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Featured
7 min read
Dennis Behrman
Richard Rosenow, One Model’s VP of People Analytics Strategy, spoke at People Analytics World in London this year on how the people analytics role has evolved. Watch the video or read our "Cliff’s Notes" below. Richard Defines People Analytics People analytics is a multifaceted field that encompasses many things. So it’s helpful to break it down into three key components: the Community, the Act, and Function. Community: The community is the heart of people analytics. It centers people analytics as a movement of people who want to make the world of work better with data. The Act: The use of data to support workforce decisions. Everyone in the business participates in the act of people analytics, including managers, leaders, and HR professionals. This practice has been around informally since the 1940s, highlighting its longstanding importance. Function: The formalization of people analytics as a business unit has been around for about 15 years, with pioneers like Jeremy Shapiro and Tom David Port leading the way. This function continues to evolve, adapting to the changing needs of the business world and supporting data-informed workforce decision-making. What is People Analytics? Learn more. Overview of the People Analytics Function Richard's experiences in the field of people analytics have given him an inside look. One unique aspect of people analytics he points out is the absence of a centralized governing body. This lack of a formal structure allows for continuous growth and evolution. It’s important to give ourselves and each other grace as we navigate and develop this dynamic field. Perhaps for the same reason, people analytics faces several common challenges, including lack of budget, data acquisition and quality issues, resistance to change, and disconnection within the company. Understanding and addressing these challenges is crucial for the continued growth and success of people analytics. One critical aspect of overcoming these challenges is understanding and connecting within what we call the People Data Supply Chain. By improving visibility and connectivity across different levels with HR, we can address many of the problems that arise. People Data Supply Chain One of the first tasks of people analytics is finding usable data, which means reaching upstream. The quality of the data inevitably leads to a focus on technology. As the people analytics leader moves into technology, a lack of standards in org structure are often revealed. And ultimately, at the very top, we see inconsistencies in strategy. If we don't decide what we're going to do and what we're going to do well, how does the operation know what to build? How do we set up our tech? How do we get our data out? And how do we do analytics? Besides the problem of unactionable data, inefficient and disconnected functions and disrupted data flow within the supply chain creates friction and politics. Connecting the Functions As the first one in people analytics to point out this infrastructure, its limitations, and its opportunities, Richard stresses that the sequence within the People Data Supply Chain is crucial. Often, there is good visibility above but poor visibility below, creating disconnects. Understanding this sequence and ensuring smooth transitions between levels can significantly reduce problems. Integrating these functions can lead to smoother operations and more effective people analytics practices. And a well-established data supply chain is especially imperative before implementing generative AI in HR. Emerging Role: Workforce Systems Leader The variety of job titles in people analytics is staggering; Richard has, in fact, identified over 2,600 unique titles. But In the midst of all this change, he has seen a new position emerging that combines people analytics with tech, ops, and strategy. Currently called by many names, this workforce systems leader reduces politics and provides a viable alternative to reporting directly to the CHRO. This new role offers an excellent career path for people analytics leaders. It allows them to leverage their unique insights and experiences to drive meaningful change within their organizations. Moving Forward As we continue to learn and grow in the field of people analytics, Richard reminds us that it’s crucial to be kind to ourselves and each other. Sharing insights and experiences within our community will drive our collective progress. Considering the People Data Supply Chain is essential for effective people analytics practices, we’ll be releasing an in-depth exploration of the topic soon. If this resonates with you, let’s continue this important conversation. Together, we can shape the future of people analytics and drive meaningful change in our organizations. Speaking of the future, Richard Rosenow covers these timely topics in greater depth in the webinar below. Take a listen!
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Featured
6 min read
Dennis Behrman
How does Human Resources help a business succeed? Like it or not, success in today’s organizations hinges on creating exceptional employee experiences. That means HR holds the key to achieving this critical objective. In this Hacking HR podcast episode, Enrique Rubio and Richard Rosenow, our VP of People Analytics Strategy, explored how HR data can transform workplaces into more human-centered environments. Yet, many HR professionals grapple with data anxiety for a variety of reasons. Listen in on their conversation or enjoy our “Cliff’s Notes” to learn how HR and people analytics professionals can overcome these challenges and embrace a data-driven approach to focusing on people. Why Building a Human-Centered Workplace Requires Data Enrique: We’ve been investing in conversations about empathy, kindness, compassion, feedback, mental health, wellness—all things that create a human-centered workplace. How can we implement these values in the workplace using data? How do we measure that it’s working well? Richard: Data has transformed HR’s ability to listen and engage in meaningful conversations at scale. Historically, HR professionals excelled at listening, but data now allows us to listen to larger populations effectively. For instance, in a company of four thousand employees, it’s impossible for leadership to talk to everyone personally. Data helps us understand and address the needs of employees by identifying patterns and insights that we might miss otherwise. It’s about listening at scale and making informed decisions based on those insights. Overcoming Data Anxiety Enrique: There’s a sentiment among HR professionals who feel they joined the field to work with people, not to dive into data, math, and technology. How do you address these concerns? Richard: The good news is that the technical burden on HR is decreasing. With advancements like ChatGPT, HR professionals don’t need to become data engineers. These technologies handle the heavy lifting, allowing HR to focus on strategic and consultative roles. Learning basic data literacy and understanding how to use data effectively is crucial, but the need to learn complex technical skills like SQL is diminishing. Today, the goal of successful human resource management is to leverage technology to enhance HR’s core strengths in understanding and supporting people. Real-Life Impact of Data in HR Enrique: Do you have any examples where data truly delivered value in creating a human-centered workplace? Perhaps looking into absenteeism versus engagement, or something similar? Richard: One memorable example is from my time as an HRBP for a large retail population experiencing high attrition. We collaborated with a professor researching job embeddedness, a measure of how well employees fit into their roles and communities. By running surveys before and after implementing a targeted program, we were able to decrease attrition significantly. This experience highlighted the power of using data to design effective HR programs and measure their impact, reinforcing the importance of HR success metrics. Surprising First Steps Enrique: It can be challenging to know where to start with integrating analytics into HR practices. What would be your first steps? Richard: Focus on connection and confidence. Start by making connections between HR metrics and business outcomes. Understand how HR activities impact operational results and find ways to measure these connections. Additionally, build confidence in your data. Reliable data allows HR to make informed decisions and advocate for necessary changes. At OneModel, we help HR leaders build unified data models, providing the confidence needed to understand and drive business success. Identifying HR Success Metrics Enrique: One common issue is investing time and resources into HR projects without setting up indicators of success. How can HR professionals ensure they have the right indicators? Richard: It’s crucial to set up indicators of success early on. Engage with analytics teams from other departments, if needed, to establish these indicators. While measuring complex human aspects like well-being can be challenging, finding proxy indicators and triangulating data can provide meaningful insights. For example, asking employees if they have a best friend at work can be a good proxy for workplace happiness, which can be linked to engagement and productivity. How One Model Helps Successful human resource management involves combining data insights with a deep understanding of human behavior, allowing HR professionals to develop programs that enhance employee satisfaction and business performance. One Model makes this possible by enabling listening at scale and efficiently providing deep data insights never before available. We enable HR teams to turn data into meaningful “stories” that drive action and growth. Want to focus on people not data? Learn how to tell better data stories with One Model.
