Episodios

  • Designing Future Narratives in a Changing Workplace: Lisa Kay Solomon and Jeffrey Rogers
    Apr 15 2026
    In this episode, we welcome Lisa Kay Solomon, designer-in-residence at Stanford's d.school and host of the "How We Future" podcast, and Jeffrey Rogers, principal of Learning and Facilitation at Radical and co-founder of Projectory. We discuss why foresight—the ability to anticipate and design the futures we want—is everybody's job, not just the domain of senior leaders or specialized futurists. They challenge the idea that organizations operate on an "official future" built from unexamined assumptions, and explore how narrative shapes both our approach to work and our readiness for rapid change, especially in the face of AI disruption. You will want to hear this episode if you are interested in...[00:00] Rethinking future-focused leadership[03:39] HR's evolving role in shaping the future[07:18] Understanding contested narratives and the potential to challenge them [21:50] The importance of adopting futures thinking through broad learning across multiple perspectives[25:47] Strategic foresight and future practices[35:13] Rethinking knowledge and learning priorities[39:21] Reflecting on AI adoption barriers[47:08] Helping leaders develop future-oriented skills[51:14] Looking ahead to the futureThe Leadership Muscle We Forget to UseOne of the most powerful ideas to emerge from the conversation is that of foresight as a "leadership muscle." Most leaders are trained and incentivized to focus on quarterly results and annual plans. The urgent often squeezes out the important, leaving little room for the kind of long-term, strategic thinking that anticipates disruption rather than simply reacts to it.Foresight isn't someone else’s job—it's every leader's job. Yet, most organizations have let this muscle atrophy. Through scenario planning and immersive exercises like those facilitated at last year’s Summit, the hosts argue that HR and organizational leaders can rediscover the collective ability to inquire, imagine, and influence the future, rather than endure it.Challenging the "Official Future" and the Power of NarrativeEvery organization operates on an "official future," a set of unspoken assumptions about what tomorrow holds. In stable times, these guiding narratives are rarely questioned. But when the world is in flux, from technological disruptions like AI to geopolitical shocks, such narratives become vulnerabilities.Leaders, especially in HR, have a responsibility to both recognize and challenge prevailing stories about the future. Wherever there’s a narrative, there’s also the possibility for a counter-narrative, and organizations need to cultivate the skill of holding multiple possible futures in mind, letting diverse perspectives inform strategic choices rather than defaulting to inherited assumptions.Building Organizational Foresight: Tools, Skills, and CommunityThe value of events like the Red Thread Summit lies in three core takeaways: the experience of stepping back to envision the future, a toolkit of practices that can be applied immediately, and the creation of a community dedicated to learning and experimentation.There are three critical skills:Recognizing the narrative: Are you taking assumptions as fact, or seeing them as just one possible story?Crafting your own narratives: Are you able to articulate clear, alternative futures?Communicating vision: Can you equip others to see and believe in those visions?Perhaps nowhere is the need for foresight and narrative-shaping more acute than in the realm of AI and automation. Today’s leaders are under immense pressure to adopt and justify new technologies, to navigate uncertainty, and to avoid being blindsided by change.A key theme is the emerging digital (and AI) divide: those who are experimenting, learning, and shaping technology are pulling ahead, while those waiting for certainty risk being left behind. Learning, experimentation, and cross-pollination are essential. Creating the Conditions for Resilient FuturesRather than chasing after blueprints or one "correct" answer, try to cultivate a design mindset: creating organizational conditions in which new ideas and approaches can flourish. This means expanding our definition of leadership to include not just the preservation of knowledge, but the nurturing of curiosity, experimentation, collaboration, and adaptability. Resources & People MentionedPeter DruckerArticles by Lisa Kay Solomon Pascal Finette on LinkedIn Implications WheelView from the Future at Stanford d.school Hazel HendersonConnect with Lisa Kay Solomon and Jeffrey RogersLisa Kay Solomon on LinkedIn Jeffrey Rogers on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES
    Más Menos
    53 m
  • How Workplace Culture Shapes Business Success: Ron Storn
    Apr 1 2026
    This week, we’re sitting down with Ron Storn, Chief People and Culture Officer at Truckstop, to discuss culture—how it forms, who owns it, and how it scales in growing organizations. We explore the relationships between systems, processes, and cultural values, and discuss signs of cultural breakdown and the keys to recovery. We also discuss how AI is reshaping workplace dynamics, hiring practices, and performance management, and Ron offers practical, research-based insights and strategies for understanding and supporting positive workplace culture. You will want to hear this episode if you are interested in...00:00 How company culture is formed09:19 Building strong HR and leadership systems11:54 Creating a positive culture for business success18:59 Scaling and preserving company culture22:53 Defining team behaviors and principles29:26 Aligning culture with decision-making32:13 Signs of a broken workplace36:50 Challenges with management and team culture41:45 Advantages of remote vs in-person work44:56 AI's