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Dive into the raw truth of HR analytics, why it’s all about storytelling backed by solid numbers. This episode uncovers how HR leaders can finally translate their human capital efforts into undeniable business value. Prepare to be inspired, challenged, and energized to rethink what your HR data can do!  Key Insights  The gap between HR stories and financial impact is real; HR needs to quantify their contributions.  Successful organizations are integrating HR metrics with business and financial data for compelling storytelling.  External benchmarks are critical to understanding where your organization stands are you best in class or in need of improvement?  Using visualization and advanced analytics makes complex data accessible and impactful for HR leaders.  Building tight collaborations with operations and finance is essential for accurate, meaningful HR metrics.  Small steps like analyzing turnover costs or onboarding ROI can start a powerful transformation.  HR must embrace a mindset of continuous measurement, storytelling, and adjusting based on macroeconomic shifts.  Investing in analytics tools and skills early helps HR lead from a position of influence and credibility.  Timestamps  00:00 - Welcome & intro to Schon Parris, HR data rockstar 02:45 - Schon’s musical side and leadership journey at ADP 03:58 - Helping HR quantify workforce value through analytics 04:40 - The gap between HR stories and quantifiable business impact 05:34 - Why HR struggles to show ROI like sales or operations 06:39 - Bridging HR and finance through better skills and tools 07:32 - How AI and advanced analytics are changing the game 09:02 - Turning HR metrics into financial and business outcomes 10:02 - The importance of collaboration in understanding turnover costs 11:01 - Performance metrics for hourly workers and ubiquitous data 12:13 - The challenge of rolling up workforce data in organizations 13:10 - Building business cases for HR investments 14:16 - The power of visualization and storytelling with analytics 15:04 - Using metrics to tell compelling, data-backed HR stories 17:15 - The importance of granular data to prevent surprises 18:30 - Small steps that HR can take to demonstrate value 20:10 - Putting the numbers into business language for leadership 21:43 - Using external benchmarks to inform strategy 23:08 - Visual storytelling to connect HR efforts with profitability 24:15 - Deep-diving into specific workforce segments 25:03 - Tracking HR impact continuously, not just quarterly 26:40 - The importance of contextualizing data within macroeconomic shifts 27:57 - Steps to start building a data-driven HR culture  Resources & Links  How to Measure HR’s Impact on Business  Power of Data Visualization in HR  Turnover Cost Analysis Tool  External Benchmarks for HR Metrics  Connect with Schon Parris  LinkedIn  Twitter  Final Thought  This episode is a rallying cry for HR leaders to step into their data-driven power. Metrics are no longer optional,they are the language of impact and influence. Start small, visualize boldly, and tell your stories with undeniable proof. Your workforce’s true value depends on it!

 Discover how a bold new approach to evaluating performance could revolutionize your organization. Jacob Chase shares groundbreaking insights on moving away from traditional systems to fully leverage collective intelligence, fairness, and meritocracy.   Main Topics Covered:  Why current centralized performance reviews are broken and how decentralization offers a solution  How stock market principles apply to internal organizational valuation  Building a culture of transparency through peer-to-peer feedback systems  Transforming pay equity via contribution-based assessments  Practical steps for leaders to pilot decentralized evaluation methods    Timestamps:  00:31 - Introduction to Jacob Chase and his background 01:34 - The story behind Infin and its purpose 02:23 - Fun fact: Jacob's chaotic car and the humor of parenthood 03:34 - The core topic: valuing organizational contribution beyond traditional pay structures 04:33 - What is pay equity in modern terms? 05:29 - The problem with centralized evaluation systems and the benefit of decentralized approaches 06:45 - How individual perspectives enrich performance assessment 08:27 - Learning from stock markets: decentralized valuation models applied internally 09:32 - Creating internal markets for credit attribution within organizations 10:00 - How collective intelligence can self-assess performance 10:46 - Safeguards and motivations in decentralized data collection 12:01 - Peer feedback, confidentiality, and fostering a feedback culture 13:21 - Cultural shift required for decentralized evaluation to succeed 14:01 - How performance data can shape careers and future growth 14:37 - Quantifying contributions versus narrative assessments 15:06 - Replacing traditional evaluations with real-time performance insights 16:20 - Using data to improve workforce decisions and recognition 17:05 - The econometrics of contribution and how it enables meritocracy 17:58 - The importance of true merit-based rewards and reducing bias 18:52 - Moving beyond incremental changes—wholesale transformation needed 19:12 - Practical steps for HR and leadership to pilot decentralized systems 22:01 - Starting with the executive team to build credibility 23:08 - Overcoming the fear of transparency and trust issues 24:06 - Long-term benefits: Fairness, transparency, and organizational excellence 24:44 - The power of fairness in motivating exceptional contribution 26:01 - Final thoughts: embracing decentralized performance for competitive advantage   Resources & Links:  Infin Platform  Stock Market as a Model for Internal Valuation  Performance Management Systems: Why They Fail  Build a Culture of Feedback    Connect with Jacob Chase:  LinkedIn  Twitter    Unlock the Future of Performance Management Today!  This isn’t just a reset, it’s a revolution. If you’re ready to empower your team, eliminate bias, and create truly fair compensation, start with a bold step: decentralized, contribution-based evaluation. The future is fair, transparent, and driven by collective intelligence. Will you lead the change? 

