This post was on LinkedIn from my friend Gary Cookson.  He is working on his next great book, and is looking for input from others that he could possibly incorporate in his new work.

If you have great stories or examples, either email him at - gary.cookson@epichr.uk.co or connect with him in LinkedIn and message him.

Here's the post - Steve

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A few weeks ago, I asked for examples for a book idea I am developing - those moments when a system produces an answer that is technically correct, procedurally defensible, but obviously wrong.

The idea has developed since then. I am now interested not only in systems going wrong, but in why people follow them when they can see the problem -and what enables someone to question, override, or improve them responsibly.

I am particularly looking for examples where:

• A rule or process produced a result that was clearly wrong, but nobody felt able to challenge it.
• A target, score, or label left out something important and led to a poor decision.
• One person was allowed an exception while somebody in a similar position was not, without a convincing reason.
• Someone did challenge or change a system - and the organisation learnt from what happened.

The “system” could be a policy, form, approval process, target, piece of software or AI tool. The example does not need to be dramatic - everyday decisions can reveal just as much.

Most of my current examples come from recruitment, HR policy, performance management and education. I want the book to reflect what happens across whole organisations, not simply HR talking to HR about HR. I would therefore love to hear examples from other areas of work: operations, finance, customer service, healthcare, public services, technology, manufacturing - or anywhere else that rules and systems shape decisions.

And if you do not have an example yourself, who might? Please consider forwarding this post or introducing me to someone with a different perspective. Examples can be named or anonymised. A short outline of what the system did, why the result felt wrong, and what happened next would be enormously helpful.

This is not about proving that systems are bad or that human judgement is always right. It is about understanding how systems can support good decisions without becoming a substitute for them.

Thanks in advance for anything you're willing to share! - Gary