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12 min read
The One Model Team
In 2015, The New York Times reported that among S&P 1500 companies, there were more CEOs named John than there were women. That stat struck a nerve—and since then, similar analyses have shown that Davids have also outnumbered women in top leadership roles across the Fortune 500. The comparison was cheeky. But it wasn’t just a quirky stat—it was shorthand for a deeper truth: diversity in leadership was nowhere near where it should be. Fast forward to today, and while the numbers have improved, they still make the case: only 10.4% of Fortune 500 CEOs are women. That’s progress—but not parity. The real issue isn’t about names. It’s about systems and the secrets they contain: -Why do some candidates never make it past the first interview? -Why does representation stall at certain levels, even when promotion rates are equal? These aren’t just philosophical questions—they’re People Analytics challenges. Turning Awareness into Action Headlines grab attention, but numbers drive change. The companies making real progress on DEI aren’t just tracking how many women they’ve promoted. They’re building systems that let them see exactly where representation drops off—and why. They’re setting KPIs that go beyond compliance. They’re giving HR and DEI teams tools to act on the data. (Vogue Business) For instance, Neiman Marcus Group (NMG) has implemented a strategy called "bias interruption," which addresses systemic biases in hiring, engagement, and retention. This approach utilizes data-driven practices to fix biases in hiring, employee engagement, and retention by understanding how certain practices deter candidates and employees of color. As a result, NMG surpassed its 2025 goal of having over 21% racial and ethnic diversity in leadership roles, achieving 21.4% in 2023. The new target is 28% by 2030. (Vogue Business) This example illustrates that DEI isn’t just about ideals. It’s about data. And if you're not measuring what matters, you're just guessing. DEI Data in Action: One Model + Company X At One Model, we’ve seen firsthand how organizations can go from intention to impact by turning diversity into something measurable—and actionable. Consider a Fortune 100 financial services organization we'll call Company X. When they partnered with One Model in 2016, they weren’t just looking for reporting tools—they were looking for visibility, accountability, and a way to actually move the needle on workforce diversity. Here’s what that looked like: Rescuing and Rebuilding Data Company X was transitioning from SAP to Workday and had a goldmine of workforce survey data at risk of getting lost in the shuffle. Using One Model, they recovered and normalized that legacy data across multiple systems, enabling the team to report from a single, cohesive source. This meant they didn’t have to redeploy a massive survey—and their DEI metrics didn’t reset to zero. Spotting the Gaps Others Miss As the team reviewed self-ID data, they found that a significant number of employees had skipped over racial/ethnic identification entirely. This wasn’t just a reporting glitch—it was a missing chunk of reality. With One Model, they were able to isolate this group and launch internal processes to close the gap. Within months, they had identified 95% of those employees—restoring accuracy to their diversity picture. Building Real KPIs Around Hiring Equity They took it a step further by setting department-level DEI hiring targets. Teams that met or exceeded their goals were studied—their processes, outreach, and interview practices documented and shared org-wide to replicate success. The result? DEI stopped being “a nice idea” and became part of performance strategy. Turning Interview Stage Data into Promotion Equity One of the most revealing insights came from interview stage analytics. Although promotions were evenly split—55% of internal promotions were women—managerial roles were still male-dominated. Digging deeper, they discovered that female candidates were only making it to the final interview stage 50% of the time. That bottleneck became a turning point. Company X created a new KPI: ensure that 80% of female managerial candidates reach the final interview round. They began testing different interventions—changes to panel composition, structured scoring rubrics, recruiter training—and tracked all of it in One Model to measure what actually worked. Tracking and Monitoring Changes Company X wanted more visibility into why females had a lesser presence in managerial roles within the organization. While, male to female promotions were equal. (This past year, 32 people were promoted. 55% of promotions (16 people) were women), there were significantly more males than females in managerial roles. Upon reviewing the data, they learned that out of the company’s requisitions, females applicants only made it to certain stages within the interview process (namely, an in-person interview) 50% of the time. Half the time, the only applicants that made it to a particular stage were male. They determined a hypothesis surrounding a particular KPI - that if more females made it to this particular stage, the odds were higher that more females would fill these roles. Company X set a goal that they wanted a female candidate make it to a manager interview stage 80% of the time. They are testing different methods on how best to achieve this, and with One Model's help, they are able to measure the effectiveness of those methods. By providing this visibility, One Model’s platform is currently helping them monitor their progress towards this goal, and allows them to see the affect - the direct impact on numbers of M/F managers in real-time. Company X is one of the many companies that has embraced the importance of diversity in workforce planning. We’re proud to be a part of the solution helping them meet their goals. Metrics That Move the Needle More companies are now following this lead—using People Analytics to ask better questions and close more meaningful gaps. Some of the key DEI metrics organizations are tracking today include: Representation Metrics (By role, level, department, gender, ethnicity, veteran status, IWD) Recruitment Funnel Drop-off Points Interview Progression by Demographic Promotion and Pay Equity Analytics Training Penetration Rates by Group Culture & Climate Sentiment Scores Exit Reasons by Demographic Because if you're not tracking it, you're not fixing it. Data is Where DEI Gets Real So yes—once upon a time, there were more CEOs named David and John than there were women CEOs and probably still are. And while that point made headlines, it didn’t change the numbers. Data did. DEI needs more than good intentions. It needs visibility. Targets. Measurement. Feedback loops. And the right platform to make all of that possible. If you're building a more inclusive workforce—and you want the data to back it up—One Model can help. Want to see what better data can do for you? Take a look at One Model. About One Model One Model pioneered people data orchestration and flexible predictive models that empower large and rapidly growing companies to unlock transformative insights and data-driven workforce strategies. Built to reduce technical burdens for data scientists, engineers, and HR leaders alike, our platform is the most flexible and secure solution available today. We are committed to ethical data practices, ensuring unmatched security, privacy, and transparency, providing confidence in every decision powered by One Model.
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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 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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28 min read
Richard Rosenow
Welcome to the One Model resource page for books about People Analytics. This is meant to be a living document, so if we missed one of your favorites, please don't hesitate to reach out to Richard Rosenow with a recommendation. He's always looking to add to the library. August People Analytics Book Pick: How to Measure Human Resource Management "This book, by Jac Fitz-enz and Barbara Davison, is a cornerstone of our field. It was groundbreaking when it was first published in 1984 and remains incredibly relevant today. Fitz-enz's insights into quantifying and evaluating HR practices were years ahead of their time, laying the groundwork for the sophisticated analytics we use now." - Richard Rosenow Past Book Club Books: June People Analytics Book Pick: Creepy Analytics by Dr. Salvatore V. Falletta "This book is already on my bedside table, and I cannot wait to dive in. As we continue to explore the power of people analytics, I find it essential to keep an eye on ethical HR practices." - Richard Rosenow Meet the Author Webinar - Register to hear the recording! Join the conversation on LinkedIn. People Analytics Essentials - Reading Starter Kit When it comes to books about people analytics, we are finally at a point where we have the luxury of having too many choices. The virtual library is well stocked and all of these books come highly recommended and vetted by our experts, but if you had to start somewhere, we recommend the following 7 books to kick things off. Work Rules - Best “painting the dream” “Work Rules” by Laszlo Bock is the first book I recommend to folk looking to learn more about People Analytics. Written by Google's former SVP of People Operations, this book offers a behind-the-scenes look at Google's unique approach to attracting and retaining top talent. Through compelling anecdotes and evidence-based insights, Bock presents actionable strategies for building a dynamic, innovative, and people-centric organization. Work Rules has held the top spot on my book recommendation list for a long time as it’s the right blend of real-life case study and inspiration. It’s not too technical, but you leave feeling excited to learn more about the space. Whether you're in HR and new to this people analytics space or looking for ideas about how to infuse people analytics into your existing practices, "Work Rules!" is a great introduction in how it paints the picture of what people analytics can look like at scale within an organization. Moneyball - Best at “building excitement” "Moneyball" by Michael Lewis (the movie is great, but the book is better!) serves as an unexpected guide for people analytics leaders. While it tells the story of the Oakland Athletics baseball team's innovative use of statistics, the takeaways from the book reach far beyond baseball. The application of data analytics to assess baseball players and make strategic decisions on the field makes for an easy transition to talking about how people analytics can assist business decisions. For those new to people analytics or HR, "Moneyball" offers relatable examples of how data-driven decisions can lead to surprising and effective outcomes. Its engaging narrative can even serve as a conversation starter with business leaders outside the typical HR function, demonstrating how unconventional thinking about talent practices, paired with data analysis, can lead to success. "Moneyball" is not only a gripping story but a playbook for those seeking to introduce people analytics into their organization. Excellence in People Analytics - Best at “Overall introduction” "Excellence in People Analytics" by David Green and Jonathan Ferrar is the classic resource now within the people analytics field. Their book is specifically tailored for those in the people analytics field or those seeking to embark on this fascinating journey. The authors, both renowned experts in the field, offer a comprehensive guide to understanding, implementing, and excelling in people analytics within an organization. With a blend of theoretical frameworks and practical case studies, the book provides a holistic view of how people analytics can drive better decision-making and foster organizational