Monte Carlo vs. Fixed-Percentage Contingency

The "add 10%" habit versus a measured number — how they differ, why it matters at bid time, and when each one is the right call.

Most contingency in construction is set the same way it was fifty years ago: pick a percentage, add it on, move on. Ten percent is the reflex. But "add 10%" is a habit, not a method — and when a reviewer or a client asks why that number and not 8% or 15%, there's rarely a good answer. This guide compares the traditional fixed-percentage approach with a Monte Carlo simulation, and makes the case for why the second produces a number you can actually defend.

How fixed-percentage contingency works

The traditional method is simple: total your estimate, multiply by a contingency percentage, and add it to the bid. The percentage usually comes from company convention, personal experience, or a gut read of how risky the job feels.

It's fast, and it's better than nothing. But it has three real weaknesses:

• It's uniform. A flat 10% treats a well-defined mechanical scope the same as a wildly uncertain sitework package. Risk isn't distributed evenly across a job, but a single percentage pretends it is.
• It's unexplainable. You can't say what a 10% contingency actually buys you in terms of probability. Is it enough to cover the job 6 times out of 10? 9 times out of 10? The number doesn't know, and neither do you.
• It ignores how risk compounds. A flat percentage has no way to account for the scenario where several trades overrun together — which is exactly the scenario that turns a thin bid into a loss.

How Monte Carlo contingency works

A Monte Carlo simulation approaches the problem from the other direction. Instead of guessing a buffer, it prices the job thousands of times — each pass drawing a cost for every line item from within its realistic range — and builds a distribution of possible totals.

From that distribution, contingency falls out naturally: it's the gap between your expected cost (P50) and whatever confidence level you choose to price at (say P80 or P90). The number isn't assumed. It's measured from the ranges you actually set.

The honest case for keeping it simple sometimes

To be fair: fixed-percentage contingency isn't wrong for every situation. On a small, familiar, low-risk job where you've done twenty like it, your gut percentage may be perfectly adequate, and a full simulation is overkill. The value of Monte Carlo climbs with the size, complexity, and unfamiliarity of the job — exactly the bids where getting contingency wrong hurts most.

Why the difference matters at bid time

The two methods don't just differ in rigor — they change the conversation. With a fixed percentage, the contingency line is a soft target, the first thing a competitive review wants to cut, and you have no data to defend it. With a simulation, you can say precisely what cutting it costs you: "drop to this number and we're pricing at P60 — the job comes in over four times out of ten." That reframes contingency from a negotiable cushion into a measured business decision. And that's the difference between defending your number and just hoping it holds.