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Featured
7 min read
The One Model Team
Securing budget for new HR technology often hinges on one question: What’s the return on investment? People Analytics, while universally acknowledged as valuable, can still raise skepticism among finance teams or executives who want hard evidence that it will pay off. The good news is that a well-structured approach can deliver both financial and strategic returns, and People Analytics platforms like One Model offer clear proof points that help justify the spend. Going Beyond “Nice-to-Have” Historically, HR initiatives have been labeled as “soft” investments that are tough to measure in dollar terms. Yet turnover, engagement, and productivity each have a direct effect on the bottom line. Consider the cost of replacing a mid-level employee—recruiting fees, onboarding expenses, and lost productivity can easily total 20% of that individual’s salary. By applying People Analytics to spot flight risks early and prioritize retention strategies, companies can significantly lower those replacement costs, creating a measurable impact executives can’t ignore. Tying Metrics to Business Outcomes Building a solid business case means linking your HR data to tangible business drivers: Reduced Turnover: If a department has a historically high churn rate, even a modest improvement can free up thousands—if not millions—of dollars annually.Here’s how to calculate turnover costs and their impact. Improved Productivity: Identifying the skills gaps causing performance issues can lead to targeted training programs that raise output and reduce error rates. Faster Hiring Cycles: A shorter time-to-fill for crucial roles means key projects don’t stall, potentially preserving revenue and customer satisfaction. Learn more about key People Analytics dashboards that visualize these metrics. When you show how these metrics directly influence revenue, profitability, or operational efficiency, leadership is far more willing to invest. Hypothetical ROI Scenario: One Model in Action Imagine an organization with 2,000 employees and an annual voluntary turnover rate of 15%. Replacing a single departed employee might cost 20–30% of their salary—let’s approximate $15,000 in combined hiring and onboarding expenses per exit. Over a year, 300 employees leave (that’s 15% of 2,000), costing around $4.5 million. By leveraging One Model to unify disparate HR data—engagement metrics, performance reviews, and compensation details—HR spots patterns that predict which employees are at risk of leaving. Targeted interventions reduce that turnover by just 2 percentage points (to 13%). The organization now loses 260 employees instead of 300, saving about $600,000 in direct turnover costs annually. Factor in intangible savings like retained institutional knowledge and smoother team dynamics, and the ROI climbs even higher. A Broader Strategic Value Hard-dollar savings are compelling, but they’re not the only factor to consider. People Analytics also provides strategic benefits that shape long-term competitive advantage: Enhanced Talent Strategy: Predict where the business might face skill shortages in the next year and invest in reskilling or recruiting accordingly. Elevated Employee Experience: Correlate engagement scores with performance metrics to ensure top talent remains challenged and motivated. Data-Driven Culture: Position HR as a credible, analytics-informed function that advises on broader business issues—not just hiring or compliance. By presenting both financial and strategic gains, you offer leadership a more holistic narrative about why this isn’t just another HR tool. It’s a catalyst for organizational resilience and growth. How One Model Simplifies the Pitch One Model helps make the ROI case crystal clear. Through pre-built dashboards, predictive modules, and real-time analytics, you get a transparent view of how workforce changes affect business outcomes. Instead of wrestling with spreadsheets or siloed systems, HR teams can quickly deliver the numbers executives want—be it turnover cost projections or scenario planning for expansion into a new region. This level of clarity can be the difference between a polite nod at budget time and an enthusiastic yes. Before making your case, it helps to prepare your approach to proving People Analytics ROI. Closing the Deal When crafting your final pitch: Quantify the costs of problems like turnover or low engagement. Highlight tangible savings and revenue protection—if you can reduce churn by a few percentage points, how much money is saved? Demonstrate strategic wins like improved succession planning or a stronger employee value proposition. Ultimately, People Analytics isn’t a gamble—it’s an investment that pays dividends through cost containment, culture improvements, and data-driven foresight. With One Model’s track record and clear ROI scenarios, you’ll have the proof points needed to secure the budget and propel HR to the forefront of strategic decision-making. See how measuring the value of People Analytics can be easier than you think. Curious About Your Potential ROI? Explore how One Model can unify your data, clarify the true costs of people challenges, and help you present a business case that resonates with every level of leadership. Request a Demo
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Featured
11 min read
The One Model Team
As the world emerges from years of working from home, some organizations are facing the complex challenge of crafting an effective Return to Office (RTO) strategy. This task is not as simple as flicking a switch; it involves a labyrinth of data-driven decisions that must factor in various aspects such as employee engagement, facilities management, and overall workplace safety. For leaders in finance, facilities, and human resources, the stakes are remarkably high. The pitfalls of a poorly executed RTO strategy can lead to disgruntled employees, high turnover rates, overcrowded facilities, and potential public relations nightmares. Wherever You are in Your RTO Journey, One Model has You Covered Many companies have already implemented RTO, while others are just starting to transition (and some are staying home). Either way, we’re here to help. Whether you’re refining a fully operational office-based schedule or still weighing the pros and cons of remote vs. hybrid approaches, One Model’s platform delivers the insights needed to make informed decisions at every stage. In this intricate puzzle, One Model emerges as a crucial partner, adept at unifying and streamlining the disparate data sources that are essential for tracking time, attendance, badge data, leave of absence, operations data, and more. Our platform is uniquely positioned to tackle the massive data integration challenge, providing you with the actionable insights needed to navigate this complex journey. Want to learn more specifics for your RTO strategy? Join our March 18 webinar: Return to Office - Creating Positive Impact. Why RTO Planning is a Herculean Task The years spent working from home globally have permanently altered the landscape of work, making the transition back to physical offices anything but straightforward. Many reports and research studies indicate that a significant portion of employees prefer the flexibility of remote or hybrid work arrangements. However, many organizations still believe in the benefits of having employees in the office for at least part of the week, citing productivity, company