success. Ideal for HR professionals, analytics leaders, and business executives, "Excellence in People Analytics" will help set the stage for people analytics and inspire you to leverage data in innovative ways to enhance people processes. Sensemaking - Best at “reminding you that humans still matter” "Sensemaking" by Christian Madsbjerg is a thought-provoking exploration of the human context in the era of data and analytics. Madsbjerg argues for a balanced approach that marries data with a deeper understanding of human behavior, culture, and emotion. I go back to read Sensemaking every couple of years to remind myself to focus on the people in people analytics. Knowing what data can do for an organization is important, but it’s just as important in a people analytics role to understand the limitations of data. For those entering the field of people analytics or looking to expand their HR perspective, "Sensemaking" provides a unique standpoint, emphasizing that not everything can be reduced to numbers. It encourages readers to blend analytical thinking with empathy, intuition, and cultural awareness. This approach can lead to more nuanced and effective decisions in people management. "Sensemaking" is a must-read for those who wish to infuse their analytical work with human insights and achieve a more sophisticated and holistic understanding of the people they serve. Cartoon Guide to Statistics - Best at “Stats without fear” The "Cartoon Guide to Statistics" is a breath of fresh air for anyone who has ever felt bewildered by statistics. Whether you're a people analytics leader or an HR professional looking to dip your toes into the world of data, this lighthearted and engaging guide speaks plain English and turns complex statistical concepts into digestible and even enjoyable lessons. As someone who came to statistics later in life, this book was a blessing and I can’t recommend it enough. Through witty cartoons and crystal-clear explanations, the book proves that relearning statistics as an adult doesn't have to be a daunting task. In fact, it can even be funny! A breakthrough resource for those who may struggle with traditional statistical texts, the "Cartoon Guide to Statistics" offers a welcoming entry point to the crucial world of data analysis. The Fundamentals of People Analytics: With Applications in R - Best at “mastering the stats” While leading people analytics teams at Experian, Mastercard, Robinhood, and Roku, Craig has somehow also found time to teach, give back to the people analytics community, and write a full statistics textbook, end to end, with people analytics at the core. The Fundamentals of People Analytics: With Applications in R is what happens when a true practitioner sees a problem, no great statistical resources with HR folk in mind, and applies himself to it fully. The result is a masterwork guide to statistics for the people analytics professional. If you are looking to learn statistics for HR or build your confidence in the applications in HR, look no further than this book. Talent Intelligence - Best at “Talent intelligence” "Talent Intelligence" by Toby Culshaw explores the field of talent intelligence, an area adjacent to, but one that is starting to appear to be distinct from, people analytics. Overviewing the world of both internal and external talent markets, Culshaw's insights provide a deep understanding of how to strategically approach talent acquisition and talent management through data-informed practices. This book is an ideal recommendation for those involved in recruiting or those in people analytics seeking to expand their perspective. Whether you're an HR leader or a professional looking to understand the broader landscape of data-informed HR, "Talent Intelligence" offers a comprehensive guide to leveraging data to make informed talent decisions. It's an eye-opener for anyone wanting to deepen their understanding of the ever-evolving landscape of talent in today's business world. The field of People Analytics In this section are books that cover the full field of People Analytics. These are excellent overviews that share a range of topics from what this field is, to how to go about it, to case studies in the space. A great place to start for folk looking to learn more about how analytics is used to better understand the workforce. Excellence in People Analytics - Jonathan Ferrar and David Green The Power of People - Nigel Geunole, Jonathan Ferrar, and Sheri Feinzig People Analytics for Dummies - Mike West Introduction to People Analytics - Nadheem Khan and David Milnor People Analytics: How Social Sensing Technology Will Transform Business and What It Tells Us About the Future of Work - Ben Waber Work Rules - Laszlo Bock HR analytics: The What, Why, and How - Tracey Smith Predictive Analytics for Human Resources - Jac Fitz-enz and John Mattox II Strategic Analytics: Advancing Strategy Execution and Organizational Effectiveness - Alec Levenson Data-Driven HR: How to Use Analytics and Metrics to Drive Performance - Bernard Marr Human Capital Analytics - Gene Pease, Bryce Byerly, and Jac Fitz-enz The Practical Guide to HR Analytics: Using Data to Inform, Transform, and Empower HR Decisions - Shonna Waters The Basic Principles of People Analytics: Learn how to use HR data to drive better outcomes for your business and employees - Erik van Vulpen The New HR Analytics: Predicting the Economic Value of Your Company's Human Capital Investments - Jac Fitz Enz Specialized People Analytics Similar to the first section, this section is for books that cover a broad overview of the space, but for a more narrow vertical within the space. These are books that still touch people analytics, but specialize is sub-topics such as DEI, L&D, Workforce Planning and Talent Intelligence. Great for learners who want to go deep on a given topic or transition into people analytics from their prior field. Talent Intelligence - Toby Culshaw Inclusalytics: How Diversity, Equity, and Inclusion Leaders Use Data to Drive Their Work - Victoria Mattingly, PhD, Sertrice Grice, and Allison Goldstein Agile Workforce Planning: How to Align People with Organizational Strategy for Improved Performance - Adam Gibson Strategic Workforce Planning: Developing Optimized Talent Strategies for Future Growth - Ross Sparkman Next Generation Performance Management: The Triumph of Science Over Myth and Superstition - Alan Colquitt Learning Analytics: Measurement Innovations to Support Employee Development - John Mattox II, Mark Van Buren, and Jean Martin Adaptive Space: How GM and Other Companies are Positively Disrupting Themselves and Transforming into Agile Organizations - Michael Arena Positioned: Strategic Workforce Planning That Gets the Right Person in the Right Job - Dan Ward and Rob Tripp People Analytics focused Analytics, Data Science, and Statistics With the maturity of the people analytics space, we've seen a rise in textbooks covering the fundamentals of HR analytics from an anaytics technical perspective or statistical overview of the space. If you are looking to brush up on your technical knowledge or just starting down your journey with statistics and looking for an HR analytics textbook, you're in the right place. The Fundamentals of People Analytics: With Applications in R - Craig Starbuck Handbook of Regression Modeling in People Analytics: With R - Keith McNulty Handbook of Graphs and Networks in People Analytics: With R - Keith McNulty Introducing HR Analytics with Machine Learning: Empowering Practitioners, Psychologists, and Organizations - Austin Hagerty and Christopher Rossett Doing HR Analytics - A Practitioner's Handbook With R Examples - Lyndon Sundmark Storytelling with Data - Cole Nussbaumer Predictive HR Analytics: Mastering the HR Metric - Dr. Martin Edwards and Kristen Edwards General Analytics, Data Science, and Statistics The benefit of people analytics being a younger discipline in the analytics field is that we have many other disciplines that have gone down this path ahead of us. We can learn from analytics and statistics books across many disciplines and bring that knowledge back to people analytics. Here is a sample of books that come up frequently when speaking to people analytics leaders about their favorites from outside the field. Competing on Analytics: The New Science of Winning; With a New Introduction - Thomas Davenport and Jeanne Harris Weapons of Math Destruction - Cathy O’Neil The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World - Pedro Domingos Naked Statistics: Stripping the Dread from the Data - Charles Wheelan The Signal and the Noise: Why So Many Predictions Fail--but Some Don't - Nate Silver Cartoon Guide to Statistics - Larry Gonick Statistics in Plain English - Timothy Urdan Understanding Humans At the end of the day, we are people analytics, not just analytics, and with that comes a real need to understand our subject area - people! These are some of the goto books in the space and some of my favorites when it comes to engaging with the social sciences. They are hand picked for being engaging, thoughtful and educational reads. Moneyball - Michael Lewis Sensemaking: The Power of the Humanities in the Age of the Algorithm - Christian Madsbjerg Humanizing Human Capital: Invest in Your People for Optimal Business Returns - Stela Lupashor and Solange Charas Irresistible: The Seven Secrets of the World's Most Enduring, Employee-Focused Organizations - Josh Bersin The Model Thinker: What You Need to Know to Make Data Work for You - Scott Page The Undoing Project: A Friendship That Changed Our Minds - Michael Lewis Thinking, Fast and Slow - Daniel Kahneman Superforecasting - Phillip Tetlock, Dan Gardner Evidence-Based Management: How to Use Evidence to Make Better Organizational Decisions - Eric Barends and Denise Rousseau Humans at Work - The Art and Practice of Creating the Hybrid Workplace - Anna Tavis and Stela Lupashor Misbehaving - Richard Thaler It’s Not Complicated - Rick Nason Want to learn more from an expert about the space? Let's schedule time to chat. Measuring HR We won't get far with people analytics if we don't have well defined inputs, outcomes, or measures within HR. Understanding how HR is measured is critical to a people analytics team success. There is a full second library worth of HR measurement books out there and this section just scratches the surface. The HR Scorecard: Linking People, Strategy, and Performance - Dave Ulrich, Mark Huselid, Brian Becker Human Resource Management: People, Data, and Analytics - Talya Bauer, Berrin Erdogan, David Coughlin, and Donald Truxillo Investing in People: Financial Impact of Human Resource Initiatives - Wayne Cascio and John Boudreau Victory Through Organization: Why the War for Talent is Failing Your Company and What You Can Do About it - Dave Ulrich, David Kryscynski, Wayne Brockbank, and Mike Ulrich Investing in People: Financial Impact of Human Resource Initiatives - John Boudreau, Wayne Cascio, and Alexis Fink The ROI of Human Capital - Jac Fitz Enz Positioned - Dan Ward, Rob Tripp HR Technology Last but not least, the HR technology space has its own set of fantastic resources. We won't get very far in people analytics without technology to produce data, so understanding this space is critical. Here are some standout HR technology books from the past few years. Introduction to HR Technologies: Understand How to Use Technology to Improve Performance and Processes - Stacey Harris Artificial Intelligence for HR: Use AI to Support and Develop a Successful Workforce - Ben Eubanks I, Human - Tomas Chamorro-Premuzic Talent Tectonics: Navigating Global Workforce Shifts, Building Resilient Organizations and Reimagining the Employee Experience - Steve Hunt Finished this list? Check out One Model's whitepapers and ebooks. Also, did we miss your favorite? Recommendations are welcome! Send Richard Rosenow your recommendations and we'll add to the list. Learn how to up your game with One Model's people analytics software.
