The “One More” Trap: How Small Risks Turn Into Big Failures

One More” Becomes the Problem: Escaping the Static Risk Trap

The Comfort of Familiar Risks

There’s a quiet illusion that creeps into most systems over time — the belief that if a single risk was acceptable once, it must still be acceptable now. It feels harmless, almost logical. After all, if adding one admin account didn’t cause a breach, what’s the harm in adding another?

That’s the trap.
The danger isn’t in the single decision — it’s in the repetition.

The static risk fallacy happens when we judge each risk in isolation instead of looking at how they multiply together. The first exception feels like a small compromise. The tenth feels like “business as usual.” And before anyone realizes it, the organization has quietly drifted into a position of systemic fragility.

In law, risk is about totality. No one evaluates a case without looking at the whole picture. Yet in security and systems, we often do the opposite — approving one-off risks without pausing to consider their accumulation.

The truth:
Repetition transforms the shape of risk. A single point of failure can be tolerated; ten identical ones become a network of vulnerability.

Tip:
Whenever you hear “it worked last time,” pause. That phrase often signals a creeping normalization — the slow slide from one exception to an entire culture of exceptions. Ask instead: Has the context changed? Because risk doesn’t stay static; it compounds silently.

How Risk Accumulates Without Being Noticed

Think of every decision — every new account, vendor integration, or system access — as adding a thread to an invisible web. Individually, each thread looks weak. Together, they create tension that eventually snaps under its own weight.

Inside organizations, this looks like:

• Multiple privileged accounts across departments.

• Repeated vendor approvals with similar access levels.

• Unpatched systems left waiting “just one more sprint.”

Across entire ecosystems, it looks like:

• Thousands of companies relying on the same open-source dependency.

• Shared infrastructure or libraries maintained by a single individual.

Each decision is small. But collectively, they redefine exposure.
That’s the essence of the static risk fallacy — treating replication as harmless when it’s mathematically the opposite.

The risk doesn’t grow in a straight line; it multiplies. Ten accounts with a 1% annual chance of compromise don’t equal 10% risk — the odds of any one of them being breached climb much faster. The math turns tolerance into inevitability.

Tip:
Quantify repetition. Create visibility into how many times a certain “approved” risk has been duplicated. Seeing the total count often reframes what feels tolerable into something obviously unsustainable.

How Canva, Perplexity and Notion turn feedback chaos into actionable customer intelligence

Support tickets, reviews, and survey responses pile up faster than you can read.

Enterpret unifies all feedback, auto-tags themes, and ties insights to revenue, CSAT, and NPS, helping product teams find high-impact opportunities.

→ Canva: created VoC dashboards that aligned all teams on top issues.
→ Perplexity: set up an AI agent that caught revenue‑impacting issues, cutting diagnosis time by hours.
→ Notion: generated monthly user insights reports 70% faster.

Stop manually tagging feedback in spreadsheets. Keep all customer interactions in one hub and turn them into clear priorities that drive roadmap, retention, and revenue.

Get a personalized demo

Why It Feels Rational — and Why It Isn’t

Human reasoning naturally bends toward consistency. If one risk was okay before, rejecting the same risk later feels inconsistent, even unfair. Psychologists call this creeping normality — slow changes that blend into the background until you forget where you started.

This is why the static risk fallacy feels persuasive. Each new exception looks familiar, and familiarity feels safe. But comfort is not control.
In security — and in any system built on trust and access — consistency must give way to perspective.

Every “yes” adds to the pile, even if that pile is invisible. And yet, frameworks like NIST and ISO have only lightly touched on aggregation. They recognize that risk adds up — but few require leaders to confront it directly. No built-in checkpoint forces the question: Has our total exposure become unacceptable?

The result is a landscape of organizations that manage risk logs instead of risk reality — documenting each approval individually while missing the cumulative curve that eventually breaks their defenses.

Tip:
Reframe approvals. Don’t evaluate each new risk on its own merit. Evaluate it against the total. Ask, What’s the new sum of exposure once we say yes again? That single shift in framing is where strategy starts.

The Gold standard for AI news

AI will eliminate 300 million jobs in the next 5 years.

Yours doesn't have to be one of them.