culture, and team cohesion as key considerations. Let’s set that debate aside for a minute. If you are looking to head back, here are some ideas and tips to help you accomplish that goal easily, efficiently, and from a data-informed perspective. With multiple stakeholders involved—finance, facilities, and HR—each bringing their own set of needs and expectations, coordination can be immense. The data needed to effectively manage this transition is often scattered across various systems, making integration a colossal task. Here’s why RTO planning presents such a challenge: Diverse Data Requirements: A successful RTO strategy requires a holistic view of numerous data points, including time and attendance records, badge access logs, facilities usage, and even employee preferences regarding remote work. Cross-Functional Coordination: Aligning different organizational units like HR, finance, and facilities management toward a cohesive plan is inherently complicated without the right tools and data insights. Risk of Misalignment: Ineffective planning can lead to underutilized or overcrowded spaces, lapses in safety protocols, reduced employee satisfaction, and damaging headlines. Complex Data Integration: Consolidating data from various HRIS, time management systems, and facility usage trackers into a unified, actionable format is a monumental task. Real-World Consequences of Poor RTO Execution Countless organizations have stumbled in their attempt to bring back their workforce, suffering severe repercussions. For instance, Apple faced employee backlash when it insisted on returning to a predominantly office-based work structure, resulting in public resignations and bad press. According to an article by The Verge, the company had to deal with resignations from several high-profile employees who cited the rigid RTO policy as a critical factor in their departure. Similarly, companies like JPMorgan Chase encountered hurdles when their initial RTO policies were met with discontent, leading to a re-evaluation of strategies to better accommodate employee demands. Multiple news outlets reported on the tensions this friction created between management and employees, highlighting the delicate balance organizations must strike to avoid such controversies. These examples underscore the potential pitfalls of an inadequate RTO strategy: They not only disrupt operations internally but can also tarnish an organization’s external reputation. The Risks of RTO Missteps The pressure to “get it right” is immense because the downside of errors is particularly stark: Employee Dissatisfaction and Turnover: A mismatched RTO strategy can fuel dissatisfaction, prompting a mass exodus of talent—a risk that’s especially heightened in today’s competitive job market. Operational Inefficiencies: Inaccurate planning can lead to poor space utilization, thereby increasing operational costs and diminishing productivity. Public Relations Challenges: In the age of social media and 24-hour news cycles, a poorly managed return to office can quickly turn into a PR crisis. Health and Safety Concerns: Failing to consider updated health guidelines or employee comfort levels can pose real safety risks. How One Model Powers Data-Driven RTO Success The challenges of RTO planning demand a strategic, analytics-driven approach rather than guesswork. One Model acts as your essential command center for HR, finance, facilities, and operations teams, simplifying how you manage and leverage scattered data, ensuring that decisions are grounded in reality, not assumptions. Integrating Disparate Data Sources for a Unified View One Model excels at consolidating a wide range of data from multiple functions—bringing the data you have, whether it be time-tracking systems, attendance logs, badge usage data, or employee sentiment, into a single cohesive view accessible by all of the teams, but with role-based security to ensure data privacy. This central hub facilitates smooth, informed decision-making processes for finance, facilities, and HR departments, ensuring alignment across all stakeholders. Actionable Insights to Craft an Effective RTO Plan Through advanced analytics and intuitive dashboards, One Model can provide a detailed, accurate picture of your workforce’s dynamics. With customizable dashboards tailored to track key metrics such as attendance trends and space utilization rates, you gain the clarity needed to design policies that meet both business objectives and employee needs. AI-Powered Predictive and Proactive Management Our predictive analytics capabilities can allow you to forecast trends. By understanding potential future issues—whether it's employee turnover risks, facility overcrowding, or engagement declines—you can make proactive adjustments to your RTO strategy, ensuring minimal disruptions and fostering higher levels of employee satisfaction. Comprehensive Support for Successful Execution Beyond just providing a platform, One Model offers expert guidance to help integrate and interpret your workforce data effectively. From automating reporting processes to identifying trends that shape long-term policies, our tools empower you to build a sustainable RTO strategy that adapts to evolving needs. By leveraging One Model’s analytics capabilities, organizations gain the ability to create structured, data-driven RTO plans that align with operational goals while prioritizing employee well-being and retention. The Ripple Effect of a Successful RTO Strategy By effectively leveraging One Model’s capabilities when implementing RTO, you stand to gain numerous organizational benefits: Reduced Risk: Don’t get caught without data when it comes to reporting on progress or making decisions related to RTO. Sensitive topics require careful attention to details. Improved Employee Engagement: A well-crafted RTO strategy acknowledges and respects employee preferences, which can enhance engagement and retention. Optimized Space Usage: Strategic data insights allow for better use of facilities, reducing overhead costs while improving the workplace experience. Bolstered Corporate Image: Successfully managing the return to office showcases your organization as thoughtful and proactive, boosting its reputation internally and externally. The Path Forward with One Model Navigating the complexities of a Return to Office strategy might seem daunting, but with One Model’s comprehensive data integration and analytics platform, you’re equipped to overcome challenges with confidence. Our tools and expertise help you build a strategy that supports business goals, employee satisfaction, and efficient facility usage all at once—no matter where you stand in your RTO journey. Are you ready to take the next step in your RTO journey? Reach out to schedule a demo, and discover how our dashboards and data engineering solutions can illuminate your path forward and ensure a smooth transition back to the office. Together, we can translate complex data into actionable strategies that foster a resilient and adaptable organizational environment. This comprehensive approach not only positions you to avoid common pitfalls but empowers you to make informed, strategic decisions that bolster both your workforce and facilities management. Trust One Model to guide your organization toward a successful RTO strategy that meets the demands of the present and sets the foundation for future operational agility. See how One Model can support your unique approach to RTO. Request a demo of One Model.