impact on workplace cultureDefining CultureSome companies treat culture as little more than a list of values on the wall, disconnected from the day-to-day decisions and actions that define what it’s really like to work there. Ron believes culture is best understood as a set of shared behaviors, decision rights, and expectations to determine how a company actually executes its strategy when no one is watching. It’s how decisions are made, how people are hired or rewarded, and how work gets done when leadership isn’t in the room.In smaller organizations, culture often starts with a clear vision or set of norms, and systems are built around it. As organizations scale, systems and practices increasingly shape (and sometimes reshape) the prevailing culture, the challenge is finding ways to make culture systemic, woven into processes, rewards, and leadership behaviors, so that the company’s values endure as it grows.Who Owns Culture? Leadership, HR, and SystemsWhile HR is often perceived as the “owner” of culture, Ron believes it should be a shared responsibility, with ultimate ownership being at the very top. CEOs and founders define and embody desired cultural norms, while executive leaders model and cascade those norms through decisions and behaviors. HR’s role is to craft the mechanisms for how people are hired, evaluated, and developed to reinforce the company culture at scale. If only HR champions culture while leadership pays lip service or models different behaviors, culture will break down. Everyone, especially managers, must reinforce and live the culture for it to endure.Signs of Cultural Erosion and How to RecoverWhen culture unravels, it’s usually a gradual process, increasing decision friction, high performers becoming disengaged, and inconsistent behaviors creeping in across teams. If left unchecked, the result is a loss of trust, bureaucracy, and top talent walking out the door.Recovery is possible, but it needs radical transparency and recommitment.Ron recommends that organizations in crisis go back to their roots and principles, engaging teams in candid conversations about what must change. Leaders should model vulnerability, drive clarity on decision-making and expectations, and ensure every manager is accountable for rebuilding the cultural fabric. Resources & People MentionedTruckstop.com Connect with Ron StornRon Storn on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES
    Más Menos
    56 m
  • A Culture of Development at the Federal Reserve Bank of New York: Jenna Filipkowski
    Mar 18 2026
    On this episode, we’re with Jenna Filipkowski, the Head of Learning and Development at the Federal Reserve Bank of New York. With a background in organizational psychology and research, Jenna brings a fresh, outsider perspective to the world of L&D, challenging traditional approaches and driving innovation within the unique environment of the Fed.We discuss the importance of team development over individual learning, the shift from self-directed "Netflix of learning" approaches to more guided, in-person experiences, and the crucial role of branding and communication in building credibility for L&D organizations. You will want to hear this episode if you are interested in...00:00 Team-based learning evolution05:06 Improving the workforce experience07:59 Embracing opportunity in HR leadership15:46 Team coaching as facilitation19:56 Aligning learning with business goals25:40 In-person vs. virtual leadership training33:12 Improving organizational learning through data37:46 Cohesive branding and storytelling40:20 Leadership accountability and developmentFrom Individual Focus to Team DevelopmentHistorically, L&D programs have targeted individual upskilling and career navigation. At the Federal Reserve Bank of New York, Jenna Filipkowski is pioneering an approach grounded in 6 Team Conditions, a research-backed model that moves beyond one-off workshops.Her Energize program uses diagnostics, assessments like Hogan and Insights Discovery, and customized workshops to identify and strengthen the underlying conditions for team success. Rather than a one-size-fits-all or quick-fix model, teams undergo a tailored process, allowing for deeper systemic improvement. It’s about giving teams the tools and support to accelerate their performance because they’re set up for success, not just treating every challenge as an off-the-shelf problem.The Death of Netflix of LearningFor years, L&D has been swept up by the promise of Netflix learning, providing endless on-demand content and empowering employees to self-direct their learning journeys. But this laissez-faire model has started to unravel, because organizations and individuals are craving more structure and intentionality. At the New York Fed, the move to in-person, cohort-based programs is intentional. In-person learning provides social connection, time to focus, and shared experience, resulting in deeper reflection and lasting impact. While technical upskilling may still leverage digital and asynchronous methods. Blending modalities based on program intent, not defaulting to digital just because it’s easier.Branding L&DStanding out in a large, multifaceted organization is a challenge for any L&D team, and Jenna’s approach is to treat L&D as a brand. Programs at the Fed share unified branding with cohesive names and visual identity, making offerings memorable and fostering a sense of exclusivity and aspiration.Branding goes hand-in-hand with effective communication. Frequent roadshows, town halls, engaging graduation ceremonies, and leadership conferences help communicate value not only to employees but also to senior leadership. Measurement and AccountabilityAt the Fed, Jenna and her team use a mix of reach, participant demand, stakeholder feedback, and practical business cases solved to demonstrate L&D’s value. They push to correlate L&D participation with metrics like engagement and retention—demonstrating impact beyond traditional learning outcomes. The vision for the future includes more robust, passive data collection and real-time intelligence—but for now, using multiple data sources creatively is key.As workplaces shift once again, the future of L&D will center on three things: helping people grow in their roles, building strong leaders, and fostering connection through learning alongside others. The journey away from content chaos and toward strategic, human-centered, and measurement-driven L&D is just beginning. Resources & People MentionedHogan Development Survey Insights Discovery® 6 Team ConditionsConnect with Jenna FilipkowskiJenna Filipkowski on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES