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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
5 min read
Dennis Behrman
For employees, recognizing a bad company culture isn’t difficult. Their feelings of being overwhelmed, frustrated, unvalued, and unsupported serve as clear indicators. When employees experience these emotions, it’s a red flag that something is amiss within the organization. Leaders may see the downstream effect of a negative culture in the workplace in various ways. They might see low productivity, high employee turnover rates, and a general low return on investment (ROI) for the organization. Our VP of Sales and Solutions Architect Leader Phil Schrader discussed this topic with our friends at Culture Curated. Partners Season Chapman and Yuli Lopez shared several common ways they see leaders contributing to toxic workplace cultures. #1 You’re Fostering an Environment of Disconnection Yuli pinpointed siloes as a significant issue that impacts culture. “When there is poor work culture, you see it reflected in not enough connectivity between departments or peers. Siloes impact the way work is getting done.” The lack of connectivity not only affects internal operations but also has a tangible impact on customer satisfaction and organizations’ bottom line: A Towers Watson study found that strong internal communication strategies can lead to a 47% higher return to shareholders compared to the least communicatively effective firms. According to Forbes, siloes are often a trickle-down effect of conflicted leadership.The #1 key to solving this problem that plagues most organizations and creates a toxic workplace culture? Transparent communication. #2 - You Haven’t Defined Your Organization’s Core Identity Season notes that as an organization evolves, defining its core identity is crucial. It boils down, she says, to “being honest about what you want, what you need, and what competencies and behaviors you need your employees to display.” For example, while growth and innovation may have once defined a company, there may come a point when consistency and predictability become essential. If leaders fail to define this new season for their teams, results can be disjointed and a poor work culture results. With no clear sense of their organization’s purpose and identity, employees can struggle to connect their individual roles to the broader mission. This disconnect hampers motivation and engagement, ultimately affecting overall organizational performance. Conversely, a well-defined core identity is the compass that guides an organization toward success. It aligns teams, fuels innovation, and ensures a cohesive, purpose-driven workforce. #3 - You're Eroding Trust and Teamwork Every organization goes through seasons where employees are “in the trenches,” so to speak, when the work is challenging and collaboration is a must. Season shares that in healthy organizations, employees jump in and work together. Believing in and removing obstacles for each other has a catalyzing effect on the team and the results. However, where teams exhibit unhealthy competition, distrust, disengagement, or failure to communicate, a toxic work culture is born. Leaders can unintentionally foster these negative conditions by withholding information, showing favoritism, being disorganized, and failing to recognize and support their teams. On the other hand, when leaders model the collaborative, encouraging spirit they want to see in employees, they positively shape team dynamics, building trust and nurturing motivation. How One Model Helps Create Healthy Organizational Culture People Analytics is the answer to many culture challenges. The One Model People Analytics platform empowers HR leaders to effectively use their workforce data to understand and manage virtually every aspect of the employee experience. From Data to Decisions: What Is People Analytics?
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Featured
5 min read
Dennis Behrman
In the rapidly evolving landscape of Human Resources (HR), where technology and automation are reshaping the way businesses operate, the role of HR tech influencers has taken on paramount importance. As organizations navigate this dynamic environment, insights from trusted HR influencers have become indispensable in making informed decisions, adopting innovative tools, and embracing data-driven strategies. A testament to this influence is the recognition of Richard Rosenow with the "2024 Top HR Tech Influencer" award. The Role of HR Influencers in Technology Adoption HR departments across the globe have been in the process of transitioning for nearly 2 decades. From a subjective people operation to one of the most important analytical business assets. At the forefront of this transformation are the HR influencers whose insights and expertise have been guiding HR leaders through the emerging technology jungle and helping expand the roles inside their teams. in their HR strategies. The annual list of "Top 100 HR Tech Influencers," curated by Human Resource Executive and the HR Technology Conference & Exposition, serves as a testament to the pivotal role these influencers play in shaping the HR technology landscape. This list, now in its sixth year, comprises a diverse array of professionals, including analysts, consultants, and practitioners, who collectively represent the vanguard of HR technology thought leadership. Their contributions extend beyond their respective fields, encompassing thought-provoking perspectives, innovative solutions, and a deep understanding of the synergy between technology and HR. How do you become an HR Influencer? Becoming an HR influencer entails a journey of expertise, innovation, and consistent value delivery. Richard Rosenow's path to becoming an HR influencer exemplifies this process. With a background rooted in HR and technology, Richard leveraged his real-world experience building and leading people analytics teams to create insightful content and share actionable strategies across various platforms. Through engaging articles, speaking engagements, and thought leadership on LinkedIn, he demonstrated a deep understanding of HR technology's evolving landscape. Richard's dedication to staying updated on industry trends, sharing real-world solutions, and fostering meaningful connections established him as a trusted voice. His deep sense of caring and creating goodwill has also made him a friend to many. By consistently adding value, addressing pain points, and offering innovative perspectives, he garnered a dedicated following. One Model is honored to have Richard on our team. As a previous customer and evangelist who exemplifies our values, we could not be happier to have him on our team. More about the 2024 HR Tech Influencer Award The year 2024 marks a pivotal juncture in the realm of HR, with automation and generative artificial intelligence redefining traditional workplace dynamics. These advancements have underscored the need for HR operations to be optimized for efficiency, agility, and adaptability. HR departments are increasingly turning to technology to streamline processes, make informed decisions, and enhance overall organizational performance. The selection process for the "Top 100 HR Tech Influencers" list is rigorous and thorough, spearheaded by the editorial team at Human Resource Executive in collaboration with the HR Technology Conference organizers. The primary objective is to identify individuals who possess the transformative power to reshape how technology is leveraged within the HR industry. Rebecca McKenna, senior vice president of the HR portfolio at ETC, emphasizes the significance of this year's cohort, especially given the rapid advancements witnessed in HR technology. These influencers stand as beacons of reliable guidance, offering organizations across the globe profound insights and dependable advice. Interested in talking to Richard and the One Model team? Let us know! In conclusion, in a world where technology and HR are intricately intertwined, HR influencers have emerged as essential conduits of knowledge and innovation. Richard Rosenow's upcoming recognition underscores the significance of their contributions, reminding us that the path to HR excellence is paved by those who illuminate the way forward.