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Featured
4 min read
Steve Hall
When it comes to People Analytics, the most valuable tool is one that lets you to ask the right questions and explore solutions. Canned insights can't answer the real questions you need to answer. Recently, during a demo with a prospective client, a question came up that perfectly illustrates how One Model is a platform built for problem-solving rather than just offering irrelevant canned insights. The Situation: A Forecasting Challenge The scenario began with a focus on Female Representation metrics, specifically forecasting whether the organization was on track to meet its diversity targets for women. The forecast feature showed trends for different job levels, and while representation looked promising for some levels, there was a noticeable downward trend for the executive level. Naturally, the prospect wanted to know: Why is this happening? This was not a question with an easy, pre-packaged answer. Instead, it required a deeper dive into the data—an approach that highlights One Model's value as a tool for discovery and insight generation. Digging Deeper: How We Tackled the Problem To address the question, we demonstrated how to use filters and visualizations to isolate and explore the data. Here's how it unfolded: Applying Filters: We filtered the data by job level and gender to focus specifically on female executives. From there, we looked at key metrics like net hiring trends and termination rates. Identifying Patterns: The data revealed a significant drop in representation between 2023 and 2024, which appeared dramatic due to the auto-scaling of the graph. Exploring Causes: By clicking through different visualizations, we identified that termination rates, particularly "other" terminations, were higher than expected. Using One Model's hotspot maps, we further pinpointed the specific business unit and region where the issue was most acute. Forming Hypotheses: Using this information, we leveraged One Model's built-in predictive AI capabilities to identify potential turnover drivers and develop actionable insights. Flexibility Matters This scenario underscores something critical about One Model: We don’t solve all your problems; we give you the tools to solve them. Other platforms that rely on rigid, canned use cases might struggle in this situation; no solution can offer pre-built analyses for all possible scenarios. Without a pre-built guide addressing their specific issue in this specific organization, the user will hit a wall. One Model, by contrast, enables users to dynamically filter, explore, and analyze data to uncover answers. Why This is Critical for People Analytics This scenario demonstrates the real-world challenges of People Analytics. Insights are rarely handed to you on a silver platter. Instead, they require a combination of curiosity, exploration, and judgment —qualities not even AI will bring to the table. While some HRBP-level professionals might not engage in this level of analysis, advanced People Analytics practitioners understand that solving complex, niche problems—like representation trends at a specific level—requires more than surface-level data. The One Model Advantage Here’s why One Model is different: Speed: Because One Model creates a unified single source of truth for your organization, you can explore complex interactions without having to manually manipulate data, saving you time. Flexibility: You’re not limited to prebuilt Storyboards or canned content. You can adapt and dig into unique questions in real-time, even in situations where you need to create new metrics to explore an issue. Depth of Insights: By enabling dynamic exploration, One Model allows for nuanced and complete answers that out-of-the-box solutions can’t deliver. The takeaway from this use case is simple: Good insights require effort. Platforms that promise quick, prebuilt solutions often oversimplify problems or deliver incomplete answers. One Model’s strength lies in empowering users to dig deeper and uncover real insights—even when the questions are complex. With One Model, you’re not just using a People Analytics platform—you’re solving real problems.
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Featured
3 min read
Kelley Kirkpatrick
Workplace gender equality is a critical focus for Australian employers, supported by initiatives like the Workplace Gender Equality Agency (WGEA). Established to promote and improve gender equality in workplaces, WGEA regulations require organisations with 100 or more employees to report gender data across six gender equality indicators. These indicators include key aspects such as pay equity, workforce composition, and representation in management roles. The reporting process is detailed, requiring a combination of point-in-time employee data and aggregate metrics spanning the reporting year. While this mandate enables organisations to reflect on and address gender equality, the process itself is challenging. Teams often spend weeks—or even months—sourcing data from disparate systems, aligning it with WGEA’s strict criteria, and meticulously validating it. However, with the right tools, this complex task can be streamlined with One Model. Tackling the Challenges of WGEA Reporting For most organisations, WGEA reporting is not just about compliance—it’s about leveraging the reported data to foster deeper insights into workforce gender equality. Yet, the process is notoriously cumbersome. Compiling detailed employee information, annualised salary data, and metrics such as leave and movement patterns often requires manual intervention and significant cross-team collaboration. This can lead to inefficiencies, inaccuracies, and limited time to analyse the results. But what if the data collection and validation process could be automated? This is where One Model comes in. Automating WGEA Reporting: How One Model Makes it Simple The One Model People Analytics platform transforms the arduous WGEA reporting process into a streamlined, automated operation. By centralising workforce data, aligning it with WGEA’s submission templates, and enabling robust validation, One Model allows organisations to achieve compliance efficiently while focusing on what matters most: understanding and acting on the insights derived from the data. Customer Spotlight An Australian customer recognised the platform’s potential to simplify their WGEA reporting. Some of the required workforce data was already housed in One Model, but integrating the full dataset—including annualised salary details and movement metrics—was the next step. By ingesting and modelling all the necessary data, One Model provided the customer with: A single source of truth: Data was centralised, validated, and securely accessible to analysts across various teams. Streamlined workflows: Automation reduced the need for manual data manipulation and cross-referencing. Tailored insights: The customer leveraged One Model’s analytics capabilities to create Storyboards and executive reports, turning raw data into actionable insights. The outcome? The customer not only completed their WGEA submission in one day instead of five, but also unearthed valuable insights for their leadership team, who were impressed by the quality and depth of the analysis. Beyond Compliance: The True Benefits of Automating WGEA Reporting Automating WGEA reporting increases efficiency and confidence while shining a light on what’s going well and areas for improvement. Efficiency: Teams save weeks of effort through automation, ensuring submissions are accurate and on time. Data Integrity: By centralising data and applying consistent validation, organisations can trust their numbers. Insights-Driven Culture: Once the reporting is complete, the data can be repurposed to drive conversations around workforce planning, pay equity, and diversity initiatives. With One Model, you can transform a complex compliance process into a streamlined, automated workflow. This not only saves time but also provides valuable insights that drive meaningful progress in workplace gender equality across the country. Ready to simplify your WGEA Reporting?
