’s about clear communication, mutual accountability, and, sometimes, standing our ground to get what we need. Thanks, everyone! Ready for a deeper dive? Download Achieving People Analytics Maturity with a People Data Platform today for more insights on maturing your workforce data for actionable insights.
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4 min read
The One Model Team
Having the right vendor partnership can make a huge difference. And the wrong one can lead to huge headaches. One Model understands this, and we strive to be more than just another software provider. We seek to be a trusted partner for both HR and IT teams, deeply entrenched in the success of both departments. By partnering with One Model, tech teams get: Expert resources to field HR’s requests A common challenge many businesses face is the reliance of HR teams on their internal IT for business intelligence (BI) support. This not only strains IT resources but also may not always result in optimal solutions tailored for HR needs. With One Model, HR gets access to expert People Analytics resources. This isn't just about having an extra set of hands; it's about having a skilled set of hands, well-versed in BI, ready to converse, collaborate, and create. More time to focus on IT initiatives With One Model, tech teams can channel their energies and expertise towards initiatives directly tied to their KPIs. Our proposition is simple: let us empower HR with solutions that meet their BI needs while IT reallocates their time towards other tech initiatives. This isn't about pitting departments against each other; it's about recognising and optimising strengths of both groups. Increased transparency and accessibility If there's ever a need for IT to get involved, no problem. One Model's platform is built on transparency. Developers can literally inspect the SQL, ensuring a seamless integration of our platform into your ecosystem. This creates a harmonious interplay between HR and IT, with both departments benefitting. A cost-effective approach to People Analytics The cost of hiring and maintaining a single data engineer is substantial, and it’s not easy to find IT candidates with People Analytics experience. Data engineers often earn an annual salary of over $110,000 each year. And this doesn’t even include additional expenses your organisation will need for data architects, project managers, and other resources — especially as you scale. Partnering with One Model's team is much more cost-efficient, allowing you to allocate your resources more strategically. “From the tech leader’s perspective, there’s a significant cost to having HR rely on your internal IT team for BI support. So as you consider building your own solution from scratch or buying a People Analytics tool, One Model’s flexible platform is ideal because we’ll partner with your HR team and deliver the best of both worlds. We specialise in supporting HR’s needs, so tech teams can focus on their own KPIs. And, if developers ever have questions, One Model is open enough for them to jump in and literally look at the SQL. It’s a win-win for HR and IT.” — Taylor Clark, Chief Data Scientist, One Model Navigating the complexity of people data While many development teams are adept builders, navigating the labyrinth of people data is a different beast altogether. A common misconception is that IT teams can effortlessly manage data extractions, transformations, and integrations from HR systems. The reality? People data is complex, intricate, and often disorganised. “Many IT teams are already handling data extractions, transformation, and integrations across HR systems. With that experience, the justifiable assumption is that People Analytics will be a straightforward project. But the challenges of People Analytics are unique. For example, creating historically accurate, effective dated data models across multiple systems. One Model is the only vendor that confronts these challenges head on.” — John Carter, Senior Sales Engineer, One Model With One Model, you're not just getting a People Analytics platform, you're gaining a partner skilled in deciphering, managing, and optimising people data. Where many falter, we excel. The challenges that often stymie others, like managing Workday's unique constraints, are where our expertise comes to the forefront. We do the heavy lifting, ensuring that HR's data needs are met so tech teams can avoid the typical complexities. Our approach isn't just about providing a platform. It's about building a valuable, long-term partnership and commitment to ensure the success of HR, IT, and the overall company. Ready to learn more Download our whitepaper Why Tech Leaders Prefer One Model’s People Analytics Platform to learn 4 key reasons IT teams choose our platform over others on the market.
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6 min read
The One Model Team
As we look ahead to the coming year, we’re proud to reflect on the groundwork we’ve laid. This year has been about creating and improving the tools and partnerships you need to transform your workforce analytics and HR technology into a strategic advantage. At One Model, we know the best insights come from seamless HR data integration. That’s why we’ve doubled down on enhancing our connections with industry-leading platforms like Workday People Analytics, SAP SuccessFactors HR solutions, and Oracle PeopleSoft HCM. These integrations don’t just connect systems — they unlock the full potential of your workforce data, empowering you to make decisions that drive real impact. 1. Our Workday Integration: Driving Innovation Through Partnership This year was a big one for us: One Model became a proud Workday Innovation Partner! This milestone reflects our commitment to delivering cutting-edge solutions for Workday customers. Our enhanced Workday Connector is designed to ensure you can move beyond the basics and get actionable insights that truly make a difference. Why Workday + One Model stands out Direct access to Workday’s core data sets without disrupting your workflows. Advanced analytics that make Workday data even more impactful. Innovation recognized by Workday itself through our official partner status. Curious about what this means for you? Take a deeper dive into the possibilities of liberating your data with our updated Workday People Analytics Playbook. 2. Our SuccessFactors Integration: Unlocking Your HR Powerhouse SuccessFactors is a go-to platform for HR leaders, known for its robust workforce data. But having great data is only half the battle — making it actionable is where One Model comes in. With our SuccessFactors integration, you get clean, consistent data flows and a foundation for high-impact analytics. What makes this integration special? Streamlined extraction of key people data like workforce demographics, performance, and learning metrics. Flexible data models that adapt to your business needs. Real-time insights that empower smarter decision-making. Explore how to make the most of your HR AND non-HR data. Download our guide to Unlocking SuccessFactors People Data. 3. Our Oracle Integration: Turn Complex Data Into Actionable Insights Oracle’s platforms are known for their depth and versatility, offering rich data opportunities. But managing that complexity can sometimes feel overwhelming. With One Model’s Oracle integration, you can cut through the noise, unifying data streams and simplifying access and empowering your team to focus on insights that drive results. Why this integration matters: Brings together diverse Oracle data sources for a unified view of HR metrics. Scales with your organization’s needs, no matter how complex your data ecosystem gets. Provides decision-ready insights so you can spend less time wrangling data and more time driving strategy.. Get the full story on maximizing Oracle’s potential and bringing your data to life. Download our Oracle People Analytics Playbook. Ready to Unlock Your People Data? Integrations are the backbone of effective analytics, and with One Model’s solutions for Workday, SuccessFactors, and Oracle, (and many other data platforms) you can empower your team with the insights they need to drive success. Whether you’re looking to simplify data extraction, enhance workforce planning, or align your HR strategies, our integration whitepapers are a great way to get started. Explore them now and see what more your data could be doing for you.
