Category: Corporate Culture

Email trees are not an accident. They are the predictable outcome of organisations repeatedly using the wrong tool for the wrong job. Despite decades of evidence, email is still treated as a collaboration platform rather than what it actually is: a slow, lossy message delivery system. The result is wasted time, fragmented thinking, and an extraordinary amount of invisible labour.

1. The One Finger Typist Problem

Few things better capture the absurdity of corporate communication than watching someone sit at their desk, hammering out a long, verbose email with one finger, addressed to a colleague sitting directly behind them. Sentence after sentence is typed, retyped, and expanded, often explaining context that could have been resolved in thirty seconds of spoken conversation or a short chat message.

This behaviour feels productive because it looks like work. In reality, it is delay disguised as diligence. Email encourages over explanation, defers feedback, and removes the natural corrective pressure of real time interaction. The longer the email, the higher the probability that it should never have been an email in the first place.

Email trees are born right here.

2. The Five Sentence Rule

One of the simplest and most effective countermeasures to email abuse is the five sentence rule, popularised at http://five.sentenc.es/.

The rule is brutally simple:

If you cannot state your request clearly in five sentences or fewer, do not use email.

This rule forces clarity. It requires the sender to decide what actually matters, what action is required, and who truly needs to be involved. Long narratives, exploratory thinking, and collaborative problem solving do not belong in email. They belong in conversations, shared documents, or collaborative spaces where context is visible to everyone.

Five sentences is not restrictive. It is generous. Anything longer is usually a sign of unresolved thinking being offloaded onto the reader.

A particularly effective tactic is adding the five sentence rule to your email signature as a subtle hint rather than a mandate. Something as simple as:

“Emails over five sentences probably belong in a conversation.”

quietly resets expectations without confrontation. Over time, it changes behaviour.

3. TL;DR as a Discipline, Not a Courtesy

When longer messages are unavoidable, the TL;DR is mandatory.

A TL;DR at the top of a message is not about politeness. It is about respect for attention. It allows the reader to understand intent immediately and decide how deeply to engage. More importantly, it exposes weak thinking. If the message cannot be summarised in two or three lines, the sender has not yet done the work.

There is also power in replying with TL;DR only. This is not rude. It is corrective. Over time, teams learn to lead with outcomes instead of narratives.

4. Actively Prohibiting Email Discussions

High performing organisations do not merely suggest better communication practices. They explicitly prohibit using email for discussion.

Email is appropriate for formal communication, external messaging, approvals, and record keeping. It is fundamentally unsuitable for debate, iteration, brainstorming, or back and forth problem solving. When those activities are forced into email, context fragments, accountability blurs, and decisions disappear into inbox archaeology.

Leaders must say this out loud. If they do not, email becomes the default because it is familiar, not because it is effective. The cost shows up as wasted time, repeated conversations, and decisions that have to be re made because nobody can find them.

This is not inefficiency at the margin. It is systemic waste.

5. Chat Alternatives and the Governance Reality

Tools like WhatsApp and Slack demonstrate how quickly collaboration improves when friction is removed. Questions get answered in minutes instead of days. Context remains visible. Decisions emerge naturally rather than being negotiated across parallel threads.

But speed without governance is dangerous.

WhatsApp, in particular, is unsuitable for corporate collaboration beyond informal coordination. It lives on personal devices, has no enterprise grade exit controls, and should never be used for client data, financial information, or regulated discussions. When people leave, the information leaves with them.

Slack and similar platforms are more appropriate but still require discipline. Access must be revoked immediately when people exit. Sensitive topics must be explicitly prohibited. Channels must be structured and purposeful. Without governance, chat platforms simply accelerate bad habits instead of fixing them.

Collaboration tools amplify behaviour. They do not correct it.

6. Why Microsoft Teams Is So Painful in Practice

Microsoft Teams is often positioned as the answer to email overload. In practice, many organisations experience it as email with more surface area and more ways to get lost.

From a user experience perspective, Teams is cognitively heavy. Chats, channels, meetings, files, and tabs overlap in ways that are not intuitive. Users frequently do not know where a conversation should live, which thread is authoritative, or where the final decision was made. Finding information often requires training rather than intuition.

Corporate security controls frequently make things worse. In the name of risk management, organisations disable clipboard functionality, block attachments, restrict downloads, and partially or fully blank screen sharing. Each control might be defensible in isolation. Together, they break the channel. What remains is a collaboration tool that cannot collaborate.

Support burden is another hidden cost. Teams is resource intensive on client machines, sensitive to network quality, and prone to inconsistent behaviour across updates. Crashes, dropped calls, audio desynchronisation, and failed screen sharing are common enough to be normalised. Supporting Teams at scale consumes significant IT capacity simply to keep it usable.