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Featured
5 min read
Dennis Behrman
Transitioning to a data-driven HR system can be daunting. So our VP of Sales and Solutions Architect Leader, Phil Schrader, met up with Yuli Lopez, Partner and Principal at Culture Curated, to discuss best practices for HR leaders embarking on or looking for guidance on that journey. Yuli describes her own mindset to this transition in the video below. Read on for a few additional tips for anyone going through or leading this level of change and upheaval. Embrace a Growth Mindset Adapting to digital systems is a learning curve for everyone involved. It’s crucial to approach this transition with an open mind, ready to embrace new methodologies and technologies. Yuli was two steps ahead in this regard. “[As an HRVP], it was exciting to be able to have information that I had been chasing,” she said. For teams or individuals feeling nervous about or resistant to using data in HR, she encourages new users to “jump in and put time on your calendar for just exploring.” She’s right. Venturing beyond familiar or unexpected information can unveil insights you weren’t even aware you needed. This exploration can help users begin to understand how data stories are constructed from visibility into the details impacting employees. Of course, a willingness to experiment works best in a culture where mistakes are seen as opportunities for growth rather than failures. A growth mindset not only enhances individual capabilities but collectively elevates the organization. Practice Adaptability The transition to using data in HR is less a straight line and more a series of learning opportunities, commonly thought of as obstacles. In this journey, embracing change and having the ability to pivot your HR mindset is paramount. Leaders who quickly adapt to the unexpected and use every challenge as a stepping stone towards innovation will cultivate a flexible environment. Open dialogue will be the norm, ensuring that every team member feels they have a voice in this transformative process. Adaptability is undergirded by two key characteristics (Source) that leaders must both personify and incentivize employees to develop: Emotional Resilience: The inner strength required to navigate through challenges and preserve mental and emotional health during times of change. Personal Responsibility: The commitment to proactively manage how we react to change, ensuring we are in control of our own development and progress. In addition to technical training, coaching on the dynamics of change and change management can be useful. Prioritize Collaboration Digital transitions benefit significantly from diverse perspectives and expertise, not to mention a strong, collaborative team. Engaging team members in the planning and implementation phases ensures that the digital solutions adopted are user-friendly and genuinely address the needs of the organization. Yuli notes that it’s important to partner with other departments. “There may be other aspects you’re not thinking about. If you go to them with a hypothesis, together you may be able to draw unexpected insights. This collaborative approach not only facilitates smoother adoption but also strengthens the sense of ownership among staff, fostering a supportive environment for change. Create a Strong Visionary Perspective Vision casters are like seasoned captains navigating through uncharted waters. They have a keen eye on the distant horizon, focusing on the incredible benefits that lie ahead. For a data transition, that could be delivering impactful insights across your organization and easily translating workforce data into cost allocations. These visionaries don't just keep these exciting perspectives to themselves; they share them, painting a vivid picture of the future and recruiting buy-in for an efficient process. As both cheerleaders and coaches rolled into one, these leaders are in the trenches, reminding everyone why the upheaval of transition is worth it. They champion and model patience and persistence, highlighting what every step closer to using data in HR means for the team, the organization and clients. How One Model Helps These mindsets are fundamental for HR leaders guiding their departments through the digital transition, but the technology of choice plays an enormous role in the outcomes of the journey. One Model provides the people analytics solution technology that orchestrates everything decision makers need to be able to quickly make brilliant workforce decisions.
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Featured
5 min read
Dennis Behrman
We asked our friends at Culture Curated why organizations should have a strong focus on human resource compliance. That led to a more foundational question: What is an organization’s culture? Culture: Ping Pong Tables or Compliance in HR? In the quest to boost workplace culture–and thus performance, our initial instinct might be to think of adding fun elements, like a ping pong table in the break room. However, the journey to improving corporate culture delves much deeper than surface-level entertainment. It begins with the bedrock of strong human resource compliance. In fact, “Any good culture is going to be built on the foundation of strong compliance,” says Season Chapman, Partner & Principal Consultant of Culture Curated. “It’s about how we must treat people.” But compliance isn't just about adhering to HR compliance laws or procuring a human resources compliance solution. It's about establishing a framework within which people are treated fairly and decisions are made responsibly. This foundation of compliance in HR is essential, not just for its own sake, but as the ground floor upon which the rest of the company culture is built. Laying Your Culture’s Foundation: Accountability and Belonging Moving beyond the notion that culture is merely about having fun, culture is–at its core–about accountability, achieving results, and fostering trust among team members. But how do we shift the conversation towards these deeper aspects of culture? The answer lies in starting with human resources compliance as the base layer. Drawing from psychological principles, humans seek a sense of belonging and connection. They want to feel aligned with the company's mission and vision. The secret to that goal starts with a focus on building meaningful relationships with employees and fostering a sense of belonging and support. In today's workplace, the concept of psychological safety is paramount for cultivating a culture where employees feel confident in sharing ideas. This safe space is critical for a vibrant, innovative workplace culture. Starting the Journey Towards a Balanced Culture So, how does an organization embark on this journey towards a culture that balances fun, compliance, and psychological safety? According to Yuliana Lopez, Partner & Principal Consultant of Culture Curated, “The starting point is an organizational assessment.” She explains that such assessments gauge the current state of compliance and how employees feel about their work environment and relationships with peers. This comprehensive evaluation can identify areas for improvement and set the stage for developing a culture that not only meets legal requirements but also fulfills and inspires its workforce. Are You Ready for the Coming Wave of AI Regulation for Human Resources? How One Model Helps With Compliance Foundations One Model assists with compliance by providing an integrated analytics platform designed to manage and analyze workforce data according to legal standards and best practices that includes: Offering advanced analytics and reporting capabilities that enable compliance with regulatory requirements. Prioritizing robust data security and privacy measures to protect sensitive information and comply with data protection regulations. Featuring role-based access controls so that only authorized personnel have access to sensitive data, in order to maintain continuous compliance with labor laws, and occupational safety and other standards. Providing customizable dashboards to monitor key compliance indicators, from wage and hour laws to benefits regulations and beyond. While the allure of quick fixes like a ping pong table may seem like an easy way to boost morale, the real work in improving culture goes much deeper. By establishing a strong foundation of compliance with human resource compliance solutions like One Model, organizations can lay the groundwork for a positive culture. This foundation enables leaders to enhance performance, foster genuine connections, and support the well-being of every employee. Wondering about compliance in the world of AI and Machine Learning? We’ve got you covered. 1. Understand how ethics are changing in a world with AI. Read more. 2. Be prepared with regulations coming to HR. 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.
