Redesigning Ways of Working: Let's Open-Source Our Expertise

In 2008, I co-authored an article on meetings for the International Standards Organization (ISO). I don't fully agree with everything I wrote back then, but no worries - no one's reading that article anymore anyway. Why bother updating it?

Come to think of it, that's true for the bulk of the ideas with which I've wallpapered the universe. I know I'm not alone. Many of us published lots of great guidance that could use refinement, but with it just sitting in our libraries, does it matter? Very few of the people who could benefit from these ideas will ever see them.

Yet we persist because this is supposedly how we advance our thinking. I throw something out there, you do, the big five consulting agencies do, and the university professors do. All of these ideas recombine and reproduce, giving birth to the next generation of great ideas. That's just happy sticky evolution doing its job!

Only, when it comes to ideas about how organizations can lead teams and get stuff done—their ways of working—we aren’t evolving all that much. Instead, we’re often iterating, proliferating, or straight-up regurgitating old ideas that rarely make it into practice.

Collaboration is Broken

Does this imply that practice has advanced beyond what thought leaders recommend? Hardly. The status quo involves an unholy pairing of straightjacket policies with wild West management, leaving 84% of workers unhappy with their core workplace interactions. We've poured 50+ years into business management books and productivity tech—uncountable hours and insane bags of money—only to find that collaboration remains mostly broken in most organizations.

What's that saying about the definition of insanity, again?

Sure, some of the brokenness stems from people being people, and yes, societal changes play a role. But I believe much of the dysfunction starts with how we design, train, and implement ways of working in organizations. We've set ourselves and the people we serve up to fail.

I believe we can do better. Over the past several months, I've been chatting with many others who feel we can do better, too.

We believe adopting an open-source approach to how we publish and evolve our thinking is a good first step. We believe it's a step we need to take now.

Here's why.

The Misaligned Incentives Behind the Business of Expertise

First, we should acknowledge that the incentive structure behind the publication of business management know-how is fundamentally misaligned with the needs of modern organizations.

Academia: Insights Without Integration

Academic research has deepened our understanding of collaboration, particularly in areas like individual behavior and market dynamics. However, the systems that govern academic success prioritize discovery over application:

• Novelty over utility: Academic careers are built on producing new theories, even when they address niche problems or lack relevance to real-world complexities.

• Frequency over depth: The pressure to publish frequently discourages long-term, systemic studies, favoring controlled experiments that fail to reflect organizational realities.

• Locked knowledge: Even the most relevant academic findings are often hidden behind paywalls or presented in inaccessible jargon, limiting their practical impact.

While academia excels at advancing knowledge, these incentive structures result in fragmented insights that rarely translate into scalable, actionable solutions for organizations.

Consulting: Simplicity Without Flexibility

Consultants and industry thought leaders, by contrast, focus on creating frameworks that are practical and easy to adopt. Many of these frameworks deliver value, but the underlying incentives often prioritize marketability over adaptability:

• Proprietary models as differentiation: Unique, trademarked frameworks signal expertise and generate revenue, but discourage collaboration across practices.

• Simplicity as a selling point: Frameworks are designed to be easily taught, but this simplicity often limits their ability to address complex realities.

• Forcing false choices: Organizations feel pressured to choose between competing frameworks—SCRUM, SAFe, Kanban, Design Thinking—as if adopting parts of one precludes integrating aspects of the others. This rigidity undermines innovation and customization.

• Claiming success without shared benchmarks: Consultants can measure results at the case-study level but lack common standards to compare outcomes across engagements or against other methods.

• No iterative infrastructure: While some thought leaders publish under open licenses, there is no systematic way for others to refine or build upon these tools, leaving each framework static and siloed.

These dynamics reward consultants for creating polished, standalone solutions rather than contributing to a shared, evolving ecosystem of practices.

Case in Point: 50 Unique Perspectives with No Incentive to Change

Take a look at the Thinkers 50 list of top thought leaders from academia and consulting. The lists include many friends and people I admire for their amazing work. These are great lists!

Now, how do you think a team leader could use the Thinkers 50 list to make their workplace better? They can check out books and interviews. Perhaps they could take a class. Maybe their company could bring one or two of these luminaries in to give a talk, but they'd have to be selective because this talk isn't cheap. How to choose?