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7 min read
The One Model Team
As you know, People Analytics has evolved far beyond basic HR metrics like turnover rates or headcount tracking. As organizations seek to make smarter, proactive decisions about their workforce, they’re turning to more sophisticated People Analytics techniques. Moving beyond foundational metrics, advanced analytics — like predictive modeling, sentiment analysis, employee journey mapping, and ethical AI considerations — offer HR professionals the opportunity to play a powerful, proactive role in shaping their organization’s future. With these tools, HR leaders can anticipate challenges, influence key decisions, and drive meaningful, strategic change. This blog explores four advanced analytics techniques that help People Analytics leaders move from basic reporting to making decisions that resonate throughout the organization. 1. Predictive Analytics: Looking Ahead with Confidence What It Is: Predictive analytics leverages historical data to forecast future workforce trends, such as turnover risks, performance outcomes, or employee engagement levels. By identifying patterns within existing data, organizations can make proactive decisions, positioning them to address issues before they arise. Applications: Predictive analytics is highly valuable for HR teams aiming to prevent turnover in high-risk teams, pinpoint factors that impact employee engagement, or understand potential productivity trends. For instance, if a team shows signs of elevated turnover risk, leaders can intervene early — offering targeted support or resources to improve retention. Example: Consider a company that uses predictive analytics to identify teams with high burnout risk based on previous data trends, like prolonged overtime hours or low engagement scores. With this foresight, HR can intervene with support initiatives, helping employees recharge and boosting retention. Learn more about our One AI and One AI Assistant predictive analytics. 2. Sentiment Analysis: Understanding Employee Emotion at Scale What It Is: Sentiment analysis uses natural language processing (NLP) to interpret the emotional tone behind employee feedback, open-ended survey responses, and internal communication channels. By analyzing this data, companies gain a real-time understanding of employee morale and can detect early signs of dissatisfaction. Applications: Sentiment analysis can track morale trends across the organization, identify engagement dips, and help HR better understand employee needs. This technique allows for “pulse” insights, where sentiment can be monitored continuously, alerting leaders to shifts in morale. Example: A company might use sentiment analysis to monitor feedback on a recent policy change. If negative sentiment spikes, leadership can quickly address concerns, maintaining trust and morale by responding with empathy and transparency. 3 Keys to Effective Listening at Scale 3. Employee Journey Mapping: Visualizing the Employee Experience What It Is: Employee journey mapping visualizes each stage of an employee’s experience, from recruitment to exit, identifying critical touchpoints that affect engagement, satisfaction, and retention. By mapping these interactions, HR can see where employees thrive or struggle, allowing for targeted interventions. Applications: Journey mapping is valuable for tracking specific experiences such as onboarding effectiveness, career development paths, and retention at pivotal moments. It provides insights into the employee lifecycle, helping HR design initiatives that enhance satisfaction and reduce turnover. Example: Using Sankey diagrams, a company could visualize the journey from onboarding through various career milestones — revealing, for instance, that many employees exit after two years in certain roles. This insight enables HR implement targeted engagement or development programs during critical points in an employee’s journey. 4. Ethical Considerations in Advanced Workforce Analytics Why It Matters: As People Analytics methods become more advanced, ethical considerations grow in importance, especially around data privacy and employee consent. Ensuring responsible data use is essential for maintaining employee trust and aligning with broader organizational values. Best Practices: To conduct People Analytics ethically, companies should anonymize data wherever possible, obtain clear employee consent, and maintain transparency about data collection and usage. A commitment to ethical guidelines isn’t just about compliance — it strengthens trust and encourages openness to analytics-driven initiatives. Example: Organizations risk overstepping by monitoring too closely, which can lead to feelings of surveillance among employees. Ethical People Analytics is about balance: using data to benefit the organization while respecting employees’ privacy and autonomy. Conclusion: Moving from Insight to Impact The field of People Analytics has grown into a powerful strategic tool, and advanced HR analytics techniques like these (and others) enable HR leaders to anticipate, understand, and enhance the employee experience in proactive, strategic ways. Ready to take your People Analytics impact to the next level? Measuring the Value of People Analytics dives even further into implementing these advanced analytics strategies and gaining a sustainable advantage. Complete the form below to download it today and empower your People Analytics team with the tools needed for meaningful, data-driven change.