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18 min read
Lauren Canada
Human resources (HR) departments play a crucial role in shaping a company's success by managing its most valuable asset — its workforce. But traditional HR practices often rely on gut feelings, intuitions, and subjective observations, which can result in bias and poor decision-making. People Analytics, also known as HR analytics, offers a data-driven approach to understanding and optimising the workforce's performance, productivity, and engagement. What Is People Analytics? People Analytics is essentially the process of collecting, analysing, and interpreting workforce data to gain insights into HR practices' effectiveness and improve decision-making. What does People Analytics involve? It involves using various data sources, such as employee surveys, performance metrics, turnover rates, and other HR-related data, to measure and analyse different HR aspects. HR professionals can leverage this data to identify patterns, trends, and relationships that are otherwise invisible, enabling them to make informed decisions that positively impact the workforce and the organisation's bottom line. While the terms "analytics," "reports," and "business intelligence" are sometimes used interchangeably, they are not synonymous. Analytics involves the systematic analysis of data to uncover meaningful patterns and insights, whereas reports refer to structured presentations of data in a summarised format. On the other hand, business intelligence encompasses a broader scope, including the collection, analysis, and interpretation of data to support strategic decision-making. So, what is People Analytics? The People Analytics definition goes beyond general analytics, reports, and business intelligence by focusing specifically on the analysis of HR-related data and the extraction of insights pertaining to the workforce. Unlike generic analytics, People Analytics centers around human-centric data, such as employee demographics, performance metrics, and engagement surveys. It delves deep into the behavioral aspects of work, uncovering correlations and patterns that provide valuable insights into talent management, employee engagement, and workforce planning. With People Analytics, you can gain a more holistic understanding of your workforce and make data-driven decisions tailored to HR needs. What Does People Analytics Involve? Data Collection What does people analytics involve? People Analytics involves the seamless collection of relevant HR-related data from a multitude of sources, including HR systems, employee surveys, performance evaluations, and other pertinent data repositories. Other data sources include employee benefits, employee turnover rates, and workforce demographics. The goal is to collect as much data as possible from various sources for a more comprehensive and accurate view of the workforce. Data Cleansing The data collected from various sources often contain errors, inconsistencies, and missing data that can lead to flawed insights and ill-informed decisions if not addressed. Once the data is collected, People Analytics software will clean, validate, and transform it into a format suitable for analysis. This process can also include consolidating data from multiple sources, standardizing data formats, and filling in missing data. Data Analysis In this step, data is analyzed using statistical methods, machine learning algorithms, and data visualization tools. This enables HR professionals to identify patterns, trends, and relationships that are critical to understanding the organization's workforce and answer important HR-related questions, such as: What factors contribute to employee turnover? What skills and attributes are required for high-performing teams? What training and development programs are most effective in improving employee performance and productivity? Through this analysis, HR professionals can identify potential issues and opportunities, allowing them to take proactive measures to address them. They can also explore different scenarios and test hypotheses to make more informed decisions about the workforce. Data Visualization Data visualization tools are crucial in this process, allowing HR professionals to communicate insights to stakeholders effectively. These tools can take many forms, from simple charts and graphs to complex dashboards that display a wide range of data. HR professionals can use visualization tools to identify patterns and trends in the data, spot anomalies, and explore correlations between different variables. They can also use them to compare data across various departments, locations, or time periods, tell compelling stories, and generate persuasive reports. Effective data visualization can be an essential factor in the success of People Analytics initiatives because it makes data digestible — enabling stakeholders to grasp complex concepts and insights quickly and easily. Get the Ultimate Download Whether you're new to People Analytics or ready to enhance your existing program, this eBook covers everything you need to know about establishing a strong foundation for a successful People Analytics function that leads to smarter HR strategy and meaningful change across your organization. Four Key People Analytics Trends 1. Revolutionizing the Role and Function of HR People Analytics is reshaping the HR function from being primarily administrative and operational to becoming a strategic partner in driving business outcomes. By leveraging advanced analytics tools and techniques, HR teams can extract valuable insights from data, enabling them to make data-driven decisions that align with organizational goals. This transformation empowers HR professionals to shift their focus from transactional tasks to strategic initiatives, such as talent acquisition, retention, and development. 2. Transforming HR Business Interactions People Analytics provides HR teams with the ability to deliver data-backed insights to business leaders, fostering more meaningful and impactful conversations. HR professionals can then effectively communicate the impact of HR initiatives on key business metrics, such as revenue, productivity, and profitability. This transformation strengthens the partnership between HR and other business functions, positioning HR as a valuable contributor to overall business strategy and success. 3. Elevating the HR-Employee Connection People Analytics is also driving a transformation in the HR-employee relationship. By analyzing employee data, organizations can gain deeper insights into employee sentiments, preferences, and needs. This data-driven approach enables HR teams to personalize employee experiences, tailor development programs, and create a more inclusive and engaging work environment. The result is a stronger bond between HR and employees, as HR professionals can better understand and meet the individual needs of employees, leading to higher levels of engagement and satisfaction. 4. Enhancing the Quality of People Analytics With the advancements in AI and machine learning, HR teams can unlock more sophisticated and accurate insights from complex data sets. Predictive analytics models can forecast future workforce trends, identify potential attrition risks, and even recommend personalized learning and development opportunities for employees. These enhanced insights enable HR professionals to be more proactive and strategic in their decision-making, optimising talent management strategies and improving overall organisational performance. Embracing these four trends empowers HR teams to become strategic partners in driving organisational success, creating a more data-driven, agile, and employee-centric HR function. Choosing the Right People Analytics Tool: 3 Key Metrics When selecting the right People Analytics tool for your organization, it's essential to consider three key metrics to make an informed decision. These metrics will enable you to evaluate the effectiveness, usability, and compatibility of the tools with your HR objectives. 1. Data Integration Capabilities Ensure the tool can seamlessly integrate with your existing HR systems, such as your HRIS, performance management software, and learning management system. The ability to aggregate data from various sources is vital to obtain a comprehensive view of your workforce and maximize the insights derived from the analytics tool. Look for a tool that offers flexible and efficient data integration capabilities to support your data-driven decision-making processes. 2. Analytical Capabilities Evaluate the tool’s capabilities in data analysis, statistical modeling, and predictive analytics. Consider the range of analytics techniques and algorithms it offers, as well as its ability to generate actionable insights. Robust analytics capabilities enable you to uncover patterns, trends, and correlations within your HR data, facilitating strategic workforce planning, talent management, and employee engagement initiatives. Look for a tool that aligns with your specific analytical requirements and provides advanced analytics features to address your organization's unique challenges. 3. User-Friendliness and Accessibility Consider the user interface, ease of use, and the availability of user-friendly dashboards and visualization features. The tool should empower you to navigate and extract meaningful insights from the data effortlessly. Accessibility is equally important. Ensure the tool is accessible across devices and provides secure data access to authorized users. Look for a tool that prioritizes user experience and provides intuitive interfaces to maximize adoption and utilization across your HR teams. One Comprehensive Solution for Data Integration One Model offers a comprehensive People Analytics platform that integrates data from multiple sources, making it easier for HR professionals to gain insights into their workforce. The highly customizable platform allows organizations to tailor their HR data needs to their specific requirements. One Model's platform can also save organizations significant amounts of money. For example, a leading provider of HR outsourcing solutions used One Model's platform to expand its People Analytics capabilities, resulting in an 800% savings over the cost of an internal build. Why Is People Analytics Important? Why should you invest in People Analytics? Why is People Analytics important? At the core, HR analytics means driving better, faster talent decisions at all levels of the organization. You need to invest resources in HR data to drive and accelerate this mission.The value of People Analytics should be judged by the quality of talent decisions that are being made across the organization and the ROI of those decisions on the business. With the right People Analytics tool, users can quantify and measure the ROI of People Analytics on an organization, including cost savings, employee retention, new hires, and more. Below are several core benefits of People Analytics: Improved HR Practices: People Analytics tools enable HR professionals to make informed decisions based on data rather than subjective observations or intuition. HR analytics means more effective HR practices that are aligned with the organization's goals and objectives. Better Workforce Management: By analyzing workforce data, HR professionals can identify skills gaps, training needs, and performance issues, allowing them to take corrective actions to improve workforce management. Increased Employee Engagement: HR analytics can help identify factors contributing to employee engagement, such as job satisfaction, work-life balance, and career growth opportunities. By addressing these factors, organizations can improve employee engagement and reduce turnover. Higher Return on Investment: By optimizing HR practices and improving workforce management, HR analytics can help organizations achieve a higher return on investment (ROI) and improve their bottom line. The Role of AI in HR According to Bersin’s research, a mere 2% of HR organizations actively utilize People Analytics. This presents a significant advantage for innovative businesses looking to tap into this field and leverage its potential. People Analytics profoundly impacts how HR functions by transforming recruitment, performance measurement, compensation planning, growth mapping, learning, and retention management. In fact, studies by Deloitte indicate that People Analytics is rapidly becoming the new currency of HR, providing benefits such as increasing job offer acceptance rates, reducing HR help tickets, and optimizing compensation. As the new currency, People Analytics brings a wealth of benefits to HR professionals, enabling them to enhance key aspects of their work. HR analytics is evolving from a one-time initiative to becoming a real-time, easily adaptable tactic that offers immense benefits for HR as processes scale with business needs. HR analytics means HR teams can make data-driven decisions that result in more successful recruitment outcomes, streamlined HR processes, and better alignment of compensation practices with employee performance and market trends. This shift towards people analytics as the new currency signifies its increasing importance and its pivotal role in shaping the future of HR practices. At the core of People Analytics is artificial intelligence (AI). AI allows HR professionals to analyze vast amounts of data quickly and accurately. AI-powered HR analytics can even inform candidate screening, performance evaluation, and workforce planning, freeing HR professionals' time to focus on higher-value activities. AI can also provide predictive insights, allowing them to anticipate workforce trends and take proactive measures to address them. How People Analytics Has Evolved People Analytics has evolved significantly over the past few years, thanks to advances in technology and data science. Although managing humans may be the most complex aspect of work, other humans have been the primary means of interpreting and managing them thus far. But this is gradually changing, with computers beginning to provide more nuanced and targeted support for managing humans. People Analytics is now becoming an expected way to enhance HR teams' decision-making, with more and more teams relying on this function daily. Initially, HR analytics primarily focused on HR reporting and compliance, such as tracking headcount, turnover, and diversity metrics. But as technology and data science advanced, it’s now more sophisticated, enabling HR professionals to gain deeper insights into the workforce's performance, productivity, and engagement. As a result, organizations that embrace HR analytics are gaining a competitive edge by making data-driven decisions that positively impact their bottom line. As more HR leaders become aware of the advantages of People Analytics and these teams learn to integrate it into their function, they will recognize its benefits and embrace it as an essential part of their work. The Stages of People Analytics Maturity To truly understand the question, “What is People Analytics?” you also need to know that People Analytics is a journey, and organizations can be at different stages of maturity. The spectrum of People Analytics maturity consists of four stages: Descriptive Analytics: Organizations at this stage use basic HR metrics to describe what has happened in the past, such as headcount, turnover, and time to fill vacancies. Diagnostic Analytics: At this stage, organizations use data to diagnose the reasons behind HR-related issues, such as high turnover or low productivity. Diagnostic analytics involves identifying patterns and relationships in data to understand the root causes of problems. Predictive Analytics: Organizations at this stage use data and AI to predict future HR trends and outcomes, such as workforce demand and supply, turnover, and performance. Predictive analytics enables organizations to take proactive measures to address potential issues before they occur. Prescriptive Analytics: Organizations at this stage use data and AI to prescribe specific actions to improve HR outcomes. Prescriptive analytics involves recommending specific HR interventions to achieve specific goals and objectives, such as training and development programs or employee engagement initiatives. Leveraging the Latest People Analytics Solutions The latest People Analytics solutions enable organizations to delve deeper into the behavioral aspects of work, better understand the cause-effect relationship between various human and non-human aspects at work, and make data-driven decisions. There are three key points to make the most of a People Analytics solution: Identify and quantify the relevant data to be analyzed. Stay updated on the latest industry trends. Create clear end goals when implementing these solutions. Additionally, HR professionals must continually update and upskill their knowledge and capabilities to ensure that the organisation can optimise the latest people analytics offers and effectively leverage the latest trends for a more productive and satisfied workforce. Why One Model Beats The Competition One Model stands out as the best-in-class People Analytics solution on the market. With its comprehensive platform, organizations gain access to a robust suite of tools and features designed to streamline data collection, analysis, and visualization. The customizable nature of One Model empowers HR teams to tailor their analytics needs to fit their unique requirements, enabling them to extract actionable insights that drive strategic decision-making. Unlock the full potential of your HR analytics capabilities with One Model. Book a demo today to discover how One Model can revolutionize your People Analytics journey, helping you uncover valuable workforce insights and propel your organization towards greater success. Request Your Time to Meet with Us.