Each thought leader focuses on just one or two pieces of the management puzzle, which doesn't get you very far when your team believes 84% of the picture is missing. Right now, even if these thought leaders wanted to build something bigger together, there's no shared space or system for that.

The Smoking Tinder of Growing Discontent

This misalignment between what organizations need and what current solutions offer hasn’t gone unnoticed. Regarding consulting, the media increasingly features stories about the ineffectiveness of change and training programs, the rise of employee frustration driven by “consultant of the month” change fatigue, and the outright immoral harm perpetuated by consultants like McKinsey in pursuit of profits. Academia is also under threat, with recent scandals involving high-profile papers that reportedly include plagiarism and “fudged” data, popular findings that can’t be reproduced, and a growing number of retracted papers.

Despite these widely acknowledged criticisms, there’s been little motivation for changing the status quo. Without an outside reference for quality or viable alternatives, what choice do clients seeking insights have? How else are those of us who support these clients supposed to reach them?

AI: Pouring Gas on the Fire

Ah! Ok then. Hello, AI. It looks like clients have an alternative after all!

With access to an unprecedented trove of academic research, proprietary frameworks, and real-time organizational data, AI breaks down the silos that kept academic, consulting, and organizational intelligence apart. It ignores role and organizational boundaries, offering:

• Rapid, context-specific recommendations that integrate insights from multiple schools of thought.

• Scalable, on-demand solutions at a fraction of the cost of traditional consulting or training.

• The ability to iterate in real-time based on feedback and new data.

AI highlights the inadequacies of legacy approaches and renders many of them obsolete. Proprietary models lose their economic drivers when AI can replicate or combine their principles into more flexible, adaptive solutions. The barriers created by exclusivity and silos are collapsing, leaving academics, consultants, and organizations with a stark reality: we can no longer solve new problems using old approaches, nor can we make a living by clinging to them.

We’re in very early days, yet AI's impact on consultants is already beginning to play out. As organizations integrate AI and train people to use it, the likelihood that managers will rely on AI instead of human experts will also rise. This will work well often enough that the downsides won’t be immediately apparent.

AI is designed to provide concise, "good enough" solutions to the questions it is asked, satisfying immediate needs without considering broader implications. For example:

• Among competing approaches to structuring a team, AI has no reason to advocate for the most rigorous or effective approach. Instead, it will provide a satisficing answer based on incomplete context, especially when users are unaware of existing research or best practices.

• Diagnosing collaboration challenges isn’t the same as other areas where AI outperforms humans, like predicting the weather or reading radiology reports, because there’s no objective way to determine what constitutes a “correct” answer.

• AI will only give people answers to the questions they know to ask. Left unchecked, this dynamic risks devolving further into the lowest common denominator, where organizations adopt fragmented, shallow solutions simply because they lack the expertise to ask better questions.

Without human experts actively shaping shared standards and refining collaborative practices, we risk outsourcing decision-making to AI tools that lack the depth, empathy, motivation, and long-term contextual understanding required to address complex organizational challenges. And with AI dismantling the economic underpinnings of proprietary models, the need for human experts to take a new approach becomes essential.

A New(ish) Approach: Building an Open-Source Ecosystem for Business Management Knowledge

To meet these challenges, experts must rethink how we design, share, and evolve the tools and frameworks we provide. The old models—fragmented, proprietary, and competitive—are no longer sufficient. Instead, we need to adopt a new-to-us approach: an open-source ecosystem for collaboration frameworks.

What This Approach Looks Like

• Integrated Development Across Silos
  Break down the barriers between academia and consultants. By contributing to a shared framework, we can combine the best of both worlds:

  • Academia’s deep, research-driven insights.

  • Consulting’s practical, actionable tools. This integration would unlock modular, adaptable frameworks that organizations can combine and tailor to their unique needs.

  • Technology’s ability to rapidly integrate, synthesize, distribute, and transform knowledge.

• Collaborative Iteration
  Build infrastructure for experts to contribute, refine, and iterate on knowledge collectively. Inspired by open-source software, this approach would allow:

  • Continuous improvement based on diverse perspectives and real-world feedback.

  • Frameworks that evolve alongside organizational challenges.

  • Greater innovation driven by collaboration rather than competition.