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5 min read
The One Model Team
The Cost-Time-Quality triangle can be a helpful tool when comparing various technology options. This framework is commonly called the “Project Triangle,” but we have modified it here to break out Flexibility as a critical fourth element — creating a diamond shape. The rationale for extending the triangle to include Flexibility is that analytics in all domains is full of unknowns. A rigid design could never anticipate all the future use cases and content demands of an ever-changing world. Doing a meaningful comparison of solutions requires an understanding of the relative flexibility of the various options being considered. And so our suggested framework for comparing people analytics technology options is the Project Diamond. Comparing the three options Below you’ll find a generalised comparison of each option using the Project Diamond framework. These findings are based on our direct experiences and discussions with customers and other people analytics experts, so consider it illustrative. Cost To build a solution from scratch, you’ll still need to buy a bunch of technology (eg, BI tools, data warehouses, and hardware). And there are often many hidden costs associated with that approach. In a buy option, the cost is typically the technology license/service fee, which has a two or three year commitment, as well as any initial implementation services. In a build option, the cost represents the IT and PA resources that are needed to create the data model and metrics definitions, the warehouse and visualisation tool costs, and any required maintenance and change order costs. Opting for a platform that offers the best of both buy and build generally has the same initial entry cost as the buy option, but is less expensive overall since access to the skilled data engineers and an experienced customer success team augments your resources, supports additional requests, and reduces rework throughout your people analytics journey. Depending on the vendor you select, that type of support will cost you extra red tape, extra dollars, and potentially even extra resources towards manual work. Time Internal build projects nearly always run slower than planned, and they often fail altogether. There are countless stories and statistics on failed business intelligence projects. Buy options leverage pre-built assets to deliver a “turnkey” people analytics experience that can get you up and running relatively quickly. But for some vendors, implementation can be a long and drawn-out process. Instead, you could opt for the best of both buy and build. So you get a fast implementation experience with a proven and pre-built starting point, and you also get the ability to enhance and build upon that starting point over time — either on your own or alongside the vendor’s knowledgeable customer success team and skilled data engineers. Quality This element has more potential for overlap. There is wide variation in what may be built internally since internal IT teams have considerably less experience working with data from HR systems in an analytics context. While high quality builds can exist, they require superb internal IT resources and incredible amounts of time and money. A common downfall here is that the initial implementation team declares success and rolls off to another project, leaving a knowledge and capability gap. Buy could be better quality than a build since you get a pre-built starting point, but that depends on the vendor. Choosing a PA platform that can deliver the best of both buy and build will ensure the highest quality solution. This option allows teams to get the full value out of all their HR data — by centralising it into a single source of truth, transforming it into an integrated dataset purpose-built for people analytics, and configuring the platform and analyses to their organisation’s exact requirements. And if the vendor has a highly-skilled team of data engineers available to support, PA teams gain a partnership with talented individuals who can ensure the quality of the data assets they create. Flexibility The most significant gap is in flexibility. Internal build solutions usually involve multiple teams, and the data and analytics needs of HR must compete for resources with the business’ core product and customer data needs. Meaning the HR function often needs to wait in line for basic changes to their data warehouse and visualisations, and their simple request could be very challenging to execute. In a buy scenario, there is ongoing innovation from the provider as they need to remain relevant and competitive in the marketplace. But that vendor may not make the enhancements your team needs or allow for configuration within the tool they’re selling. If you’re looking for the best of both worlds, you’ll want to purchase a flexible PA platform that allows teams to either build their own data assets within the purchased solution, or partner with the vendor to support that build. The ideal vendor will focus on transparency, flexibility, and customisation — enabling people analytics teams to access the backend of the platform to configure their instance to fit their exact needs. Ready to learn more? As you use Project Diamond to assess your people analytics technology options, you may want to download our whitepaper The Evolution of the Buy vs. Build Conversation in People Analytics, which can help you use Project Diamond to determine if buying an out-of-the-box solution, building an in-house solution, or choosing a path that delivers the best of both worlds is right for you.
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5 min read
The One Model Team
In his talk, "Under the Hood: AI-Driven Engineering Workflows for Future of Work," Chris Butler, CEO of One Model, addressed what's coming and how it will impact everything. The key takeaway? AI is about to change the game for productivity by enabling what Chris calls "agentic workflows." Here’s a peek at what that means and why it’s a big deal for your workplace. The AI Ecosystem is Opening Up The enterprise AI ecosystem is evolving quickly. Imagine an AI at work that doesn’t just answer questions but can also take action—accessing tools, managing processes, and optimizing workflows. According to Chris, the likes of Microsoft’s Copilot, Apple’s assistant, and other major players like Salesforce are poised to become the AI linchpins of the workplace. Soon, AI won’t just assist; it will be seamlessly integrated into every facet of your digital workspace. Enter Agentic Workflows One Model is currently building agentic workflows to turbocharge workplace efficiency. Think of a group of specialized AI agents, each with its own job description, working collaboratively—just like a project team. From gathering data, analyzing it, and critiquing results to creating dashboards, these agents mimic the roles of a traditional data team. The result? Faster, smarter outputs that scale without needing more people. Chris gave real-world examples of ai agents in action: An AI project manager, data engineer, and analyst worked together to gather compensation data, clean it, and create insightful reports—tasks that normally take days were completed in hours. The AI agents interact with each other in natural language, refine each other’s work, and iterate until the job is done right. From Four Agents to a Swarm What started as four distinct agents evolved into a swarm—a scalable network of specialized agents able to handle increasingly complex projects. By shifting to a directed graph model, One Model made it possible for multiple agents to work in parallel, dramatically reducing project time. Chris shared an impressive example: A task that two senior data engineers estimated would take twenty days was completed by AI in just 45 minutes. Another key takeaway is that the more specialized the agents work, the higher quality the output. Therefore, having more specialized agents is better than a few multi-purpose ones. What Does This Mean for Productivity? The implications are huge. AI-driven workflows mean fewer manual tasks, faster data processing, and a deeper focus on insights that matter. Companies can double down on their core missions while relying on AI to handle tedious, data-intensive work. Chris predicts that enterprise AI will become the interface we use to ask questions and get work done—a one-stop assistant that pulls insights from different tools and presents them in a digestible way. Dashboards Are Dead—Almost In the future dashboards as we know them may become secondary. Instead of static reports, enterprise AI will generate dynamic, on-demand insights and even make recommendations. Dashboards will still exist, but they’ll be an interface controlled by the AI—just one of many tools in the box. The first point of interaction will be the AI itself, which will decide what tools to use to provide you with answers. Securing the AI Frontier Chris also highlighted a critical concern: securing enterprise AI. As these AIs gain more access to tools and data, the risk of improper usage grows. HR and People Analytics teams need to partner closely with IT to ensure that the right security measures are in place—because once access is lost, it’s hard to regain control. Welcome agentic workflows to the team. Agentic workflows are reshaping the future of work. The enterprise AI of tomorrow won’t just assist employees; it will be an active participant in getting work done—faster, smarter, and more securely. Are you ready to work with your new AI teammates? Are you thinking about using AI? You'll need a solid data platform. Learn why that is so critical and see how you can achieve success by reading our whitepaper.