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6 min read
John Carter
When examining the workforce dynamics of an organization, it's common to fixate on revenue-generating roles. After all, these positions are directly responsible for bringing in profits. However, focusing solely on revenue-centric roles leaves out a significant chunk of the workforce: the non-revenue employees. The Role of Non-Revenue Employees While non-revenue employees might not directly contribute to the financial bottom line, their contributions are foundational to the organization's success. They constitute the vast business “machinery” that powers the organization, supports revenue-generating roles, and ensures smooth business operations. In fact, they can represent more of your workforce. These include roles in HR, IT, administration, and many other indirect revenue employees who maintain the infrastructure of a business. Non-revenue units keep the operations of a business running. Imagine a product-based company without a logistics team to ensure timely deliveries or a multinational enterprise without HR personnel to manage its vast workforce. The value of non-revenue-producing departments becomes clear when you consider the chaos that would ensue in their absence. Non-revenue employees often introduce efficiency, stability, and scalability into an organization. They identify bottlenecks, streamline processes, and ensure that the revenue-generating departments can operate at peak productivity. Indirect revenue employees may not directly contribute to sales, but they directly influence revenue by performing at a high level of customer satisfaction, meeting or exceeding CSAT goals, reducing churn and creating referenceable champion customers. It took me 10 minutes and 15 seconds to create this breakout. Want to see me do it live? Fill out the form, and let’s connect our teams. The Value of Non-Revenue Units in People Analytics While non-revenue-generating (NRG) roles may not directly influence the new sales revenue stream, they are foundational to an organization's long-term success. Here's why: Holistic Workforce Analysis: An organization only gets a skewed view of its workforce by concentrating on revenue-producing roles. People analytics should consider every layer and department to ensure a balanced strategy for talent acquisition, retention, and development. Reducing Churn in Non-Revenue Departments: Turnover in non-revenue producing departments can be just as detrimental as in sales or business development. For instance, frequent changes in the support and client services roles leads to a loss of inherent knowledge, long ramp up times and loss of confidence with customers reflecting in low CSAT scores, while turnover in HR can impact talent management strategies. Organizations can reduce churn, stabilize operations, and indirectly boost revenue by applying people analytics to these non-revenue units. Identifying Opportunities for Upgrading Skills: As businesses evolve, the roles of non-revenue employees change. People analytics can help identify the need for new skills or training in these non-revenue units, find employees with the skills already and utilize those people, ensuring they continue to support the company effectively and saving money in the long term (training and recruitment costs). The dilemma often faced revolves around headcount — is it worth investing in these indirect revenue employees? The perceived short-term pain of increasing payroll for NRG employees often becomes a deterrent. As leaders, it's tempting to don many hats, especially with constrained budgets. But in doing so, are leaders truly optimizing their own roles? An organization's head, tasked with vision, direction, and often direct revenue-generation through donations, can get tangled in the intricacies of non-revenue units, thereby diluting their effectiveness. The Opportunity Cost with Non-Revenue Departments Convincing a board to hire for NRG roles, especially in medium or smaller organizations, is not straightforward. How you frame the argument is key. One approach is the opportunity cost perspective. By calculating an executive director's (ED) hourly pay and then juxtaposing that against time spent on non-revenue-producing department tasks, organizations can discern the real costs. For instance, if an ED earning $70,000 annually spends 10 hours weekly on tasks better suited for an NRG role, that's an annual cost of $17,498. If reallocating those 10 hours could generate more than this amount, it’s a stronger case for hiring specialized staff. While it's not always as black and white, this method provides tangible metrics, bridging the gap between HR and finance in understanding the worth of non-revenue employees. Ultimately, the emphasis should be on the organization's health and growth. While NRG roles might not bring in direct revenue, their contribution allows revenue-generating sectors to flourish. The Future of Non-Revenue Employees in Business Strategy The line between revenue-generating roles and non-revenue employees is blurring. As businesses increasingly adopt interdisciplinary strategies, the contributions of non-revenue units become more intertwined with revenue outcomes. For example, an effective marketing campaign (often considered a cost center) can significantly boost sales, making it an indirect revenue employee function. The bottom line? While the spotlight often shines brightest on revenue-generating roles, the silent machinery of non-revenue employees is what keeps a business thriving. It's time we acknowledge the importance of non-revenue producing departments and give them the attention they deserve in our people analytics endeavors. Want to see if your people analytics team can answer the top questions asked of HR as fast as us? Download the people analytics challenge!
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7 min read
Dennis Behrman
Few tasks can be as perplexing — and oddly satisfying — as the alchemy of turning headcount numbers into meaningful cost allocations by work days in a month and then having the option to break it down by department or any other variable you desire. With business demands rapidly evolving, the age-old adage of "time is money" has never been more accurate. Yet navigating the complexities of cost allocation, also referred to as overhead allocation, and crafting the perfect cost allocation plan can be a Herculean task. As you may know, cost allocation involves the identification and allocation of expenses to various activities, individuals, projects, or any relevant cost-related entities. Its primary objective is to equitably distribute costs among different departments, facilitate profitability calculations, and establish transfer pricing. Essentially, cost allocation serves as a means to gauge financial performance and enhance the decision-making process. Since your employees are by in large your greatest investment, understanding their cost allocation on many levels has immense benefits. As Phil shows in the video above, One Model makes this process seamless — and it’s all thanks to the power of our data orchestration model. Learn more about our People Data Cloud Platform. The Changing Landscape of HR Data It is no longer enough to get a holistic cost allocation from your headcount. Organizations across the globe need to be able to slice and dice their data to really understand how those costs are changing over time and how to best build a thriving workforce. Traditional views showing headcount over time are excellent starters, but the main course? That's translating those numbers into actionable cost insights. After all, understanding not just the size but also the cost of your workforce over time is the key to informed decision-making for both finance and operations teams. For example, slicing and dicing dynamic cost allocation over time, like total days in month breakout and broken down by department, supervisor hierarchy level, or by length of time employed can lead to insights that can change policy or articulate critical headcount needs. How does One Model accomplish this? One Model possesses unique capabilities that can transform your traditional headcount chart into a sophisticated cost analysis tool. What makes us unique? It all has to do with the data model. Once your data is modelled, you gain access to a variety of metrics that you can use as is or modify to fit your specific business needs. Diving into your compensation grouping of metrics, you can replace the “headcount, end of period” metric with “headcount, beginning of period” or append it with the “average salary, end of period” metric. Delving deeper, the real magic happens as One Model enables you to convert that average salary into a robust cost allocation strategy. With the dynamic "compensation cost daily allocation" metric at your disposal, it's like having a personal assistant that adjusts effortlessly to varying time durations, including accommodating leap years. Furthermore, One Model recognises the fluctuations in costs, especially during shorter months or leap years, ensuring a more precise and insightful view of your financial landscape. This capability allows you to make more informed decisions and gain a deeper understanding of your organisation's financial dynamics. Segmenting Cost Allocation Metrics Each organisation is akin to a mosaic, with numerous sections and subdivisions. With One Model, you can delve into each segment, examining the cost allocation intricacies at every level. The insights gleaned can empower both finance and operations professionals, offering clarity in strategy and resource allocation. Why is Overhead Allocation such an important metric? Cost allocation is crucial for various reasons in business and financial management. Here are four key reasons why it's important to pay attention to cost allocation: Fairness and Equity Overhead allocation ensures that costs are distributed fairly among different departments, products, or projects. This fairness is essential for budget allocation and growth in each department. Performance Measurement Allocating costs accurately allows for better measurement of the performance of different departments or business segments. By attributing costs to specific activities, it becomes easier to identify areas of inefficiency and make necessary improvements. Profitability Analysis Cost allocation helps in determining the profitability of products, services, or business units. This information is invaluable for making strategic decisions about resource allocation, product pricing, and business expansion. However, read our other considerations when breaking down revenue in our average revenue per employee blog. Resource Allocation When costs are allocated appropriately, organisations can allocate resources more effectively. It helps in identifying where additional resources are needed and where resources might be overallocated, leading to cost savings. Visualising Cost: The Power of Representation One Model lets you visualise your cost allocation journey over time through detailed charts. While this can present a plethora of data, each data point offers invaluable insights. For those who prefer a more structured representation, a tabulated view can provide clarity. All you need to do is create a data set that shows the amount of cost to allocate, along with the start and end dates of that allocation. From current headcount to cost allocation for recruiting, the process to get the answer is the same. For example, if you spent $10,000 on job advertisements on LinkedIn from Jan. 1, 2018, to Dec. 31, 2018, One Model can efficiently allocate that spend per day throughout the year. This becomes very useful when combined with other metrics over periods of time. For example, I can compare what I'm spending on LinkedIn with the number of applications I receive from LinkedIn during that period. This yields a "Cost Per Application" metric that I can use to compare the effectiveness of LinkedIn relative to other sources. The Takeaway If the daunting task of juggling countless spreadsheets, numbers, and formulas sounds all too familiar, there's a better way. One Model is designed to transform the perplexing world of cost allocation and overhead allocation and creating a tailored cost allocation plan into a more straightforward, efficient process. So, if late-night data crunching is your current reality, it's time to explore the capabilities of One Model. Let us show you how One Model does this 1:1
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14 min read
Lisa Meehan
The way a company structures its workforce is crucial to its success. Workforce structures determine how employees are organised, how work is delegated, and how communication flows throughout the organisation. Workforce structures refer to the way a company organises its employees, financial responsibilities, and the relationships among them. It provides a framework for managing and coordinating work activities. There are several types of enterprise structures and your organisation uses several of them, so let’s talk through different ones and see how you can visualise them. Types of workforce structures Most workforce structures can best be displayed as an org chart. An organisational chart, or org chart, is an essential tool for any enterprise structure as it provides a clear and concise visual representation of the hierarchy, roles, and relationships among employees. It enables employees to understand where they fit into the organisation and how their role contributes to the overall goals of the company. Functional One of the most common structures in business today, a functional organisational structure groups employees according to the functions they perform, such as marketing, accounting, or operations. This allows for specialised expertise in each function, where everyone has a defined role and clear lines of communication. Location and structural overlay It may be that only a division of the company is broken up into location-based structures. For instance, this can be common in sales or HR talent acquisition departments where you have an East, Northeast division of responsibility. Supervisor hierarchy You may have also heard of position hierarchy or supervisory hierarchy. This is a slight modification of the traditional Hierarchical model. You can see these a lot in support or in places within the organisation where approvals are needed. Hierarchy establishes the connection between a superior and the subordinates within an organisation. The supervision hierarchy report exhibits the designated supervisor, presenting their immediate reports, followed by their respective reports, and so on. It encompasses the option to include the employee number, along with the name and job title of each individual, based on the chosen level of supervisory depth. A supervisor hierarchy shows who reports to who. It refers to the structure of reporting relationships within an organisation, where supervisors are responsible for overseeing the work and performance of their subordinates. In a typical supervisor hierarchy, each supervisor has a team of employees reporting directly to them. Often for the people running those units, there is a 1:1 but that’s not always perfect. The supervisors themselves report to higher-level managers or executives, forming a chain of command. The reporting relationships follow a top-down approach — with information, instructions, and feedback flowing from higher-level supervisors to lower-level employees. This hierarchical structure ensures clear lines of authority, accountability, and efficient communication within the organisation. Cost centre structure hierarchy The cost centre structure refers to the total collection of different cost types, including both fixed and variable expenses, that constitute the overall expenditures of a business. This is where the financials are run. It’s normally wrapped up in the chart of accounts. Organisations use the cost centre structure to establish pricing and pinpoint opportunities for minimising costs. This is typically how the finance system works and who is financially accountable for the funds that they spend. This can be different from who runs the business units. Therefore, this view can often be out of alignment with the structural hierarchy. To put it simply, it’s because Finance runs the financials and HR runs the business structure. This type of view often coincides with internal company political struggles. Why? Finance likes to be in control of its space and typically doesn’t like HR veering into it. But if HR can get a cost structure into a people data view, it’s typically a good thing. For instance, this will allow the