Workplace Stories by RedThread Research

Christine Crouch, Senior Director of Learning at General Mills, joins Workplace Stories to discuss a massive shift in how one of the world's legacy food companies approaches talent development. After years of operating in a deeply decentralized and siloed manner, General Mills has recently transitioned to a centralized and integrated learning model.In this episode, Christine lays out one of the clearest cases for centralization we have heard. While efficiency is a benefit, she argues that the true drivers are decision-making power and better data. By unifying the function, General Mills gains a stronger view of learning activity and business needs, creating the strategic infrastructure necessary for the future of work.You’ll hear how Christine’s team manages to be centralized without losing the "local feel" through a robust Learning Business Partner model. She also details how centralization unlocks the ability to correlate learning metrics with talent outcomes like retention and performance. Finally, Christine shares her philosophy on AI, not as a replacement for human connection, but as a tool to elevate the human side of learning.You will want to hear this episode if you are interested in...[06:07] Background on General Mills and its culture.[07:00] The shift from decentralized to centralized L&D.[11:11] How to make centralization feel local to business stakeholders.[18:30] The Learning Business Partner model explained.[21:07] Correlating learning metrics with talent outcomes.[27:58] Managing "rogue purchases" in a centralized model.[34:20] Why AI will elevate, not replace, the human side of learning.[47:35] Piloting AI coaching tools like "Nadia".The Strategic Case for CentralizationFor many organizations, the move to centralize L&D is purely a cost-cutting exercise. However, Christine frames the shift at General Mills as a play for better data and strategic decision-making. A centralized function provides a unified view of the organization's needs, allowing L&D to prioritize investments that drive enterprise-wide capabilities rather than just solving isolated functional problems. As AI accelerates, this strong data infrastructure is what will allow the organization to distinguish between what people actually need to know versus what can be offloaded to technology.The Learning Business Partner ModelCentralization often brings the fear of losing touch with the business. General Mills solves this through the "Learning Business Partner" role, individuals who sit on the leadership teams of specific functions or segments but report back to the central L&D organization. These partners act as a bridge; they understand the HR strategy and business plans of their specific function while ensuring continuity with the broader enterprise goals. They are expected to be performance consultants first, identifying the root problems to solve rather than just taking orders for training.AI: Elevating the Human ElementChristine’s approach to AI is grounded in optimism and human-centricity. She believes AI will not replace the human side of learning but elevate it. General Mills is actively piloting AI for tasks like personalization, automation, and coaching via a tool called "Nadia," which acts as an "always-on" coach. However, Christine emphasizes that deep skill building, like change leadership, still requires human connection, peer discussion, and the ability to "read the room," skills that AI cannot fully replicate. Connect with Christine CrouchChristine Crouch on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES

On the latest episode of Workplace Stories, we sit down with Koreen Pagano, author of "Building a Skills-Based Organization," to talk about one of the hottest and most complex topics in the world of work: how organizations can become truly skills-based, and what that really means in today’s rapidly changing, AI-driven landscape. The conversation was loaded with practical insights, candid stories, and wisdom from the front lines of workforce transformation.Koreen shares her journey from ed-tech and product leadership to guiding hundreds of organizations through the maze of skills transformation. We discuss the crucial front-of-house and back-of-house elements, from clear communication and partnership models to building the right data and technology infrastructure. You’ll hear fresh perspectives on using skills data as an early signal for retention, the shifting role of tasks versus skills, and what it means to future-proof your workforce for ongoing change. You will want to hear this episode if you are interested in...[05:17] Skills vs job architecture approaches.[10:04] Navigating skills-based organizations.[14:33] Workforce data challenges with AI.[23:04] Skills over jobs for strategy.[27:04] Building resilient data systems.[34:33] Building trust in skill data.[39:32] Predicting employee retention through data.