Teams does not fail because it lacks features. It fails because complexity combined with controls erodes trust. When people do not trust a collaboration tool to work reliably, they retreat to the one thing they know will always deliver a message.

Email.

And with it, the email trees return.

7. Intentional Communication Design

The solution to email trees is not another tool rollout. It is intentional communication design.

Set clear rules about where different kinds of communication belong. Enforce brevity. Separate discussion from record keeping. Choose collaboration tools deliberately and govern them properly. Train people not just how to use tools, but when not to.

Email will always exist. The mistake is allowing it to pretend to be something it is not.

Collaboration is not about sending messages. It is about shared understanding. Email trees destroy that.

Culture is not revealed by behaviour under control, but by motive under autonomy.

Highly controlled environments mask intent and allow organisations to promote leaders whose inner compass has never been tested. When controls are later removed at seniority, behaviour shocks leadership and risk materialises.

Durable outcomes, whether in fraud prevention, customer trust, or leadership quality, only occur when actions are driven by genuine care rather than compliance, optics, or profit alone. Boards should insist not only on strong controls, but on leadership systems that deliberately create space to observe motive early, before authority becomes irreversible and consequences become systemic.

Most leadership systems obsess over what people do. What was delivered. What was measured. What was complied with. What was audited. These things are visible, countable, and comforting. They fit neatly into dashboards, scorecards, and board packs. But culture does not live there.

Culture lives in why people do things. And why is internal, invisible, and deeply problematic to measure when behaviours are constrained. You can of course mandate behaviour, but you cannot mandate motive. Yet motive is the thing that determines what happens when nobody is watching, when tradeoffs get hard, and when doing the right thing becomes expensive, slow, or personally costly.

This is where most organisations fool themselves. They mistake control for character, compliance for conviction, and execution under instruction for leadership potential. As long as the system is tight, everyone looks aligned. But alignment under constraint tells you almost nothing about who someone really is.

If you want to understand your culture, and the leaders your organisation is actually producing, you have to look past what people do and start paying attention to why they do it.

1. Control Masks Motive

Highly controlled environments create a dangerous illusion. When everything is prescribed, what to do, how to do it, when to do it, who approves it, motive becomes irrelevant. People comply not because they believe, but because they are told.

In these environments, obedience looks like alignment, silence looks like agreement, and compliance looks like character. But this is a mirage. You are not observing who someone is. You are observing who someone is when constrained.

2. Autonomy Is the X Ray for the Soul

Motives only become visible when control is reduced. When there is less instruction, fewer approvals, real discretion, and real tradeoffs, people start to reveal their internal compass. Some step up, protect others, and take responsibility without being asked. Others optimise for personal safety, defer hard decisions, hide behind process, shift blame, or exploit ambiguity.

This is not a failure of governance. This is the test. If you do not allow upcoming leaders space, you never get to see their heart condition or their true motivation for doing things.

3. The Leadership Time Bomb

There is a common pattern that quietly destroys organisations. Juniors operate under heavy control. Motives are never observed. Promotions happen based on execution under constraint. Then, at seniority, controls are removed and behaviour suddenly changes. Leadership is shocked.

By that point, authority has already been granted, political capital has already been accumulated, and reversing the decision is expensive and destabilising. The problem was not that the leader changed. The problem is that you never saw them clearly before.

4. Motives Decide Whether You Will Do the Hard Thing

Consider fraud as a concrete example. Why are you investing in fraud controls? Is it because regulators compelled you? Because the media embarrassed you? Because you fear financial losses? Because auditors raised findings? Or is it because you genuinely love your clients and want to protect them?

These motivations are not equivalent. They produce radically different outcomes.

5. Love Is the Only Motivation Strong Enough

If being good at fraud requires rewriting your app, rebuilding your call centre stack, rearchitecting identity flows, retraining staff, and accepting real short term friction and cost, you will not do it for compliance, optics, or risk registers. It is simply too much effort.

Only love sustains that level of commitment.

Think about children. Even without love, you would still make sure they were fed, clothed, educated, and statistically unlikely to perish. Civilization has standards. But without love, you would almost certainly look for distance. You would outsource the problem to a boarding school, a relative, or an institution with timetables and rules, because children are exhausting, irrational, and profoundly inefficient unless you love them.

Love is what makes the sleepless nights tolerable, the mess forgivable, and the long view worth taking. Children raised without love may survive perfectly well in the short term, but they tend to return later as far more expensive problems. Organisations behave the same way. Without genuine care, leaders will meet minimum obligations, optimise for containment, and outsource discomfort. And just like neglected children, cultures raised without love do not disappear. They grow up.

6. Money as a Motive: How Clients Instantly Know

Now consider a more everyday interaction. If your primary motive is money, then every interaction with a client becomes an opportunity to sell. Cross sell. Up sell. Bundle. Close a deal.