Here's how to future-proof your career:

• Join the Superhuman AI newsletter - read by 1M+ professionals

• Learn AI skills in 3 mins a day

• Become the AI expert on your team

Start learning AI now

The Human Side of the Fallacy

It’s easy to blame this problem on systems or frameworks, but at its core, the static risk fallacy is human. It’s how people make decisions under uncertainty — one at a time, without realizing the patterns they’re creating.

When a system tolerates exceptions too easily, it’s not just a technical issue; it’s cultural. Teams learn to think short-term, optimizing for convenience instead of resilience. The pressure to move fast overrides the need to think holistically. And over time, that bias turns into muscle memory.

Normalization of deviance — the idea that “it hasn’t failed yet, so it must be fine” — is often confused with this pattern. But they’re cousins, not twins.

• Normalization of deviance ignores evidence of a single risk.

• Static risk fallacy ignores the math of repetition.

The first blinds you to warning signs. The second blinds you to accumulation.

Tip:
Embed the habit of reflection. Before repeating a decision, ask: Would I still approve this if I had to make the same choice ten more times?
That mental exercise instantly reframes short-term convenience as long-term exposure.

Used by Execs at Google and OpenAI

Join 400,000+ professionals who rely on The AI Report to work smarter with AI.

Delivered daily, it breaks down tools, prompts, and real use cases—so you can implement AI without wasting time.

If they’re reading it, why aren’t you?

Join 400K+ pros

Breaking the Pattern — Designing for Awareness

Escaping the static risk fallacy starts with visibility. The moment you can see repetition, you can control it.

Here’s how to break the pattern — without slowing everything down:

1. Shift the frame.
   Don’t ask whether one more risk is acceptable; ask whether ten of them would be. Context turns a single approval into a strategic decision.
   

2. Name the blast radius.
   Every new dependency, vendor, or integration adds an outage surface. Map the total impact — not just for today, but across all existing approvals.
   

3. Cap repetition.
   Approve a new instance only if another can be retired. Rotation prevents silent accumulation and forces prioritization.
   

4. Make accumulation visible.
   Add a “Risk Approval Threshold” in governance. Before signing off on a recurring risk type, calculate the new aggregate exposure. Make it visible, reviewable, and owned.
   

5. Assume breach.
   Design with failure in mind. Privileged access management, zero-trust architecture, segmentation, and just-in-time credentials are not luxuries — they’re acknowledgments that “eventually” is always sooner than expected.
   

6. Justify repetition.
   The burden of proof should grow with every duplicate decision. Each repetition should have to earn its place.

Because the truth is simple: risks don’t stay still. They stack, they amplify, and they evolve faster than policies do. And the only real defense against the static risk fallacy is awareness — not just of what’s been approved, but how often it’s been repeated.

Final Thought:
Most systems fail not because of one bad decision, but because of a hundred small, reasonable ones that no one stopped to total.
Strategy, security, and stability all begin in the same place — with someone finally asking, “What’s the whole picture?”

What’s your next spark? A new platform engineering skill? A bold pitch? A team ready to rise? Share your ideas or challenges at Tiny Big Spark. Let’s build your pyramid—together.

That’s it!

Keep innovating and stay inspired!

If you think your colleagues and friends would find this content valuable, we’d love it if you shared our newsletter with them!

PROMO CONTENT

Can email newsletters make money?

With the world becoming increasingly digital, this question will be on the minds of millions of people looking for new income streams in 2025.

The answer is—Absolutely!

That’s it for this episode!

Thank you for taking the time to read today’s email! Your support allows me to send out this newsletter for free every day. 

 What do you think for today’s episode? Please provide your feedback in the poll below.

Share the newsletter with your friends and colleagues if you find it valuable.

Disclaimer: The "Tiny Big Spark" newsletter is for informational and educational purposes only, not a substitute for professional advice, including financial, legal, medical, or technical. We strive for accuracy but make no guarantees about the completeness or reliability of the information provided. Any reliance on this information is at your own risk. The views expressed are those of the authors and do not reflect any organization's official position. This newsletter may link to external sites we don't control; we do not endorse their content. We are not liable for any losses or damages from using this information.