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Featured
14 min read
Phil Schrader
As a people analytics leader, you’re going to be confronted with some not-so-simple, horribly open-ended questions: “Hey, so what do you want to measure?” Where should we start?” or… “What HR dashboards should we build?” Perhaps these words have been uttered by a well-intentioned business analyst from IT, peering at you from behind a laptop, eager to get your items added into an upcoming sprint before all their resources get tied up with something else. What do you say? Something really gnarly and fancy that shows your analytic savvy? Something that focuses on a key issue confronting the organization? Something basic? Fear not. In this blog post, we’ll walk you through eight essential people analytics dashboards. You should be able to get the HR data for all of these from your core HRIS or HCM solution, even if they’re in different modules and you have to combine it into one dataset. The key performance indicators (KPIs) in these views will give you the highest impact: Headcount Metrics Dashboard Span of Control Dashboard Employee Turnover Dashboard or Attrition Dashboard Talent Flow Dashboard Career Growth / Promotions Dashboard Diversity (DE&I) Dashboard Employee Tenure Dashboard …see below… 1: Headcount Metrics Dashboard Headcount metrics are the foundation of people analytics. Headcount speaks volumes. Trend it over time, break it out by key groupings, and you are well on your way to doing great people analytics. Here’s an initial view that captures the basics. Here’s what’s included in this dashboard so you can get a handle on headcount. In the upper right, you’ve got what I call the “walking around the number”. It’s not anything that will help you make an informed decision on anything. But this is the stat that you would feel embarrassed if someone asked you and you didn’t know off the top of your head. Here it’s the total number of employees as of the current point in time. (EOP is shorthand for End of Period. Be precise in how you define things. More on this at the end.) Next, you’ll want to see the headcount trended over time. Here we have a monthly trend paired with the same period last year. Boom. Now you can see how things are changing and how they compare with the previous year. Also, these two visuals are a great test run for your existing reporting and analytics capabilities. In the bottom right, here you have headcount broken out by org unit (or business unit, or supervisory org for you Workday types). Here you want not only the total counts but ideally a stacked column view so you can see the proportion of contractors, part-time, co-op, or other employment types. Different orgs might get their work done in different ways. You should know the differences. Finally, a map view of headcount by geography. It’s not a basic visual, but it has certainly become essential. Things happen in the world. You need to know where your workforce is so you can quickly estimate the impact and plan support. In just the past two years, employees have been impacted by wildfires, heat domes, political unrest, blizzards, cold snaps, flooding, and, of course, COVID. Geo maps have officially gone from fancy visual to essential view. 2: Span of Control Dashboard I’m going to change things up a bit by elevating the span of control to the second slot on this list. Don’t worry. We dive into attrition and representation later in the article. As a people leader, you’ve got to maintain some perspective on how efficiently your workforce gets work done. There are many ways to do this. You could calculate the total cost of your workforce. You could align those costs against revenue over time. By all means, do that. But this list is also there to help you get started. With just the data from your core HCM / HRIS system, your team should be able to show you the span of control and organizational layers. These metrics always remind me of stepping on a scale. If your span of control is ticking down, you’re getting less lean. If you’re adding more layers, your internal coordination costs are going up. There could be good reasons for this– but there sure as heck can be bad reasons for this. Here you’ll find your key Span of Control Metrics, your trend over time, and your layers and org units visualized. The real killer metric – if you’ve got the stomach for it – is a simple list of the number of managers in your organization that have only one or two direct reports. Use these views to keep your talent management processes grounded in business reality. If your existing team/technology can’t produce these views then shift them back. 3: Employee Turnover Dashboard or Attrition Dashboard Ok, we can’t go any further without employee turnover. Attrition if you’re feeling fancy. Turnover is the strongest signal you get from your workforce. Someone worked here and– for one reason or another– it didn’t work out. Changing jobs and firing an employee are both major events. Your workforce is telling you something and you need to listen to help you with employee retention. Here’s a basic view to get you started. Again, get your rolling 12-month termination rate up at the top and trend it out with the previous year for context. Below that, you see a breakout of voluntary and involuntary termination rates. Then, you can see breakouts by business unit, location, and org tenure groupings. Now with a glance, you can see how turnover rates are changing, where they are high, and whether it’s you or the employee forcing the change. Learn more how to calculate the cost of turnover. 4: Talent Flow Dashboard Once you’ve got a turnover view squared away, you can move into broader views of talent movement within your organization. Here’s a high-level talent flow view to get started. It leads off with a consolidated view of hires, terms, and net hires trend over time. I love this view because it lends itself to discussions of churn and the cost of turnover. The top area (green) shows external hires. The bottom (red) shows exits/terminations. The dark bars show the difference: net hires. The big question. How much of that time and money that you put into recruiting is just to replace the people who leave the company? A great variation on this view is to limit it to women or underrepresented groups. Are you working hard to attract these demographics, only to have them leave because they don’t find the organization to be a fit for them? We’ll get to more workforce representation views below. Next to the Net Hire Trend, you can mix in a growth metric and a helpful breakout by “business unit, so you can keep an eye on what segments of the organization are growing/shrinking. Are they the ones you expect? Later when you bring in data from other systems like learning, this view can be a place to collaborate with the learning team to answer questions like: Are you adding more employees, when you could be upskilling? Finally, get a solid crosstab view of promotions or movements. This will help you optimize talent development and answer questions like: Do people move from function to function? If so, what are the common paths? What paths don’t exist? Should they? 5: Career Growth / Promotions Dashboard After you get the big picture on movements, dig into promotions. In my mind, the movement and span of control views are about what the organization is experiencing. Promotions put you more in the mind of your employees and what career opportunities look like in your organization. I’ve added two of our key metrics to the top of this one. What’s the rate at which people get promoted and how long is the typical wait for promotion? Once you know the typical (average or median is fine) wait time, keep your ears out for high potential / high performers who have run past that mark. They’re probably keeping a rough estimate of that metric in their minds as well. Below that are two breakout views. The first one - “Manager Hires vs. Promotions to Manager” - is meant to look at a key milestone in career growth. I’ve used promotion to manager, but you might have unique ones. Then for each business unit, I’ve compared the number of promotions into that key group with the number of outside hires in that group. Are you growing your own leaders (or another key group)? If not, why? Filling out the bottom row is the “Termination Rate and Headcount by Time since Last Promotion” view. Look for two things here: 1) Do people leave if they don’t get promoted? 2) Do people leave right after they get promoted? 6: Diversity (DE&I) Dashboard It’s past time we brought in views of the diversity, equity and inclusion (DE&I) in your workforce. Many of the views in the dashboard below are split out versions of the metrics introduced above. Above is a sample diversity dashboard using male / female breakouts. Use this as a template for other representation breakouts including ethnicity, gender identity, age, etc. Any of these views could be modified to incorporate multiple, rather than just two, groupings. The top bar shows activity differentials over time. Hires are done simply as counts. Do you hire more men than women? Are promotions and terminations handed as rates to monitor for disproportionate outcomes?, i.e. are men promoted more often than women? The second row shows representation by key grouping in stacked horizontal bars. I like organizational layer and salary band to show if high career outcomes are disproportionate. I’d recommend the inclusion of tenure as well, however. If your organization had a history of disproportionate staffing, you will get a clue in this view. That could explain why today’s initiatives have not yet balanced out outcomes in level or pay. Or differences in tenure might be explained by differences in termination rates, depicted directly above in this view. This is a multifaceted issue. 7: Employee Tenure Dashboard Confession. I love tenure. I’ve come of age in my career amid data telling me that I’ll work for something like 11 companies before I retire. And, to be honest, I’ve done my share of career hopping. But it turns out that when you stick around somewhere, you learn things. You make connections with your co-workers. Employee tenure represents the accumulation of invaluable knowledge and connections that help you measure the value of your human capital. Next to average tenure, this dashboard shows the total accumulated workforce tenure in years. While not exactly a “walking around number,” you can use this to impress your fellow leaders into thinking about your workforce like the treasured asset it is. “Hey, our team has x millennia of accumulated experience!” Rounding out this view is a sorted view of positions or job titles with lots of accumulated experience as well as a stacked trend over time to see how tenure groupings are changing. 8: Dashboard Definitions and Details This final section is not a specific dashboard suggestion. Rather, it’s intended as a sobering reminder that none of the dashboards above will make an impact in your organization if you can’t explain your logic and build trust in your data. I like to build little glossary style views right into the dashboards I create. For example, at the bottom of our standard attrition storyboards, I’ve added breakouts showing which termination reason codes are included as voluntary and which are involuntary. Next to my glossary, I’ve created a table that breaks out the subcomponents of turnover rate, such as total headcount and days in period. I like to include at least one leap year for a bit of showmanship. “Look, I’ve even accounted for the fact that 2020 had 366 days, so back off.” Ready To Learn More? Get All Your Questions Answered One-on-one. Finally, if your security models and technology support it, drill to detail. This is the number one, all-time champion feature of people analytics. Click on headcount, terminations, whatever and see the actual people included in the data. Bonus points for adding the definition and “bread crumb trail” for metrics that build off of other metrics. Below is a view of how we do that in One Model. If you’d like to see these people analytics dashboards in action or learn more about people analytics software for your organization, reach out to us!