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Featured
6 min read
Dennis Behrman
In a timely conversation on DEI data, Phil Shrader of One Model and Season Chapman and Yuli Lopez of Culture Curated shed light on the importance of diversity and inclusion data analytics. While strides have been made in leveraging people analytics to propel the DEI movement forward, they reveal a stark reality: The journey towards achieving comprehensive diversity data standards is far from over. What’s Missing and What’s Present in Your DEI Data? As we delve deeper into the complexities of gathering DEI data, it becomes evident that significant gaps in what is collected hinder progress toward truly inclusive environments. Critical areas needing attention and improvement include: Performance reviews and gender bias Season Chapman highlighted a concerning statistic: In a significant study, 66% of women received negative personality-related feedback in performance reviews, compared to less than 1% of men. (Source) This discrepancy not only exposes a gender bias but underscores the need for a more nuanced approach to evaluating performance and collecting performance data. By systematically analyzing both the written and verbal components of reviews, organizations could begin to identify biases entrenched in their evaluation processes. Ageism and Strength-Based Diversity The often overlooked dimension of age bias, dubbed by the American Psychological Association as 'the last socially acceptable prejudice,’ highlights a gap in DEI initiatives’ predominant focus on racial and gender bias. Season also highlighted the tendency to emphasize weaknesses rather than strengths in organizational cultures. Incorporating strength-based analytics into DEI strategies could revolutionize how talents are matched with roles, fostering a more inclusive and productive workplace environment. Do you track and measure these 4 diversity metrics? Awareness of DEI Data Bias Types The above examples and many others highlight the significant potential for bias in data and data collection. Bias can exist within current data due to a variety of factors, including but not limited to: Historical bias can exist when past data, such as male-dominated hiring patterns, favors men over women for certain roles. Representation bias can occur when data used to train an algorithm may over- or underrepresent some groups. An example of this is found with facial recognition tools that produce higher error rates for certain groups. Measurement bias can happen when data that is collected disproportionately values behaviors or achievements that are more accessible to a particular group. Algorithmic bias can result when algorithms use their own predictions to make future decisions, which can replicate and even amplify existing biases in the dataset. It’s important to note that there’s no such thing as completely bias-free data. (Source) But we must seek to mitigate bias in our analytics by choosing effective technology, increasing our awareness of how it occurs, and applying safeguards. 3 Key Considerations in Advancing DEI Through Analytics Exploring the landscape of diversity data reveals three pivotal areas essential for effective DEI strategies: Accurately interpreting and applying DEI data: To achieve this, organizations can use advanced analytics and visualization tools that enable stakeholders to see beyond the surface-level numbers. This enables them to identify underlying patterns and insights that drive targeted, effective DEI interventions. Ensuring data collection methods capture the full diversity of an organization: This involves developing and implementing data collection strategies that are inclusive of all identities and experiences, thus mitigating biases that could skew the understanding of the organization's diversity landscape. Addressing privacy, confidentiality, and bias in data and algorithms: Organizations should establish multidisciplinary ethics committees that regularly review data collection, analysis practices, and algorithmic decisions for biases. This oversight ensures continuous alignment with ethical standards and promotes fairness and equity in all AI-driven DEI decisions. How One Model Supports DEI Initiatives Modern enterprises must do more than just track hiring metrics; they need to deeply analyze diversity data to drive genuine improvements. Leveraging people analytics software like One Model enables organizations to reduce bias and harness insights for crafting policies that foster long-lasting diversity and inclusion. Our clients use One Model's powerful analytics to visualize and monitor their DEI journey, establishing robust strategies that not only report but actively shape a more inclusive workplace. Ready to project your diversity in 5 years? One Model can calculate that for you.
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6 min read
Dennis Behrman
The One Model team just returned from Las Vegas after an exciting HR Tech 2023. We launched some new products, evangelized the basics of connecting data from around the organization, and partied with our new partner Lightcast. Watch our team recap and see some fun images from our time at the show or scroll down to read our takeaways. Great Minds in HR Tech Shared a Ton of Insights HR Tech 2023 offered something for everyone, across many roles. It was great to see so many HR analytics and people analytics evangelists and enthusiasts. It's an inclusive community that offered incredible diversity of thought and experience. My colleague Richard Rosenow noted that an evolution of the field was actively taking place at HR Tech, specifically toward model governance. I personally told dozens of visitors to our booth that sooner or later, regulators and auditors are going to be asking questions about how a decision was made. Leaders in that room should be prepared to show every aspect of their data-driven decision process in a trustworthy and explainable way. Our HR Tech Conversations from the Expo Hall Check out our entire event interview playlist on Youtube. We Felt the Energy of HR Tech An event in Vegas always has a high level of energy, but our feeling was that organizations are buzzing about the opportunity to build the very best workforce through productivity and well-being. Most people know that people analytics is the path to every workforce story. About 70% of the folks we spoke with said their team is interested in People Analytics and were actively looking for solutions that provide great insights. Do the Basics Right There was so much talk about skills and generative AI, but many companies haven't finished with the basics of enterprise data orchestration. Many companies still struggle organize all of their people data. The cool stuff is difficult or impossible without a data foundation of well-connected enterprise systems. Lots of Hype Around Generative AI It seemed as though most software vendors were discussing their own generative AI technologies. I felt some enthusiasm from would-be technology buyers, but most are rightfully concerned about transparency and accountability as AI regulations become more likely. Most vendors have a very common large language model implemented, but we've seen analysis that shows generative AI isn't a reliable interpreter of quantitative data. In that study, only 70% of the answers that the AI generated were correct. So Many Opportunities for Fun One Model really allows our customers to get out of the late-night data crunching and come out and have a good time. Several companies were so excited about the prospect of having a scalable people analytics solution that they even joined us and our partners at a special VIP event. So, if late-night data crunching is your current reality, it's time to explore the capabilities of One Model. Continue your People Analytics journey with One Model. Schedule a demo!