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8 min read
The One Model Team
Imagine you’re preparing your team for a project involving cutting-edge AI tools that didn’t even exist five years ago. You’ve assembled the best people you can find, but you quickly realize there’s a significant skills gap. Or perhaps you’re ready to expand into new markets, but the local talent is scarce, and your remote work policies are outdated. You need the right people, with the right skills, at the right time—yet it’s no small feat to make that happen. This is the reality for organizations today. Rapid technological advancements, especially in artificial intelligence, mean that the skills needed to stay competitive are constantly evolving. And while it’s tempting to address these challenges with reactive hiring and quick fixes, that approach only goes so far. What companies need is a sustainable, proactive approach to workforce planning—one that ensures your team isn’t just equipped for today’s challenges, but positioned for future growth as well. Here’s a quick overview of a modern workforce planning methodology for doing exactly that. STRATEGY: Start with the Vision Before diving into the details of talent acquisition strategy, take a step back and ask: What’s our long-term vision, and how should our workforce evolve to support it? As AI transforms job roles across industries, workforce strategy must adapt by aligning every decision about hiring for skills gaps, development, and retention with the company’s future needs. For example, a tech startup embracing AI-driven innovation might prioritize flexibility and tech-savviness in its talent acquisition strategy, looking for individuals who can work alongside AI tools and understand how to leverage them for greater efficiency. OPERATIONS: The Infrastructure that Keeps Things Moving With AI tools entering the workplace, operations play a critical role in ensuring that systems and processes keep pace. Imagine operations as the logistical backbone of workforce planning—it encompasses the workflows that handle headcount requests, onboarding protocols, and ongoing workforce management, but also integrates AI where it can streamline processes and enhance efficiency. A manufacturing company, for instance, might utilize AI-driven scheduling tools to manage production ramp-ups more effectively. Strong operations allow organizations to react to immediate needs—such as ramping up production or hiring for skills gaps—without compromising on strategic goals. ANALYTICS: Gaining Insight into the Workforce AI-driven analytics now enable organizations to gather workforce planning insights with unprecedented speed and precision. Leveraging analytics allows companies to track workforce trends, assess AI’s impact on skill requirements, and even forecast future needs based on anticipated AI developments. For instance, a healthcare organization might use workforce analytics powered by AI to predict staffing needs, identify high-turnover roles, and uncover insights that guide decision-making. By using AI-enhanced analytics, leaders can transition from intuition-based decisions to data-driven strategies that keep the workforce planning process aligned with evolving business needs. PLANNING: Mapping the Path from Today to Tomorrow Planning is where strategy and analytics converge to form a clear, actionable roadmap, especially crucial in an AI-powered world. With AI transforming industries at breakneck speed, organizations need planning that not only fills immediate gaps but also anticipates long-term shifts. Consider a retail company that uses AI to predict customer demand for the holiday season. By using this data to create a workforce planning strategy, they can assess the skills needed, optimize staffing levels, and allocate resources efficiently. A well-defined plan helps organizations stay a step ahead, allowing them to allocate talent where it’s needed most—both today and in an AI-driven future. INTELLIGENCE: Looking Beyond the Company Walls A strong workforce planning methodology also demands a focus on external intelligence. This means staying attuned to shifts in the talent market, industry developments, and the competitive landscape—especially as AI reshapes the types of skills that are in demand. By gathering insights on AI-related trends, organizations can make better-informed decisions about where and when to invest in talent. For instance, a company might discover that its competitors are investing heavily in AI training programs for employees. This intelligence can drive proactive decisions, like launching an internal AI upskilling initiative to stay competitive and attract tech-forward talent. Putting It All Together By taking a holistic approach to workforce planning, companies can move from being reactive to AI-driven change to proactively leveraging AI’s potential. Through the pillars of Strategy, Operations, Analytics, Planning, and Intelligence (what we call the SOAPI framework), leaders can create a workforce that’s equipped to not only meet today’s demands but thrive in the AI age. In a world where technology is reshaping work at every level, those organizations that take a proactive, integrated approach to workforce planning will be best positioned to lead. Whether you’re preparing for an AI-driven project, expanding into new markets, or future-proofing your team, it’s time to move beyond quick fixes and build a workforce that’s truly ready for what comes next. The One Model Difference Effective workforce planning is powered by data and AI, and One Model offers the tools to make it seamless. With One AI and the One AI Assistant integrated into the People Data Cloud™, One Model provides a powerful people analytics platform that consolidates, cleanses, and models workforce data. This AI-enhanced solution equips HR teams with real-time insights, enabling smarter, faster decisions across every stage of workforce planning. Whether forecasting talent needs or optimizing current roles, One Model ensures organizations can proactively build a workforce that’s aligned with AI-driven change while upholding high standards of data security and privacy. Ready to dive into the full SOAPI framework structure and set a foundation for a thriving workforce planning strategy? Download now!