finance team to get activity- or project-based accounting, or the total cost of the project including the hard numbers and people resources to make real assessments on the ROI of various initiatives. You can only get this view when finance and people data are combined. Matrix structure While not easy to visualise, this structure is really important to get right. A Matrix workforce structure generally refers to a type of organizational setup where employees are assigned to multiple reporting lines or managers simultaneously, as opposed to a traditional hierarchical structure where each employee reports to only one manager. In a matrix workforce, individuals are part of cross-functional teams and can work on various projects simultaneously, often with different sets of colleagues and supervisors. The matrix structure is most often used in large, complex organizations that handle multiple projects simultaneously and require a high degree of collaboration across departments. It is commonly found in industries such as technology, engineering, consulting, and pharmaceuticals. Additionally, matrix structures are prevalent in multinational corporations, where teams need to coordinate and work across different geographical regions. How does One Model help? As you can see, getting different views of the various structures within your business can have profound impacts on your understanding. One Model creates alignment for customers, so they can pivot between those different views with the included people insights. This is really important so you can create a mapping between your financial structures and people structures to become the translator that brings that world together within the organisation. Senior leaders typically want to see where all the money is being spent and where the people are so they can make informed decisions. So views that bring this data together make One Model incredibly valuable to our current customers. Our products empower you to change the view with a click of a button, so you get a complete view of what is actually going on. You can also cross-tabulate those views and link them together. Want to see One Model in action? Watch this quick demo video. How security plays into analysing workforce structures A basic organisational breakout may not be too concerning, but once you start applying analytics to your charts to get a better understanding of how key insights or talents are distributed throughout your organisation, you run into issues. That’s why having a tool like One Model with strong roles-based security that locks sensitive information to specific roles allows you to create a public view that instantly keeps your data safe. Security plays a crucial role in analysing workforce structures by focusing on access controls, user authentication, data protection, security awareness, incident response, vendor and third-party risk, and compliance with regulations. By incorporating security considerations into workforce analysis, organisations can identify vulnerabilities, mitigate risks, and establish a robust security foundation for their operations. Explore the evolution of workforce models Want to learn more about the evolution of workforce planning models over the past four decades and the key role that enterprise segmentation plays in achieving great analytics? Watch our webinar with Peter Howes, a thought leader and pioneer in the field of analytics and strategic planning models. He discusses how these structures have changed to a more strategic approach that’s focused on meeting the needs of the business. 7 benefits of incorporating people analytics into your workforce structures Incorporating people analytics into various workforce structures can provide organisations with valuable insights and significant benefits. People analytics, also known as HR analytics or workforce analytics, involves gathering and analysing data about employees to make informed decisions and improve organisational performance. Here are seven ways incorporating people analytics can positively impact workforce structures: 1. Data-Driven Decision-Making: People analytics paired with workforce structure views allows organisations to base their decisions on objective data rather than relying solely on intuition or anecdotal evidence. By overlaying workforce data on top of various structures, organisations can gain insights into critical aspects such as employee performance, engagement, turnover, and productivity to quickly see where trouble resides in the business. These data-driven insights enable more informed decision-making in areas like talent acquisition, talent development, succession planning, and performance management. 2. Talent Acquisition and Retention: People analytics inserted into your workforce structure views can highlight where your most loyal and high-performing employees exist. Seeing this allows you to identify the most effective recruitment channels, evaluate candidate profiles, and predict the likelihood of candidate success — so your team can build impactful strategies. By analysing data on employee turnover and retention, organisations can better visualise the factors influencing attrition rates and develop targeted retention strategies. It can also facilitate the identification of high-potential employees for succession planning and talent development initiatives. 3. Performance Management: Incorporating people analytics into an enterprise structure allows organisations to evaluate employee performance objectively and uncover great leaders and employees. By analysing performance data, organisations can identify top performers, evaluate goal attainment, and provide targeted feedback and development opportunities. People analytics can also help uncover performance patterns and trends, enabling managers to make data-driven decisions regarding promotions, rewards, and recognition. 4. Employee Engagement and Satisfaction: Organisational structures paired with people analytics provides a map of employee engagement levels, job satisfaction, and factors that impact overall employee experience. This will quickly allow you to understand the health of various teams within your business. By analysing data from employee surveys, feedback platforms, and other sources, organisations can identify areas for improvement and take proactive measures to enhance employee engagement and satisfaction. 5. Workforce Planning and Optimisation: Workforce hierarchy paired with people analytics plays a vital role in strategic workforce planning and optimisation. By analysing workforce data, organisations can assess their workforce's current and future needs, identify employee gaps, and develop strategies for workforce development and succession planning. People analytics can also help optimise workforce structures by identifying areas of organisational inefficiency or redundancy, enabling resource allocation and restructuring initiatives. 6. Diversity and Inclusion: Where do your DE&I community members reside in your org? Which areas of the business are most diverse? Incorporating people analytics into your workforce structure can support diversity and inclusion efforts by analysing demographic data. This allows organisations to assess representation, identify potential biases, and implement targeted diversity and inclusion initiatives. 7. Predictive Analytics and Future Insights: People analytics enables organisations to leverage predictive analytics to forecast future trends and outcomes related to the workforce. By analysing historical data, organisations can identify patterns and make predictions about attrition rates, talent shortages, skill requirements, and workforce needs. These insights allow proactive planning and decision-making, ensuring the organisation is prepared for future workforce challenges. In summary, workforce structures already exist in your organisation, the question is can you use them to better understand your business and create efficiencies? If you can’t, or if the process is a major project for your HR team, then you need to consider people analytics software like One Model that empowers you to transform how your leaders make decisions. We’d love to show you how One Model can help your organisation make better talent decisions. Request a demo today!
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Featured
10 min read
Richard Rosenow
What’s the difference between talent intelligence and people analytics? As I speak with people analytics leaders, HR tech vendors, and research analysts, this question comes up a lot. To help clarify the difference, I've developed a quick two-step trick, complete with real-life examples. Read on and let me know what you think. Why is there confusion between people analytics and talent intelligence? Since HR Tech 2022, talent intelligence (TI) has been on fire in the HR tech branding space. There was an incredible market valuation of a few TI companies that woke up the market, and since then there has been a “run on the brand”. This created a lot of noise and complications as companies that weren’t doing TI started calling themselves “TI vendors”. But we’ve seen that “generative AI” has taken the crown for this latest hype cycle — meaning the pretenders are quickly changing their banners to #GAI and we’re seeing the true talent intelligence companies remaining. The core talent intelligence platforms seem to be Lightcast, TalentNeuron, Claro, SkyHive, Revelio, People Data Labs, Draup, Horsefly, and LinkedIn Talent Insights. They gather and generate labor market data, make sense of resume data, social profile data, government data, and job posting data, and make it available for use by teams who analyze the market. We’ve also seen a rise in talent intelligence teams this past year that are distinct from people analytics (PA) teams. Toby Culshaw’s Talent Intelligence Collective is a distinct community with their own conference and conversations. I would suggest that it’s common to find folk who are part of both communities, but we’re starting to see the TI community come into its own and separate from the people analytics community. People analytics had similarly separated from IO psychology in the past 20 years. While there’s a lot of overlap and people participating in both communities, they’re becoming more distinct over time. Lastly, I’ve heard one too many people just give up and say these words mean the same thing. I think that could be true for workforce analytics / HR analytics / people analytics, but talent intelligence is proving distinct. Naming something is the first step to understanding it, so if we blur names, we blur our understanding. I’ve found two big tricks to defining these terms: Differentiating the function from the act Focusing on the second word Trick 1: Differentiating the function from the act The first step is to clarify whether we are referring to the business unit or department that performs the work (the function) or the act of doing the work itself. Function Act People analytics The business unit responsible for centralized people analytics, typically within HR, but not necessarily. The act of performing people analytics with workforce data, performed by anyone in HR, management, or leadership roles. Talent intelligence The business unit responsible for centralized talent intelligence, usually within recruiting organizations. The act of performing talent intelligence, typically done by sourcers, recruiters, facilities, or strategy teams. We often see people analytics as an umbrella term that encompasses workforce planning, people strategy, and sometimes even compensation and HR technology. This doesn't necessarily mean that all of these teams engage in the act of people analytics, but they are all part of the same function or business unit. Not knowing the difference between the function and the act of doing something can cause confusing, semantic arguments. The name of the function? Honestly, it doesn't matter. The name of the act? That's important because it helps us understand who is doing what, whether it needs to be centralized or decentralized, and to distinguish the work from the skills required to do it. So when someone asks you what you think PA or TI are, make sure you clarify the function of the business unit vs the act of doing the work first. Trick 2: Focusing on the second word The second trick, and the most important one, is to ignore the first word and focus on the core meanings of “intelligence” and ”analytics” in the human resources space. Simply put: Intelligence - the ability to gather and combine data about the world to support decisions Analytics - the ability to make decisions based on insights from data We now have real starting places for our definitions. Focusing on the second word highlights the true difference between “intelligence” and “analytics”. These are distinct words with unique contexts that they bring into conversations. By bringing back the first words and ensuring that we stick to the definitions of the second word, we get a clear definition of the two spaces: The term talent intelligence refers to the act of gathering and combining data about the labor market and talent to inform decisions. The term people analytics refers to the process of making decisions based on insights from data we have about our people. To illustrate how these definitions of talent intelligence and people analytics play out, let’s consider two examples: Talent intelligence: A global company is planning to expand its operations to a new region. By leveraging talent intelligence, they can gather data about the local labor market, including the availability of skilled professionals, salary expectations, and competitor presence. This information helps the company make informed decisions about where to establish their new office and how to attract top talent. People analytics: An organization is experiencing high employee turnover rates. Using people analytics, they can analyze workforce data to identify patterns and trends, such as which departments have the highest turnover and which employee demographics are most affected. Armed with this information, the organization can make better decisions and develop targeted retention strategies to improve employee satisfaction and reduce turnover. These examples may still hold confusion, except in the largest organizations where a people analytics or talent intelligence function are both represented and responsible for distinct areas, but ideally this language can help define the space. Taking this further Let's take this thought exercise further. Another benefit of the approach of separating the first and second words is that it can be mapped onto a 2x2 matrix, which uncovers further insights. Intelligence Analytics Talent Talent intelligence - the act of gathering and combining data about the labor market and talent in the world to support decisions Talent analytics - the action of making decisions with insights from data we have about our talent and labor markets. People People intelligence - the act of gathering and combining data about our people to support decisions. People analytics - the action of making decisions with insights from data we have about our people. Playing this out, there are people analytics (function) teams that do all four of these tasks. Some also do 3/4, 2/4, or 1/4 and some of these tasks are centralized by another team or just decentralized within the business unit still. Knowing which is which before digging into a conversation with someone on names and tasks is critical. Unraveling the Mystery By embracing these two handy tricks, we've successfully untangled the web of confusion surrounding talent intelligence and people analytics. Remember, the key is to differentiate between the function and the act, and to focus on the core meaning of the second word. Talent intelligence solutions are all about gathering and combining data on the labor market and talent, while people analytics revolves around making decisions with the data we have about our people. With these distinctions in mind, we can avoid misunderstandings and promote effective communication in the HR and talent management world. Our handy 2x2 grid further showcases the range of functions and acts that people analytics teams can perform, emphasizing the versatility and breadth of their work. By fostering a comprehensive understanding of talent intelligence and people analytics, organizations can better harness the power of their workforce data to drive informed decision-making and achieve their business objectives. So, go ahead and spread the word — it's time to put this newfound clarity to good use! What are you doing for talent intelligence and people analytics? Let's have a conversation.