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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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9 min read
Dennis Behrman
Human resources (HR) management has become more critical in today's rapidly evolving business landscape. HR departments face the challenge of attracting, retaining, and nurturing talent while ensuring the organization's success. To address these demands, HR management platforms have emerged as invaluable tools. However, implementing AI-powered people analytics solutions has transformed HR platforms, empowering organizations to make data-driven decisions and optimize their practices for improved efficiency and effectiveness. With AI-powered people analytics platforms, organizations can leverage insights and trends to enhance their HR strategies, leading to better talent decisions and organizational outcomes. AI-Powered HR Management Platforms AI is changing the landscape of HR management by augmenting and automating various tasks. Based on Society for Human Resource Management research, AI adoption for HR tasks was particularly widespread among larger companies, with 42% of firms employing at least 5,000 workers utilizing AI in 2022. While having specialized data analysts is still crucial for effectively utilizing AI, user-friendly tools increasingly empower employees across all roles to perform data analysis. HR analytics tools examples leverage advanced algorithms and machine learning to analyze vast data and make intelligent recommendations. Some key use cases of AI in HR processes include: Recruitment and Candidate Screening HR professionals prioritize streamlining the recruitment process, and AI technology is crucial in achieving this goal. By automating job advertising, AI helps save time and optimize campaigns for better results. AI algorithms measure outcomes, predict future trends, and reduce costs. Furthermore, AI addresses unconscious bias by reaching a diverse candidate pool and engaging passive candidates. It automates routine tasks, provides feedback, and ensures transparent communication, enhancing the candidate experience. AI in job advertising improves efficiency, diversity, and the recruitment experience for potential employees. Employee Onboarding and Training AI platforms revolutionize employee onboarding and training by automating administrative tasks, offering personalized onboarding plans, and providing interactive learning experiences. They streamline paperwork, documentation, and scheduling, ensuring a smooth organizational transition. AI platforms offer diverse online training resources and use machine learning to analyze performance and suggest personalized skill development. Moreover, they facilitate knowledge sharing and collaboration through natural language processing and chatbots. These platforms enhance efficiency, effectiveness, and employee experience during onboarding and training processes by leveraging AI technologies. Performance Management and Feedback One of the key benefits of AI platforms in performance management is their ability to capture and analyze vast amounts of data. By leveraging machine learning, they identify patterns and correlations, providing managers a comprehensive understanding of individual and team performance. These platforms automate performance evaluations, offer real-time feedback, and track key performance indicators, facilitating ongoing feedback and coaching conversations. They also provide personalized recommendations for improvement, suggesting relevant training programs and resources based on individual strengths and career goals. With AI platforms, organizations can optimize performance management processes, empower employees to drive their development and foster a culture of continuous improvement. Predictive Analytics for Workforce Planning Through the analysis of historical data, HR analytics software can identify patterns and trends in workforce behavior, such as employee turnover rates, skill gaps, and recruitment success. This enables organizations to make accurate predictions about future workforce demands and make proactive decisions to address potential challenges. AI platforms also consider external factors such as market trends, economic indicators, and industry forecasts to provide a holistic view of the workforce landscape. By incorporating this external data into predictive models, organizations can anticipate talent supply and demand changes and align their workforce planning strategies accordingly. AI-Powered People Analytics Solution in HR Management In the swiftly evolving business landscape, staying ahead requires more than mere intuition; it demands insights derived from data. AI-Powered People Analytics Platform is a transformative tool poised to redefine how organizations understand and nurture their most valuable asset: their people. Seamlessly adopting advanced AI capabilities with comprehensive workforce data, this platform unlocks a deeper understanding of employee dynamics. According to Straits Research, as of 2022, the worldwide people analytics market was estimated at $2.58 billion, and it is projected to reach $7.67 billion by 2031, exhibiting a CAGR of 12.88% during the forecast period of 2023-2031. From predictive analytics that shapes strategic decisions to personalized development paths that amplify individual growth, embark on a journey where data-driven precision meets human-centric leadership. Discover how this platform redefines success by empowering companies to cultivate thriving, resilient, and engaged teams. Key aspects of people analytics in HR management include: Employee Engagement and Retention Through analyzing various data sources such as employee surveys, performance data, and employee feedback, people analytics can identify patterns and trends related to engagement. It aids organizations in recognizing gaps and issues related to engagement and retention, measuring progress, and establishing objectives to enhance employee engagement and retention strategies. Through data analysis concerning turnover rates and mobility efforts, organizations can pinpoint trends that affect engagement and retention, uncover any underlying biases, and develop precise approaches for improvement. Diversity and Inclusion Initiatives People analytics empowers organizations to improve corporate culture and drive diversity and inclusion initiatives by leveraging data and insights. Organizations can identify gaps and set goals by analyzing employee demographics, representation, and inclusion metrics. People analytics helps uncover biases in talent processes and enables organizations to develop strategies for fair and equitable practices. Additionally, it measures the impact of diversity and inclusion initiatives on employee experiences and outcomes, allowing organizations to make data-driven adjustments. Ultimately, people analytics provides valuable insights to foster inclusive workplaces where all employees feel valued and empowered to contribute their unique perspectives. Succession Planning and Talent Management People analytics is vital in talent management and strategic workforce planning within organizations. By analyzing employee performance, skills, and potential, people analytics provides valuable insights for identifying and nurturing high-potential employees for future leadership roles. It helps organizations create talent pipelines by identifying skill gaps and developing targeted development programs. People analytics also aids in succession planning by enabling data-driven assessments of potential successors, allowing organizations to make informed decisions for key positions. With the help of people analytics, organizations can effectively manage and develop their talent, ensuring a smooth transition of leadership and fostering a culture of continuous growth and development. AI-Driven Insights for Informed Decision-Making Utilizing AI algorithms, which can dissect intricate data sets, yields valuable insights that can be acted upon. HR professionals stand to benefit significantly, as these insights empower them to execute well-informed judgments regarding recruitment, performance assessment, and the cultivation of talent. Implementing AI-driven analytics enables a strategic approach to HR, fostering enhanced decision-making across hiring, performance management, and talent development. Predictive Analytics for Identifying HR Trends and Patterns According to McKinsey, 70% of corporate leaders regard people analytics as a top priority. Organizations are placing a strong emphasis on understanding the skills and capabilities of their workforce. This proactive approach empowers them to preemptively tackle hurdles, fine-tune workflows, and execute impactful HR strategies. By harnessing AI-driven insights, HR leaders gain the ability to discern underlying dynamics, ensuring that their initiatives are both finely tuned and aligned with evolving organizational needs. Enhanced Employee Experience Through Personalized Recommendations AI-powered people analytics platforms can provide personalized recommendations to employees, such as learning and development opportunities, career pathways, and wellness programs. This improves employee engagement and satisfaction. Additionally, AI-powered HR platforms integrated with enterprise learning management systems can go beyond traditional training and development initiatives. Enterprise learning management systems can recommend wellness programs and resources that promote employee well-being, including mental health support, fitness activities, and stress management techniques. By addressing the holistic needs of employees, an enterprise learning management system contributes to a healthier and more productive workforce, fostering a positive work environment. Harnessing the Power of AI-Powered Analytics Platforms for Organizational Success The AI-powered people analytics software is revolutionizing HR management platforms. By harnessing the power of artificial intelligence and data-driven insights, HR professionals can make more informed decisions, improve employee engagement, and enhance overall organizational performance. These advanced platforms enable the automation of repetitive tasks, enabling HR teams to focus on strategic initiatives and personalized employee experiences. Moreover, AI-driven predictive analytics tools for HR can provide valuable insights into workforce trends, enabling proactive talent management and effective succession planning. As organizations embark on this transformative journey, the collaboration between technology and human expertise will shape the future of HR, driving innovation, productivity, and success in the workplace. Learn more about One Model's people analytics software.