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The One Model Team
Workforce planning and forecasting have become paramount for finance leaders to navigate market uncertainties and stay ahead of the competition. One Model's advanced People Analytics platform enables finance leaders to make smarter data-driven decisions, propelling their business toward sustainable growth and increased profitability. Centralise HR and Finance data for accurate predictions. The foundation of effective workforce planning lies in the ability to consolidate data from various sources into a single, reliable location. One Model achieves this by seamlessly integrating HR data with finance data, creating a centralized hub of valuable insights. By breaking down silos and allowing for data collaboration, finance leaders can gain a comprehensive understanding of their workforce, leading to more accurate predictions and tactical strategies. Slice and dice data more efficiently. Traditional ERP systems often struggle to handle the sheer volume and complexity of workforce data, leading to sluggish reporting and analysis. One Model, on the other hand, offers the ability to slice and dice data with ease, providing real-time insights and a granular, employee-level detail. Finance leaders can effortlessly examine the cost and productivity drivers at a departmental or individual level, empowering them to implement strategic initiatives with surgical precision. Identify high performers and which roles deliver the most value. Understanding the contribution of each role within an organization is crucial for effective workforce planning. One Model's advanced analytics capabilities offer improved visibility into productivity, revealing which roles deliver the most value to the organization. By identifying top-performing roles and focusing on their development, companies can reduce costly turnover, unleash the full potential of their workforce, and bolster overall performance. Better prepare for mergers, acquisitions, and divestitures. The financial services sector often witnesses mergers, acquisitions, and divestitures, which can lead to complex organizational changes and talent restructuring. With One Model, finance leaders can confidently embark on these transformations by leveraging the platform's capabilities. One Model can provide quick insight into topics such as your spans and layers that would traditionally involve high-cost and time-consuming consulting projects. From developing clear organizational structures to conducting talent audits to retain key personnel, One Model ensures a smooth transition and alignment of talent with strategic goals. Make more data-informed business decisions. Quick and informed decisions are critical for CFOs. With One Model, you can build your own metrics and definitions for headcount, FTE (full-time equivalents) updated daily, and other performance indicators to assess the return on investment from talent programs. And if Finance and HR can’t agree on how a certain metric (e.g., headcount) is calculated, One Model can support both variations. With clear insight into headcount and FTEs, you can better measure performance and plan labor needs. One Model delivers a holistic view of talent distribution and performance so Finance leaders can optimize headcount for the company’s needs, maintain cost-efficiency, and strike the perfect balance between talent and resources. Facilitate deeper conversations between HR and Finance. HR and Finance teams can have more meaningful and pointed conversations using One Model — where all the workforce data is captured, data quality is managed, and all related dimensions (e.g., hierarchies, employee attributes) are available for analysis. Bringing HR and Finance teams together can help your company accelerate your People Analytics journey and more easily identify opportunities to turn a profit. With One Model you can gain insight into more advanced metrics like Return on Human Investment Ratio (the ratio of operating profit, adding back total compensation expense, returned for every dollar invested in employee compensation and benefits) and hundreds of others to level up your HR and Finance decision making. Two examples of content specifically designed to align HR and Finance teams and empower them to make smarter data-driven decisions are: Headcount Storyboard — Setting up a storyboard which shows headcount represented in multiple ways: FTEs vs. employee counts, variations of which statuses are included/excluded, etc. This information becomes readily comparable with the metric definitions only a click away. Even better, the storyboard can be shared with the finance and HR partners in the discussion to explore on their own after the session. One Model is the best tool for counting headcount over time because it can support multiple variations. Hierarchy Storyboard — Providing views of the headcount as seen using the supervisor and cost hierarchies side-by-side will help to emphasize that both are simultaneously correct (i.e., the grand total is exactly the same). This can also provide an opportunity to investigate some of the situations where the cost and organizational hierarchy are not aligned. In many cases, these situations can be understood. Still, occasionally there are errors from previous reorganizations/transfers which resulted in costing information not being updated for a given employee (or group of employees). One Model is your partner for profitable growth One Model stands out as the ideal People Analytics partner for companies seeking to drive profitability through data-driven decision-making. If you’re ready to learn more, download our eBook 4 Ways CFOs Can Increase Profitability with One Model’s People Analytics Platform to discover even more ways our platform can enhance your profits.
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3 min read
The One Model Team
One Model was founded around a goal of helping teams tell data-informed stories that lead to brilliant, data-driven talent decisions. By leveraging data and story, we can help teams communicate a deeper understanding of the tangible benefits of diversity, equity, and inclusion initiatives, and how they contribute to the success of a business. Data-informed stories can be a powerful tool for uncovering how the work environment is impacting our employees. Through data, we can demonstrate the positive impact of treating people well, and how this can drive business success. Let’s walk through one of the “classic stories” we hear in HR and people analytics for a fictional organisation called Innovative Enterprise. We’ll start with the story, introduce the data, and then apply One Model’s data-informed storytelling framework to the story to show how our platform easily weaves the narratives together. This is a common story that HR teams are asked to tell around employee experience and the impact that a positive work environment can have on the overall business. Story alone: Within Innovative Enterprise, while we have a diverse workforce, this diversity is yet to permeate our leadership effectively. Our leadership team, although competent and committed, does not fully represent the diverse perspectives present within our broader team. This lack of representation in leadership could potentially influence our culture and engagement levels. Data alone: Internal data at Innovative Enterprise shows that while 49% of our workforce identifies as ethnically diverse, only 15% of our leadership does. Recent industry studies that the people analytics team analysed indicate that organisations with diverse leadership teams outperform those without by 35% in terms of innovation and creativity. Moreover, organisations that boast diverse leadership report a 25% higher employee satisfaction score compared to companies with less diverse leadership teams. Data story: At Innovative Enterprise, the lack of diversity in our leadership team becomes evident. Our internal data reveals that while our workforce is 49% ethnically diverse, only 15% of our leadership reflects this diversity. It's clear we're falling short, and this is a challenge that we share with many organisations across our industry. However, industry data provides a clear directive: organisations with diverse leadership teams are more innovative and creative by 35%. They also report a 25% higher employee satisfaction score, indicating a more engaged and motivated workforce. This compelling combination of our internal situation and broader industry data paints a powerful argument for enhancing diversity, equity, and inclusion at the leadership level. The data provides clear guidance — it's time for us to take action. Ready to learn more This example from Innovative Enterprise demonstrates the power of data-informed storytelling in HR. For more impactful stories and detailed analysis, download our eBook Why Data-Informed Storytelling Is the Future of HR to explore additional examples and learn how One Model can help your organisation tell compelling, data-driven stories.