• Accessible to All
  Ensure that collaboration knowledge is open and widely available:

  • Remove barriers like journal paywalls and proprietary restrictions.

  • Create free or low-cost tools that organizations can implement directly.

  • Foster transparency and shared ownership.

Learning from Open Source Software

This approach mirrors the transformation seen in software development. The open-source movement revolutionized technology by unlocking collaboration across boundaries, sidestepping proprietary silos, and accelerating innovation.

Now, young engineers can build experience and reputations by contributing to open projects. Senior developers provide mentorship and oversight. Contributors exercise their intellectual autonomy and find meaning by contributing to projects they value. Demand for developers who build with and on top of open-source ecosystems remains high. Robust markets connect clients with people who provide open-source software training, hosting, customization, and support. Open-source components are the building blocks of the modern internet, accelerating an explosion of software startups.

Open-source software didn’t eliminate competition; it raised the bar for what success looks like. From Linux to GitHub to WordPress, and most recently, Deep Seek, open-source software projects have proven that openness and collaboration can drive progress at a scale no single company or individual could achieve alone.

How Taking an Open-Source Approach Can Benefit Experts

This approach addresses key challenges faced by business management experts:

• Better Benchmarks: Shared infrastructure enables more meaningful comparisons of outcomes across frameworks and engagements. Transparent usage and feedback information will elevate the truly great practices over those that merely look good on paper.

• Sustainable Innovation: Collaborative iteration creates a continuous feedback loop, allowing contributors to stay relevant and refine their methods. Buhbye, dusty shelves of ancient PDFS!

• Defensible Expertise: People who help develop shared frameworks and have their approach vetted in the fire of critical scrutiny gain reputational authority that exceeds any conveyed by marketing alone. 

• Succession Rather Reinvention: Experts nearing the end of their career can see their work actively maintained and updated by a new generation, instead of appropriated and then “rediscovered” under a cloak of modern language.

• Application Through Transformation: Open knowledge can take many forms. People can contribute alternate presentations for existing material and use technology to adapt material into formats that integrate directly into the workplace. Do you want that guide in a document, as a poster, or as a configured template in your project management system? Those options are on the table, increasing the odds of teams accessing knowledge in a form they can use.

• Smarter Marketing: Contributing to a shared ecosystem lets experts pool their outreach efforts, dramatically reducing individual marketing costs while reaching a far bigger audience. Instead of each thought leader building their platform and audience from scratch, the collective effort creates a rising tide that lifts all boats.

Re-Asserting the Value of Human Judgment

An open-source ecosystem does more than solve practical challenges. It reasserts the irreplaceable value of human judgment in shaping how organizations work together. Unlike AI, humans can:

• Advocate for Excellence: Experts can elevate the best frameworks, ensuring solutions are intentional and rigorous.

• Establish a Quality Baseline: A human-curated open-source framework creates a recognized benchmark for excellence, making it harder for both human and AI practitioners to justify poorly conceived or unvetted approaches.

• Provide Contextual Understanding: Humans bring empathy, story, and creativity to decisions, aligning solutions with organizational values and goals.

• Ensure Collective Evolution: Open collaboration invites experts to challenge assumptions and improve practices over time.

By embedding human expertise in a transparent, collaborative process, we ensure that AI remains a tool, not the driver of organizational decisions.

Interested? Let's Talk.

Collaboration experts—academics, consultants, and system providers—let's band together to create this new ecosystem. The need is clear, and the opportunity is immense.

We can redefine the game. We can liberate proven practices from those that prioritize profit over organizational health. We can build a commons that creates a new marketplace for experts and better serves leaders who genuinely want their organizations to thrive.

Our First Steps: Refine the Concept and Build a Founding Team
If you're interested in contributing to this initiative:

1. Add your comments and questions below, by email, and on LinkedIn. Carrie Goucher will kick off the LinkedIn conversation, so follow her to chime in there.

2. Watch for the next few articles. We'll share our initial answers to questions we've heard, like 'How is this different from a wiki?', 'Won't this just be a big mess?', 'What happens to all the certification programs?', and 'Hasn't someone tried this already?'"

3. Join us for an open conversation about the next steps on February 26th and 27 in the MIC.

Looking forward to exploring the next possible with you,
Elise