FearOS: How Our Orgs Run on Fear and What We Can Do About It (According to Chris Argyris)
Part 3: Doubling the Loop
In Part 2 of the series, we looked at Chris Argyris’ concept of “single-loop learning,” where individuals and organizations seek to optimize well-established, repetitive, formulaic processes.
We also introduced his concept of “theories in use” — the assumptions that individuals and organizations operate under.
Argyris distilled the most common down to four prevailing theories centered around maintaining control, loss aversion, avoidance of negativity and consistent adherence to rationality.
What this boils down to is a mindset that I would describe as a “Hamster Wheel Illusion of Safety.”
The wheel is simple. The wheel is familiar. The hamster feels safe inside.
But there is a whole ever-changing world outside of the wheel that could threaten the hamster, no matter how blissfully unaware it might be.
This is why the ability to leverage what Argyris calls “double-loop learning” is so important — it’s ultimately the ability to survive change.
But those “theories in use” often stand in the way. They create a barrier for some of the critical ingredients to making a “double-loop”:
Objective assessment. Looking at all the facts without bias.
Open inquiry. Asking the uncomfy questions out loud.
Critical introspection. Taking a hard look at your own involvement.
These activities are hugely important to answering the “why behind the why” and finding better ways.
But they‘re also huge amygdala triggers. 🧠🔫💥😡
Remember Argyris’ most common theories in use?
You can’t control the assessment.
It might feel like losing.
It could be humiliating.
Your response might be defensive, and even seem irrationally so.
No one wants to be seen as “falling short.”
Any criticism is a threat of identified underperformance.
And even those who claim to be open to this sort of approach often struggle to navigate it well in practice.
They enthusiastically offer critiques of others’ contributions but bristle at the first critique of their own contribution.
Or they want to get to the root of the problem, but start to get uncomfortable when the digging reveals that the root connects back to them.
In order to make “double-loop learning” possible, Argyris says that individuals within the organization must first become aware of:
Their “theories in use.” The assumptions that individuals and the organization are operating under.
Their inconsistencies. Differences between their stated assumptions and what actually drives their decision-making behaviors.
Their defense mechanisms. The barriers they create to protect themselves that negatively impact the organization.
Only once an organization has created an environment where these can be openly and objectively acknowledged can “double-loop learning” happen.
What this ultimately unlocks is a move from what Argyris calls “defensive reasoning” within an organization to “productive reasoning.”
In essence, it’s a move from individual protection to collective production when diagnosing and solving organizational problems.
But notice that Argyris roots it in reason.
Another quick tangent into etymology:
The word “reason” has the same Latin word as “rational” — ratio ("a reckoning, account, a numbering, calculation”). This word also conveyed the core concepts of thought and belief, and was often used as a translation of the Greek word logos, the root of the word “logic.”
So one way to think about “reasoning” is that we are ultimately making calculations about a situation. Dividing things up, adding them together, subtracting this from that — all to try and figure out what’s going on.
It’s “mathing” a problem in a “logical” and “rational” way.
You may be thinking “Wait, wasn’t rationalism one of Argyris’ common theories of use?” And you would be correct.
The difference here is between using logic to collectively produce rather than individually protect.
Or more simply, the difference between reasoning and rationalizing.
To quote this article by Ian Moorhouse:
Reasoning involves reaching conclusions based on logical thinking and evidence… Rationalization involves explaining or justifying something to make it appear proper or correct, often without a solid foundation.
When we’re reasoning defensively (aka rationalizing), we’re trying to stack the equation in our own individual favor so that the problems are always due to external factors.
At the same time, we treat internal factors as constants instead of variables that could be solved for (e.g., “Well, I know I’m not the problem, so let’s look at everything/everyone else”).
This all may feel like “mathing” but it’s a fear formula, and Argyris says it’s impossible to learn from those equations because they are inherently flawed.
They’re unproductive because they’re designed to protect, not produce.
When we reason productively, we use a different type of math — one rooted in objectivity with all factors as variables, and with an intent to produce a real solution for the core problem.