This episode dives deep into a critical issue that affects nearly 80% of the workforce, substance use disorder (SUD), and explores how HR professionals and organisations can lead the change. Get ready for an eye-opening conversation filled with practical steps, inspiring examples, and a powerful message: supporting employees through recovery is not just compassionate, it’s strategic. In this episode: Amy Dufrane reveals why substance abuse is a silent epidemic impacting organizations across all sectors The startling statistics surrounding SUD and its toll on productivity and healthcare costs How organizations are pioneering recovery-friendly workplace certifications and initiatives Practical advice for HR on cultivating a supportive, stigma-free environment The importance of education, policies, and manager training for long-term organizational health Resources for organizations to implement real change—without reinventing the wheel Timestamps: 00:00 - Welcome and introduction to Amy Dufrane, CEO of HRCI 00:24 - Amy’s background and passion for HR’s evolution 02:09 - Why substance use disorder is a critical issue for HR and employers 04:01 - The impact of SUD on productivity, turnover, and healthcare costs 05:28 - Understanding SUD as a chronic condition, not a choice 06:23 - How HR can start addressing substance abuse in the workplace 07:11 - Navigating HIPAA and legal considerations around employee health disclosures 08:39 - Partnering with organizations like Global Recovery Initiatives Foundation for education and certification 10:00 - The role of company certification and building a recovery-friendly culture 11:14 - Why leadership commitment is essential for change 12:44 - The importance of manager training and creating safe communication channels 15:08 - Overcoming organizational culture and resource barriers 16:08 - The long-term investment in employee wellbeing and organizational health 17:00 - The non-legal, human-centered approach to supporting employees in recovery 17:59 - How organizations can get started with certification and resources 21:07 - Practical first steps for HR and leadership 22:24 - The importance of proactive, organizational commitment over reactive responses 23:05 - Final advice for CHROs and leaders to prioritize this issue 23:44 - Gratitude and closing thoughts. Resources & Links: National Recovery Friendly Workplace Institute — Certification and tools for creating recovery-supportive workplaces HRCI — Certification and education for HR professionals White House Initiative on Substance Use — Government leadership in supporting workplace recovery efforts Connect with Amy Dufrane: LinkedIn Twitter Take Action: Start today by educating your leadership and HR team about SUD Explore certification programs to build a recovery-friendly culture Implement ongoing training for managers to recognize and support employees Remember: your organization’s health depends on your compassion and commitment. Let’s break the stigma and embrace a future where recovery is supported and celebrated.