    Más Menos
    47 m
  • Strategic Workforce Planning: David Edwards
    Mar 4 2026
    Strategic workforce planning is back, and not in a nostalgic “this trend is back around” kind of way. It is back because the old staffing model, react late, hire fast, hope the market delivers, is failing more often than it works. The biggest misunderstanding is still the same one: strategic workforce planning is not long-term headcount forecasting. It is not a spreadsheet exercise dressed up with better visuals. It is a business discipline that exists for one reason, to stop leaders from committing to strategies the workforce cannot deliver.In this episode of Workplace Stories, David Edwards, author of The Strategic Workforce Planning Handbook, lays out a definition of SWP that is refreshingly usable. Strategic workforce planning is workforce planning for the strategic things in the organization, not an attempt to plan the entire workforce. That single shift makes SWP more approachable, more realistic, and far more effective.If you have not listened yet, this is one of those episodes worth hearing end-to-end. The conversation is practical, occasionally blunt, and full of the kind of “this is what actually happens inside companies” detail that most workforce planning content avoids.You will want to hear this episode if you are interested in...[00:00] A clearer, more usable definition of strategic workforce planning.[00:43] Why SWP is back right now.[03:20] How SWP supports scenario thinking without false precision.[09:50] The questions SWP must answer to be useful.[11:40] Uncertainty, talent scarcity, and skills half-life as drivers.[14:30] Why SWP is an exercise in ambiguity, not certainty.[17:20] Why SWP works best as a business process, not an HR project.[20:05] What HR should do if it is not included in strategy conversations.[22:00] How to define “strategic” beyond leadership roles.[25:10] Why tasks matter more than skills for future work.[28:00] The contextual data missing from most workforce planning.[31:15] How AI forces better workforce planning questions.[41:20] What happens when SWP forces leaders to narrow priorities.[45:30] What to do when the business will not listen.[46:45] Why this work matters at the human level.Strategic Workforce Planning Starts With One Uncomfortable QuestionStrategic workforce planning becomes useful the moment it stops pretending it can predict the future. The real starting point is simple: Is the workforce fit for the organization’s future business purpose? That framing does two things immediately. First, it moves SWP out of the “HR process” bucket and into the “business execution” bucket. Second, it forces the conversation away from false certainty and toward risk, trade-offs, and feasibility.One of the most helpful parts of this episode is how clearly the conversation draws a line between strategic and long-term. Strategic does not automatically mean five years out. In some organizations, planning 15 months ahead is strategic compared to how they have historically operated. If you want the cleanest definition of SWP in the most human language possible, it is worth listening to the early part of the conversation where this is unpacked in real time.Why Workforce Planning Has ReturnedWorkforce planning always comes and goes. It resurfaces when the world feels unstable, and it fades when leaders believe they can hire their way out of problems.Right now, hiring your way out of problems is not working.There is too much uncertainty, and it is coming from too many directions at once. Geopolitical instability affects where work can happen. Talent shortages continue to constrain hiring. Skills decay faster than most organizations can reskill. Generational shifts are changing expectations around mobility and development. And technology is changing the shape of work itself.The point is not that leaders suddenly became more disciplined. The point is that the environment is forcing discipline.Strategic workforce planning is the response to that reality. Not because it gives certainty, but because it gives options. It gives a way to talk about what might happen without having to pretend anyone knows exactly what will happen.Strategic Workforce Planning Works When It Stops Being “HR’s Thing”A lot of SWP efforts fail for a predictable reason. They are treated like an HR deliverable. A report. A deck. A spreadsheet. A set of numbers handed over to leadership. Strategic workforce planning is not a deliverable. It is a business process. It is a feasibility process. It is a risk conversation. One of the strongest through-lines in this episode is the idea that HR must initiate this conversation, not because HR owns strategy, but because HR holds the missing information. HR knows things about recruiting realities, workforce behavior, retention patterns, internal mobility, and capability development that business leaders often overlook.But knowledge is not enough. The shift HR has to make is from reporting to synthesis. People analytics without business ...
