Stop Re-Fixing the Same Problem: The Root Cause Excavator
When a problem survives three different fixes, you're treating symptoms. A 5-step recipe (plus a paste-and-run AI prompt) to dig out the cause that keeps regrowing it.
The stuck moment. You run a 12-tech HVAC company and your callback rate on installs has sat near 15% for a year. You retrained the crews, rewrote the install checklist, and replaced your lead installer. Each fix bought you one good month. Then the callbacks came back. Now you're debating $30K on new job-management software, and you quietly suspect it won't fix it either.
The signal: when the same problem survives three different fixes, the fixes aren't failing: they're aimed at the wrong layer. Time to excavate.
The recipe: Root Cause Excavator
- List every recurrence. Pull every instance from the last 90 days (dates, jobs, crews, what actually went wrong). The pattern lives in the instances themselves, and a summary smooths it away.
- Autopsy your fixes. For each fix you tried, write down the cause it silently assumed. "Retraining" assumed a skill gap. "New checklist" assumed forgetfulness. Those assumptions have now been tested, and disproven.
- Dig below the fix layer. For each instance, ask "what allowed this to happen?" until the answer is a process, incentive, or information gap rather than a person or a one-off.
- Find the survivor. The root cause is whatever shows up across most instances AND was untouched by every fix. (Often it's an incentive: crews get paid when the install is completed, whether or not it holds.)
- Run the prevention test. If this cause had been fixed a year ago, would most of those instances have been prevented? Yes → fix that. No → keep digging.
The AI move. Paste this, fill the brackets:
Role: You are a root-cause analyst for a [business type] doing [$X revenue] with [team size] people.
Context: The same problem keeps returning despite repeated fixes. The problem: [describe it]. Every instance from the last 90 days: [dates + what happened]. Every fix I've tried and when: [list].
Task: 1) For each fix, state the cause it implicitly assumed. 2) For each instance, ask "what allowed this?" 3–5 times until you reach a process, incentive, or information-flow cause, never a person. 3) Identify candidate root causes that appear across most instances AND were untouched by every fix. 4) Prevention test: for each candidate, state which past instances fixing it would have prevented. 5) Recommend ONE fix for the top root cause, with a first step I can take this week.
Format: Table of fixes vs. assumed causes → the why-chains → ranked root causes with prevention-test scores → the single recommended fix.
Constraints: Do not accept "human error" or "needs more training" as a root cause. If my data is too thin to be confident, tell me exactly what to log for the next two weeks instead of guessing.
What it's worth: every repeat fix costs a month of margin and morale. Excavating once ends a problem you'd otherwise re-buy quarterly.