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7 min read
The One Model Team
If you're preparing for people analytics, there’s a lot to do before you hire that first data scientist. To build the right foundation for success, there are five important steps you should follow that don’t even involve data, insights, or statistics. Following these steps will help you establish and support an efficient and impactful people analytics practice at your organisation. 1. Find your why Understanding why you're pursuing people analytics is vital to your journey. This not only means identifying the specific business needs that would benefit from a better understanding, deeper insights, or more precise analysis of your workforce, but also exploring the underlying reasons behind those needs. You could start by asking questions like: What are the biggest challenges or pain points we're facing as an organisation? What are the key areas where we could improve our workforce, and how would we measure success? What are the most critical business decisions we need to make, and what do I need to know to help us make them more effectively? What are the specific gaps in our knowledge that we need to fill in order to make better decisions? Without taking the time to find the why for your organisation, you risk getting lost or going off course before you even begin. By finding your why early and holding onto it through the process, this will keep you focused throughout your people analytics journey. 2. Look upstream When starting your people analytics journey, it’s important to remember that the data you’ve generated is only as good as your processes and technology. There’s a flow we like to think about from process to tech to data to analytics. When people analytics teams run into challenges, there’s likely an upstream challenge in one of these steps to address. Begin by examining your processes. Technology is only as good as the process it’s automating, so if your processes are poorly designed and documented, your technology is unlikely to be implemented correctly. Technology should reflect how you want your business to run. If it doesn’t, you’ll likely end up with incomplete or incorrect data flowing out of the technology — making it difficult or impossible for people analytics teams to create value.This is not to say “don’t start on people analytics until the rest is done”. People analytics teams can absolutely provide great value, and some of the best teams out there are scrappy with what they have on hand. This is more of an acknowledgement of the flow and a callout that if you want long-term success of your people analytics team and to unlock that next level of value, you’ll have to address these upstream challenges. A strong people analytics leader will also be able to help you identify and navigate these challenges upstream. So begin by ensuring that your processes are well-designed and documented. Next, double check on your technology implementation and ensure that it matches your processes. Finally, check in on the data. The data ultimately doesn’t lie, so it will tell you if the processes and tech are clean. Doing so will ensure that data flows smoothly and accurately from the technology preparing you for analytics. 3. Address data management Another early focus for starting down the path of people analytics is data management. Without data, there’s not much for people analytics teams to do. It’s the oil to the people analytics engine. We’ve seen a number of teams get started, but then plateau around a lack of good data. At times the resources to fix data problems sit outside of HR, which makes it all the more important to navigate and commit that resource request up front when pursuing people analytics. Making sure your data is accessible is critical, but raw data extraction is also only the beginning. A robust workforce-specific data model, proper data architecture blending your different systems data, and HR-led workforce data privacy and workforce data governance are also part of your people analytics foundation. This may require marshalling what are typically scarce internal resources, capabilities, and priorities from IT or data engineering teams to ensure that your data is clean, systematically organised, and readily analysable. Or you can save those internal resources by working with people analytics platforms like One Model. We were founded to make this upstream challenge easier. We provide named data engineering resources, have experience developing business-specific workforce data models, and provide the data foundation that people analytics teams need to thrive. If you skip this step, you may experience the following problems: Missing data: Without the right data management structure in place, you may find it difficult to extract the data you need for a given project. This can lead to incomplete or incorrect data and difficult analysis. Slow data: Improper data management can leave you with only monthly (or quarterly!) snapshots and that pace just doesn’t reflect how fast your business moves — let alone back-dated changes, which are frequently found in HR. Inability to build predictive models: Data management is critical to building predictive models. To develop predictive models, you need to extract data in a very specific way (e.g. time-stamped changes). It’ll be difficult or even impossible to build accurate and effective models without this proper data management. By addressing data management early on in your people analytics journey, you can avoid these symptoms and ensure that your people analytics initiatives are successful. To learn more, here are five tips for getting HR data extraction right. 4. Set the tone Setting the tone at the top is crucial for demonstrating that data-driven decision making is the way forward. This involves garnering support from your organisation's senior leaders, as well as regular reminders, activities, and actions from the CHRO or HR head. If you’re in a leadership position, setting the standard that data is required for new projects and investment decisions goes a long way. Cultivating a data-minded culture will trickle down from the top, setting a precedent for the entire organisation. Without this high-level endorsement and sustained backing, making significant strides in people analytics can prove challenging. 5. Find help Consider engaging with a seasoned people analytics leader either full-time or as a consultant to spearhead your people analytics initiatives and education within your function. Experienced people analytics leaders, with their unique combination of data analysis skills, HR orientation, ethical understanding, and team management expertise, can provide invaluable guidance. They’ll work to ensure alignment between your analytics efforts and broader business objectives. Remember to also tap into the people analytics community. This strong and enthusiastic network can provide invaluable support. Engage with professionals on LinkedIn, ask questions, and use the expertise of vendors in the space. The team here at One Model is always willing to connect and assist at every stage of your people analytics journey. New to people analytics or ready to enhance your existing program? Either way, our eBook People Analytics 101 covers everything you need to know about establishing a strong people analytics foundation for smarter HR strategies and meaningful change across your organisation.