But imagine a client who has had a problem with your company and waited 30 minutes to speak to someone. Trying to sell to them in that moment is not clever. It is inappropriate and insensitive, and the client feels it instantly and the discomfort of the consultant trying to push something at an inappropriate time, is palpable to all.

When the motive is right, the response changes completely. You let them go. You apologise properly. You fix the issue. You give them a loyalty reward. And perhaps quietly, inside that reward, you include the special offer you were hoping to sell. The sale is no longer the point; the relationship is.

When money is the motive, you optimise for extraction. When care is the motive, you optimise for trust.

7. Why Motives Trump Marketing Every Time

Without good motives, nothing is durable. Clients may tolerate you for a while. They may respond to discounts or campaigns. But they will not trust you.

Motives leak. They show up in tone, timing, tradeoffs, and priorities under pressure. They are externally visible, and they overpower whatever marketing budget you have. No amount of brand spend can hide bad intent for long.

Motives make you naked. They expose who you really are to your staff, your peers, and your clients. Which is why it is far better to understand where your team is coming from before your clients do.

8. Culture Is Observed, Not Declared

You cannot train motive, policy motive, or audit motive. You can only observe it. And observation requires reduced control, real autonomy, real responsibility, and real consequences.

Leadership development is not about preparing people to perform. It is about creating conditions where their true motivations surface.

9. The Counterintuitive Leadership Discipline

Great leaders do something uncomfortable. They release control before people are senior. They watch carefully, take notes, and intervene early. This feels risky, but the real risk is discovering too late who someone becomes when they are finally free.

10. The Choice Every Organisation Faces

You can control tightly, promote safely, and be shocked later. Or you can release thoughtfully, observe honestly, and promote with conviction.

Culture is not built by rules.

Culture is revealed by motives under freedom.

1. The Question That Exposes Everything

Walk into any large organisation and ask a deceptively simple question:

“What does everyone do?”

Not what are your job titles, not what does your org chart say, but what do people actually do all day.

The silence that follows is never accidental.

This blog is a reframing of Pournelle’s Iron Law of Bureaucracy, but instead of stopping at criticism, it moves toward organisational design. Not growth. Not scale. Design.

The uncomfortable truth is this:
Most organisations are not designed. They are accumulated. And as with all accumulated systems, organisations will typically overdevelop the wrong muscles.

2. Pournelle’s Law, Reframed for Builders

Jerry Pournelle’s Iron Law of Bureaucracy is often quoted but rarely explained properly. Pournelle observed that in any bureaucratic organisation, two groups inevitably emerge:

1. Those dedicated to the goals of the organisation
2. Those dedicated to the organisation itself

Over time, group two always wins. Not because they are malicious. Not because they are incompetent. But because bureaucratic systems naturally reward process management, risk avoidance, and internal justification over outcome creation.

This is usually presented as an inevitability. A law of nature. Something to be managed rather than designed against. That framing is wrong. The problem is not bureaucracy. The problem is muscle imbalance.

3. The Human Body Got This Right

The human body is not symmetrical. It is intentionally imbalanced.

• The bicep is larger than the tricep
• The quadriceps overpower the hamstrings
• The muscles responsible for action dominate those responsible for restoration

Why?

Because doing work is the primary objective.
Restoring from work is a necessary but secondary function.

If your triceps were as strong as your biceps, you would struggle to lift anything. If your hamstrings dominated your quads, you would fall over trying to walk. Balance is not symmetry. Balance is intentional asymmetry.

4. Organisations Ignore Biology

Most organisations do the exact opposite. They grow antagonist muscles without restraint:

• Risk teams grow faster than delivery teams
• Compliance expands while execution stalls
• Oversight multiplies while accountability evaporates
• Reporting increases while action decays

Soon, the organisation can review, approve, audit, escalate, and govern far better than it can build, ship, fix, or change anything. At that point, the organisation is not safe. It is immobile.

5. The Risk Team Thought Experiment

Imagine a risk function with thousands of people. Now imagine there is nobody with the authority, skills, or capacity to action the outcomes. What do you actually have?

• Risk is identified ✔
• Risk is documented ✔
• Risk is escalated ✔
• Risk is reported ✔

But risk is not reduced. This is not risk management. This is risk theatre.

A massive tricep attached to a withered bicep does not make you safer. It makes you weak in slow motion.

6. Growth Is Not a Neutral Act

Teams cannot be allowed to arbitrarily grow. Headcount is not free. Every new role changes the force distribution of the organisation.

Uncontrolled growth does three dangerous things:

1. It creates internal demand for justification
2. It invents work to sustain itself
3. It shifts power away from execution toward process

At some point, people are no longer hired to do work. They are hired to explain work to other people who do not do it. That is the moment Pournelle’s law stops being theoretical.

7. Composition Beats Size Every Time

The question is never:

“Do we need a risk team?”

