Comment by tptacek | Hacker News Reader

Comment by tptacek | Hacker News Reader

I'm a broken record on how important I think this document is, and that it's hard to appreciate it until you've had extended experience with complex systems actually failing.

The most commonly cited subtext or thrust of it is that "root cause analysis", at least on complex systems, is a fools errand. Something goes wrong, say, in a distributed lock system, and your whole deployment system enters a metastable failure state. Naturally, the "root cause" seems like lock system resiliency. But definitionally a metastable failure is one that persists after the inciting condition is resolved. Now you have two "root causes", the lock failure and the metastability of the deployment system fault. Keep looking and you'll find more.

But to me the biggest brick to the forehead in this piece is further observation that random things are failing all the time in any complex system. "Complex systems run in degraded mode". Resilient components are good, but it's the resiliency of the overall process that orchestrates the whole system that determines whether things are going to blow up.

All practitioner actions are gambles. I should have that inked somewhere.

>The most commonly cited subtext or thrust of it is that "root cause analysis", at least on complex systems, is a fools errand.

It's only an issue when people take that phrase very literally. People have common sense to understand that things have multiple causes and a chain of events. NASA has "Root Cause Analysis" (singular) all over various official documentation and it doesn't stop them from understanding that the failed O-rings were not the single root cause of the Challenger explosion. Another cause was management normalizing the deviations of previous unsafe datapoints of prior launches which let them greenlight the launch in freezing temperatures. Another cause was the unrealistic flight schedules which can subconsciously pressure management into normalizing dangerous deviations. It wasn't The Rogers Commission that found the multiple causes; it was NASA engineers and management themselves explaining the multiple causes as they were interviewed by the Rogers Commission members.

For whatever reason, alternative jargon such as "Root Causes Analysis" (plural) or "Proximate and Distal Causes Analysis" isn't as widely used.

> Another cause was the unrealistic flight schedules which can subconsciously pressure management into normalizing dangerous deviations.

In the case of Challenger, I think it's pretty clear this was the "root cause":

> According to testimony by Kilminster and Boisjoly, Mason finally turned to Bob Lund and said, "Take off your engineering hat and put on your management hat." Joe Kilminster wrote out the new recommendation and went back on line with the teleconference.

> The new recommendation stated that the cold was still a safety concern, but their people had found that the original data was indeed inconclusive and their "engineering assessment" was that launch was recommended, even though the engineers had no part in writing the new recommendation and refused to sign it.

-- https://onlineethics.virginia.edu/cases/engineering-ethics-c...

If you want to take the "system" view here, as is often the case, it is the organizational power structure and incentives therein that comprise the dangerous system. You had engineering experts easily predicting the disaster, but they had no decision making power. That was the problem. But if you set up an organization like that, where the egos of "get it done" managers are allowed to gamble with other people's lives to win their own accolades, the system is doomed from the start.

If you’re doing “five* whys” analyses correctly, you don’t stop at the technical causes. You continue further to analyze the causes that precipitated the technical errors, too. This exposes the business reasons behind them and forces management to face them.

* the number five isn’t magical here. You don’t have to stop at five, and you often shouldn’t.

A deeper cause there, as I understand it, is that the statistical analysis was incomplete/flawed but in a way that none of the technical practitioners caught and called out at the time. The way the data was presented was to the effect of "half of the o-ring damage incidents were in cold temp launches", which made things seem less bad. The way it could have been presented was more like "nearly every cold temp launch has resulted in damage, only like 10% of others do" (I forget the exact numbers) which is far more effective highlighting the impact of the temperature and the magnitude of the increased risk. And that would've let people make a stronger case "hey, we know temps in the 50s cause damage almost every time, and it's way colder today."

There's a "system" aspect (outside of power structures and incentives) which is that prob/stats knowledge among almost all engineering disciplines (industrial engineering waves from the sidelines) is exceedingly poor and often viewed as "soft" and "less important" than calculus, linear algebra, etc. And so practitioners are ill-equipped at spotting things like that ("wait, is this the right denominator? what about frequency of incident?").

> I'm a broken record on how important I think this document is, and that it's hard to appreciate it until you've had extended experience with complex systems actually failing.

If you want a bit of cheese to go with that wine, this article pairs nicely with The Grug-Brained Developer: https://grugbrain.dev/

“Root cause analysis”, like “single point of failure”, is often misunderstood. A root cause analysis often finds multiple root causes. And a system can have multiple single points of failure.

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