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10 min read
Dennis Behrman
Ever play with a Magic 8 Ball? Back in the day, you could ask it any question and get an answer in just a few seconds. And if you didn't like its response, you could just shake it again for a new prediction. So simple, so satisfying. Today's HR teams and businesses obviously need more reliable ways of predicting outcomes and forecasting results than a Magic 8 Ball. But while forecasting and predicting sound similar, they're actually two different problem-solving techniques. Below, we'll go over both and explain what they're best suited for. What is HR forecasting? Remember the Magic 8 ball? At first glance, the Magic 8 ball "predicts" or "forecasts" an answer to your question. This is not how forecasting works (at least, for successful companies or HR departments). Instead, HR forecasting is a process of predicting or estimating future events based on past and present data and most commonly by analysis of trends. "Guessing" doesn't cut it. For example, we could use predictive forecasting to discover how many customer calls Phil, our product evangelist, is likely to receive in the next day. Or how many product demos he'll lead over the next week. The data from previous years is already available in our CRM, and it can help us accurately predict and anticipate future sales and marketing events where Phil may be needed. A forecast, unlike a prediction, must have logic to it. It must be defendable. This logic is what differentiates it from the Magic 8 ball's lucky guess. After all, even a broken watch is right two times a day. What is predictive analytics? Predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and trends that could potentially predict future outcomes. It doesn't tell you what will happen in the future, but rather, what might happen. For example, predictive analytics could help identify customers who are likely to purchase our new One AI software over the next 90 days. To do so, we could indicate a desired outcome (a purchase of our people analytics software solution) and work backwards to identify traits in customer data that have previously indicated they are ready to make a purchase soon. (For example, they might have the decision-making authority on their people analytics team, have an established budget for the project, completed a demo, and found Phil likeable and helpful.) Predictive modeling and analytics would run the data and establish which of these factors actually contributed to the sale. Maybe we'd find out Phil's likability didn't matter because the software was so helpful that customers found value in it anyway. Either way, predictive analytics and predictive modeling would review the data and help us figure that out — a far cry from our Magic 8 ball. Managing your people analytics data: how do you know know if you need to use forecasting vs. predictive analysis? Interested in how forecasting and/or predictive modeling / predictive analytics can help grow your people analytics capabilities? Do you start with forecasting or predictive modeling? The infographic below (credit to Educba.com - thanks!) is a great place to compare your options: Recap: Should you use forecasting or predictive analysis to solve your question? Forecasting is a technique that takes data and predicts the future value of the data by looking at its unique trends. For example - predicting average annual company turnover based on data from 10+ years prior. Predictive analysis factors in a variety of inputs and predicts future behavior - not just a number. For example - out of this same employee group, which of these employees are most likely to leave (turnover = the output), based on analyzing past employee data and identifying the indicators (input) that often proceed with the output? In the first case, there is no separate input or output variable but in the second case, you use several input variables to arrive at an output variable. While forecasting is insightful and certainly helpful, predictive analytics can provide you with some pretty helpful people analytics insights. People analytics leaders have definitely caught on. We can help you figure it out and get started. Want to see how predictive modeling can help your team with its people analytics initiatives? We can jump-start your people analytics team with our Trailblazer quick-start package, which really changes the game by making predictive modeling agile and iterative process. The best part? It allows you to start now and give your stakeholders a taste without breaking the bank, and it allows you to build your case and lay the groundwork for the larger scale predictive work you could continue in the future. Want to learn more? Connect with Us. Forecasting vs. Predictive Analysis: Other Relevant Terms Machine Learning - machine learning is a branch of artificial intelligence (ai) where computers learn to act and adapt to new data without being programmed to do so. The computer is able to act independently of human interaction. Read Machine Learning Blog. Data Science - data science is the study of big data that seeks to extract meaningful knowledge and insights from large amounts of complex data in various forms. Data Mining - data mining is the process of discovering patterns in large data sets. Big Data - big data is another term for a data set that's too large or complex for traditional data-processing software. Learn about our data warehouse. Predictive Modeling - Predictive modeling is a form of artificial intelligence that uses data mining and probability to forecast or estimate more granular, specific outcomes. Learn more about predictive analytics. Descriptive Analytics - Descriptive analytics is a type of post-mortem analysis in that it looks at past performance. It evaluates that performance by mining historical data to look for the reasons behind previous successes and failures. Prescriptive Analytics - prescriptive analytics is an area of business analytics dedicated to finding the potential best course of action for a given situation. Data Analytics - plain and simple, data analytics is the science of inspecting, cleansing, transforming, and modeling data in order to draw insights from raw information sources. People Analytics - All these elements are important for people analytics. Need basics? Learn more about people analytics. About One Model One Model’s people analytics solutions help thriving companies make consistently great talent decisions at all levels of the organization. Large and rapidly-growing companies rely on our People Data Cloud™ people analytics platform because it takes all of the heavy lifting out of data extraction, cleansing, modeling, analytics, and reporting of enterprise workforce data. One Model pioneered people data orchestration, innovative visualizations, and flexible predictive models. HR and business teams trust its accurate reports and analyses. Data scientists, engineers, and people analytics professionals love the reduced technical burden. People Data Cloud is a uniquely transparent platform that drives ethical decisions and ensures the highest levels of security and privacy that human resource management demands.