The real question is:

“How strong should this muscle be relative to the others?”

A healthy organisation has:

• A dominant delivery muscle
• A smaller but sharp oversight muscle
• A thin but highly competent governance layer
• A direct and short feedback loop between them

The moment an antagonist muscle becomes larger than the muscle it exists to protect, you have inverted the system. And inverted systems always collapse inward.

8. Designing for Intelligent Weakness

Here is the counterintuitive rule:

Some organisational muscles must be kept deliberately weak.

Not incompetent.
Not underfunded.
Weaker – relative to execution.

This forces discipline:

• Risk must prioritise, not catalogue
• Governance must decide, not defer
• Compliance must enable, not smother
• Strategy must choose, not narrate
• Management, team leaders, delivery leads etc must all have dedicated execution teams with agree ratios.

Weakness creates focus.
Strength without constraint creates entropy.

9. Ask Better Questions, Not Just More Questions

“What does everyone do?” is not a one off audit question. It is a leadership habit. But it is not enough on its own. Leaders must also ask:

• What would actually break if this person stopped doing their role tomorrow?
• And do we care?

If nothing breaks, or the only impact is that a report is late or a meeting is cancelled, you are not looking at a critical muscle. You are looking at organisational scar tissue. Closely related is an even more dangerous question:

• Who reads these reports?
• What decisions do they make because of them?
• What actions follow?

If the answers are vague, ceremonial, or deferred to another committee, the output exists to justify the role, not to reduce risk or improve outcomes.

Auditors will never find this.
Dashboards will never show it.
Only a technically and operationally competent leader will.

10. Calculating Your Bloat Ratio

Divide your organisation into two buckets.

Builders:
People who build, design, operate or fix systems.
If they disappeared and outcomes degraded, they are builders.

Everyone else:
Management, coordination, reporting, governance and oversight.

Bloat Ratio =
Non builders divided by builders.

Set targets for this. If you do not, the organisation will choose for you.

Ask the Question Regularly:

What does everyone do is a leadership habit?

Ask:
Who creates value?
Who restores the system?
Who only talks about the system?
What would break if this role stopped?
Do we care?

11. Conclusion: Build Like a Body, Not a Bureaucracy

Organisations are not machines.
They are not flowcharts.
They are living systems.

Living systems survive through asymmetry, constraint, and intent.

If everyone exists to restore, nobody builds.
If everyone governs, nothing moves.
If everyone reviews, nothing improves.

So ask the question.
Then ask what would break.
Then decide if you care.

What does everyone do?

And more importantly:

Which muscles have you allowed to grow without thinking?

Do not be misled, bloat left unmanaged will create its own connected ecosystem and slowly choke your companies life blood. It will kill you faster than your competitors ever could.

Why do Companies Get Stability So Wrong?

Most companies do not fail because they cannot innovate. They fail because they misjudge stability.

Some organisations under invest. They chase features, growth, and deadlines while stability quietly drains away. Outages feel sudden. Incidents feel unfair. Leadership asks how this happened “out of nowhere”.

Other organisations over invest. They build process on process, reviews on reviews, controls on controls. Delivery slows to a crawl. Engineers disengage. The system becomes stable but irrelevant. Eventually the business collapses under its own weight. Both groups are wrong for the same reason.

They treat stability as a thing you can reason about intellectually instead of a resource that behaves physically. Most corporate conversations about stability sound like this:

• “Are we stable enough?”
• “Do we need more resilience?”
• “Let’s prioritise reliability this quarter”
• “Teams can work on stability when they think it’s needed”

These are the wrong questions. Stability is not binary. It is not something you have or do not have. It is something that is constantly leaking away.

Entropy never pauses.
Complexity always grows.
Dependencies always drift.

So the real question is not how much stability do we want? It is how do humans reliably maintain something that is always degrading, even when it feels fine?

To answer that, it helps to stop thinking like executives and start thinking like biology. And that brings us to a very simple walking experiment.

1. A Simple Walking Experiment

Imagine three groups of walkers.
All three walk at exactly 5 km per hour.
The terrain is the same.
The weather is the same.
The only difference is how they consume water.

This is not a story about hydration. It is a story about engineering stability.

Group 1: No Water

This group decides they will push through.
Water is optional. They feel strong. They feel fine.

No surprises. they fail after 3 hours.

Group 2: Unlimited Water

This group has all the water they could ever want. Drink whenever you feel like it. No limits. No rules.

This group goes longer, BUT still fails after 6 hours.

Group 3: One Cup Every 15 Minutes

This group is forced to drink one cup of water every 15 minutes. Even if they are not thirsty. Even if they feel fine. Even if they think it is unnecessary.

They walk forever.

2. Who Wins and Why?

The obvious loser is Group 1. Deprivation always kills you quickly.

