Workplace Stories by RedThread Research

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 Done
At 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 Flow
For 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 Talent
Manuel 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 World
Leadership 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 feedback.

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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. 

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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” World
There’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 Right
We 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 Verification
Organizations 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 Structures
Often, 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 Tasks
Perhaps 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 Mentioned
Building the Skills-Based Organization: A Blueprint for Transformation by Koreen Pagano 
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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

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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 Leverage
Lori’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 Mentioned

L&D Tech Ecosystem 2020
Skills Oddyssey
Learning Strategy paper
Lori's book
Connect with Lori Niles-Hoffman

Lori on LinkedIn
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