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Featured
6 min read
Dennis Behrman
Anyone who analyzes data knows there's always a need to drill into reports to answer the questions that pop up. One Model is the only people analytics platform that allows you to drill into literally anything and everything, as if your siloed enterprise data sources were a single source of truth. Working with Metrics, Dimensions, and Time Explore is a powerful tool designed to help you perform powerful ad-hoc analysis on your One Model storyboards, reports, and visualizations. Here's a quick look at how the Explore tool works. Select Your Metrics Metrics are quantifiable measures used to understand the results or outcomes that you observe in your business. The Explore tool presents the entire list of metrics available to you based on your organization's metrics library and the access permission associated with your user profile and your group/team membership. You can add and remove metrics by dragging and dropping them from your metrics library to your metrics selection fields. Your metrics library contains all of the direct and derived values that are used to tell the stories hidden within your data. To learn more about how metrics are established in your One Model instance, check out this article or this video. (You may need to login with your One Model account to view Help Center content.) Pick Your Dimensions Dimensions are attributes or categories by which data can be grouped. Dimensions organize data into meaningful sections for comparing. For example, in a turnover report, dimensions could include rank, business unit, performance rating, and so on. To sub-group your data even further, you might want to add pivoted dimensions, which help you compare groups by more than one attribute. One Model's Explore tool allows you to drag and drop any number of dimensions into your report to see an analytical picture with more detail. Mind Your Time Model Time modeling is perhaps the trickiest and most important activity that happens on the One Model platform. Since time is a constant, your data analysis depends on the most comprehensive coverage of observable and measurable events for analyzing data over different periods. In theory, time subdivides infinitely. But in practice, most analysts and decision makers prefer to view time within a standard set of available lenses such as days, months, quarters, and years. But since months, quarters, and years can have different numbers of days within them, it is critical to getting time right to understand your business in the most accurate way possible. It's important for these cumulative measures to "add up" or "sum to the right number" when aggregated (or drilled through) at scale. It's equally important for data about events to be captured at various time intervals. For example, a group of employees who are currently high-performing rock stars may inform a decision today about high performers. But in reality, many of those rock stars may have been groupies in the past. One Model has no peer when it comes to the most effective application of time series analysis. Here's why. I created the Sankey diagram below with fake data to show a point. Observe how none of the more than 4000 high performers at the end of 2021 remained high performers at the end of 2023. So any analysis conducted in 2024 that uses the pool of 2023's high performers to infer multi-year trends would be an incomplete and possibly flawed analysis of the company's high performers. Most other approaches don't account for the question of "how it looked" in the past. Explore Explore's Unrivaled Speed to Insight Your organization needs the most accurate and current information to make the most informed talent decisions. The Explore tool is one of many keys to telling the stories within your data. Approachable & Intuitive One Model's Explore tool features a professional-class user interface designed to cater to both casual and highly technical users. This balanced design ensures that casual users can easily navigate and utilize the tool without feeling overwhelmed, while technical users have access to advanced functionalities and customization options. The interface’s adaptability fosters a productive environment for all users, enabling them to swiftly uncover insights and make data-driven decisions. Consistent Metrics Definitions Paired with Flexible Dimensional Pivots The Explore tool ensures the consistent application of organization-wide metrics definitions and offers the flexible application of dimensions, enabling users to tailor analyses to their specific needs. By presenting a cohesive and accurate picture of organizational data, the Explore tool enables faster and more reliable insights, accelerating the overall time-to-insight. Better, Faster Insights to More Decision-Makers Around Your Organization One Model's Explore tool excels in its ability to deploy sound insights to any team or decision maker within an enterprise. By seamlessly integrating with various data sources and offering robust reporting features, the tool ensures that actionable insights are readily accessible to all relevant stakeholders. No other people analytics platform drives more data-driven decision-making better than One Model, thanks to tools like Explore, which empower organizations to make informed decisions quickly and efficiently. Essential Questions to Ask When Selecting an AI-Powered HR Tool Learn the right questions to ask to make the right decisions as you explore incorporating AI in HR.