But the surprising failure is Group 2. Unlimited water feels like safety. It feels mature. It feels trusting. Yet it still fails. Why?

Because humans are terrible at sensing slow degradation. By the time thirst is obvious, damage is already done. By the time things feel unstable, they are likely in already in a really bad place.

Group 3 wins not because they are smarter.
They win because they removed judgment from the system.

3. Stability Is Like Water

Stability in engineering behaves exactly like hydration. It is:

• Always leaking away
• Always trending down
• Never something you “finish”

You do not reach a stable system and stop.
You only slow the rate at which entropy wins.

The moment you stop drinking, dehydration begins. The moment you stop investing in stability, decay begins. There is no neutral state.

4. Why does “Do It When You Need It” Fail?

Many teams treat stability like Group 2 treats water.

“We can fix reliability whenever we want.”
“We have budget for it.”
“We will focus on it after this delivery.”
“We are stable enough right now.”

This is a lie we tell ourselves because:

• Instability accumulates silently
• Risk compounds invisibly
• Pain arrives late and all at once

Your appetite for stability is not accurate.
Your perception lags reality. By the time engineers feel the pain:

• Pager load is already high
• Cognitive load is already maxed
• Trust in the system is already gone

5. Why Forced, Small, Regular Work Wins

Group 3 survives because the rule is boring, repetitive, and non negotiable.

One cup.
Every 15 minutes.
No debate.

Engineering stability works the same way.

Small actions:

• Reviewing error budgets
• Paying down tiny bits of tech debt
• Exercising failovers
• Reading logs when nothing is broken
• Testing restores even when backups “worked last time”

These actions feel unnecessary right up until they are existential.

The key insight is this:

Stability must be regular, small, and forced, not discretionary.

6. Carte Blanche Stability Still Fails

Giving teams unlimited freedom to “do stability whenever they want” feels empowering. It is not. It creates:

• Deferral
• Rationalisation
• Optimism bias
• Hero culture

Just like unlimited water, people will drink:

• Too late
• Too little
• Only when discomfort appears

And discomfort always appears after damage.

7. Stability Is Not a Project

You do not “do stability”. You consume it continuously. Miss a few intervals and you do not notice. Miss enough and you collapse suddenly. This is why outages feel unfair. “This came out of nowhere.” – it never did. You authored it, when you made stability a choice.

8. The Temporary Uplift of New Leadership and Why It Fades

There is a familiar pattern in many organisations.

New leadership arrives.
Energy lifts.
Standards tighten.
Questions get sharper.
Long ignored issues suddenly move.

For a while, stability improves.

This uplift is real, but it is also temporary.

Why?

Because much of the early improvement does not come from structural change.
It comes from attention.

People prepare more.
Risks are surfaced that were previously hidden.
Teams clean things up because someone is finally looking.

But attention is not a system. It does not scale. And it does not last. Over time, leaders get pulled upward and outward:

• Strategy
• Budgets
• Politics
• External pressure

The deep, uncomfortable details fade from view again. Entropy resumes its work. Eventually the organisation concludes it needs:

• A new leader
• A new structure
• Another reset

And the cycle repeats.

8.1 Inspection Is Not Optional

John Maxwell captured this simply:

“What you do not inspect, you cannot expect.”

Stability is not maintained by policy. It is maintained by inspection. Leaders cannot delegate this entirely.

Dashboards help, but they are abstractions.
Audits help, but they are compliance driven.
Neither replaces technical curiosity.

8.2 Why Audits Miss the Real Risks

Auditors are necessary, but they are constrained:

• They work to checklists
• They assess evidence, not behaviour
• They validate controls, not fragility

They rarely ask:

• What happens under load?
• What breaks first?
• What do engineers silently work around?
• Where are we “hoping” things hold?

A technically competent leader, even without writing code daily, will notice:

• Architectural smells
• Operational anti patterns
• Client complains
• Excessive handoffs during fault resolution
• Risk concentration
• Overly large blast radii
• “Accepted” risks no one remembers accepting

These things do not show up in audit findings.
They show up in deep dives.

8.3 Leadership Must Periodically Go to the Gemba

If leaders want stability to persist beyond their honeymoon period, they must:

• Periodically deep dive the estate
• Sit with engineers in the details
• Review real incidents, not summaries
• Ask uncomfortable “what if” questions

Not continuously. But deliberately. And repeatedly. This does two things:

• It resets attention on the highest risks
• It reinforces that stability is not someone else’s job

8.4 Sustainable Stability Outlives Leaders

The goal is not to rely on heroic leaders. The goal is to build systems where:

• Risk surfaces automatically
• Attention is forced by mechanisms
• Leaders amplify the system instead of substituting for it

New leadership should improve things.
But stability should not depend on leadership churn. When stability only improves after a reset at the top, it is already leaking. The strongest organisations use leadership attention to reinforce cadence, not replace it.

