Unstable Cognitive Chimeras: Why Combining Good Models So Often Fails

One of the most common—and least examined—failures in organizations, frameworks, and teams is the attempt to combine two good ways of doing the same thing.

We see this constantly. And, it is one of the most difficult cognitive operations to do right.

People collect frameworks (which are already problematic), then stack them, mash them up, and proudly present the result as sophistication. What they’ve actually built is usually a monstrosity: impressive on slides, fragile in practice. Something similar to a chimera—a marvelous creature with slim chances of real survival.

But this doesn’t only happen deliberately. It also happens organically when you take two coherent teams—each doing good work in a different way on the same problem—and combine them. The intuitive expectation is coherence. Afterall...they're both working on the same problem.

The net result is usually the opposite.

People Miss the Power of O

The underlying assumption is simple and wrong:

“If both models work, combining them should work better.”

In systems terms, this treats models as content (Information or I) instead of structure (Organization or O). That’s the mistake.

The math underneath the failure

In DSRP and O-Theory, a model is defined as Information multiplied by Organization where O=DSRP:

𝕄 = I · O

Information (I) is additive. Organization (O) is not. This has shown proven empirically.

Now consider two models:

𝕄₁ = I₁ · O₁ 𝕄₂ = I₂ · O₂

They often share overlapping information:

I₁ ∩ I₂ ≠ ∅

Same people. Same meetings. Same goals. Same language.

But their organization differs:

O₁ ≠ O₂

Different boundary distinctions (D), nested part-whole structure (S) , relationship logics (R), and governing perspectives or frames of reference (P).

When people try to combine them, what they actually create is:

𝕄ᶜ = I · (O₁ ⊔ O₂)

This is not a synthesis. It’s an unstable chimera.

What an unstable chimera looks like

Take a simple example of meetings everyone recognizes.

Model 1: Efficiency

1. Meetings exist to make decisions fast.

2. Clear authority.

3. Tight agendas.

4. Closure over discussion.

5. Leader perspective dominates.

Model 2: Inclusion

1. Meetings exist to ensure everyone is heard.

2. Broad participation.

3. Dialogue over closure.

4. Buy-in before action.

5. Participant perspectives dominate.

Each model works—on its own. Now the organization says: “We’ll be fast and inclusive.” What actually happens?

• Long meetings that still feel rushed.

• Decisions that exist but aren’t owned.

• People feel consulted but not influential.

• Endless frustration with no clear culprit.

Nothing is wrong with efficiency. Nothing is wrong with inclusion. The failure is structural.

Two organizing grammars are occupying the same structural role at the same time. The system oscillates: sometimes behaving like O₁, sometimes like O₂. That oscillation is the instability.

Why this isn’t just disagreement

An unstable chimera is not:

• Poor communication

• Personality conflict

• Resistance to change

It’s a specific structural condition: Partial overlap in information combined with non-isomorphic organization.

That’s why these systems survive meetings, pilots, and decks—but collapse under execution, governance, learning, and scale.

Why framework collecting makes this worse

Frameworks are already abstractions of organization. When people collect them and stack them—Agile + OKRs + Design Thinking + Lean + Systems Thinking—they rarely reconcile the underlying structure. They align vocabulary and intentions and assume coherence follows.

It doesn’t.

They create chimeras with more limbs, not better movement.

What DSRP does instead

DSRP doesn’t try to “balance” competing models. It changes the operation.

Disintegrate

Both models are broken down into their D, S, R, and P elements. This destroys the illusion that they already fit.

Diagnose structural compatibility

• Are the distinctions boundaries compatible?

• Do the system structures (part-whole) align?

• Are the relationship logics the same?

• Are the governing or framing perspectives resolved?

Sometimes one model easily nests cleanly inside another. Sometimes both models form a coherent relational process. More often, neither is true.

Reintegrate

Instead of addition (+), a new model is built (x):

𝕄₃ = (I₁ ∪ I₂) · O₃

Where O₃ ≠ O₁ and O₃ ≠ O₂.

This is not a compromise. It’s reconstruction. In the meeting example, this might mean:

1. Inclusion meetings generate inputs.

2. Efficiency meetings make decisions.

Different systems, different purposes. Explicit relationships between them. The structural instability disappears—not because people agreed more, but because the model became explicit and the organization became coherent.

Why “unstable chimera”?

A biological chimera contains distinct genetic lineages without a single developmental program.

An organizational chimera contains distinct organizing logics without a single structural "O". They look unified. They function locally. They fail globally.

Naming the condition matters, because once you can see it, you stop trying to fix it with facilitation, alignment workshops, or better language. Those all operate on I. The problem lives in O.

The takeaway

When two models share information but not organization, adding them produces an unstable chimera.

Stability does not come from balance or compromise. It comes from disintegration and reintegration into a new structure.

Or more simply: You don’t fix chimeras by combining models. You fix them by rebuilding organization.

An Aside: Chimera States: A Mathematical Parallel

The term chimera is not just metaphorical. It already exists as a formal concept in mathematics and physics—and for essentially the same reason.

In dynamical systems theory, a chimera state refers to a system of identical, coupled elements (often oscillators) in which coherent and incoherent behavior coexist. Some parts of the system synchronize, while others remain desynchronized, even though all components and coupling rules are the same.

This was surprising when first discovered. Classical theory predicted uniform behavior under identical conditions. Instead, the system settles into a configuration that is locally coherent but globally unstable. The chimera is not random noise, not full disorder, and not stable order—it is a structurally fractured equilibrium.

That description maps cleanly onto what happens when organizations or frameworks combine coherent models without reconciling their structure.

In DSRP terms, we often see:

𝕄₁ = I · O₁ 𝕄₂ = I · O₂

with overlapping information (same people, language, goals, artifacts) but non-isomorphic organization (different distinctions, system boundaries, relationship logics, and governing perspectives).

When these models are combined without rebuilding organization, the result is:

𝕄ᶜ = I · (O₁ ⊔ O₂)

This is an organizational chimera: partial coherence, persistent instability. The system oscillates—sometimes behaving like O₁, sometimes like O₂—until scale, stress, or coupling forces failure.

In physics, chimera states are not resolved by tuning parameters or negotiating balance. They disappear only when the coupling architecture itself is changed. The elements stay the same; the structure changes.

DSRP operates the same way. It does not stabilize chimeras by compromise or alignment. It dissolves them by disintegrating competing organizations and reconstructing a new one:

𝕄₃ = (I₁ ∪ I₂) · O₃ where O₃ ≠ O₁ and O₃ ≠ O₂.

The convergence here is important. Chimera states arise independently in mythology, biology, nonlinear dynamics, and organizational systems for the same structural reason: locally coherent logics forced to coexist without a unifying generative grammar.

Once named, the problem becomes tractable.

Chimeras are not people problems.They are not communication problems. They are structure problems.

And structure is something that can be rebuilt.