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Featured
9 min read
Steve Hall
In organizational management, span of control plays a key role in defining how streamlined and agile a company can be. Understanding the Span of Your Manager-to-Employee Relationships At its core, span of control refers to how many people a manager or supervisor directly oversees. The optimal number depends on a variety of factors including job type and job level, and most organizations set targets using rules of thumb and experience. The span of control metric helps determine if the organization is structured appropriately, with too large a span of control leading to ineffective management and manager burnout, and too small a span of control leading to inefficiency. To calculate your average span of control, divide the total number of direct reports by the total number of supervisors. For instance, if there are 100 direct reports to 10 supervisors, the average span of control is 10. Exploring the 2 Types of Span of Control In the context of organizational structure, span of control is classified as either wide or narrow. Each type presents unique advantages and challenges, so it is not a one-size-fits-all proposition. The choice between a wide and narrow span of control depends on various factors, including: The nature of the organization's work and its structural preferences Industry norms Complexity of tasks Managerial capacity Job level Both wide and narrow spans have their place, even across departments and job levels within an organization. The key is to find a balance that maximizes efficiency, promotes effective management, and aligns with the organization's overall goals. Wide Span of Control In a wide span of control, a single manager supervises many subordinates. This structure is often seen in companies with flat organizational structures, with fewer layers between the top and bottom levels and a shorter chain of command. Wide structures are also more common at lower levels in organizations. Features: Low supervision overhead costs Prompt response from employees Improved coordination Suitable for repetitive or low-skill tasks Advantages: Encourages delegation of authority Facilitates better manager development Ensures clear policies Promotes autonomy among subordinates Fewer levels in the managerial structure Cost-effective Suitable for larger firms and repetitive tasks Well-trained subordinates Disadvantages: Risk of supervisors being overburdened Potential loss of control for superiors Need for highly qualified managing employees Hindered decision-making Increased workload for managers Unclear duties for team members Confusion among subordinates Management challenges in large teams Reduce manager-employee interactions Narrow Span of Control Conversely, a narrow span of control is characterized by a manager overseeing a smaller number of subordinates. This approach is prevalent at the top or middle management levels, especially when tasks are complex and require more support from superiors. Features: Ideal for new managers to gain supervisory experience Beneficial for managing remote or diverse teams Necessary for jobs requiring frequent manager-employee interactions Useful in new operations and for employee training Advantages: Easier communication and management in small teams High specialization and labor division Better opportunities for staff advancement Direct supervision by managers over each subordinate Effective communication between subordinates and managers More layers in the management structure for easier control Improved management control and effective supervision Disadvantages: The potential of stifling of employees' creativity due to excessive manager control Slower decision-making in extended hierarchies Limited cross-functional problem-solving Higher costs due to more managerial positions Delays in information transmission and decision-making The Challenge of Manual Span Management Effective span management is a balancing act, nearly impossible to achieve without technology. Strong span management requires examining spans vertically, horizontally, and over time; this creates a complex situation that is not easily or effectively handled without well-orchestrated data. Span Management Impacts A high manager-to-employee ratio might lead to insufficient attention to each team member, potentially affecting employee development and performance. Conversely, a low ratio could indicate inefficiencies and a bloated organizational structure that erodes profitability. Span Management in Different Industries Span management requires a tailored approach, as the ideal ratio varies by industry and job function. In labor-intensive industries, a higher ratio is often more manageable, whereas in knowledge-based sectors, a lower ratio might be preferable to ensure quality supervision and mentorship. Seasonal Staffing Certain industries or departments may experience fluctuations in workload at different times of the year, necessitating a flexible approach to span management. During peak seasons, managers may need to handle more direct reports or delegate responsibilities more effectively, while in slower periods, they may focus on training and development. A dynamic strategy can maintain efficiency without compromising the quality of supervision or employee growth. The Role of HR and Analytics in Span of Control Human Resources plays a critical role in monitoring and adjusting the span of control. HR can track this metric in real-time by using analytics tools to help maintain an optimal balance. People analytics software like One Model offers capabilities to analyze and adjust management span of control across various levels and departments, ensuring organizational efficiency and employee satisfaction. Data-Driven Span of Control Analysis Span of control analyses help organizations identify optimal structures and make precise staffing decisions in response to changes over time. Using people analytics tools, HR can dissect span of control across different dimensions such as department, geography, and manager level. Analysts should examine span of control: Both vertically and horizontally, and over time Relative to gross and net revenue Relative to employee-related outcomes such as engagement and retention It is not practical or effective to evaluate and manage span of control manually; this is an area where robust data can be used to drive effective decision making and optimize outcomes. However, to kickstart this analysis, even basic data from a core HCM or HRIS system can be enlightening. Metrics like span of control and organizational layers are akin to stepping on a scale — they provide immediate feedback on the state of your organizational structure. Within this discussion, key metrics such as span of control trends and visualization of layers and organizational units are invaluable. One crucial metric, for instance, is the number of managers with only one or two direct reports. This simple statistic can reveal much about the nature of your management structure. These insights are essential for keeping talent management processes aligned with business reality. If your current team or technology cannot readily provide these views, it may be time to reconsider your approach and tools. It took our team under 5 minutes to find the ratio between managers and non-managers. How long will it take your team to answer Question #38 on the People Analytics Challenge? Setting Targets for Span of Control Setting the right targets for span of control involves considering various factors, including industry norms, organizational structure, and management levels. A higher ratio may be effective for frontline or production roles, while senior management might require a lower ratio to strategize and lead effectively. Organizations often set their span of control targets based on industry benchmarks, aiming for a median that balances efficiency and managerial attention. Variations in span of control targets can be set for different organizational units, such as contact centers, corporate offices, and field operations. But the best organizations strive to surpass industry norms and link span of control metrics with outcomes of interest such as efficiency, profitability, employee engagement, and voluntary turnover. By doing so, they can optimize span of control to drive desired outcomes. Mastering Span of Control with One Model Understanding and effectively managing the span of control is crucial for any organization seeking to optimize its structure for maximum efficiency and employee development. With One Model, organizations can gain the insights needed to make informed decisions about their management structures, ensuring they are well-equipped to adapt to changing market demands and internal growth dynamics. One Model also supports next-level span-of-control analytics by allowing organizations to link span-of-control with operational metrics, moving the organization from descriptive analytics into the realm of optimization. After all, blindly following industry benchmarks won't ensure optimization within the organization. One Model is equipped to support optimization through the modeling core HRIS data, employee engagement data, employee performance data, and operational data related to production, safety, and financial outcomes. If you aren’t using a tool to measure and track span of control, you’re missing out. If you aren’t linking span of control to business metrics that matter, you’re really missing out.