    Más Menos
    50 m
  • Authentic AI Adoption and Cultural Impact: Dessalen Wood
    Feb 17 2026
    From overcoming initial anxieties through hackathons and playful experiments, to setting an ambitious organizational roadmap for AI, Dessalen Wood shares how Syntax is embedding artificial intelligence across departments, focusing on pragmatic progress rather than hype.You’ll hear stories about driving excitement, learning by doing, and the all-important challenge of measuring real impact. More than just technology, this episode dives into the culture shifts, collaboration with IT, and leadership mindsets that are pushing companies out of their comfort zones and into the future, while keeping authenticity and humanity front and center.You will want to hear this episode if you are interested in...00:00 Overcoming AI fear through collaboration03:30 Defining AI readiness today09:55 AI's role in business transformation15:46 AI anxiety in the workplace22:05 Making AI adoption fun28:11 AI expertise requires human touch36:42 AI strategy: Three layers explained41:31 True transformation vs. improvement53:21 Rethinking work, technology, and AIOvercoming AI AnxietyEarly stages of AI adoption in organizations are often marked by fear. Employees worry about being displaced, making mistakes, or failing to keep up. At Syntax, Dessalen Wood and her fellow leaders tackled these concerns by creating safe, engaging, and transparent opportunities to experiment.One of the most effective strategies was an organization-wide AI hackathon. Everyone, regardless of their role, was invited to submit ideas for automation and improvement—ideas that the tech team then built. Not only did this demystify AI, but it also provided a healthy dose of competition and excitement. Dessalen describes that, “Instead of people fearing automation, it became a competition... People were saying, please, automate my tasks!” This shift from apprehension to enthusiasm helped break through adoption barriers and foster a culture of creative problem-solving.Structuring Success: A Multi-Layered AI RoadmapSyntax’s approach moves AI from a buzzword to a set of actionable strategies. The leadership distinguished between three core areas:Department Initiatives: Leveraging AI for productivity and process improvement within teamsCustomer Value: Enhancing solutions and services delivered to external clientsBusiness Transformation: Reimagining core business models and operations for strategic advantageMany organizations mistakenly assume one AI initiative will magically improve all three—but real impact comes from tailored strategies for each. In practice, this means differentiating between continuous improvement (making existing tasks more efficient) and true reinvention (fundamentally transforming how and why work gets done).The creation of AI champions, employees trained as internal advocates and solution designers, helped ensure that innovative ideas didn’t just sit in a backlog. Instead, those not ready for large-scale investment could be adapted, piloted, and iterated by these champions, keeping the spirit of experimentation alive while prioritizing resources for the highest-value initiatives.The Human Element: Authenticity, Experimentation, and MeasurementAs AI tools become more prevalent, a new challenge emerges: maintaining authenticity in communication, development, and leadership. The team discussed the “hollowed-out leader” phenomenon—where over-reliance on AI could dilute critical thinking and personal investment. Dessalen explains why expertise, context, and human customization are more important than ever: If it doesn’t demonstrate expertise and isn’t highly curated, it just turns people off.Measurement is also evolving. Early wins in AI productivity are being tracked, not just in terms of completion rates or tool adoption, but in demonstrable business outcomes and stretch goals. Syntax uses tools that help employees articulate their productivity gains and set new impact targets, ensuring that activity translates into organizational value.Resources & People MentionedExperience Qualtrics Management Resources Connect with Dessalen WoodDessalen Wood on LinkedIn Connect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES
    Más Menos
    58 m
  • Five Levels of Becoming AI Native: Melissa Reeve
    Feb 4 2026
