『Workplace Stories by RedThread Research』のカバーアート

Workplace Stories by RedThread Research

Workplace Stories by RedThread Research

著者： Stacia Garr & Dani Johnson
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 At RedThread, we love data—but we know stories are what stick. That’s why we bring together thinkers, writers, leaders, and practitioners to share real-world insights about what works in the workplace, what they’ve learned, and where the future of work is headed. We keep it insightful, thought-provoking, and maybe even a little irreverent.

But we don’t stop at conversations. Our research, events, and community turn insights into action, helping organizations and individuals navigate the changing world of work.

Want to be part of the conversation? Join our community for free and connect with others shaping the future of work.

Learn more about RedThread Research here: https://redthreadresearch.com/homeRedThread Research 2024 マネジメント マネジメント・リーダーシップ 経済学
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  • Centralizing for Strategy: Christine Crouch on L&D Transformation at General Mills

    Centralizing for Strategy: Christine Crouch on L&D Transformation at General Mills
    2025/12/17
    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 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

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    53 分
  • Building a Skills-Based Organization with Koreen Pagano

    Building a Skills-Based Organization with Koreen Pagano
    2025/12/03
    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 ...
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    57 分
  • HR in the Age of AI: Cole Napper on People Analytics, Generative AI, and Redefining Value

    HR in the Age of AI: Cole Napper on People Analytics, Generative AI, and Redefining Value
    2025/11/19
    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 Analytics
    Cole’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 It
    Cole 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 Work
    Cole 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 Illusion
    For 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 Mentioned

    • People Analytics: Using Data-Driven HR and Gen AI as a Business Asset by Cole Napper

    Connect with Cole Napper

    • Cole on LinkedIn

    Connect With Red Thread Research

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