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Featured
8 min read
Phil Schrader
I recently sat down with Culture Curated’s Season Chapman and Yuliana Lopez to ask them which metrics were their favourite and Yuliana said net hires. Let’s find out why: Net hires are a critical component of workforce management, as they help organisations determine staffing needs, forecast future headcount, and make informed decisions about recruitment and retention strategies. In this One Model blog post, we’ll explore the concept of net hires, how it’s calculated, and why it’s essential for organisations to track this metric. What are net hires? Net hires, also known as net hiring or net employment, is a measure that tracks the difference between the number of employees who leave an organisation and the number of new employees who are hired during a specific period. This metric provides valuable insights into a company's workforce dynamics, such as the rate of employee turnover, the pace of recruitment, and the organisation's overall hiring needs. This metric is an essential component of workforce planning and management, as it helps organisations to determine staffing needs, forecast future headcount, and make informed decisions about recruitment and retention strategies. For example, if a company hires 50 new employees during a quarter and loses 20 employees during the same period, the net hires for the quarter would be 30 (50 - 20 = 30). A positive net hires value indicates that the organisation is expanding its workforce, while a negative value indicates that the organisation is reducing its workforce. The chart below shows new hires juxtaposed against terminations. Explore several ways to visualize headcount here. I like using One Model for the presentation of this data because you can quickly adjust by any segment or time period to see how the story changes when looking at it from different angles. Calculating net hires To calculate net hires, organisations need to track the number of employees who join and leave the company during a specific period. This information can be obtained from various sources, such as HRIS records, payroll systems, and employee surveys. Once the data has been collected, organisations can use the following formula to calculate net hires: Net hires = Total number of new hires - Total number of terminations For instance, if a company hired 100 new employees and had 50 terminations during a specific period, the net hires for that period would be 50 (100 - 50 = 50). Having trouble balancing headcount with net internal movements? Learn more. Why is monitoring net hires important? Net hire headcount is a critical metric for organisations for several reasons. Firstly, they provide insights into the organisation's overall workforce trends, such as the pace of recruitment, the rate of turnover, and the company's growth trajectory. By tracking net hires over time, organisations can identify patterns and trends in their hiring practices and adjust their recruitment strategies accordingly. Secondly, net hires can help organisations by understanding the rate at which employees are joining and leaving the company, organisations can make informed decisions about their recruitment and retention strategies, including whether to ramp up hiring efforts, invest in employee training and development, or adjust staffing levels in response to changing market conditions. Finally, net hires can also help organisations evaluate the effectiveness of their recruitment efforts. By tracking the number of new hires, organisations can assess the success of their recruitment campaigns and identify areas for improvement. Additionally, by comparing net hires to other metrics, such as employee engagement and retention rates, organisations can gain a more comprehensive view of their overall talent management strategy. Challenges of tracking net hires While net hires are an essential metric for organisations, tracking this metric can be challenging. One of the main challenges is ensuring the accuracy of the data. HR records and payroll systems are prone to errors and inconsistencies, which can lead to inaccurate calculations of net hires. Moreover, tracking net hires requires a robust data infrastructure, including data collection, storage, and analysis tools. Another challenge is defining the period over which net hires should be calculated. Since you are measuring change over time, you could run into a situation where you get a zero result in calculated measures. In this case, having a tool that can understand and make sense of that is important. Organisations also need to determine whether to track net hires on a monthly, quarterly, or annual basis — depending on their specific workforce management needs. Moreover, organisations need to ensure that the period over which net hires are calculated is consistent across all departments and business units, to enable accurate comparisons. Optimising net hires To optimise net hires, organisations need to adopt a data-driven approach to recruitment and talent management. A key way to do that is by using people analytics tools to track and analyse workforce data, including net hires, turnover rates, and engagement levels. Final lessons from Season As you heard in the video, Season doesn’t like looking at one metric or a metric at a single point in time because it’s misleading. With that in mind, we know that net hires mean less if you don’t understand your termination metrics and recruitment rate. Remember to think of all the contributing factors and explore the data at your disposal to create a comprehensive story that creates value for your organization. The power of segmenting headcount In addition to looking at supporting metrics, you should also be segmenting your headcount audience to see if there are trends across departments or geography. Only looking at things as a whole may be misleading. That’s why using a tool like One Model with flexible storyboards is vital to put all the pieces of the same story on the same page. Make sure that a headcount dashboard is one of the first essential dashboards you build. Ready to Learn More? Watch me build this report live. Connect today.
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6 min read
Dennis Behrman
Artificial intelligence (AI) has become an integral part of various industries, revolutionizing the way organizations make decisions. However, with the rapid advancement of AI technology, concerns about its potential and ethical implications have emerged. As a result, governments around the world are preparing to enact regulations to address the use of AI in people decisions. In this blog post, we will explore the scope of these forthcoming regulations and discuss how People Data Cloud can help ensure equitable, ethical, and legally-compliant practices in automated decision-making across organizations. Broad Scope of Regulations While generative AI, such as ChatGPT, has been the catalyst for these regulations, it is important to note that the scope will not be limited to such technologies alone. Instead, the regulations are expected to encompass a wide range of automated decision technologies, including rule-based systems and rudimentary scoring methods. By extending the regulatory framework to cover diverse AI applications, governments aim to ensure fairness and transparency in all areas of decision-making. Beyond Talent Acquisition Although talent acquisition processes like interview selection and hiring criteria are likely to be subject to regulation, the scope of these regulations will go far beyond recruitment alone. Promotions, raises, relocations, terminations, and numerous other people decisions will also be included. Recognizing the potential impact of AI on employees' careers and well-being, governments seek to create an equitable and just environment across the entire employee lifecycle. Focus on Eliminating Bias and Ensuring Ethical Practices One of the primary objectives of these regulations will be to eliminate bias in AI-driven decision-making. Biases can arise from historical data, flawed algorithms, or inadequate training, leading to discriminatory outcomes. Governments will emphasize the need for organizations to proactively identify and mitigate biases, ensuring that decisions are based on merit and competence rather than factors such as race, gender, or age. Ethical considerations, including privacy and consent, will also be critical aspects of the regulatory landscape. Be Prepared. Join the Regulations and Standards Masterclass today. Learning about AI regulations and standards for HR has never been easier with an enlightening video series from experts across the space sharing the key concepts you need to know. A Holistic Approach to Compliance To comply with forthcoming AI regulations, organizations must evaluate their entire people data ecosystem. This includes assessing where data resides, which technologies are involved in decision-making processes, the level of human review and transparency afforded, and the overall auditability of automated decisions. Achieving compliance will require robust systems that enable organizations to monitor and assess the fairness and transparency of their AI-driven decisions. One AI is Your Automated People Decision Compliance Platform As governments gear up to regulate AI in people decisions, organizations must be prepared to adapt and comply with the evolving legal landscape. The scope of these regulations will extend beyond generative AI and encompass a broad range of automated decision technologies. Moreover, regulations will address not only talent acquisition but also various aspects of employee decision-making. Emphasizing the elimination of bias and ethical practices, governments seek to create fair and equitable workplaces. To ensure compliance with AI regulations, organizations can leverage platforms like One Model's One AI, which is fully embedded into every People Data Cloud product. This platform provides the necessary machine learning and predictive modeling capabilities, acting as a "clean room" to enable compliant and data-informed people decisions. By leveraging such tools, organizations can future-proof themselves against audits and demonstrate their commitment to ethical and unbiased decision-making in the AI era. Request a Personal Demo to See How One AI Keeps Your Enterprise People Decisions Ethical, Transparent, and Legally Compliant Learn more about One AI HR Software
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5 min read
Joe Grohovsky
"Strategy without tactics is the slowest route to victory. Tactics without strategy is the noise before defeat." - Sun Tzu Complex people analytics (PA) projects risk losing sight of what is profoundly important as they endeavor to fulfill all aspirational requirements. Identifying and delivering business insight is their purpose, not simply fulfilling a stakeholder’s tactical wish list of presentation-layer features. However, far too often PA initiatives are launched with requirements dominated by this tactical wish list without a true appreciation for the value of the metrics contained within each report. The funding and focus involved clearly classify these initiatives as Strategic HR projects. Instead of blindly focusing on what presentation tactics will be used, consider first a strategy for building better insights. These strategic conversations should begin with the number (metric/measure) in question. This number is critical and is the cornerstone for all other discussions. This number should be accurate and meaningful. Everything else within a PA initiative is the tactical positioning of that strategic number. Accuracy Without accurate numbers, a reporting effort is wasted. Ask yourself these questions. Is the number derived from trusted, validated source data? Is the source data modeled specifically for your organization? Does your definition of that number align with what will be provided? These questions are more than simplistic check boxes. Consider Headcount, which is the most basic HR measure. Is it based on the Start of the Period, End of the Period, or Average Daily Headcount? Are retroactive changes accommodated? What will happen when introducing additional data sources such as Engagement or Performance? Are you forced to work with templated data and a rigid data model? Interested in learning how to create a stellar People Data Platform? Read our latest whitepaper to understand the steps your team needs to take to create an analytics-ready data platform that will give your team reliable, accurate information that can help propel your people analytics projects toward success. Meaningfulness Not all numbers are equal or valuable. When considering specific metrics, consider these questions. Is this number important on its own, or does it merely provide context? Is it actionable? Considering the above, an easy analogy would be the numbers a physician uses during a patient’s annual physical examination. Those numbers include things like age, height, weight, blood pressure, etc. Age and height are uncontrollable and immune to any action. However, these numbers still provide valuable context for other numbers. Weight and blood pressure would be considered actionable and the focal point for discussion. Once actionable numbers are identified, ask yourself “So What.” Will this insight drive any internal decisions? If not, it is best to focus elsewhere. These questions will determine meaningfulness. Presentation of Numbers After accurate and meaningful numbers are established, a conversation on presentation tactics can occur. Awareness of internal culture and data consumer preferences is critical in this step. Most PA initiatives serve a broad spectrum of data consumers that may involve: HR Business Partners Analysts Center of Excellence Data Scientists Line of Business Managers Self-Service capabilities Senior Executives Each group is best served by providing varying amounts of support, flexibility, and handholding. Common differences for each group would include the decision to provide a summary or detailed data, the amount of context provided, or the amount of supporting documentation required to establish metric validity. Summary It is understandable that PA professionals become fascinated with whiz-bang features contained within presentation capabilities. Ease of data consumption is important, but please realize that it trails behind generating accurate, meaningful numbers. Storytelling your way through People Analytics without substance supporting you is risky. For examples of impactful HR projects, or information on how One Model approaches this topic, please connect with us.