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4 min read
Dennis Behrman
Now that many of our customers have complete control and access to their data like never before, they're exploring how to tell better data stories. A fun way to explore this topic is to look at the great examples from the past. Minyard’s example shows us how to tell a story with data Let’s take this example forward to one of history's most famous data stories, Minard’s visualization of Napoleon’s 1812 march into Russia. Edward Tufte, a renowned expert in data visualization, praised Minard's visualization of Napoleon's 1812 march. In his book "The Visual Display of Quantitative Information," Tufte referred to Minard's graphic as "probably the best statistical graphic ever drawn”. Although not directly HR (other than in a dark way, a visualization of workforce attrition over time), we can still analyze how this visual fits into the framework of six effective data storytelling elements and apply those lessons to HR storytelling: Business Objective: In the context of HR, the objective was to convey a message and inspire action. Minard's visualization powerfully demonstrates the disastrous consequences of Napoleon's march, highlighting the importance of understanding the impact of decisions on people. Evidence: Minard's visualization uses data from multiple sources, such as the number of soldiers, their geographic locations, and temperature. In HR data storytelling, this would translate to gathering relevant data from various sources like employee engagement surveys, performance metrics, or attrition rates, to support the narrative. Visuals: Minard's visualization is a clear, engaging visual representation of complex data. Similarly, HR professionals should utilize data visualization tools to create visually appealing and easy-to-understand representations of workforce data. Narratives: Minard's map tells the data-informed story of the march's progression and the resulting loss of soldiers. In HR data storytelling, a compelling narrative should weave together the data and insights, making them relatable and memorable for the audience. Interactivity: While Minard's visualization is static, you could imagine leaders in the armed forces looking for cuts of this data by troop category, demographics, and nationality (pre-GDPR). Interactivity would have allowed Minard to engage quickly with the graphic to see different cuts of the data. HR professionals adapt their data stories based on the audience's questions and feedback, making the story more engaging and dynamic. Action: Minard's visualization serves as a cautionary tale, prompting leaders to consider the consequences of their decisions. In HR data storytelling, ending the story with a clear call to action can drive engagement and ensure the story leads to meaningful change within the organization. By analyzing Minard's data storytelling example in the context of the simple six-element storytelling framework, HR professionals can gain valuable insights on how to create data-informed stories that effectively communicate the human impact of organizational decisions and inspire meaningful change. Check out 8 Essential People Analytics Dashboards 1 Image Source Ready to tell better data stories with your people analytics data? Download our Data Storytelling eBook today.
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5 min read
Dennis Behrman
HR leaders - are you ready? Starting from Wednesday, July 5th, enforcement begins for Local Law 144 and Department of Consumer and Work Protection (DCWP) Rules. These regulations specifically address the use of Automated Employment Decision Tools (AEDT) found in software used during the job application or promotion process for employers and candidates residing in New York City. Understanding the new AEDT regulation Now, let's break it down in simpler terms. The law and regulations cover AEDT, which is basically any process that uses machine learning, statistical modeling, data analytics, or artificial intelligence to provide simplified output like scores, classifications, or recommendations. These tools are meant to assist or even replace discretionary decision making by humans in the employment process. To comply with these new requirements, employers need to take a few steps. First, you'll need to figure out if any of the software your company uses for hiring or promotions falls under the category of AEDT. In other words, if it's helping with decision-making by "scoring," classifying, or recommending candidates or employees in NYC. This law is broader than similar laws in Illinois and Maryland that focus on facial-recognition software, so it covers commonly used HR software. If you do use software with AEDT, here's what you need to do: (1) make sure a bias audit has been conducted; (2) provide at least 10 days' notice to applicants or employees that AEDT will be used; (3) explain the qualifications the AEDT will consider during assessments; (4) disclose the data source and type of AEDT being used, along with your data retention policy if it hasn't been shared elsewhere; and (5) inform applicants or employees that they have the right to request an alternative means of assessment or a "reasonable accommodation" under other laws. But wait, there's more! The initial bias audit is just the beginning. Employers are also responsible for conducting an AEDT audit annually. And here's the kicker: the results of the bias audit need to be published on your website before using the AEDT. These audits have to be conducted by "Independent Auditors" who are unbiased and not financially connected to the employer or the software vendor. Read more here. Now, let's talk penalties. If you violate any of these requirements, you could face civil penalties. The first violation can result in a $375 fine, while subsequent violations could be at least $500, with a maximum of $1,500. There are separate penalties for violations of the notice and audit requirements. Keep in mind that this new regulation is in line with the EEOC's guidance issued in May 2023, which also requires bias audits, notice, and opt-out provisions. It's all part of the effort to ensure fairness in employment decisions. And it's not just happening in NYC – other jurisdictions are considering similar bills and regulations related to AI and employment decisions. Want to learn more about these regulations and others around the world impacting HR? Take our Regulations and Standards masterclass and be a leader in the space. Understanding your options I think a lot of companies not using One Model are going to have some big challenges. From our experience, most AI tools are like a black box. You cannot get a clear understanding of what is being used in the models that generate the insights you're using. One Model is the complete opposite. Our models are only built from your data. They have outputs that tell you exactly what data is being fed into the models and, in turn, are customizable. In addition, One Model customers benefit from being able to build models beyond talent acquisition including retention, diversity, and more. Would you like to see our AI in action? Meet with us today! Understanding the bigger global picture On a global scale, the EU's Artificial Intelligence Act is also making progress. The European Parliament recently adopted its official negotiating position on June 14, 2023. This Act covers the use of AI in various areas, including employment. If it goes into effect, AI used for employment purposes would likely fall under the "high-risk" category and face greater regulation. So, as HR leaders, it's important to stay informed about these evolving regulations. Make sure to review your software tools, conduct the necessary audits, and provide the required notices to applicants and employees. And keep an eye out for any developments in your local jurisdiction or at the EU level. Good luck navigating these changes!
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4 min read
Dennis Behrman
Phil Schrader and Stephen Haigh had an opportunity to attend the People Analytics World Conference in London April 26-27, 2023. During their visit, Phil was asked to give a public demonstration of how HR analytics software works. While we can't speak for other people analytics tools, we can speak to One Model. The crowd was mesmerized and had lots of questions at the end that you definitely have to watch. Join Phil as he walks through data import, export, and all the magic in between — even showing in real time how an AI model is built exclusively on your data. Phil, always cheeky and fun to watch, is a great teacher in all the things you should look for when assessing which people analytics tool is right for you. Compared to other HR analytics tools on the market, you'll quickly see that One Model is more transparent, easier to use, and more open than any other option on the market. Want your own personal tour of One Model? Request time to meet today. During the video, Phil walks us through each of these layers: The Consumer Layer: At the top of the platform, users, such as HR Business Partners, can access data, insights, and storyboards through a user-friendly interface. The storyboard feature allows users to interpret data visually and navigate through various tools like Explore, Storyboards, and Data. These tools enable users to slice and dice analytics, explore heat mapping, and gain insights into different data sources. From Consumer to Analyst Layer: One Model's flexibility empowers users to transition from the consumer layer to the analyst layer effortlessly. Here, analysts can customize the views, rearrange elements, and dive deeper into the data. With simple clicks, they can transform data into charts, change metrics, and connect multiple systems to gain a holistic view. Configuring Metrics and Data Engineering: As analysts continue their exploration, they can configure metrics according to their organization's specific requirements. They can modify calculations, adjust inclusion/exclusion criteria, and create unique views tailored to their audience. Furthermore, One Model offers transparency into data engineering, allowing analysts to delve into the underlying data models, processing scripts, and data sources. Unleashing the Power of Data Science: Finally, One Model empowers advanced analysts and data scientists to build predictive models. With the augmentation feature, analysts can create and maintain multiple models, evaluate their performance, and put them on schedules. The platform provides a guided walkthrough for model building, enabling users to define their objectives, select relevant metrics, and generate predictions. The prediction capabilities extend to specific employee segments or the entire population.