    The way organizations think about artificial intelligence (AI) in the workplace has shifted dramatically over the past few years. While early conversations centered on isolated experiments and technological hype, organizations now face the much harder task of integrating AI into the fabric of how work gets done. We welcome Melissa Reeve, author of “Hyper Adaptive: Rewiring the Enterprise to Become AI Native,” to discuss what AI adoption really means for people, processes, and culture.Melissa tackles some tough questions about organizational complexity, shifting operating models, and the critical role of culture and systems thinking in successful AI integration. Listeners will get candid advice on starting small, experimenting with purpose, and preparing for the rewiring ahead. You will want to hear this episode if you are interested in...03:38 Integrating AI into organizations12:47 AI Native enterprise structure15:51 Dynamic AI governance framework18:58 AI implementation foundations23:56 Process mapping for AI integration29:44 Balancing efficiency and leadership focus37:02 Start small with value streams40:59 Innovative organizational funding models42:14 Starting a skills-focused organization47:03 Digital Twins in Product TestingNavigating the AI Revolution at WorkMelissa Reeve’s journey began on the factory floors of Toyota, learning firsthand how small process shifts can drive system-wide change. Building on years of research and influence from Lean, Agile, and DevOps practitioners, Reeve authored a five-stage maturity model she calls hyperadaptive, designed to guide organizations through the incremental steps needed to become truly AI-native.The five stages of Melissa's model:Foundation – Build organizational understanding of AI; create dynamic governance structures and clarify guardrails. Optimization – Identify and optimize business processes for AI interactions; move beyond basic experimentation. Agents & Automation – Develop and manage AI agents that execute tasks and processes autonomously. Rewiring – Shift organizational architecture from rigid hierarchies to flexible, value-stream teams funded and incentivized differently. Hyperadaptive – Fully sense-and-respond organizations capable of real-time adaptation.Melissa splits these into two main categories: Basecamp (the first three stages, where most companies currently operate) and the Emerging Frontier (rewiring and hyper adaptivity).Why Organizations Struggle with AI IntegrationAccording to Melissa, most organizations are stuck because they underestimate the support structures required for successful AI adoption. It’s not just about updating technology, in fact, 70-80% of AI success depends on people, culture, and processes, not algorithms. Companies often rush to deploy AI agents or experiment without a clear North Star, leading to pilot fatigue and an 80% failure rate. Many organizations haven’t even finished laying the foundational groundwork, such as establishing unified governance or mapping work processes.Another common pitfall is the tendency to try everything at once. Pressure for fast results drives teams to bite off too much, resulting in burnout and costly errors.Moving from Experimentation to Purposeful TransformationPlaying with AI is not a strategy. While experimentation is necessary, organizations must put bounds on these efforts, know why they're experimenting, what hypothesis they're testing, and what success will look like.One necessary precursor is getting to grips with how your organization actually works. Many leaders lack visibility into workflows, decisions, and skillsets, making process optimization difficult. Reeve suggests collaborative process mapping—sometimes supported by AI tools—to unlock tacit knowledge and identify where AI can augment or reinvent workflows.Organizing Around Value StreamsOne of the most transformative elements is the shift from function-based silos to cross-functional value stream teams. Melissa draws on examples from Toyota, Zappos, and Unilever—organizations that reimagine workflows, funding mechanisms, and team incentives to deliver value rather than preserve hierarchy. Dynamic budgeting, focused experimentation, and flexible team structures help organizations scale AI success without tearing up everything at once.Culture, Upskilling, and Durable SuccessAI’s impact will be decided by how well organizations invest in people. Unilever’s Future Fit program exemplifies this approach, aligning reskilling efforts to individual purpose and business needs. It’s not algorithms that set successful organizations apart, but their ability to create cultures and support systems that empower people to adapt, reinvent themselves, and thrive amidst change.Start small, experiment with purpose, invest in support structures, and prepare to rewire not just technology, but how your organization thinks about work itself. AI may be the catalyst, but people, empowered and ...