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2 min read
Phil Schrader
It's an all too common scenario: a rush request coming in from the leadership team, in this case leadership in the finance department. They want to understand some cost impacts with our workforce and how it's changing. But it's Friday afternoon, so I want to try to get this request done as quickly and accurately as I can. Do you want to be able to knock out highly accurate, ad-hoc reports fast? Get a demo of One Model to see how!
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2 min read
Dennis Behrman
Most large employers are already required by law to ensure that workers are safe and workplace risks are minimised as much as possible. But a new school of thought has emerged around the concept of well-being at work. Whether you've followed this trend closely or this is the first you're hearing of it, well-being has been studied and there is interesting data available about it. We Asked an Expert about Implementing Well-being at Work My colleague Richard Rosenow recently invited his good friend Matt Diabes, a Ph.D candidate at the Carnegie Mellon Tepper School of Business to discuss well-being in incredible new detail. His research demonstrates that well-being is far more complex than ping-pong tables and good pay. Watch their lively and informative discussion to understand what well-being is and how managers and organisations can harness the promise of well-being for great talent outcomes. If your organisation has thousands and thousands of workers whose well-being matters to you, you'll want to be able to measure well-being at your company. Find out how One Model can help you report on well-being and how to achieve organisational well-being goals. Request a Personal Demo to See How Well-being is Measured.
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8 min read
Phil Schrader
Turnover is the strongest signal you get from your workforce. Someone worked here, and — for one reason or another — it didn’t work out. Voluntary termination of employment is a major event, and you need to pay attention to the reasoning (and the data) to help you with employee retention. While some degree of turnover is inevitable, the high cost of losing an employee can have a major impact on your bottom line. So, how do you calculate voluntary termination, and what can you do to combat it? Let's take a closer look. How to Calculate the Cost of Turnover There are a number of ways for calculating the cost of turnover. The most common (but less accurate method) is to multiply the average salary of the position by the number of separations. For example, if you have 10 employees who make an average salary of $50,000 per year and five resign, the turnover cost would be $250,000 ((10 x $50,000) / 2). However, this method needs to take into account the time it takes to find and train replacement employees. A more accurate way to calculate the cost of turnover is to use a formula that factors in recruiting costs, training costs, and lost productivity. Using this formula, the cost of turnover for our example above would be closer to $37,500 (((10 x $50,000) + ($5,000 x 10)) / 2). The ability to calculate voluntary attrition internally will bring a new dimension to your leadership team. However, these benchmarks serve as a baseline for your turnover calculator as there are several other variables and data points to consider, including: Daily rate of the hiring manager’s salary Estimated hours spent interviewing and screening resumes Estimated cost of advertising for the available position Daily rate of departed employee’s salary plus benefits Number of days the position will remain open before you rehire Cost to conduct a background check Daily rate of the hiring manager’s or trainer’s annual salary Total days the hiring manager or trainer will spend with new employee Number of working days in the new hire’s onboarding period It’s also important to factor in position levels. The Center for American Progress (CAP) found that the cost of staff turnover was, on average, 213% of the annual salary for highly-skilled employees. Segment the positions into three different salary levels for a more accurate turnover calculator: average entry level, average mid-level, and average technical salaries. Tracking Voluntary Attrition Over Time The simple truth is that you will not get a full picture of what is happening from a single calculation. It can be time-consuming to calculate on a consistent basis over time manually. You need to see the trends. Create a storyboard to see if trends emerge. You can break down the involuntary and voluntary attrition rate by business unit, location, and organization tenure groupings. You can also quickly see at a glance how turnover rates are changing, where they are high, and whether it’s you or the employee forcing the change. It took me 49 minutes to pull this cost of turnover visual together from scratch. How long does it take you to answer question #59? See how quickly you can take the People Analytics Challenge and answer over 90 of the top questions asked of People Analytics Teams. You Know How to Calculate Churn Rate of Employees and Turnover Cost — Now What? Now that we know how to calculate the cost of turnover let's look at how you can mitigate voluntary attrition in your organization. Use One AI Recipes to Predict Trends and Make Proactive Changes You know the “What” but you really need to know the “Why”. So, run a predictive model on that data to pull out the correlations and understand the why behind the attrition. One AI Recipes will help you predict the likelihood of a person in a selected population voluntarily terminating within a specified period of time. To do this, One AI will consider a number of attributes and will train the model on the population at a defined point in the past. Does distance to the office, time since last promotion, or paid sick leave correlates to a rise in attrition? AI is a tool that helps you make connections and better understand voluntary resignation reasons in order to take specific actions leading to improvement. Improve Hiring Practices Poor hiring practices could easily be one of the reasons why your voluntary attrition rate is high. Be sure to clearly define the skills and experience required for each position and only interview candidates who meet those criteria. Conduct thorough reference checks, and don't hesitate to pass on a candidate if there are any red flags. After analyzing your hiring process, you can incorporate the proper people analytics data to produce the most accurate cost of losing an employee. Promote from Within Another great way to reduce turnover is to promote from within whenever possible. Not only does this show your employees that there are opportunities for advancement within your company, but it also helps reduce training costs because you already have someone on staff who knows your company culture and how things work. Invest in Employee Development Finally, investing in employee development is a great way to reduce turnover rates. Employees who feel like they are learning and growing in their roles are more likely to stick around. Offer professional development opportunities through tuition reimbursement programs or paid memberships to professional organizations. Final Thoughts on How to Calculate the Cost of Turnover Sure we want to understand how much it costs the company. That is the first step in getting leadership to care. However, the real work begins when you understand why people are leaving and can build a plan to curb the costs. People analytics offers real-time labor market intelligence to help businesses identify pain points causing turnover. And considering the high cost of losing an employee and its impact on your bottom line, employee retention is critical in today’s economy. One AI Recipes make creating a predictive model from your people data as easy as choosing the outcome you want to predict and answering a series of questions about the data you want to leverage to make the predictions. The result is a predictive model based on robust, clean, and adequately structured data — all without engaging a data engineer or data scientist. Calculating turnover is the first step toward helping you understand and predict trends, reduce turnover rates, and keep your business running smoothly. Watch Me Build A Turnover Analysis Live Request a Personal Demo Today.