Get ready to challenge the status quo. In this episode, Jess von Bank and David Turetsky confront the fast-paced AI revolution, urging us to see beyond profit and speed. They reveal why women’s voices should lead our design decisions, advocating for a human-centric approach in a world speeding towards automation and loss of trust. In this episode: Why current AI development prioritizes efficiency over human values The critical need for women to be at the center of AI design and decision-making How capitalism’s extraction model is hollowing out jobs across demographics The dangers of unregulated AI—bias, privacy breaches, and ethical mishaps Examples of AI’s impact in HR—from recruitment to unconscious bias The importance of governance, transparency, and interruptibility in AI systems Practical ideas for democratizing skills and opportunities through AI How to shift from reckless adoption to intentional, human-first AI strategies   Timestamps: 00:00 - The mission to center womenin AI design and HR innovation 02:05 - Jess von Bank’s journey from talent practitioner to industry analyst 06:21 - Why fast AI development risks sacrificing human values 09:01 - The false promise of EQ-focused AI and the need for broader perspectives 10:07 - Designing for safety and well-being: lessons from parenthood and Maslow’s hierarchy 13:34 - Rethinking social media and AI with a human lens in HR tech 16:21 - The hollowing out of middle and entry-level jobs due to AI 17:19 - Demographics impacted by AI-driven job displacement and systemic inequality 20:16 - The role of governance in protecting human interests and privacy 22:39 - The risks of unchecked data collection and the “out-of-control” AI genie 25:06 - The hidden costs of convenience—the loss of trust and control 30:34 - Rethinking success: measuring meaningful progress, not just adoption 34:41 - Real-world examples: democratizing recruitment through AI and reducing bias 37:08 - Opportunities to support displaced workers with AI-driven skill matching 39:39 - The call for slower, human-centered AI innovation to avoid future catastrophe   Resources & Links: Book: The Future of Work by Jack Zenger Jess von Bank - LinkedIn | Twitter Capita AI Governance Framework HireVue video interview platform TikTok’s addictive content studies   Connect with Jess von Bank: LinkedIn Twitter Join us in reshaping HR and AI—center human values, demand transparency, and slow down the rush. Our future depends on it.

In this electrifying episode, Charlene Li shares her insights on how AI is transforming HR strategies, leadership, and the very way we define jobs in this rapidly evolving landscape. Get ready to rethink what’s possible and how you can take immediate steps toward an AI-empowered future.Key Topics: Why start AI initiatives with your business strategy, not the technology itself How AI can support and revolutionize HR functions like recruitment, team building, and workforce planning The importance of asking the right questions to harness AI effectively Rethinking "entry-level" in the age of automation and AI-enabled skills Building a foundational, invisible layer of AI that drives everyday workflows without flashy interfaces The ethical responsibility of HR to lead AI adoption responsibly and transparently The shift from traditional roles to "superhuman" workers enhanced by AI tools Strategies for HR leaders to prepare their teams for AI-driven change The critical need for deep conversations with vendors and internal teams to shape meaningful AI solutions Curiosity and critical thinking as the ultimate skills in the AI era Winning with AI: The 90 Day Blueprint for Success Charlene Li - Website OpenAI - Developer Resources Perplexity AI LinkedIn Twitter Timestamps: 00:00 - Welcome & Introduction to Charlene Li’s background 02:00 - Disruptive transformations and the leadership needed for AI success 06:00 - Where to start with AI in HR and aligning with business strategy 08:00 - Rethinking HR processes and outdated data practices 11:00 - The role of nuanced skills and team chemistry in a new AI-powered workplace 12:45 - How AI tools assist in hiring, team collaboration, and decision-making 19:00 - Human in the loop vs. automation – when and how to let go 20:40 - Redefining the role of humans in AI-enhanced organizations 24:00 - The strategic role of HR in AI ethics, transparency, and future workforce development 28:00 - Building an AI roadmap, vendor conversations, and responsible adoption 31:00 - The skills needed to ask the right questions in the AI age 34:00 - Experimenting, failing fast, and continuous learning with AI 36:00 - The importance of curiosity, imagination, and specialized expertise 36:30 - Almost out of time, a recap of Charlene’s book, Winning with AI 37:13 - Final thoughts & actionable steps for HR leaders to lead AI transformationResources & Links:Connect with Charlene Li:Call to Action: Don’t wait for the future to arrive — start asking better questions today! Grab Charlene Li’s Winning with AI to kickstart your 90-day strategic plan. Lead your organization boldly into this new era, because your role is more crucial than ever. The future of HR is here — are you ready?