    Más Menos
    50 m
  • Reimagining Work at Scale: Manuel Smukalla on Skills, Dynamic Shared Ownership, and the Future of Bayer
    Jan 21 2026
    Manuel Smukalla, Global Talent Impact, Skills Intelligence, and Systems Lead at Bayer, joins Workplace Stories to unpack one of the most ambitious organizational transformations underway today. As Bayer confronts significant market, legal, and profitability pressures, the company has taken a radically different approach to how work, leadership, and talent are structured, rethinking everything from management layers to career progression.In this episode, Manuel walks through Bayer’s shift to Dynamic Shared Ownership (DSO), a decentralized operating model built around networks of teams, 90-day work cycles, and leaders who coach rather than control. He explains why skills visibility became a foundational requirement for this model to work and how Bayer is using skills data to democratize opportunities, improve talent flow, and fundamentally rethink careers inside a global enterprise.You’ll hear how Bayer reduced management layers by more than half, redesigned leadership expectations through its VAC (Visionary, Architect, Catalyst, Coach) model, and moved toward a culture where employees are empowered, and expected, to own their work, development, and impact.You will want to hear this episode if you are interested in...[01:01] Why Bayer embarked on a radical organizational transformation.[04:30] What Dynamic Shared Ownership really means in practice.[06:55] Moving from hierarchical structures to networks of teams.[10:40] Why skills visibility became a critical business problem.[14:05] How 90-day work cycles change accountability and outcomes.[18:10] Building organizations around customer problems, not functions.[21:15] Launching skills profiles as a starting point, not an endpoint.[23:00] How Bayer’s talent marketplace democratizes opportunity at scale.[27:00] The three pillars of a skills-based organization.[33:00] Rethinking careers, performance management, and feedback.[43:10] The VAC leadership model explained.[52:30] Measuring success in a decentralized organization.[53:45] Advice for organizations considering similar transformations.Dynamic Shared Ownership: Redesigning How Work Gets DoneAt the core of Bayer’s transformation is Dynamic Shared Ownership, an operating model that replaces traditional hierarchies with flexible networks of teams. Manuel explains how Bayer reduced its management layers from thirteen to six and reorganized work into 90-day cycles focused on clear outcomes. After each cycle, teams reflect on what worked, what didn’t, and whether the work should continue at all.This approach decentralizes decision-making and forces a shift away from command-and-control leadership. Leaders are no longer expected to direct every task; instead, they create the conditions for teams to succeed, setting direction while trusting teams to determine how outcomes are achieved.Skills as the Engine of Talent FlowFor Dynamic Shared Ownership to function, Bayer needed a new way to understand and deploy talent. Manuel shares a pivotal realization: managers were turning to LinkedIn to understand employee skills because the organization lacked internal visibility. That insight sparked Bayer’s skills journey.Rather than starting with complex taxonomies, Bayer focused first on skill visibility. Employees created and maintained skills profiles, supported by workshops on how to describe capabilities effectively. Over time, this evolved into a talent marketplace that matches people to work based on skills, not job titles, career level, or location, helping democratize access to opportunities across the enterprise.Moving Talent to Work, Not Work to TalentManuel outlines three defining pillars of a skills-based organization. First, talent must move to work rather than work being constrained by static roles. Second, organizations must commit to permanent upskilling, recognizing that development is continuous, not episodic. Third, opportunities must be democratized at scale, reducing reliance on manager sponsorship or informal networks.Bayer’s marketplace supports fixed roles, flex roles, and fully agile project-based work, encouraging employees to actively shape their careers while remaining accountable for outcomes. This model challenges long-held assumptions about promotions, ladders, and linear advancement.Leadership and Performance in a Decentralized WorldLeadership at Bayer has been redefined through the VAC model: Visionary, Architect, Catalyst, and Coach. Leaders set direction, help teams design how value is created, remove barriers, and support rapid cycles of learning. This requires significant unlearning for leaders shaped by traditional hierarchies.Performance management has also shifted. Goals are set in 90-day cycles at the team level, with feedback coming from peers and work leads rather than solely from a direct manager. Over time, this creates richer data on contribution and impact, but also demands a cultural shift toward transparency, shared accountability, and continuous ...
    Más Menos
    59 m
  • Centralizing for Strategy: Christine Crouch on L&D Transformation at General Mills
    Dec 17 2025
    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. 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 Centralization

    For 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 Model
    Centralization 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 Element
    Christine’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 Crouch

    • Christine Crouch on LinkedIn
    Connect With Red Thread Research

    • Website: Red Thread Research
    • On LinkedIn
    • On Facebook
    • On Twitter

    Subscribe to WORKPLACE STORIES
    Más Menos
    53 m