Woundwise Leadership
The Organizational Architecture of What We Refuse to See
Organizations don't just have blind spots. They have systematic architectures of what they refuse to see.
I've spent the past months deep in a complex enterprise project that's fundamentally inverted how I understand organizational intelligence. The deeper I go, the clearer a pattern becomes: what we label as "waste" isn't random inefficiency or human error. It's the structural consequence of how we've chosen to represent reality itself.
This recognition has led me to develop what I'm calling Woundwise Leadership™—a framework that extends the core insights from my book on post-structural philosophy, Woundwise, into organizational contexts. What follows is both theoretical provocation and practical methodology for how leaders can learn to read the architecture of their own systematic blindness.
The Ontological Turn in Organization Theory
Every organization operates with an implicit ontology—a formal (even if unconscious) representation of what entities, relationships, and actions it considers "real." Your org chart, your KPIs, your data models, your ERP systems, your reward structures—these aren't neutral descriptions of an objective reality. They're ontological commitments about what deserves to exist, what deserves measurement, what deserves resources.
In philosophy, ontology asks "what is?" In organizations, ontology answers "what counts?"
And here's the critical insight: ontologies work through systematic abjection.
The term "abjection" comes from psychoanalytic theory—Julia Kristeva's concept of what must be rejected to maintain identity boundaries. An organization's ontology doesn't just define what it includes; it systematically excludes what threatens its current categories of understanding. This isn't incidental. It's structural.
Six Sigma has trained generations of leaders to identify, measure, and eliminate waste. But what if waste isn't deviation from an ideal state? What if it's reality that your current ontology cannot accommodate?
The Three Ontologies Problem
Most organizations are unknowingly managing three different, often divergent ontologies:
- Logical Data Models — What your systems need to function (database schemas, APIs, technical architecture)
- Business Glossaries — What governance defines as official terminology and definitions
- Knowledge Graphs — What AI and analytics actually discover in your data patterns
Gartner research indicates that ontological misalignment between these three layers costs enterprises an average of $12.9M annually in coordination friction, rework, and missed opportunities.
But here's what conventional thinking misses: The misalignment isn't the problem. The misalignment is the signal.
When your logical models, your governance definitions, and your AI-discovered patterns tell three different stories about "what is," your organization is revealing the precise architecture of its systematic abjection. The divergence shows you exactly where you've drawn boundaries around what you're willing to know.
Waste as Ontological Excess
Traditional Lean and Six Sigma methodologies identify seven types of waste: Defects, Overproduction, Waiting, Non-utilized talent, Transportation, Inventory, Motion.
But Woundwise Leadership asks a different question: Why did we categorize this as waste in the first place?
What does your definition of "defect" reveal about what you value—and what you fear? When you classify certain kinds of knowledge work as "non-utilized talent," what ontological categories are you protecting? When you optimize for eliminating "waiting," what emergent possibilities are you systematically foreclosing?
The waste you identify is always downstream from the ontology you've committed to. Change what you're willing to count as "real," and the category of waste transforms.
Distributed Intelligence and Temporary Assemblages
This is where the framework becomes generative rather than merely diagnostic.
The most sophisticated research on human-AI collaboration reveals something counterintuitive: performance gains don't come from specialization or division of labor between humans and machines. They come from what researchers call ensemble aggregation—combining complementary error patterns to surface what neither human nor AI can detect alone.
These human-AI ensembles function as temporary assemblages—heterogeneous elements (humans, algorithms, data, processes) temporarily configured to accomplish specific cognitive work, then dissolved. Drawing on assemblage theory from philosophers like Manuel DeLanda, we can see organizations not as permanent structures but as constantly forming and reforming configurations.
And here's what matters: these assemblages form at the boundaries of formal structures, in the spaces your ontology has classified as waste.
When a data scientist notices an anomaly that doesn't fit current business definitions, and collaborates with an AI to explore the pattern, and pulls in a domain expert who recognizes something the models can't see—that temporary assemblage is accessing the possibility space your formal ontology has foreclosed.
The coordination tax you're paying to maintain boundaries between incompatible ontological representations isn't just inefficiency. It's the cost of refusing to acknowledge what your fragmented ontologies are trying to teach you.
The Auger Hypothesis
There are organizations beginning to operationalize these insights. Auger, for instance, describes their approach as building "the autonomous operating system for complex enterprise operations" by creating a "living ontology of your business physics."
"We don't just predict reality: we execute it. Precision replaces mass. Velocity replaces latency."
But I'd argue that Dave Clark and his team at Auger are pointing toward something even more profound. A truly living ontology wouldn't just execute your current understanding of business physics—it would continuously reveal where your understanding is systematically incomplete. It would make visible the architecture of your abjection.
The velocity they're describing isn't just operational speed. It's epistemic velocity—the rate at which an organization can learn from what it previously classified as irrelevant.
Woundwise Leadership in Practice
So what does this actually look like as a leadership practice?
- Map Your Ontological Commitments: Make explicit what your organization treats as ontologically real. Not what you say you value in mission statements, but what your systems, metrics, and resource allocation reveal you're committed to counting as real. Then ask: What are we systematically excluding to maintain these categories?
- Treat Divergence as Signal, Not Noise: When your data models, governance frameworks, and AI insights tell different stories, resist the urge to force alignment. Instead, study the divergence. What is each ontology protecting? What would become visible if you allowed them to coexist in tension?
- Create Conditions for Temporary Assemblages: The assemblages that can metabolize what your permanent structures reject need space to form. This means protecting time for exploration, enabling cross-functional configurations, and giving human-AI collaborations permission to pursue anomalies.
- Reframe "Waste" as Ontological Excess: When something gets labeled waste, ask: What reality is this trying to represent that our current categories can't accommodate? The rejected code, the failed experiment, the questions that made people uncomfortable—these aren't inefficiencies to optimize away.
- Build Organizational Courage for Ontological Humility: This requires the courage to say: "Our success has been built on particular ways of seeing. Those ways of seeing necessarily exclude. What are we now refusing to learn from because it would require admitting our categories are incomplete?"
The Wound as Teacher
The central claim of Woundwise Leadership™ is this: The wound isn't the problem. The wound is the teacher.
Your organization's systematic exclusions—its abjections—aren't failures to be corrected. They're diagnostic revelations of your ontological boundaries. They show you exactly where you've prioritized coherence over truth, efficiency over emergence, stability over adaptation.
Traditional leadership tries to eliminate the wound through better planning, tighter processes, clearer definitions. Woundwise Leadership™ learns to read what the wound is revealing about the architecture of your refusal.
About this Concept: I studied post-structural philosophy at Calvin University, management at Michigan State's Eli Broad School of Business and Yale School of Management—trying to understand how individuals and organizations systematically exclude what threatens their current categories of understanding. Woundwise emerged from connecting those threads around a single question: what do we refuse to learn from, and why? I'm currently working on a major enterprise initiative testing whether organizations can build capacity to learn from what they systematically exclude. Woundwise Leadership™ is what's emerging from that work.