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The One Model Team
What should your first people analytics project be? Many teams start with employee attrition because it has clear outcomes, it has a direct impact on the company, and attrition data is already in your HRIS. So to understand the five steps you need to follow during people analytics projects, let’s walk through an example of how Penelope, a fictional people analytics practitioner, might approach an employee attrition project, from start to finish. Step 1: Define the problem The first step in any people analytics project is to define the problem you want to solve. In this case, the problem is employee attrition. Specifically, we want to understand why employees are leaving the company and what we can do to reduce attrition. "As an HRBP, I noticed a trend of high employee turnover in the company. I began to investigate why employees were leaving and how we could reduce this trend. My goal was to identify the underlying causes of this issue and develop a plan to address it," says Penelope. Step 2: Gather the data The next step is to gather the data you need to analyse the problem. In this case, you'll need data on the employees who have left and their reasons for leaving (if available). This data can often be found in your HRIS, as well as employee surveys or exit interviews. "To gather the necessary information, I dove into the company's HRIS system, as well as employee surveys and exit interviews. I collected data on employee demographics, job history, performance metrics, and reasons for leaving. I made sure to gather as much relevant information as possible to ensure a comprehensive analysis," shares Penelope. Step 3: Analyse the data Once you have the data, it's time to analyse it. There are a variety of statistical methods you can use to analyse attrition data, including survival analysis, logistic regression, and decision trees. But you can also start with descriptive methods. Your choice of method will depend on the nature of your data and the questions you want to answer, and you don’t always need advanced methods. "I took a look at attrition trends across each of the major groups within the company. Using descriptive statistics, I found that some teams were experiencing higher attrition than others within similar business units. I wanted to identify why the attrition rate was high, so I looked for factors that were strongly correlated with attrition," notes Penelope. Step 4: Tell the story After analysing the data, it's time to tell the data story. This is where data visualisation and data storytelling come in. You'll want to create charts, graphs, and other visualisations that help you communicate your findings to stakeholders. You'll also want to craft a narrative that ties the data together and explains what it means for the company. "Using the results from the data analysis, I created charts, graphs, and other visualisations that I could use to communicate my findings to stakeholders. I crafted a narrative that brought my business knowledge into the story and explained the factors contributing to the high attrition rate and the steps we could take to address it. I presented the data and narrative to the company's leadership team," explains Penelope. Step 5: Implement solutions Finally, it's time to implement solutions based on your findings. This might involve changes to HR policies, changes to compensation structures, or changes to management practices. Whatever the solution, it should be informed by the data you've gathered and analysed. "Based on the data and narrative, I recommended changes to HR policies, compensation structures, and management practices. I presented the recommendations to the company's leadership team and worked with them to implement the changes. Over time, we saw a decrease in the attrition rate and an increase in employee satisfaction," says Penelope. Overall, attrition is a great starting point for any people analytics team. It's a universal problem that every company faces, and the data is often readily available. By analysing attrition data, you can gain valuable insights into your workforce and make data-driven decisions that improve retention and reduce turnover. New to people analytics or ready to enhance your existing program? Either way, our eBook People Analytics 101 covers everything you need to know about establishing a strong people analytics foundation for smarter HR strategies and meaningful change across your organisation.
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A well-crafted data-informed story can effectively influence decision-making, foster understanding, and drive meaningful change within the organization. A data-informed story blends the art of storytelling with data-driven insights, creating a compelling narrative that resonates with the audience and inspires action. Here's a framework for how to develop data-informed HR stories: Business Objective: Setting the Stage Every compelling data-informed story begins with a clear business objective. It's essential to know what you want to convey and the actions you want to inspire from your audience. Defining your objective gives direction to your story, shaping its structure and maintaining its focus. A well-articulated objective ensures your story remains purposeful and impactful, driving the narrative towards your desired outcome. “Using people data to get to a scientific insight is only half the battle. If you can't step back and crisply describe your findings in terms of business impact, you quickly lose the room, lower credibility, and break trust with business leaders.” — Ian O’Keefe, Head of Talent Analytics and Data Science, Amazon Evidence: The Backbone of Your Story Your story's credibility stems from its findings: both data evidence and the story context. Data Evidence: Collect and analyse data pertinent to your objective. This data acts as the backbone of your story, supporting your narrative and revealing valuable trends, patterns, and insights. It's the facts and figures that make your story believable and persuasive, reinforcing your arguments and enhancing your story's validity. Story Context: Context adds depth to your data, making it meaningful and relevant. Explain why your data matters, its relation to broader organisational objectives, and its direct impact on your audience. This context helps your audience comprehend the data's significance, allowing them to connect the dots between raw data and its implications. Visualization: Bringing Your Data to Life Visualising your data helps to clarify and accentuate your key messages. Rather than presenting raw data or lists, craft clear and engaging visual representations of your data. This could involve charts, infographics, or diagrams, which enable your audience to quickly grasp the information and easily identify the patterns or trends you're emphasising. Narrative: The Art of Engaging Your Audience Narrative is the act of weaving together data and insights into a compelling story that resonates with the audience and inspires action. By using an engaging narrative, relatable examples and analogies, and emotional appeal, HR professionals can effectively communicate the human impact of organisational decisions and drive meaningful change. “To infuse more storytelling into People Analytics, understand the business and people context, use narrative techniques and visualisations to present data engagingly, and go beyond data by exploring the human factors driving it. Enhancing storytelling in this field can significantly boost its impact on business outcomes.” — Tony Truong, Vice President of People Strategy and Operations, Roku Engaging Narrative: To captivate your audience, weave your data and insights into a compelling narrative. Ensure your story flows logically, featuring a beginning, middle, and end, each part reinforcing the key message you wish to convey. Relatable Examples and Analogies: Examples and analogies act as bridges between complex data and familiar concepts. By relating your data to real-life scenarios or recognisable concepts, you make it more accessible and understandable for your audience, making your story more relatable and engaging. Emotional Appeal: The magic of storytelling lies in its ability to evoke emotions. Incorporate elements that resonate with your audience on an emotional level. This could involve personal anecdotes, inspiring stories, or connections between the data and the organisation's values and goals. “People Analytics insights have an easier path to landing as a compelling story if quantitative findings are combined with qualitative findings. Pulling anecdotes from HR and non-HR leaders, managers, and employees in your business lines is a validating and powerful storytelling device.” — Ian O’Keefe, Head of Talent Analytics and Data Science, Amazon Interactivity: A Living, Breathing Story Data stories are not static monologues but dynamic dialogues. Build your stories in a way that allows you to be prepared for follow-up questions and additional requests. Consider building your data stories in platforms where you can treat them as living documents, flexible and adaptive, fostering interactivity and ongoing engagement. This approach will enrich your narrative, keeping it relevant and resonant over time. Action: The Impetus for Change The goal of any data-informed story is to inspire action. Conclude your story with a clear call to action, outlining what steps you want your audience to take based on the insights presented. This crucial step ensures your story doesn’t merely inform but also drives engagement, leading to tangible change. Ready to learn more? Download our eBook Why Data-Informed Storytelling Is the Future of HR to explore additional examples and learn how One Model can help your organization tell compelling, data-driven stories.