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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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4 min read
Dennis Behrman
Corporate culture plays a pivotal role in driving organisational success, but quantifying its impact has often relied on subjective assessments. However, with people analytics, human resources teams can adopt a scientific approach to measure and predict the impact of corporate culture more effectively. Phil Schrader caught up with Season Chapman and Yuli Lopez, both One Model enthusiasts who have ventured out as founders of Culture Curated, for a captivating dialogue about culture. They share their firsthand experiences of using One Model's software platform to directly measure and address human resources challenges. The Power of People Analytics in Culture Assessment: Traditional methods of understanding corporate culture, relying on gut instinct and after-the-fact observations, can be subjective and limited in providing actionable insights. People analytics, on the other hand, uses data-driven methodologies to uncover patterns and make predictions about culture's impact on business outcomes. By analysing various data points, such as employee surveys, performance metrics, and feedback channels, organisations gain a comprehensive understanding of the underlying factors shaping their culture. Measuring Culture in Real Time Phil Schrader's conversation with Season and Yuli highlights the transformative potential of people analytics in directly measuring and monitoring key drivers of corporate culture. Culture Curated leveraged One Model's software platform, empowering HR teams to collect and analyse vast amounts of data to transform it into meaningful insights. With objective metrics and data visualisations, organisations can now track culture-related issues in real time, enabling proactive interventions to address them promptly. This shift from reactive observations to predictive analysis empowers leaders to make informed decisions that positively impact culture. Predicting and Enhancing Culture The true power of people analytics lies in its ability to predict the outcomes of culture-related initiatives. By examining historical data and identifying patterns, organisations can forecast the potential impact of cultural interventions. This predictive capability allows leaders to develop targeted strategies to enhance their desired culture and align it with their business objectives. People analytics provides evidence-based guidance for redesigning performance management systems, fostering diversity and inclusion, and enhancing employee well-being initiatives. With these insights, organisations can drive meaningful change and achieve their desired results. The Video Dialogue: A Firsthand Account To delve deeper into the transformative effects of people analytics on corporate culture, we invite you to watch the engaging video dialogue between Phil Schrader, Season Chapman, and Yuli Lopez of Culture Curated. In this video, they share their experiences of using One Model's software platform to directly measure and address culture-related challenges. Their insights provide a firsthand account of the power of people analytics in driving organisational success through a data-driven approach to culture assessment. It's All About Attracting and Retaining Top Talent People analytics has revolutionised the way organisations measure, monitor, and improve their corporate culture. By harnessing data-driven insights, leaders can make informed decisions and actively shape their culture to drive success. We trust experts like Season and Yuli when it comes to transforming culture measurement. Ultimately, organisations can create thriving cultures that attract top talent, foster innovation, and achieve sustainable success in today's competitive business landscape. Request a Personal Demo to See How to Measure and Improve Culture with People Analytics
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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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Featured
8 min read
Dennis Behrman
Brilliant talent decisions require superb data. But how do you know what decision power lies in your data? Test it for yourself! Our People Analytics Challenge can give you a sense for the state of your human resources data and your organization's ability to make great decisions. To find out just how prepared your organization is to make brilliant talent decisions with the data you have, download our handy worksheet here. People Data Cloud™, One Model’s leading people analytics platform, can transform how you make talent decisions by making the human resources and related enterprise data that you already have access. Unlocked and properly harnessed people analytics can be an incredibly valuable asset to your company. Understanding the People Analytics Challenge Where did we get the questions? Our very own Phil Schrader (One Model's Solution Architect), along with his peers across our business, spent decades in the human resources function applying data analysis to common HR decisions and solving talent challenges. Phil compiled the most common questions into this worksheet. He then used our proprietary People Data Cloud technology to produce the tables, charts, graphs, and reports to demonstrate how a true people analytics capability can help HR practitioners. For sh*ts and giggles, we also timed how long it took Phil to arrive at these answers. Here are some of those questions. Question #74: What is our new hire failure rate, by tenure and by department? Phil's time on this KPI: 4 minutes 45 seconds Finding out where your new hires fail, and at what point in their tenure, gives you a clear place to focus attention. Addressing new hire failures with this data reduces the average cost to hire and gives the organisation continuity and increased productivity. Here's the most important people metrics of all time. Question #1: What is our revenue by employee Phil's time on this KPI: 5 minutes 24 seconds Building a straightforward report like this doesn't take much time, but One Model also has a lot of pre-built views that interpret your data after ingestion and create the data visualization for you. Let's see how quickly Phil can get information like this. Are you ready to take the People’s Analytics Challenge? Download our whitepaper and put your team to the test. Follow the hashtag #peopleanalyticschallenge on LinkedIn and let us know if you can beat Phil! Question #38: What is ratio of managerial to non-managerial employees, and how does this vary by department? Phil's time on this KPI: 2 minutes 43 seconds It actually took Phil longer to take the screenshot I needed for this blog post than it did for him to pull the answer to this question. Now, let's pick a question that may require a little debate on how the metrics are built. This question will require Phil to meet with key players in the company to ensure the customizable calculations are exactly what we need to get the best insight. Question #25: What is the depth of our leadership pipeline within the company? Phil's time on this KPI: 44 minutes 56 seconds Benchmarks and succession planning in people analytics are not always measured the same from company to company. To make our timing as realistic as possible, we put together a quick meeting with our VP of Strategy and mapped out the best methodology for the three charts. If you'd like to better understand Succession Planning and see how the build was done, watch the video on this post. After we aligned on the variables that we needed to include and how to piece them together, connecting the dots did not take much time, about 15 minutes. Do you have a team of data scientists at your fingertips? All People Analytics Enterprise Solutions customers get a custom Blueprint and ongoing support to get the most out of their data. As the final part of this challenge, I want you to ask your team this question, “Can we trust the data?” If your team is working tirelessly in spreadsheets or SQL, they can probably tell you exactly how those metrics were calculated. However, if you were using some other HR analytics reporting tools, you’re trusting a black box. Moving to One Model not only means you can get to the analysis you need in record time, but you also have a fully transparent platform that is adjustable to meet the specific requirements of your organization. Are you Stumped? Get a Demo: Regardless of where your organization is on the maturity scale, this “challenge” can help you determine the selection of the right people analytics key performance indicators and analyses for your business context. Arguably any strong people analytics function should be able to answer these KPI questions, but success is found in focusing on the questions that matter and will drive business outcomes. Take the #PeoplesAnalyticsChallenge and let us know how fast you can pull that information in your organization.
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