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10 min read
Phil Schrader
Succession planning is a strategic HR function. Its purpose is to map out key positions in the organization and identify potential successors who are (or will be) ready to step into those key positions when they become vacant. Organizations with effective succession planning programs are more resilient. When a critical role is vacated, they already know who can step up and fill the role. Succession management also boosts employee motivation because they can see a path forward within the organization. Strategic HR activities like this go hand in hand with People Analytics. In order to effectively plan for the future, you need clarity around what you want to accomplish and whether you are improving.. Metrics help you create that clarity. How many of our plans have successors? How ready are they? What’s our bench strength? Are our successors representative of the wider talent pool? So let’s dig in and talk about that union of strategy and analytics. How do you measure your succession plan readiness, and what are the key metrics for succession planning and leadership development? Measuring Succession Planning First, here is an "oldie but a goldie" video walking through the succession planning process. Second, here are the key elements of measuring succession planning. Scope: What are the critical roles that require identified successors. Ideally, your program covers all non-entry level roles, but time is scarce so prioritize. Coverage: Given the scope above, do you have plans set up for all critical roles? Readiness: Have you evaluated each successor’s readiness for each plan they are in? Remember that one person might be a successor for multiple positions, and they might be more ready for some roles than others. Readiness can be categorized in high-level groupings. For example, “Ready Now”, “Ready in < 1 Year”, and “Ready in > 1 Year”. Bench Strength: Given completeness and individual readiness, how strong is your bench? Can you fill all critical roles? Is it still strong if you net out the successors, i.e. account for people who are selected in multiple plans. Diversity: Does your plan make full use of the available talent in the organization? Have historical tendencies caused you to overlook strong successors because they have different backgrounds and experiences from the incumbents? Will your leadership ranks become more or less diverse when your plans move into action? It took me 44 minutes and 56 seconds to pull together the metrics above to answer Question #25 from the People Analytics Challenge. Let me show you the full Succession Dashboard. Connect with us today! Key Metrics (with Definitions) Here are the key metrics you can use to address the strategic questions above. Percent of Leaders with a "Ready Now" Successor Bottom line. What does your successor coverage look like right now? Count up the number of leaders who have a successor that is ready now. Divide that count by the total number of roles in your succession planning program (see Scope above). For example, if you have 10 positions that you’ve identified as needing a successor and you have a ready now successor for 7 of those roles, then your percentage of leaders with a ready now successor is 70%. Now flip that number around and say to yourself, “Ok if one of our really key people left today, there’s a 30% chance that we’d have no one ready to take over that position.” Don’t let that be you. Use the detailed data from this calculation to create an operational list of the positions without a successor. Then work the list! Gross and Net Bench Strength The first metric tells you how ready you are to move on from one key person. Gross and Net Bench strength give you a sense of how resilient your organization would be in the face of multiple changes. Technical note: These calculations will assume that your program has set out to have 3 successors identified for each key role. Gross Bench Strength: Total successors divided by total successors needed, ignoring whether the successors are used in multiple plans. Net Bench Strength: Total successors divided by total successors needed, only counting each successor once. i.e. taking into account whether the successors are used in multiple plans. So let’s look at these calculations together. Let’s say you have 10 key roles and you have determined that you should have 3 successors for each. That means your total successors needed is 30. Now go through your plans and add up all the listed successors. Perhaps you have 26. That means you have 26 successors out of the 30 you need making a gross bench strength of 87%. Awesome. Ok. Now let’s get more nuanced. Let’s deduplicate the list of successors. Maybe there are 2 high potentials in that pool who are listed on all 10 plans. Extreme example but useful for our illustration. That means that there are really only 8 unique successors. That makes your net bench strength 8 / 30 or 27%. This difference between a gross bench strength of 87% and a net bench strength of 27% tells you that you have good immediate coverage but low resiliency. You can effectively respond to 1 or 2 people leaving, but beyond that, your bench will be depleted. Incumbent vs. Successor Diversity % Generally speaking, today’s organizations are looking to take full advantage of their available talent by ensuring that traditionally underrepresented groups are considered for advancement. A simple way to check on this progress is to compare the representation numbers of your incumbents to the representation of your successors. Let’s suppose the current pool of employees in key roles is 10% diverse while your pool of successors is 20% diverse. This is a signal that your succession planning process will contribute to greater diversity in your key positions in the future. Remember to align your successor diversity metrics with the key groupings defined by your organization’s DE&I program. These could include gender, ethnicity, or other employee attributes. Promotion Rate and Time on Bench If you make progress on the metrics above, then you’ll be leading your organization into a more resilient future. Good job! But remember, resilience is great for the organization, up to a point. Remember that the high potential employees in your plans have their own career goals. If they feel stuck on the bench, they’re likely to find their next role outside the company. If you are so resilient that you could back up all your key leaders for the next 25 years, then you are fooling yourself. Those high potential employees listed on your plans will be long gone by then. So keep an eye on the promotion rate of your internal candidates over time. (Number of promotions / average headcount). They’ll be making their own estimates as well. Alternatively, you might calculate the time on bench for your successors. When one of your successors leaves the company, check to see if they were on the bench too long. Or just ask them in your exit interview. Pay particular attention to the time on bench for your diverse successors. It’s not enough to say, “Look at how diverse our bench is!” if those candidates are continuously passed up for the next big job. Using Successor Metrics to Support People Strategies The metrics above are just a starting point. The key to strategic HR and people analytics is a willingness to ask important questions and use data to answer those questions. Ideally your succession planning process fits into a larger talent management vision that is supported by a wide range of interconnected datasets and measures. For example, you may be ready to fill key roles with external candidates. Your time to fill for similar positions will help you know if that’s a reasonable backup strategy. Alternatively, your employee pulse survey data and turnover by attrition analyses may indicate that you are having a hard time retaining diverse employees. Perhaps this will link back to the time on bench calculations discussed above. You are unlikely to find meaningful answers in a single data source, so invest in building the right underlying data architecture to connect data from succession plans, core HR, recruiting, engagement, compensation, and other workforce data. At the same time, keep the strategic focus in mind so that you’re not just doing analytics for analytics sake. Come back to the important questions like, “If we lost someone in a key role today, what’s the percent chance we’d be totally flat footed with no idea how to replace them?”
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Featured
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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Featured
10 min read
Joe Grohovsky
John Sumser, one of the most insightful industry analysts in HR, recently wrote an article providing guidance on the selection of machine learning/AI tools. That article is found HERE, and can serve as a rubric for reviewing AI and predictive analysis tools for use in your people analytics practice or HR operations. Much of our work day is filled with conversations regarding the One Model tool and how it fits into an organization's People Analytics initiative. This is often the first practical exposure a customer contact has using Artificial Intelligence (AI), so a significant amount of time is invested in explaining AI and the dangers of misusing it. Good Questions to Ask About Artificial Intelligence Solutions - And Our Answers! Our product, One AI, delivers a suite of easy-to-use predictive pipelines and data extensions, allowing organizations to build, understand, and predict workforce behaviors. Artificial Intelligence in its simplest form is about automating a decision process. We class our predictive modeling engine as AI because it is built to automate the decisions usually made by a human data scientist in building and testing predictive models. In essence, we’ve built our own automated machine learning toolkit that rapidly discovers, builds, and tests many hundreds of potential data features, predictive models, and parameter tuning to ultimately select the best fit for the business objective at hand. Unlike other predictive applications in the market, One AI provides full transparency and configurability, which implicitly encompasses peer review. Every predictive output is not only peered reviewable within a given moment of time but also for all time. This post will follow a Q&A style as we comment on each of John’s 12 critical questions to ask an artificial intelligence company. 1) Tell me about the data used to train the algorithms and models. Ideally, all data available to One Model is used for feeding the machine learning engine - the more the better. You cannot overload One AI because it is going to wade through everything you throw at it and decide which data points are relevant, and how much history it should use, and then select, clean, and position that data as part of its process. This means we should feed every single system we have available into the engine from the HRIS, ATS, Survey, Payroll, Absence, Talent Management - everything and the kitchen sink as long as we’re ethically okay with its potential use. This is not a one size fits all algorithm; each model is unique to the customer, their data set, and their target problem. The content of training data can also be user-defined. Users define what type of data is brought into the modeling process, choosing which variables, filters, or cuts will be offered. At any time if users want to specify how individual fields will be treated, they have the ability to do so with the same types of levers as you would have in creating your own model externally. 2) How long will it take for the system to be trained? The scope of data and the machine learning pipeline determine training time. The capacity to create models is intrinsically available in One AI and training can take anywhere from 5 minutes to 20+ hours. For example, we automatically schedule re-training a turnover prediction model for a 15k employee-customer in the space of 45 minutes. 3) Can we make changes to our historical data? Yes, data can be set to be held static or use fresh data every time the model is trained. One AI acts as a data science orchestration toolkit that automates the data refresh, training, build and ongoing maintenance of the model. Models are typically scheduled to potentially refresh on a regular basis e.g. monthly. With every run extensive reports are created, time-stamped, and logged so users can always return to summary reports of what the data looked like, the decisions made, and the performance of the model at any given time. 4) What happens when you turn it off? How much notice will we receive if you turn it off? One AI models and pipelines are completely persisted. They can be turned on and off with no loss of data or logic. We are a data science orchestration toolset for building and managing predictive models at scale. Is AI being offered in a solution for your HR Team? Download our latest whitepaper to get the questions you should ask in the next sales pitch when someone is trying to sell you technology with AI. 5) Do we own what the machine learned from us? How do we take those data with us? Yes, customers own the results from their predictive models, and those results are easily downloaded. Results and models are based upon your organizations data. One Model customers only see their own results, and these results are not combined with other data for any purpose. All the decisions that the machine made to select a model are shown and could be used to recreate the model externally as well. 6) What is the total cost of ownership? Predictive modeling, along with all features of our One AI product, are inclusive within the One Model suite subscription fee. 7) How do we tell when the models and algorithms are “drifting”? Each predictive model is generated and its results are fully transparent. Once a One AI run is finished, two reports are generated for review: Results Summary – This report details the model selected and its performance. Exploratory Data Analysis – This report details the state of the data that the model was trained on so users can determine if the present-state data has changed drastically. Models are typically scheduled to be re-trained every month with any new data received. The new models can be compared to the previous model using the output reports generated. It is expected that models will degrade over time and they should be replaced regularly with better performing models incorporating recent data. This is a huge burden on a human team, hence the need for data science orchestration automating the manual process and taking data science delivery to scale. 8) What sort of training comes with the service? One Model’s customers are trained on all aspects of our People Analytics tool. Training is offered for non-Data Scientists to be able to interpret the Results Summary and Exploratory Data Analysis reports so they can feel comfortable deploying models. A named One Model Customer Service Manager is available to aid and provide guidance if needed. 9) What do we do when circumstances change? One AI is built with change in mind. If the data changes in a way that breaks the model or the model drifts enough that a retrain is necessary, users can restart the automated machine learning pipelines to bring in new data and create a new pipeline. The new model can be compared to the previous model. One AI also allows work to occur on a draft version of a model while the active model is being run in production. 10) How do we monitor system performance? The Results Summary and Exploratory Data Analysis charts provide extensive model performance and diagnostic data. Actual real-world results can be used to assess the performance of the model by overlaying predictions with outcomes within the One Model application. This is also typically how results are distributed to users through the main analytics visualization toolsets. When comparing actual results against predictions, One Model cautions users to be aware of underlying data changes or company behaviors skewing results. For example, an attrition model may identify risk due to an employee being under-trained. If that employee is then trained and chooses to remain with the organization, then the model may have been correct but because the training data changed results can’t really be compared. In the case of this employee their risk score today would be lower than their risk score from several months ago prior to training. The action to provide additional training may indeed have been a response from the organization to address the attrition risk, and actions like these that are specifically made to address risk must also be captured to inform the model if mitigation actions have taken place. The Results Summary and Exploratory Data Analysis reports typically build enough trust in cross-validation that system performance questions are not an issue. 11) What are your views on product liability? One AI provides tooling to create models along with the reports for model explanation and interpretation of results. All models and results are based exclusively on a customer’s own data. The customer must review the model’s results and choose to deploy and how they use those results within the organization. We provide transparency into our modeling and explanations to provide confidence and knowledge of what the machine is doing and not just trusting a black box algorithm is working (or not). This is different from other vendors who may deliver inflexible canned models that were trained on data other than the customers or are inflexible to use a unique customer data set relevant to the problem. I would be skeptical of any algorithm that cannot be explained or its performance tracked over time. 12) Get an inventory of every process in your system that uses machine intelligence. Each One Model customer decides how specific models will be run for them, and how to apply One AI. These predictive models typically include attrition risk, time to fill, promotability, and headcount forecast. Customers own every model and the result generated within their One Model tool. One AI empowers our customers to combine the appropriate science with a strong awareness of their business needs. Our most productive One AI users utilize the tool by asking it critical business questions, understanding all relative data ethics, and providing appropriate guidance to their organization. If you would like to learn more about One AI, and how it can address your specific people analytics needs, schedule some time with a team member below.
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