9. The Engineering Lesson

Great engineering organisations do not trust feelings. They trust cadence. They bake stability into time:

• Weekly reliability work
• Fixed chaos testing intervals
• Mandatory post incident learning
• Forced operational hygiene

Even when everything looks fine. Especially when everything looks fine. Because that is when dehydration is already happening.

10. Conclusion: Turning Stability from Belief into Mechanism

Stability does not survive on intent.
It survives on structure.

Most organisations say the right things about reliability, resilience, and operational excellence. Very few hard code those beliefs into how work actually gets done.

If stability depends on motivation, maturity, or “good engineering culture”, it will decay.
Those things fluctuate. Entropy does not.

The only way stability survives at scale is when it is embedded as a forced, recurring behaviour.

10.1 Make Stability Time Non Negotiable

The first rule is simple: stability must have reserved time.

Set aside a fixed day each week, or a fixed percentage of capacity, that is explicitly not for delivery:

• Automation
• Observability improvements
• Reducing operational toil
• Fixing recurring incidents
• Removing fragile dependencies

This time should not be borrowable.
It should not be traded for deadlines.
If it disappears under pressure, it was never real to begin with.

Just like forced hydration, the value is not in intensity.
It is in cadence.

10.2 Always Run a Short Cycle Risk Rewrite Program

High risk systems should never wait for a “big modernisation”.

Instead, always run a rolling program that:

• Identifies the highest risk systems
• Rewrites or refactors them in small, contained slices
• Finishes something every cycle

This creates two critical properties:

• Risk is continuously reduced, not deferred
• Engineers stay close to production reality

Long lived, untouched systems are where entropy concentrates.
Short cycles keep decay visible.

10.3 Encode Stability as Hard Parameters

The most important shift is this:
stop debating risk and start flushing it out mechanically.

Introduce explicit constraints that surface outsized risk early, for example:

• Maximum database size: 10 TB
• Maximum service restart time: 10 minutes
• Maximum patch age: 3 months
• Maximum server size: 64 CPUs
• Maximum operating system age: 5 years
• Maximum sustained IOPS: 60k
• Maximum acceptable outage per incident: 30 minutes

These numbers do not need to be perfect.
They need to exist.

When a system crosses one of these thresholds, it triggers a conversation. Not a blame exercise. A prioritisation discussion.

The goal is not to prevent exceptions. The goal is to make embedded, accepted risk visible.

10.4 Adjust the Numbers, Never the Principle

Over time, these parameters will change:

• Hardware improves
• Tooling matures
• Teams get stronger

That is fine.

What must never change is the mechanism:

• Explicit limits
• Automatic signalling
• Early discussion
• Intentional action

This is how you prevent stability debt from silently compounding.

10.5 Stability Wins When It Is Boring

The organisations that endure do not heroically fix stability problems in crises.
They routinely prevent them in boring ways.

Small actions.
Forced cadence.
Hard limits.

That is how Group 3 walks forever.

Stability is not something you believe in. It is something you operationalise. And if you do not embed it mechanically, entropy will do the embedding for you.

Why More Information Doesn’t Mean More Understanding

We’ve all heard the mantra: data is the new oil. It’s become the rallying cry of digital transformation programmes, investor pitches, and boardroom strategy sessions. But here’s what nobody mentions when they trot out that tired metaphor: oil stinks. It’s toxic. It’s extraordinarily difficult to extract. It requires massive infrastructure, specialised expertise, and relentless refinement before it becomes anything remotely useful. And even then, used carelessly, it poisons everything it touches.

The comparison is more apt than the evangelists realise.

1. The Great Deception

Somewhere along the way, we convinced ourselves that accumulating information was synonymous with gaining understanding. That if we could just capture enough data points, build enough dashboards, and train enough models, clarity would emerge from the chaos. This is perhaps the most dangerous illusion of the modern enterprise.

I’ve watched organisations drown in their own data lakes, though calling them lakes is generous. Most are swamps. Murky, poorly mapped, filled with debris from abandoned projects and undocumented schema changes. Petabytes of customer interactions, transaction logs, sensor readings, and behavioural metrics, all meticulously captured, haphazardly catalogued, and largely ignored. The dashboards multiply. The reports proliferate. And yet the fundamental questions remain unanswered: What should we do? Why are we doing it? What does success actually look like?

Information is not knowledge. Knowledge is not wisdom. And wisdom is not guaranteed by any quantity of the preceding.

2. The Refinement Problem

Crude oil, freshly extracted, is nearly useless. It must be transported, heated, distilled, treated, and transformed through dozens of processes before it becomes the fuel that powers anything. Each step requires expertise, infrastructure, and enormous capital investment. Skip any step, and you’re left with toxic sludge.