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9 min read
Chris Butler
A major shift has occurred in Human Resources over the past five years. The world went from a handful of companies experimenting with people analytics - early adopters - to thousands of companies investing in dedicated roles and teams to take on a new way of thinking about Human Resources. What can you learn from the early adopters? Every CHRO who has moved forward with people analytics has some secrets to success. These secrets will help you provide a better, faster way to more effectively deploy HR resources and build a successful organization. Better human resources strategy means better business You need to accept and measure change There will be change. That is the only constant. Change could come from any number of places like new technology, new customers, new leadership, new products, new competition, new market and strategies. You will get maximum benefit from your HR strategy if you accept the reality that change is the only constant - the only certainty is a world of uncertainty. If you want to survive in a world of uncertainty you need to have a process to constantly take in new information to understand changing reality and use this new information to adapt. You need a way to measure to see if your organization is changing in the way that you and your leadership team expect. Change is what people analytics is for. Hire specific talent for a meaningful business advantage The problem is that most HR strategies are far too general to develop any sustainable advantages: “We will hire great people.” Great idea - you and everyone else! You cannot do everything well all the time - as the cost to attract and retain top talent just gets more expensive so you have to choose. You have to choose specifically where you want your business advantage to be and then you have to figure out how to create this advantage through People. In this way we and others may realize that the people's perspective of the business is not necessarily based in “soft stuff”, “political correctness” and administrative minutia, but profound business insights that arise in conjunction with observation and reason. Basically there are two types of insight: that which is not based on any special observable reason and that which is backed by observable reason. In the case of the second type of view, an individual is motivated to examine an insight and investigate its relevance to his or her situation, needs and requirements. Actions are applied after seeing the reason why this insight is advantageous. Change with people, new action, is motivated by new insight; that insight is powered by people analytics. Don’t get led astray by “traditional” HR metrics it is not always clear how to relate HR actions to business impact, and so we settle to monitor activities as a measure of progress which is a traditional metric for success. Measuring progress as activities that have an unknown relationship to current business objectives leads HR into waste. HR is broken into multiple functional centers of excellence (Staffing, Benefits, Compensation, Labor Relations, Talent Management, Organization Design), each with different goals and activities, we end up with hundreds of metrics that do not align with each other and do not drive towards a unified goal. This results in efforts that either have no impact or work against each other, not to mention waste in the process of analytics itself. Because we have not previously devised a single HR metric that has a direct business impact that can be applied universally across organizations and sub organizations, we substitute simplistic measures that while a good intention, may not be a universally good idea, may conflict with other objectives and may not correlate in any way with measurable business impact. This results in the wrong efforts/objectives. Investing heavily in quantitative metrics doesn’t automatically give us solutions. Metrics can usually tell us what’s going wrong, usually not why. The more you invest in quantitative metrics, with a process for qualitative input, the more you end up drowning in a sea of non-actionable data. Create a culture of success Those leaders who want to create a healthy organization or “culture of success” are motivated (or should be motivated) to attain a genuine camaraderie with all people in an organization. When a group of people have a common vision, maintain a sense that they are all in it together, and have compassion for each other then there is nothing that cannot be accomplished. At this juncture, in addition to many great spiritual teachings of varied doctrines, we also have a foundation of great insights in science and engineering and access to those examples and methods. At the heart of it: we analyze people within an organization for benefit to that organization - and that is also the people. It must be both. Useful analysis helps us all understand current reality and take the right actions now to achieve optimal outcomes: an outcome of joint benefit to managers, employees, shareholders and possibly society. A continual reduction in tenacious organizational problems and continual reinforcement of a culture of success is the ultimate result of useful analysis. Disciplined action (as opposed to frantic thrashing) is the benefit of useful analysis. Our concept of a healthy organization is not something physical. Therefore the spread of a healthy culture depends on increasing the depth of understanding of the benefit of new actions to provide strong motivation to pursue those new actions. When we are able to reduce the defects in how we think about people in an organization a healthy culture will naturally increase. Thus, effecting positive transformations in organizations through observation and feedback situation by situation, subdivision by subdivision, manager by manager, and employee by employee is the method we will employ to effect the change we desire. Unlike manufactured goods it should be fairly obvious that culture is not a tangible entity, that it cannot be sold or bought in the marketplace or physically constructed. Watch out for HR constraints (budget, credibility, time) Most of the programs HR watches over have very large budgets. Labor costs are frequently 70% or more of revenue. Benefits may represent 30% or more of labor costs. On an absolute basis these costs increase over time as the employee base grows. Things get sideways when business plan projections get off track and the cost of labor grows faster than revenue or when revenue retracts. It is critical for CHROs to be able to identify—quickly, early, and accurately— whether a project or activity is worth pursuing, rejecting, continuing or dropping so it may protect its commitments and preserve resources for those programs that drive the most value. Besides the obvious constraint of budget, the other constraint is credibility. In order to influence, HR professionals need to hold on to and build on what little credibility they start with. As CHRO you will have to justify HR’s right to have a seat at the business table by demonstrating the business impact of your programs to a CEO, management team or business line head to whom you support. At some stage, you will all be called on to demonstrate progress. Finally, we are all constrained by time. Every minute spent on an activity that is doomed to fail is wasted. HR has historically relied on two categorical measures of progress: how much stuff they are doing and how much people like what they are doing. Yet unfortunately, both of these metrics are unreliable proxies of business impact and both of these lead us down the wrong path—building something that ultimately does not matter, has no impact on the business or worse, the wrong impact. People analytics can be hard First, there is a misconception around how successful earth shattering people analytics get built. The media loves stories of “wunderkind” nerds invading HR who are so smart they helped the moribund HR function (usually at some cool tech company) figure this problem out. The reality, however, rarely plays out quite as simply. Even the unveiling of the hiring algorithms at Google, in Laszlo Bock's words, was years in the making, built on the contributions of many and several incremental innovations (and failures). Second, the classic technology-centric Reporting or “Business Intelligence” approach front-loads some downstream business partner involvement during a “requirements-gathering phase” but leaves most of the HR business partner and business customer validation until after the reporting solution is released. There is a large “middle” when the Analytics function disengages from the ultimate intended users of these reports for months, maybe even a year, while they build and test their solution. Sometimes the solution is rolled out in HR first, just to be sure it is safe for humans before inflicting it on the rest of the organization. Imagine a few wild eyed HR people hiding in the bushes outside the office preparing to jump up on an unexpecting executive on his way into work one morning. During this time, it’s quite possible for the Analytics function to either build too much or be led astray from building anything remotely useful to the organization. Third, People are complex and messy. People are not structural engineering challenges that are within the abilities of an engineer to control precisely. People and organizations are not like machines or computers. There is always a certain degree of uncertainty about the effect of our actions on people and organizations. We try things based on an entirely plausible premise and they fail. Usually we had not factored in or considered the thing or things which made it fail. There are too many variables, too many possibilities and too much change occurring within and all around us. Is this not in some sense the beauty of life? Would you rather take this away? In human systems, failure is not the problem, the problem is failure to learn from the failure. If we want to improve HR we should shift our attention to how we can learn more quickly. These Secrets are the CHRO’s Real Guide to People Analytics People analytics gives CHROs a better, faster way to more effectively deploy HR resources and build successful organizations. People analytics enable better listening, learning, strategic focus, measurable business impact, and rigorous process.
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3 min read
Nicholas Garbis
There are whole books written about Workforce Planning. I read them and enjoy them (maybe even more than I would like to admit). I will include a short list below for your reference. So, what can be added to the body of thought leadership on this topic? My former SWP colleague, Phil Mische and I got together (in person!) to discuss some elements of SWP and decided to create a video hitting on a handful of topics in rapid succession. We decided to call it "Lightning Round Learning." As background, Phil and I worked together on successfully designing and implementing SWP at scale at a global financial services firm. It was an intense experience but was the greatest test of everything that I had wanted SWP to be. Nothing is perfection, especially in year one of a multi-year journey, but it was world-class SWP and we each have an abundance of learnings to share. We listed out several topic ideas and then selected these in real-time, then hit each of them for a few minutes each: Operationalization of SWP Technology (data, tools, models) Granularity of Skills data Change Management Strategic v. Operational workforce planning There is way more depth on each of these elements -- we could easily have filled most of a day unloading our experiences -- and there are many other elements of SWP that we didn't cover. So, sit back and check out the video below. Then do these 2 things: Schedule time to chat with me on SWP, People Analytics, or One Model more generally. https://meetings.hubspot.com/nicholas-garbis Let me know what SWP elements you think we should cover in Part 2! You can message me here or post your comment to LinkedIn here. SCHEDULE TIME TO CHAT! Workforce Planning Book List: Agile Workforce Planning, by Adam Gibson Strategic Workforce Planning, by Ross Sparkman Strategic Workforce Planning: Guidance and Back-Up Plans, by Tracey Smith ... and one day I may write an SWP book to add to this list! .... :)
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6 min read
Stacia Damron
It’s sounds ridiculous, but it’s true. According to the New York Times, 4.2% of women held CEO roles in America’s 500 largest companies. Out of those same 500 companies, 4.5% of the CEO’s were named David.* While shocking, unfortunately, it’s not incredibly surprising. Especially when a whopping 41% of companies say they’re “too busy” to deploy diversity initiatives. But for every company out there that’s “too busy”, there are plenty of others fighting to get it right. Take Google, for example. In 2016, Google’s tech staff (specifically tech roles - not company-wide roles) was 1% Black, 2% Hispanic, and 17% women. They announced a plan to invest 150 million in workforce initiatives. The tech staff is now 2.5% Black and 3.5% Hispanic/Latinx, and 24.5% female, according to their 2018 diversity report. So what does that mean? It means that even the brightest and most innovative companies have their work cut out for them in regards to improving diversity. Change doesn’t happen overnight. Diversity breeds innovation; a diverse talent pool leads to diverse ideas. Get this; a Forbes article touts that transitioning a single-gender office to a team equally comprised of men and women would translate to 41% in additional revenue. “Metrics” (which is just a fancy word for data btw) don’t lie. It’s important to set, track, and monitor workforce diversity goals - especially when we have more tools than ever at our disposal to do so. Over the past few years, here at One Model, we've seen a huge push for placing a priority on monitoring diversity metrics. In 2016, a Fortune 100 financial services organization, Company X (name anonymized) selected One Model’s platform to measure and monitor company-wide trends in diversity data and metrics. As their people analytics and workforce planning solution, One Model allowed them to not only better report on their data - but also more easily track and monitor changes, determine key KPIs, and see how improvements they’re making internally are affecting the data. More Accurate Data = Better Reporting. During Company X's transition from SAP to Workday, they used One Model to retrieve and migrate survey data. This platform allowed them to combine and normalize the data from several sources, enabling the team to report off of it as one source. The successful migration provided the HR team with the recovered data and prevented the team from having to redeploy the survey, allowing them to more accurately reflect their current diversity metrics and progression towards goals. This was a win. Here’s the challenge: When pulled together, the data referenced above indicated that out of several thousand employee responses, a number of employees failed to select or identify with one of the given race selections. This represented a sizeable portion of the employees. One Model’s software helped them identify this number. Once they realized this, they realized they had an opportunity to setup other processes internally. They did just that - which helped identify 95% of the employees who fell within that group, obtaining vital missing data that raised the percentage of diversity within the organization. Determining Key KPIs and Measuring Improvements Furthermore, Company X used the One Model platform to identify and reward the departments that successfully hit their recruitment-based diversity goals. This allowed the team to survey these departments and identify the hiring trends and best practices that led to these improved diversity metrics. By identifying specific process and KPI’s surrounding these diversity metrics, departments that successfully met their goals could share recruiting tactics and best practices to ensure appropriate actions were taken to maximize diversity throughout the whole of the recruiting pipeline. Company X is currently implementing these processes and working towards replicating a similar outcome amongst other departments in need of workforce diversity improvement. Tracking and Monitoring Changes Last but not least, Company X wanted more visibility into why females had a lesser presence in managerial roles within the organization. While, male to female promotions were equal. (This past year, 32 people were promoted. 55% of promotions (16 people) were women), there were significantly more males than females in managerial roles. Upon reviewing the data, they learned that out of the company’s requisitions, females applicants only made it to certain stages within the interview process (namely, an in-person interview) 50% of the time. Half the time, the only applicants that made it to a particular stage were male. They determined a hypothesis surrounding a particular KPI - that if more females made it to this particular stage, the odds were higher that more females would fill these roles. Company X set a goal that they wanted a female candidate make it to a manager interview stage 80% of the time. They are testing different methods on how best to achieve this, and with One Model's help, they are able to measure the effectiveness of those methods. By providing this visibility, One Model’s platform is currently helping them monitor their progress towards this goal, and allows them to see the affect - the direct impact on numbers of M/F managers in real-time. Company X is one of the many companies that has realized and embraced the importance of diversity in workforce planning. We’re confident they’ll eventually hit their goals, and we’re proud to be a part of the solution helping them do so. Is your company ramping up it’s People Analytics Program or diving into workforce diversity initiatives? One Model can help you better view and report on the data associated with your diversity goals. Here are just a few of the top metrics companies are currently focusing on: Recruitment Metrics Representation Metrics, such as: Minorities / URMs Veterans Women IWDs Staffing/Placement Metrics Transaction Metrics Training Metrics, such as: Penetration of diversity-related training, general training participation rates, and demographics of talent pipeline Advancement Metrics External Diversity Metrics Culture / Workplace Climate Metrics *based on 2016 NYT data. Want to see what One Model can do for you? Scheduled some time to chat with a One Model team member. About One Model: One Model provides a data management platform and comprehensive suite of people analytics directly from various HR technology platforms to measure all aspects of the employee lifecycle. Use our out-of-the-box integrations, metrics, analytics, and dashboards, or create your own as you need to. We provide a full platform for delivering more information, measurement, and accountability from your team.
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