Discover the transformative power of applying Amazon’s working backwards framework to HR. This episode unpacks how HR leaders can turn employees into loyal customers and leverage AI to create impactful HR products that truly delight. If you're ready to revolutionize your HR tech game, listen now! Timestamps:00:00 - Introduction to applying Amazon’s customer obsession in HR02:00 - Historical perspective: Dell’s direct approach as employee-internal customer model06:00 - Justifying HR technology investments with ROI examples from compensation software11:00 - The five questions of the working backwards framework12:00 - Constructing a true customer persona & insights from HR data15:00 - Defining the core customer problem in HR: Building confidence in managers16:30 - Crafting solutions & benefits — example of an AI-powered coaching tool19:00 - Writing the future press release & internal FAQs to clarify the product vision21:00 - Iterative testing & how to involve stakeholders in feedback cycles24:00 - Measuring success & validating assumptions through prototypes & beta tests26:00 - How AI accelerates customer understanding & innovation in HR28:00 - Making HR a product team: influencing leadership & fostering customer obsession30:00 - Conclusion: Start small, ask questions, test assumptions, and keep the customer at the heart

Are you ready to feel the heartbeat of what's next in HR technology? In this episode, Oz Khan from ADP Ventures pulls back the curtain on how AI is transforming workflows, building trust, and reshaping the very fabric of work. This isn’t just talk — it’s a revolution happening right now, and you need to hear it. In this episode: The evolution from AI assistance to autonomous workflow execution Why HR is shifting from co-pilot to control tower — and what that means The critical importance of trust, compliance, and risk management in AI adoption How enterprise complexity and trust influence product development and investment The overlooked power of judgment — why human experience remains priceless The strategic focus of investors and founders navigating AI’s wild waters Real-world examples: ADP’s scale, the impact of startups like Naya and Emma The role of people, process, and tech — and how they coexist in solving real HR problems Timestamps: 00:00 - The pulse of HR innovation — what’s coming next 02:10 - How ADP’s labs culture sparked real growth 05:10 - Oz shares a fun, surprising fact about himself 06:10 - The seismic shift from AI tools to workflow automators 08:25 - How stability and proven value shape HR tech adoption 09:42 - The co-pilot becomes the control tower — deep dive 11:00 - APIs, data connectivity, and solving enterprise complexity 12:44 - Navigating compliance, risk, and the law in HR AI 13:51 - Why generative AI isn’t ready to replace humans yet 15:54 - The real challenge of trust: transparency, training, guardrails 17:46 - The importance of judgment and experience in AI-driven decision making 20:40 - Building confidence with high-fidelity, deterministic AI solutions 23:38 - The last mile decision — where human judgment still rules 26:11 - The dangers of overhyping AI’s potential — and the truth 29:52 - Education, skills, and the demographic shifts AI will bring 33:53 - The art of flexible, configurable HR tech — how founders navigate ‘craft’ 37:16 - From $1M to scale — what it takes to grow AI-driven HR solutions 42:56 - Real-world impact — ADP’s investments in Naya, Emma, and beyond 43:38 - The human side: solving emotional and organizational problems, not just tech 44:22 - The future is OpenClaw and beyond — what’s next in AI bots Resources & Links: Naya — Transforming benefits decisions at scale Emma AI — Agentic platform powering workflows ADP Ventures — Driving innovation in HR tech Data Cloud Stanford Research — Insights on entry-level hiring and labor shifts ADP — Join the leaders in HR and payroll solutions Connect with Oz Khan: LinkedIn Twitter This isn’t just a conversation — it’s a call to action. Whether you’re in HR, investing, or building the future, you’ve got to understand the truth about AI’s power, limits, and the human judgment that will always be king. Don’t get left behind. Your next big move is waiting — listen now, and be part of the revolution!