Data follows the same brutal economics. Raw data is not an asset. It’s a liability. It costs money to store, creates security and privacy risks, and generates precisely zero value until someone with genuine expertise transforms it into something actionable. Yet organisations hoard data like digital dragons sitting on mountains of gold, convinced that possession equals wealth.

The transformation from data to wisdom requires multiple refinement stages: Data must become information through structure and context. Information must become knowledge through analysis and interpretation. Knowledge must become wisdom through experience, judgement, and critically, self awareness. Each transition demands different skills, different tools, and different kinds of thinking. Most organisations have invested heavily in the first transition and almost nothing in the rest.

3. Tortured Data Will Confess Anything

There’s an old saying among statisticians: torture the data long enough and it will confess to anything. This isn’t a joke. It’s a warning that most organisations have failed to heed.

With enough variables, enough segmentation, and enough creative reframing, you can make data support almost any conclusion you’ve already decided upon. This is the dark side of sophisticated analytics: the tools that should illuminate truth become instruments of confirmation bias. The analyst who brings inconvenient findings gets asked to “look at it differently.” The dashboard that shows declining performance gets redesigned to highlight a more flattering metric. The model that contradicts the executive’s intuition gets retrained until it agrees.

If the data is telling you something that seems wrong, there are two possibilities. The first is that you’ve discovered a genuine insight that challenges your assumptions. This is rare and valuable. The second, far more common, is that something in your data pipeline is broken: bad joins, stale caches, misunderstood definitions, silent failures in upstream systems. Always validate. Always check your assumptions. And be deeply suspicious of any analysis that confirms exactly what you hoped it would.

4. Embedded Lies

Here’s something that keeps me up at night: data doesn’t just contain errors. It contains embedded lies. Not malicious lies, necessarily, but structural deceits built into the very fabric of what we choose to measure and how we measure it.

Consider fraud in financial services. Industry estimates suggest that only around 8% of fraud is actually reported. That means any organisation fixating on reported fraud metrics is studying the tip of an iceberg while congratulating themselves on their visibility. The dashboards look impressive. The trend lines might even be heading in the right direction. But you’re optimising for a shadow of reality.

The organisation that achieves genuine wisdom doesn’t ask “how much fraud was reported last quarter?” It asks questions like: “Who else paid money into accounts we now know were fraudulent but never reported it? What patterns preceded the fraud we caught, and where else do those patterns appear? What are we not seeing, and why?”

These questions are harder. They require linking disparate data sources, challenging comfortable assumptions, and accepting that your metrics have been lying to you. Not because anyone intended deception, but because the data only ever captured what was convenient to capture. The fraud that gets reported is the fraud that was easy to detect. The fraud that doesn’t get reported is, almost by definition, the sophisticated fraud you should actually be worried about.

5. The Illusion of Knowing Ourselves

Here’s where it gets uncomfortable. The data obsession isn’t just an organisational failure. It’s a mirror reflecting a deeper human delusion. We believe we are rational agents making deliberate, informed decisions. Neuroscience and behavioural economics have spent decades demolishing this comfortable fiction.

We are pattern matching machines running on heuristics, rationalising decisions we’ve already made unconsciously. We seek information that confirms what we already believe. We mistake correlation for causation. We see patterns in noise and miss signals in data. We are spectacularly bad at understanding our own motivations, biases, and blind spots.

This matters because organisations are collections of humans, and they inherit all our cognitive limitations while adding a few of their own. When an executive demands “more data” before making a decision, they’re often not seeking understanding. They’re seeking comfort. The data becomes a security blanket, a way to defer responsibility, a defence against future criticism. “The data told us to do it.”

But the data never tells us to do anything. We tell ourselves stories about what the data means, filtered through our assumptions, our incentives, and our fears. Without self knowledge, without understanding our own biases and limitations, more data simply gives us more raw material for self deception.

6. The Famine Amidst Plenty

We are living through a peculiar paradox: a famine of wisdom amidst a gluttony of data. We have more information than any civilisation in history and arguably less capacity to make sense of it. The problem isn’t access. It’s digestion.

Consider how we’ve changed the way we consume information. Twenty years ago, reading a book or a longform article was normal. Today, we scroll through endless feeds, consuming fragments, never staying with any idea long enough to truly understand it. We’ve optimised for breadth at the expense of depth, for novelty at the expense of comprehension, for reaction at the expense of reflection.

Organisations have mirrored this dysfunction. The average executive receives hundreds of emails daily, sits through back to back meetings, and is expected to make consequential decisions in the gaps between. They have access to realtime dashboards showing every conceivable metric, yet they lack the time and mental space to think deeply about any of them. The tyranny of the urgent crowds out the importance of the significant.

Wisdom requires time. It requires sitting with uncertainty. It requires the humility to admit what we don’t know and the patience to discover it properly. None of these things scale. None of them show up on a dashboard. None of them impress investors or boards.