[45:59] Helping organizations align AI transformation with business goals.Why Skills Still Matter in a “Task-Talk” WorldThere’s a persistent misconception that the age of “skills” has passed and that “tasks” offer a more practical lens, especially with AI in play. Koreen shares how, at a recent industry event, she heard professionals say, “We don’t need to worry about skills, we have to focus on tasks.” But she thinks that it’s misguided to abandon skills just when organizations are barely starting to understand and leverage them.While tasks describe the work to be done, skills reflect the underlying human (and sometimes machine) capabilities that make that work possible. Both are crucial, but without a foundational understanding of your organization's skills, mapping tasks is like building on sand.Front of House, Back of House, and Getting Skills RightWe need to balance “front of house” and “back of house” considerations when building a skills-based organization. Organizations often focus either on external communications, partnerships, and culture (front of house), or purely on technology, data, and infrastructure (back of house), but rarely both. Koreen is unique in straddling the two, and it’s this holistic approach, blending people and process with tech and data, that sets successful organizations apart.The Evolution of Data and the Rise of Skills VerificationOrganizations are beginning to realize that their skills data isn’t just about upskilling or reskilling; it’s tightly connected to business-critical outcomes like retention, performance, and the ability to adapt to market shifts. Koreen shares compelling examples of using skills data to provide early warning on issues like employee retention, demonstrating data-driven HR in action.She also shared her pragmatic “3Vs” model for validating skills data: Validity (how well the data measures what it claims to), Variety (different types of data from varied sources), and Volume (quantity and frequency of data collected). You can make solid business decisions with basic self-reported skills data, but for higher-stakes calls, like hiring, you need much more rigorous, validated information.Jobs, Skills, and the Trap of Static StructuresOften, organizations anchor their skills strategy to their job architecture. Consultants and technology vendors frequently push companies to start by mapping skills to static jobs. We discuss why this is a dangerous place to “end”, because jobs, roles, and the tasks that define them are changing faster than ever, especially with AI in the mix. Koreen advocates for designing skills data that is flexible, lives independently, and can be mapped to jobs and tasks as they evolve, never becoming held hostage by legacy structures.Goals Over TasksPerhaps the most powerful call to action was the need to focus less on micromanaging the “how” (a long list of tasks) and more on the “what and why”, the goals, outcomes, and genuine business objectives. In a future where work is constantly shifting, organizations that empower people around purpose, supported by dynamic skills data, will outperform those stuck mapping today’s tasks to yesterday’s job charts.Building a skills-based organization isn't a project with a tidy endpoint, it’s a transformation. As Koreen reminds us, it’s hard, messy, and as much about culture as it is about data. But for the organizations (and the people) willing to experiment, adapt, and keep skills at the center of strategy, the payoff is a workforce that’s ready for whatever comes next. Resources & People MentionedBuilding the Skills-Based Organization: A Blueprint for Transformation by Koreen Pagano Connect with Koreen PaganoKoreen Pagano on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES

In this episode, Stacia and Dani sit down once again with Cole Napper, author of “People Analytics: Using Data-Driven HR and Gen AI as a Business Asset.” A year after his first appearance, Cole returns with bold insights about the seismic changes facing HR and people analytics, and why now is the time to rethink how we define value in the workplace.Cole argues that the future of HR depends on shedding its transactional skin and embracing a new, data-driven paradigm. He discusses why traditional models like Dave Ulrich’s COE framework won’t survive the decade, how organizations can “discorrelate” from market forces by proving business value, and why fear, not technology, is the biggest obstacle to transformation. With sharp humor and evidence from his own research, Cole makes the case for a redefined HR: one that blends human strategy with AI-powered intelligence to drive growth, not just efficiency.You will want to hear this episode if you are interested in...[00:00] Building a new HR paradigm in the Gen AI era.[06:00] Why people analytics hit its “identity crisis” after 2022.[12:00] How to prove HR’s business value beyond metrics.[19:00] The decline of the Ulrich HR model and what replaces it.[24:00] The future of AI-driven workforce transformation.[33:00] The tension between the HR and finance worldviews.[46:00] Why data infrastructure is suddenly “sexy” again.