Are we truly prepared for the dark side of AI in talent acquisition? In this episode, my great friend, Dara Brenner from Employ drops truth bombs about candidate fraud, the evolution of AI governance, and how organizations can stay ahead in this high-stakes game. If you're a leader in HR or recruiting, this is your wake-up call—trust me, you’ll want to hear this. Here is the link to the fund set up for Dara's late husband: Please click here. In this episode: The shift from traditional to AI-native hiring tech—what it really means How candidate fraud costs businesses $600 billion—yes, billion Layers of fraud detection: Swiss cheese analogy explained The role of IBM Watson in transparency and compliance The future of governance—code as the new rulebook Balancing trust and talent pool access in a hyper-suspicious world Why proactive planning for societal shifts is vital in workforce strategy Dara’s personal story: turning tragedy into impact with a brain tumor foundation Resources & Links: IBM Watson X Governance Learn about the brain tumor foundation Book: "AI Superpowers" by Kai-Fu Lee Dara Brenner on LinkedIn Connect with Dara: LinkedIn Twitter Timestamps: 00:00 - Introduction: The urgent need for trust in AI-driven hiring 02:08 - Dara Brenner’s background and journey through HR tech 03:20 - The fun side: Dara’s unexpected past as a restaurateur 05:45 - The impact of personal tragedy: Creating a foundation for brain tumor support 08:34 - The hidden threat: Candidate fraud in the age of AI 09:49 - How AI can be used nefariously in recruitment 10:56 - Layers of fraud detection: From resumes to deep fakes 12:01 - The staggering cost: $600 billion from resume fraud 14:26 - Organizations’ vulnerabilities: North Korea, bad actors, and real risks 15:36 - Balancing security with talent access: Where to draw the line 22:34 - Governance and compliance: IBM Watson’s role in transparency 23:46 - Constant AI audits: Like having a doctor in your pocket 28:31 - Future of recruitment: From ATS to AI-native systems 29:55 - Building AI into the DNA from day one—code as policy 32:29 - The evolving role of recruiters: proactive, strategic, data-driven 33:53 - Societal impacts: Demographics, immigration, and big-picture workforce planning 36:10 - Dara’s parting wisdom: Evolving trust, governance, and human oversight Final thought:The future of hiring is not just about smarter algorithms—it's about building a trustworthy system where technology and humanity work hand in hand. Stay vigilant, stay proactive, and never stop asking: are we doing this right? Because the stakes couldn’t be higher.

Are you tired of dealing with outdated recruiting strategies? Wondering if AI can truly revolutionize hiring? This episode dives into the gritty truth about how modern metrics and emerging AI tools are reshaping talent acquisition—sometimes for better, sometimes for worse.Join us as we unpack decades of recruiting wisdom, the pitfalls of cost-per-click, and what’s next in HR tech. In this episode: The history of traditional job advertising and its limitations How cost-per-application models are changing the game The messy reality of defining "qualified" applications and why subjectivity matters The myth of AI as an unbiased recruiter and its legal risks Why transparency in pay and job descriptions can fix much of the hiring chaos The dangers of scaling bad processes and how to avoid scaling mistakes Practical insights on choosing the right metrics for your hiring needs The future of AI in recruitment and the importance of process over technology Useful links: College Recruiter Work Defined Podcast Network Ultimate Guide to Recruitment Metrics Artificial Intelligence in Hiring – Industry Report The Future of Pay Transparency Reach out to Steven Rothberg: LinkedIn Twitter Timestamps: 0:00 - Welcome and episode overview: Are recruitment metrics still holding up?00:42 - Introducing Stephen Rothberg and college recruiter’s journey01:14 - The roots of traditional recruiting: From flyers to newspapers02:25 - Starting a business from a summer job and risk-taking mentality03:52 - The Winnipeg Jets story: Childhood risks and lessons in boldness05:23 - The shift from inefficient to performance-based ad models06:49 - The real meaning of "click" and the confusion across platforms08:13 - The rise of cost per application and its emotional impact on employers09:54 - Defining "qualified applications"—subjectivity and its pitfalls11:35 - Why scaling bad processes makes them worse13:08 - The evolution of pay-per-click and undisclosed definitions14:54 - The deadly cycle of bad job descriptions and reposting16:23 - How hiring for "fit" often misses the mark and costs real money17:10 - Qualification in hiring: Who judges? The subjectivity of recruiters18:29 - Scaling broken processes: The airplane manufacturing example19:54 - The quiet cost of bad candidate sourcing: The ATS funnel22:17 - The dangerous hype around AI and its current limitations in hiring23:12 - The black hole of AI decision-making and lack of transparency26:24 - The importance of honest job descriptions and pay transparency28:43 - Do employers prefer CPC, duration-based, or new models?30:01 - The chase for quality candidates and the costs involved31:27 - How to effectively invest in recruitment—long-term wins over shortcuts32:28 - The impact of AI on assessments and candidate matching35:55 - The legal peril of AI-driven hiring decisions and audit trail challenges37:25 - Final thoughts: Embracing process, transparency, and smart metrics

In this episode, we explore how artificial intelligence is revolutionizing HR, with a focus on building trust through data privacy and security. Join us as we discuss practical steps, emerging challenges, and the evolving role of HR professionals in the AI era. Key Topics: The importance of foundational data quality before implementing AI in HR Securing sensitive employee data and managing privacy concerns The role of semantic layers and data organization for effective AI use How AI impacts HR workflows and transforms knowledge work Practical approaches to integrating AI responsibly and securely Education needs for HR to understand AI risks and opportunities Future trends: AI's potential to reinvent HR practices, not just automate Resources & Links: Fuel 50 - Workforce Mobility and Talent Pipelines Amazon - Book: Data Privacy and Security in the Cloud Flurry - Official Website Amazon Bedrock - AI Model Service Anthropic - AI Safety and Privacy Guarantees OpenAI - Responsible AI Use Connect with Brian Platts: LinkedIn Twitter Timestamps:  00:30 - Welcome and introduction to the episode 01:15 - Brian Platts’ background in HR and software 02:08 - Flurry’s mission to make data meaningful for HR 03:26 - Fun fact: starting career driving a semi truck 04:44 - AI in HR: privacy, security, and data foundations 05:53 - Preparing your HR data for AI adoption 06:08 - Challenges with data quality and use cases 07:08 - Security considerations: private vs. public data 08:22 - Trusting AI vendors and data-sharing risks 09:15 - Teaching AI to query data securely 10:07 - Data organization and semantic layers 11:29 - Improving chatbots and avoiding misinformation 12:26 - Ensuring process accuracy and data integrity 13:14 - Sharing vs. protecting employee data 14:05 - Re-implementing permissions in AI-driven systems 15:01 - Education and awareness around AI security 16:13 - Learning from SaaS security issues during early cloud adoption 17:18 - HR’s role in AI education and safeguarding IP 18:14 - Balancing productivity gains with security controls 19:06 - AI’s impact on HR future: automation and new workforce roles 20:16 - The concept of the “Meat Layer” and human-AI collaboration 21:02 - Will AI replace HR jobs or empower them? 22:16 - The limits of current AI technology and future innovations 23:03 - Analogies: AI as a horse and the importance of tooling 24:06 - Embracing AI to enhance human work rather than replace it 25:16 - Reinventing HR processes beyond IT-led automation 26:18 - Regulatory challenges and incremental HR AI adoption 27:30 - How HR can lead responsible AI integration 28:03 - Final advice for HR professionals: think broadly and connect the dots

In this episode, we dive deep into the challenges and opportunities of HR data governance, exploring how organizations can improve data quality, ownership, and usability in a rapidly evolving AI landscape. Join us for practical insights from seasoned HR analytics experts on building a data-driven culture that supports strategic decision-making. Key Topics: Why HR data is often unreliable and the impact on decision-making The role of ROI and cultural mindset in improving HR data quality The importance of ownership, stewardship, and clear definitions in data governance How AI and machine learning magnify data quality issues if governance is lacking Practical steps to start building your HR data governance framework The critical role of documentation, data catalogs, and system integration Common pitfalls: managing multi-system data consistency and avoiding errors Quick wins: focusing on key metrics and stakeholder collaboration Timestamps: 00:00 - Introduction: Why HR data governance matters today 02:30 - Challenges HR faces with data quality and accuracy 06:15 - Why organizations struggle to demonstrate ROI from HR data 09:00 - Cultural and mindset barriers to effective data management 11:00 - The impact of AI and machine learning on HR data quality 12:30 - Context and system integration challenges across HR tech stack 15:11 - Defining HR data governance: Ownership, stewardship, and quality 17:00 - Creating a data glossary and system of record for HR data 19:05 - Real-world examples of poor HR data visibility and audit issues 21:00 - Using chatbots and AI: risks, benefits, and data consistency 24:00 - The importance of documentation and version control in AI applications 27:40 - Practical steps to start your HR data governance journey 30:00 - The significance of aligning metrics and defining owners 33:00 - Building a culture of data excellence and quick wins 36:00 - Addressing expectations for pristine data and managing realities 37:00 - Final recommendations for HR leaders to improve data governance Connect with Guests: Raswinder Singh - LinkedIn | Twitter Ankit Abrol - LinkedIn | Twitter

