Some of us have felt the pain.

It’s 3am. The line’s on stop. A long trudge to stores, the rummaging around, shoulder shrugs and head-scratching. The result: an empty, dusty space on the shelf where your spare once was.

Then the delicate argument of who’s going to deliver the news to Dave, the hard-to-please Line Manager.

‘It’s your turn!’ ‘No chance!’ ‘I did it last time…’

Walk into most maintenance stores and you’ll find two things sitting side by side: shelves of spares collecting dust, and an empty space for the part that just took a whole line down with it. It’s a frustrating industrial contradiction — piles of cash tied up in inventory, and still the part you need isn’t there.

This isn’t a coincidence. It’s predictable for how most stock decisions get made. And how rarely they get revisited.

In Smart Inventory Solutions, Phillip Slater describes the mechanism: “any stockout triggers an action, not only to restock but also typically to overstock, in order to avoid the negative consequences of the stockout.” The problem is what happens next. “If the inventory is already overstocked… there may not be a stockout to trigger a need to take action… A company may be overstocked and never perceive that it has a problem.”

The company doesn’t know what it doesn’t know.

Running out of a spare triggers a quick fix (as well as an argument with Dave).

But… holding too many triggers nothing (well… at least once a year… an irate Finance Manager is triggered).

‘The only reason for keeping a stock of spare parts is to avoid or reduce the consequences of failure’ John Moubray, RCM II.

Over years, that asymmetry quietly fills the stores with excess stock of parts that rarely fail, while the critical, hard-to-source items stay exposed to the same risk that caused the last stockout.

A challenging driver is the imbalance between the cost of the part and the cost of not having it.

A £500 seal or sensor is easy to justify stocking when the alternative is a production line down for days, so people stock up “just in case.” That logic can be hard to argue with in the moment or as a knee-jerk reaction to a failure. Applied without review across thousands of line items, it’s exactly how years of dead stock build up — accumulating, one reasonable-sounding decision at a time.

Then there’s the “critical spares” problem.

Every plant has a list of parts nobody is allowed to interfere with because they’re “critical.” Slater’s view is blunt: “You can still hold too much of a critical item… the comments I hear on critical spares are usually more emotional than scientific.”

Emotional – not data-driven – decisions, the eternal problem.

Criticality justifies holding a spare. It doesn’t justify holding five of them or holding one perpetually without checking whether the failure mode, lead time, or usage pattern has changed since the first decision.

That distinction matters, because being labelled “critical” tends to switch off scrutiny rather than invite it — nobody wants to be the person who cut stock that caused a shutdown… and made Dave furious. So critical spares often get wilfully ignored, despite carrying the biggest stake.

The fix isn’t a blanket instruction to cut inventory.

It’s replacing “we’ve always stocked this” with actual analysis: failure modes, lead times, consequence of downtime, and real usage data, reviewed on a cycle rather than set once at commissioning and never revisited. That’s the discipline behind effective spares optimisation, and it applies as much when you’re bereft of parts or you’re short of them.

It’s also where AI is starting to earn its place — facilitating the analysis but also making it practical to run at scale. Reviewing every line item by hand across tens of thousands of spares will not happen in most organisations; there isn’t time. AI-assisted analysis changes that by flagging the genuine outliers — the excess stock and the exposed gaps — so engineers spend their time on judgement calls instead of a tedious spreadsheet.

The paradox isn’t about too much inventory or too little.

It’s about how few organisations ever go back and test whether the original stocking decision still holds up. The ones that do tend to find both problems at once: cash tied up in stock they don’t need, sitting alongside gaps in the stock that assure asset uptime.

The leading-edge organisations are already leveraging spares demand forecasting, risk management, stock level optimisation, dashboards and KPIs.

Kickstart the solution: Come talk to ProAIM today