It’s not easy (in fact Argyris refers to it as a “tough reasoning”), but the point is to subject the thinking to rigorous criticism and scrutiny in a scientific way, forming the basis for an organization that can truly learn and evolve.
And one key component of that is data.
Not subjective “anecdata” and implicit inferences leading to “self-sealed” conclusions presented as evidence.
Instead, Argyris says you need:
consistently tracked metrics
that align with shared objectives
that can be analyzed objectively and transparently
with conclusions that can be evaluated critically and collectively
This can quickly feel like an overwhelming prospect that multiplies at scale.
The implementation, utilization and maintenance of tracking and measurement instruments can feel as resource-intensive as the organizational operation it’s meant to monitor… it can feel like the squeeze costs more than the juice is worth.
The key is to work back from target outcomes, determining what metrics are most indicative of progress (aka “key performance indicators”) or most closely tied to causes/effects in the organization.
This can be mapped to individual performance or team performance.
For instance:
The goal of the role/team is to X
Is X happening? What metrics would indicate that it is?
Is it a measure of completion or an indicator of progress?
Can the effects be attributed solely or in part to the contribution of the role/team? Was there a baseline? Is there a control?
Is the individual or team onboard with the methodology? Do they believe it to be fair, accurate and objective?
Here's an example…
Let's say you're evaluating a sales team's performance. Their goal: increase revenue via sales. You might…
Track metrics like new client acquisition, win rate, deal size, and sales cycle length.
Establish baselines, compare to benchmarks and other teams.
Involve the team in setting collective targets and individual g.
Use a dashboard with individual and team metrics.
Hold monthly self-assessments and quarterly reviews focused on analyzing data and improving strategies.
Nothing novel here, but this approach ensures there’s accountability and collaboration that lays the foundation for double-loop learning, shifting from fear to continuous improvement.
If you’ve made it this far, congrats and thank you. I hope it’s been a valuable exploration of Argyris’ concepts that can help you reframe how you think about fear in your organization.
First, a high-level TL;DR to wrap up the series:
Fear drives most organizational decisions
This leads to defensiveness and risk-aversion
People self-preserve based on fearful assumptions (“theories in use”)
Productive reasoning > defensive rationalization
Continuous improvement requires self-reflection
"Single-loop" learning = stick to safe, proven templates
"Double-loop" learning = deconstruct templates, adapt to change
Objective assessment and open inquiry unlock the "double loop"
Recognize assumptions, inconsistencies, and defensive tendencies to overcome fear, learn and grow
So what’s the practical application?
Well, here are some things you might consider trying, individually and within your team or organization:
Identify threats, real and perceived. Figure out what people are most afraid of, and then determine which fears are rational, which may not be, and which are stemming from legitimate psychological unsafety (e.g., “I’m afraid to speak up in case I say the wrong thing.”)
Conduct an “assumptions” audit. What unspoken “theories in use” is the org operating under? Look at common behaviors, decisions and policies and try to reverse-engineer the assumptions behind them (e.g., “We probably don’t offer unlimited PTO because deep down we’re afraid employees would work less and productivity would decrease.”)
Revisit employee evaluations and team goal-setting. Work on collaboratively redesigning these to connect to org strategy and underpinning them with objective, accessible data (e.g., “If our org wants to gain X advantage, this team needs to achieve Y which means team members need to Z, which we can track with metrics A, B and C.”)
Build a “double-looping” cadence into workflows. Find a way for teams to periodically poke and prod at their ways of working. Put challenges out on the table, dig for root causes. Objectively learn, productively reason and continuously improve, together.
Create a forum to share failures and learnings. Only sharing successes can inadvertently reinforce fear of failure. Find ways to highlight where things didn’t go so great, how the team assessed, what they learned, and how they improved.
Hope you enjoyed this series. If you did, I highly recommend learning a bit more about Chris Argyris and checking out his many great books.
And stay tuned for more from The Light Shed.
💡 Did this shed any light for you?
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