7. What Organisations Should Actually Do

If data is indeed the new oil, then we need to think like refineries, not like hoarders. This means fundamental changes in how we approach information.

First, ruthlessly prioritise. Not all data deserves collection, storage, or analysis. The question isn’t “can we capture this?” but “does this help us make better decisions about things that actually matter?” Most organisations would benefit from capturing less data, not more, but capturing the right data with much greater intentionality.

Second, drain the swamp before building the lake. If you can’t trust your existing data, adding more won’t help. Invest in data quality, in clear ownership, in documentation that actually gets maintained. A small, clean, well understood dataset is infinitely more valuable than a vast murky swamp where nobody knows what’s true.

Third, invest in the refinement stages. For every pound spent on data infrastructure, organisations should be spending at least as much on the human capabilities to interpret it: skilled analysts, yes, but also domain experts who understand context, and experienced leaders who can exercise judgement. The bottleneck is rarely data. It’s the capacity to transform data into actionable understanding.

Fourth, build validation into everything. Assume your data is lying to you until proven otherwise. Cross reference. Sanity check. Ask “what would have to be true for this number to be correct?” and then verify those preconditions. Create a culture where questioning data is rewarded, not punished.

Fifth, ask the questions your data can’t answer. The most important insights often live in the gaps. What aren’t you measuring? What can’t you see? If only 8% of fraud is reported, what does the other 92% look like? These questions require imagination and domain expertise, not just better analytics.

Sixth, create space for reflection. Wisdom doesn’t emerge from realtime dashboards or daily standups. It emerges from stepping back, asking deeper questions, and allowing insights to crystallise over time. This is profoundly countercultural in most organisations, which reward visible activity over invisible thinking. But the most consequential decisions (strategy, culture, longterm investments) require exactly this kind of slow, deliberate cognition.

Seventh, institutionalise self awareness. This might sound soft, but it’s absolutely critical. Decisions made from a place of self knowledge, understanding why we want what we want, recognising our biases, acknowledging our blind spots, are categorically different from decisions made in ignorance of our own psychology. Build in mechanisms that surface assumptions, challenge groupthink, and create psychological safety for dissent.

Eighth, measure what matters. The easiest things to measure are rarely the most important. Clicks are easier to count than customer trust. Output is easier to measure than outcomes. Activity is easier to track than impact. The discipline of identifying what actually matters, and accepting that some of it may resist quantification, is essential to breaking free from data theatre.

8. Decisions From a Place of Knowing

The goal isn’t to reject data. That would be as foolish as rejecting evidence. The goal is to put data in its proper place: as one input among many, useful but not sufficient, informative but not determinative.

The best decisions I’ve witnessed, the ones that created genuine value, that navigated genuine uncertainty, that proved robust in the face of changing circumstances, didn’t come from better dashboards. They came from leaders who understood themselves well enough to know when they were rationalising versus reasoning, who had cultivated judgement through experience and reflection, and who treated data as a conversation partner rather than an oracle.

This kind of wisdom is slow to develop and impossible to automate. It requires exactly the kind of patient, deep work that our information saturated environment makes increasingly difficult. But it remains the essential ingredient that separates organisations that thrive from those that merely survive.

9. Conclusion: From Gluttony to Nourishment

Data is indeed the new oil. Which means it’s messy, it’s dangerous, and in its raw form, it’s nearly useless. It stinks. It requires enormous effort to extract. It demands sophisticated infrastructure and genuine expertise to refine. And like oil, its careless use creates pollution: in this case, pollution of our decisionmaking, our organisations, and our understanding of ourselves.

The organisations that will win the next decade aren’t the ones with the biggest data lakes, or swamps. They’re not the ones with the fanciest analytics platforms or the most impressive dashboards. They’re the ones that recognise the difference between information and understanding, between metrics and meaning, between data and wisdom.

They’ll be the organisations that ask hard questions about what their data isn’t showing them. That validate relentlessly rather than trust blindly. That understand tortured data will confess to anything and refuse to torture it. That recognise the embedded lies in their measurements and actively hunt for what they’re missing.

Most importantly, they’ll be organisations led by people who know themselves. Who understand their own biases, who can distinguish between reasoning and rationalising, who have the humility to admit uncertainty and the patience to sit with it. Because in the end, the quality of our decisions cannot exceed the quality of our self knowledge.

The famine won’t end by consuming more data. It will end when we learn to digest what we already have: slowly, carefully, wisely. When we stop mistaking the swamp for a lake, the noise for a signal, and the comfortable lie for the inconvenient truth.

The first step in that transformation is the hardest one of all: admitting that we don’t know nearly as much as we think we do. Not about our customers, not about our markets, and certainly not about ourselves.

The famine won’t end until we stop gorging and start digesting.