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6 min read
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To say that HR is undergoing significant transformation is quite an understatement. But in the shadow of AI/ML, people analytics, and other massive splashes, two familiar foundations are shifting: HR team structures and what HR teams are focusing on. Here's a flyover of what's at stake. 1. Evolving HR Team Structures HR team structures are evolving to bridge traditional functions with analytics, technology, and strategic planning. It's important to know what's changing and how your business can adapt: Impact of Layoffs - Layoffs, especially in tech, force HR teams to rethink their strategies. Some companies downsize, while others use this time to attract top talent, leading to more diverse and adaptable teams. Recommended Approach: Use layoffs as an opportunity to reassess and restructure your HR team to align with new team focuses (below). Focus on bringing in diverse skills and expertise to create a more resilient and adaptable team. Optimal Team Size - There’s a growing belief that HR teams can be more effective with a smaller, well-defined team size. Bigger isn't always better; the right team size can enhance efficiency. Recommended Approach: Evaluate your organization’s specific needs to determine the optimal team size. Prioritize quality over quantity to build a lean, efficient team. Platform Approach - Modern HR platforms are reshaping team structures by automating routine tasks and streamlining workflows. This shift allows HR teams to focus more on strategic insights and less on manual processes. Recommended Approach: Invest in comprehensive HR technology platforms that offer automation and integration capabilities. This can free up your team to focus on strategic tasks and improve overall efficiency. New Emerging Roles - At the same time that some roles are becoming redundant or obsolete, new ones are forming to oversee or bridge gaps in new processes. We're seeing people analytics leaders morph into entirely new roles that span across HR functions. This cross functional people analytics position goes by many names, but we're calling it Workforce Systems Leader. Recommended Approach: Stay adaptable, proactive, and informed. Embrace emerging roles like the Workforce Systems Leader to optimize your HR processes and keep your organization at the forefront of industry trends and advancements. Joining a people analytics community can be very helpful in the midst of ongoing evolution. Stay tuned as we address the implications, functions, and ongoing shifts of roles in this industry. 2. Shifting HR Team Focuses As team structures change, so do their priorities. HR must now be focusing on three key areas: data infrastructure, productivity analytics, and skills and workforce planning. Data Infrastructure - A strong data foundation is crucial for advanced analytics and AI. Efficient data management helps HR teams create actionable insights that drive business forward. Recommended Approach: Invest in advanced data management tools and provide training for HR staff to ensure high-quality data and effective use of analytics. Productivity Analytics - The shift to remote and hybrid work has made productivity analytics essential. HR needs to measure productivity accurately and understand what influences it, especially in new work environments. Recommended Approach: Implement productivity tracking software and regularly analyze the data to refine remote work policies and improve employee performance. Skills and Workforce Planning - Integrating skills data into workforce planning is becoming vital. HR must understand the impact of specific skills on workforce dynamics and align this knowledge with company goals. Recommended Approach: Conduct a skills inventory and use advanced workforce planning tools to align skill development initiatives with the company’s strategic objectives. It's not necessarily easy, but by embracing these and other changes we've identified this year, HR departments can improve their effectiveness, foster collaboration, and drive significant business outcomes. Ready to get ahead of these shifts and redefine the impact of HR in your organization? Download this new resource today to take a deeper dive into all 6 of this year’s top emerging trends for people analytics.
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4 min read
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Have you been tasked with proving the ROI of your people analytics program? Start here. Traditional return on investment (ROI) calculations often fall short in capturing the full value of people analytics. While efficiencies and cost savings are important, they represent a narrow view of people analytics' potential and value. If you've been asked to defend your people analytics business impact, you must start with a broad approach before diving into the weeds. These 3 mindsets are just the beginning, but they're critical. 1. Understand the Limitations of Traditional ROI Metrics Traditional ROI calculations typically focus on two components: estimated savings through system efficiencies and reductions in attrition, or faster time-to-fill job postings. While these metrics are useful, they can be misleading. Establishing a direct cause-and-effect relationship is tricky. For example attributing savings from reduced attrition doesn't tell the whole story, especially in a volatile job market. Additionally, measuring people analytics effectiveness may require factoring in the cost of implementing advanced technologies. So it's important to reinforce that the value of people analytics infiltrates the entire workforce experience and efficiency, which should not be measured strictly in financial terms. 2. Embrace a Holistic Perspective, But With a Laser Focus The mission of people analytics is to foster continuous improvement in talent decisions, leading to better organizational outcomes. So people analytics should be evaluated based on its ability to drive better talent decisions across the organization. This broader perspective encompasses not only financial outcomes, but also benefits various stakeholders, including employees, customers, and the community. By focusing on the overall impact on organizational effectiveness and stakeholder satisfaction, people analytics can be seen as a critical driver of long-term success. This approach encourages investments that enhance the quality of talent decisions and support the organization's strategic goals. 3. Introduce a Simplified Value Model A more practical and effective approach to measuring people analytics value is through a 3-pronged framework: Utilization: Tracks how often people analytics content is used. Leaders regularly engaging with people analytics deliverables, such as dashboards and reports, indicates that members of your team want and are finding value in workforce data. User Level: Assigns high value to senior leaders. If a CEO frequently uses a workforce dashboard, it's likely delivering valuable insights that inform decision making. Tracking engagement levels across different user groups can highlight which tools are most effective and where improvements are needed. Deliverable Level: Evaluates the potential impact of the people analytics content by measure outcomes and decisions influenced by these deliverables. For example, a report that leads to a successful strategic initiative demonstrates high value. By focusing on key users and high-impact deliverables, this model ensures people analytics teams align and prioritize their efforts to meet organization needs. We're Here to Help Of course, these are just the beginning steps in the complex task of assessing the effectiveness of your people analytics program. If you're ready to dive into the specific metrics and tools that will help you make a solid case for people analytics based on data, we're here to help. Download our comprehensive guide, Measuring the Value of People Analytics. You'll discover the various lenses you need to look through when calculating people analytics ROI in general, as well as specific formulas for key metrics. Plus, you'll see how we calculate the value of a small people analytics portfolio based on the value-utilization framework. Get the Equations and Key Metrics You Need:
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