🚀 Dive into the future (at least the next 6 months) of HR with the latest episode of the HR Data Labs podcast! In the Season 10 recap, host David Turetsky explores the evolving landscape of compensation, strategy, and people analytics. We recap the current Season 10, where we discuss addressing training gaps, the impact of AI in HR, and other cool episode topics. Then we review our prediction for the past 6 months and make bold predictions for first 6 months of 2026. Join us for a thought-provoking discussion that prepares you for the challenges and opportunities ahead. #HRInnovation #FutureOfWork #HRDataLabs

Join host David Turetsky and guest Paul Reiman from Novo Insights as they delve into the dynamic world of compensation strategies and pay transparency. Discover how regulatory changes in the US and Europe are shaping the landscape, the critical role of job documentation, and the impact of technology in fostering transparency. Tune in for insightful predictions for 2026 and learn how political climates may influence future pay transparency laws. Chapters Introduction and Guest Introduction Compensation Strategies and Pay Transparency Regulatory Changes in the US and Europe The Role of Technology in Transparency Predictions for 2026 Conclusion and Final Thoughts Quotes: "Job documentation is crucial for pay transparency." "Regulatory changes are reshaping the compensation landscape." "Expect a shift in compensation survey methodologies by 2026." "Technology plays a key role in enabling transparency." "Implementing pay transparency presents unique challenges." "2026 will bring significant changes to HR practices." "Adapting to regulatory changes is essential for success."

Craig Friedman, Talent and Skills Transformation Leader at St. Charles Consulting Group and author of Enterprise Skills Unlocked, joins us this week to discuss the shift toward skills-based organizations. He breaks down how data-driven transformations allow companies to move from simple headcount management to true capability management. Craig also shares practical advice on how to prioritize skills projects to ensure they solve real business problems and deliver ROI. [0:00] Introduction Welcome, Craig! Today’s Topic: How Skills Data is Transforming HR into True Business Partners [5:05] What does a skills-based transformation look like in practice? Shifting the talent process from an exercise in headcount management to an exercise in capability management. Moving away from static "boxes on an org chart" to using granular data that supports the entire talent infrastructure. Leveraging skills data that lives in both business systems (capabilities) and people systems (individual skills) to better align with business functions. [11:57] How different teams leverage skills data differently Why L&D teams need granular skill details, while staffing teams prioritize context on scope and scale for compensation purposes. The importance of creating an enterprise data taxonomy where different departments can agree on a skill but append their own metadata. Using machine learning to handle the searches, connections, and adjacencies required to make the data useful across teams. [26:14] The impact on Learning and Development (L&D) How real-time skills gap analysis simplifies curriculum redesign when jobs or organizational structures change. The growing need for assessment and validation to verify skills learned through informal methods like coaching or on-the-job experience. Identifying business cases where skills can make a clear difference and prioritizing them based on value and risk. [36:20] Closing Thanks for listening! Quick Quote “A lot of the reason we're doing this now when we couldn't do it before is because of these more advanced tools in data analytics and AI and machine learning that actually help us manage data at that scale.” Link to Craig's book: https://a.co/d/0naqmvh

🚀 Exciting changes are coming in 2026! Join David Turetsky as he shares his vision for HR Data Labs, focusing on positivity and growth. Discover how we're merging brown bag lunches into our podcast and launching something new for HR Data Labs. #HRDataLabs #2026Vision #Positivity Chapters 00:00:34 Introduction and New Directions 00:01:42 David Turetsky's Personal Goals 00:03:59 HR Data Labs Evolution 00:06:19 HR Data Doodles news