[52:00] Three possible futures for HR in the next decade.Building a New Paradigm for People AnalyticsCole’s new book calls for a reset in how organizations use data, not as an isolated reporting function but as a business accelerator. He reveals how people analytics can move from being “scorekeepers” to strategic partners by tackling the questions behind the questions: Why is it happening? What should we do about it? His message is clear, analytics must tie directly to revenue, cost, or risk reduction, or it’s just a hobby.The End of HR as We Know ItCole predicts that the Ulrich model, the long-standing HR framework of COEs, service centers, and HRBPs, won’t survive the coming decade. As generative AI automates much of HR’s transactional work, only the strategic and human elements will remain. He and the hosts debate what should stay human and what can be delegated to machines, exploring the fine line between technological efficiency and organizational soul.AI, Accountability, and the Future of WorkCole cautions that while AI’s potential is vast, it cannot replace human accountability. Drawing a parallel with the evolution of chess, he argues that AI will transform HR’s “game,” not erase it. The goal isn’t to align around AI as a tool, but to use it to unlock entirely new possibilities in how we work, learn, and grow.Infrastructure, Not IllusionFor all the hype, Cole reminds leaders that the foundation of AI success lies in data infrastructure, “the least sexy but most essential lever.” Without it, organizations risk failure in the next wave of transformation. Investing in data quality, architecture, and scalability today determines who thrives, or disappears, tomorrow.Resources & People MentionedPeople Analytics: Using Data-Driven HR and Gen AI as a Business Asset by Cole NapperConnect with Cole NapperCole on LinkedInConnect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn Twitter

In this episode of Workplace Stories, we sit down with Lori Niles-Hoffman, global learning strategist, EdTech advisor, and author of The Eight Levers of EdTech Transformation. With over 25 years of experience implementing large-scale learning systems, Lori brings a no-nonsense, deeply human perspective to how organizations can thrive at the intersection of technology, data, and talent.Lori reveals why EdTech success isn’t about shiny tools, it’s about mastering eight foundational levers that determine whether your learning strategy creates value or chaos. From ecosystem thinking to stakeholder management, she explains how leaders can future-proof learning strategies through data, design, and disciplined experimentation.You’ll hear candid insights on how AI is reshaping L&D, not by changing the rules, but by exposing where we’ve been weak all along. Lori also shares why the “backend just got sexy,” and how the next competitive edge won’t come from beautiful interfaces, but from the quality of data and insights driving them.You will want to hear this episode if you are interested in...[00:00] The eight levers shaping EdTech transformation.[06:00] Lessons from 25 years in enterprise learning systems.[09:00] Why most L&D tech investments fail before they start.[14:00] The rise of data literacy and “sexy backends” in learning design.[17:00] Why clean data matters more than new tool.[24:00] A breakdown of the eight levers and how they work together.[29:00] Stakeholder management and ecosystem thinking in practice.[35:00] The new role of AI in exposing weak learning strategies.[39:00] Why skills, not titles, will define the future of learning.[41:00] The human side of transformation: keeping people at the center.The Future of Learning Isn’t About Tech, It’s About LeverageLori’s framework flips the script on how organizations approach learning transformation. Rather than starting with technology, she urges leaders to first clarify their target operating model, data readiness, and stakeholder relationships. The result? Smarter decisions, stronger credibility, and sustainable change.Her book’s eight levers, ranging from content strategy to ecosystem alignment, help leaders navigate the “medium term” (through 2028) of rapid evolution in learning technology. As Lori puts it, the goal isn’t to adopt AI or automation for their own sake, it’s to make learning adaptive, outcomes-focused, and undeniably relevant.Data, Ecosystems, and the “Sexy Backend”Forget fancy dashboards, Lori believes the true revolution is happening behind the scenes. As user interfaces disappear and voice or text prompts replace them, differentiation will come from data governance, interoperability, and predictive insights. The backend, she says, is now where strategy lives.She emphasizes that AI doesn’t change the levers, it exposes their weaknesses. The organizations winning in this new era will be those that invest in clean data, aligned systems, and smart stakeholder engagement.Skills as the Spine of the Future WorkforceAmong the eight levers, Lori highlights skills as the “spine” connecting every other element of learning strategy.She challenges L&D professionals to stop chasing shiny taxonomies and instead treat skills like a supply chain, measured, managed, and constantly replenished. The goal isn’t just mobility or efficiency; it’s resilience.Resources & People MentionedL&D Tech Ecosystem 2020Skills OddysseyLearning Strategy paperLori's bookConnect with Lori Niles-HoffmanLori on LinkedInConnect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES

Just two years ago, AI was a shiny new object in L&D, with most professionals dabbling in small pilots and content creation experiments. The latest findings reveal an inflection point: the majority of L&D teams are now actively using AI, not merely testing it.This week, on the podcast are Donald H. Taylor and Eglė Vinauskaitė, the minds behind a groundbreaking new report, "AI & Learning 2025: Race for Impact." We’re exploring the rapid changes AI is bringing to Learning and Development (L&D), from early experimentation to widespread implementation, and what it means for the future of work.In this conversation, you’ll hear about the three distinct futures for L&D departments, how AI is moving beyond simple content creation into qualitative analytics and adaptive learning, and why team culture and leadership are crucial for success. We also dig into some big philosophical questions: How do we keep humans at the center of tech-driven workplaces? And how will AI reshape the very definition of value in L&D?This episode is packed with insights, data, and stories from organizations at the forefront of change. So, get ready to rethink how learning happens and how impactful workplace transformation can be.You will want to hear this episode if you are interested in...[00:00] How AI is transforming Learning and Development.[05:40] Transition from experimentation to mainstream implementation of AI in L&D.[13:31] Debunking the maturity model.[16:03] AI integration culture in organizations.[25:07] AI's impact on L&D values.[38:54] Necessity for L&D to demonstrate clear impact and unique value beyond content.[47:36] Leadership Beyond the L&D silo.[52:25] Introduction of the “transformation triangle”: three potential strategic futures.The Rapid Evolution of AI in L&DAI usage still predominantly supports content creation and design, but there’s an intriguing rise in more sophisticated applications, especially data analysis, dynamic feedback, and even AI-driven coaching. For L&D leaders, the big question is no longer “should we use AI?” but “how can we use it to unlock deeper value for our organizations?”What Sets Successful L&D Teams Apart?A critical insight from the report is the role of mindset and organizational culture in successful AI adoption. Teams thriving with AI aren’t necessarily bigger or better-resourced; they are “open” teams, led by individuals who embrace risk, imperfect information, and proactive change. These leaders are comfortable experimenting without knowing all the answers, an essential trait for the current landscape.True transformation requires more than tech skills; it demands business acumen, a robust understanding of performance, and an ability to integrate learning with business strategy. L&D teams must move from being passive order-takers to strategic partners, actively shaping how people develop and perform.AI: Threat or Opportunity for Traditional L&D Roles?For some, the rise of AI in learning is unnerving. Tasks once considered core, like instructional design or content creation, can increasingly be automated, often cheaper and faster than before. Taylor cautions that unless L&D professionals shift their value proposition from content production to driving true impact, their roles risk being diminished or redefined.But there is an opportunity for L&D to expand its influence. Rather than being relegated to the background, teams can now focus on performance support, skills stewardship, and facilitating human growth, areas where strategic thinking and deep expertise are critical and cannot be automated away.Three Futures for L&D: Skills Authority, Enablement Partner, Adaptation EnginePerhaps the most provocative segment of the episode introduced three possible “futures” for L&D roles in the AI era:Skills Authority: L&D becomes the custodian of skills, owning skill taxonomies, plumbing, and strategic workforce development. This future demands advanced expertise in identifying, building, and tracking capabilities crucial to business success.Enablement Partner: Here, L&D empowers employees across the organization to create their own learning solutions. The team shifts from direct content delivery to building infrastructure, processes, and trust, letting expertise flourish where it’s needed most.Adaptation Engine: The most radical scenario, where L&D is absorbed into cross-functional teams focused on rapid business adaptation. Learning professionals blend with design, tech, and operations to solve holistic problems, making learning indistinguishable from broader performance improvement.While AI will eventually become as invisible as electricity, the human element in learning, facilitation, creativity, and stewardship remains paramount. The priority for leaders now is to harness AI thoughtfully, ensuring it serves genuine learning and performance goals rather than just delivering faster horses. Resources & People MentionedAI in L&D: The Race For ImpactAI in L&D (4 Reports) Connect with Donald H. Taylor and Eglė VinauskaitėEgle Vinauskaite on LinkedIn Donald H Taylor on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES