Start with the absurd: why beginning with extreme values sharpens a calibrated estimate

Outline (brief skeleton)

• Opening: a quick nudge past the common hesitation around estimates, and the surprising first move.

• Core idea: Start with the absurd — why kicking off with extreme values helps you see the full range.

• How to do it: practical steps to begin with the absurd, then tighten toward reality.

• Why it sticks: connecting the method to FAIR concepts like range, uncertainty, and real-world decision impact.

• Quick analogies: everyday examples that make the idea memorable.

• Pitfalls and tips: what to watch for and how to improve the process.

• Takeaway: a concise recap you can apply right away.

Start with the absurd: a surprisingly sturdy first step in calibrated estimates

Let me ask you a simple question: when you’re asked to estimate something risky, what’s the first value you reach for? If your answer is “the reasonable, boring number,” you’re not alone. In risk work, there’s a sneaky bias toward the middle, toward the most plausible outcome, toward what we think will happen. But in FAIR—the framework people use to quantify information risk—the bold move often pays off: start with the absurd.

Yes, you read that right. The first step in a calibrated estimate is to consider extreme or absurd values. This isn’t about endorsing crazy guesses. It’s about widening the mental sandbox so you can see the full spectrum of possibilities, including the ones you’d rather ignore. When you begin with the absurd, you force your mind to stretch beyond comfortable boundaries. That exposure helps you map out a more honest range and, ultimately, a more grounded assessment.

Here’s the thing: human intuition loves the easy path. We lean toward values that feel safe, and we cuddle up to the most likely outcome. That’s fine for quick gut checks, but risk estimation isn’t about a single number. It’s about range, probability, and impact. By starting with the absurd, you create a boundary set—a floor and a ceiling—that you’ll refine as you gather evidence and sharpen your understanding.

How to start with the absurd (without going off the rails)

• Step one: name the extremes. Think of two or three values that seem laughably unlikely. Maybe a scenario where a data breach costs millions, or a situation where a single event cascades into a multi‑million loss. Write them down without judging them. The goal is breadth, not accuracy yet.

• Step two: widen to a realistic spread. Take those absurd values and place them at the edges of a wide, plausible range. Don’t worry about exact probabilities yet. The aim is to visualize the full territory you’re dealing with.

• Step three: anchor with what you know. Now, reference concrete facts you trust: known incidents, historical losses, asset values, and your organization’s threat landscape. This is where the range starts to tighten, but it still includes the outer edges you just explored.

• Step four: layer in uncertainty. FAIR emphasizes uncertainty as a natural companion to risk. Attach qualitative or quantitative confidence to your estimates. If you’re unsure, be explicit about that uncertainty rather than pretending you know more than you do.

• Step five: converge toward a workable estimate. With the absurd values and the anchored reality in view, you can refine your numbers into a range that is both honest and actionable. The goal isn’t a single perfect figure; it’s a credible probability distribution you can use to inform decisions.

A concrete mental model you can borrow

Think of it like weather forecasting. Meteorologists don’t just predict a single temperature. They present a range: low, high, most probable, and confidence bands. The absurd start is like checking the storm’s outer limits—does the system have the potential to be much worse than the usual? From there, you adjust with data, models, and local conditions. The same logic applies to money, time, and security risk. By starting wide, you avoid the trap of “this is what we think will happen, so let’s pretend that’s exact.”

Why this approach sticks in the FAIR framework

• It surfaces uncertainty early. The method makes it natural to talk about probabilities and ranges, not just a point estimate.

• It reduces bias. Opening with extremes helps counteract anchoring and confirmation bias, two stubborn villains in estimation.

• It aligns with how risk actually behaves. Information risk isn’t a neat line from low to high; it’s a spread with tails, surprises, and interdependencies.

A few practical prompts you can reuse

• “If the worst-case here is X, what would be the impact and likelihood?”

• “What’s the ceiling value that would already trigger a serious response? What’s the floor that would barely raise an eyebrow?”

• “What would have to be true for this estimate to be off by an order of magnitude?”

Analogies that make the concept stick

• Negotiating a salary? Start by imagining what you’d ask for if money were no object. Then you scale back to a practical range based on market data and your value. The absurd start helps you see your true leverage and the potential gap.

• Planning a party budget? Picture guests who might bring anything from a cup of soda to a catered feast. You set a broad ceiling and floor, then trim as you confirm guest counts and quotes.

Common potholes to watch for (and how to avoid them)

• Overcorrecting after the extremes. It’s tempting to swing back too hard toward conservatism. Keep the process balanced: preserve the edge values, but connect them to evidence and plausible scenarios.

• Ignoring interdependencies. Risk isn’t always additive. If one event shifts the probability of another, your range can swell or shift. Note those relationships when you refine.

• Treating the absurd as a joke. The point isn’t to laugh at extreme outcomes; it’s to illuminate the possibility space. Take it seriously, even when it feels far-fetched.

• Forgetting to document assumptions. If you don’t record why you chose a value or what evidence supports it, the estimate becomes hard to defend later. Jot down the why and the how as you go.

Where this fits into the bigger picture of risk analysis

Calibrated estimates aren’t a magical number; they’re a narrative about risk. Starting with the absurd helps you tell that story with honesty and clarity. It also makes it easier to communicate with stakeholders who may not live in the numbers every day. You can walk them from the extreme scenarios to the realistic core, showing how each step narrows the uncertainty and clarifies the decision to invest, mitigate, or accept risk.

A quick tour of a practical workflow

• Gather relevant assets and threats. What are we protecting, and what bad things could happen?

• Sketch the outer limits. Think absurd, and capture a few extreme outcomes.

• Anchor with data. Reference past incidents, control strengths, and current exposure.

• Model uncertainty. Attach confidence levels and consider alternatives.

• Refine into a usable range. Produce a credible distribution the team can act on.

• Communicate clearly. Present the range, the most likely values, and the key assumptions.

A final thought to carry forward

Calibrated estimation isn’t about nailing a perfect number. It’s about building a honest line of sight into risk. Beginning with the absurd is a practical shortcut to that clarity. It invites you to think bigger, test assumptions, and then tighten the story with real data. When you do that, you’re not just estimating risk—you’re equipping your team to respond with timing, restraint, and informed judgment.

If you’re curious to explore this approach further, try a small exercise: pick a simple risk scenario relevant to your work, jot down two or three absurd outcomes, then add a grounded set of numbers you know for sure. Watch how your understanding shifts as you move from the far edges toward something actionable. The gains aren’t flashy, but they’re sturdy—and trust me, that steadiness matters when decisions hinge on it.

In short: yes, start with the absurd. It’s a surprisingly solid doorway into calibrated risk thinking, one that can sharpen your analysis, strengthen your arguments, and keep you grounded as you navigate uncertainty.