Why More Spare Parts Don’t Mean Less Downtime
From reactive stocking to strategic control
The €5 million spare part
In one of our expert interview series, Rreliability engineer Sanjib Das recalls a refinery turnaround that had been meticulously planned for two years. Hundreds of contractors were mobilised; every second was choreographed. It was meant to be a precise, high-speed shutdown.
Instead, the refinery stayed offline for two extra weeks.
The reason was not a major failure.
It was a single spare shaft.
On the ERP screen, it looked correct. In the warehouse, it appeared to match. But when the team attempted installation, they realised it was slightly out of specification. It had never been properly validated.
“It extended the turnaround two weeks because of these little spares… and that is a lot of money for a refinery.”
This story reveals a fundamental truth about industrial operations:
Spare parts do not prevent failures.
They determine how long the failure hurts.
When the right spare is available and validated, downtime is contained. When it is missing, duplicated, or incorrect, downtime escalates, often dramatically.
The instinct to stock more
In most organisations, spare parts strategies are not designed. They evolve.
A failure occurs. A part is missing. Production is impacted.
The lesson seems obvious: ensure this never happens again.
So the part is stocked. Then another. Then more.
Over time, this creates a quiet accumulation. Shelves fill up. Safety stocks increase. More items are labelled as critical, often without re-evaluation.
It feels like progress. It feels like risk is being reduced.
But something does not add up.
Warehouses full. Still the wrong part missing.
Across industries, from automotive to pharmaceuticals, the same pattern appears.
Warehouses hold tens of thousands of items.
Working capital is tied up in inventory.
And yet, when a failure occurs, the required spare is still unavailable.
It is a paradox that many teams recognise but struggle to explain.
As Meir Veisberg, CEO of SPARROW, puts it:
“Most companies don’t have a spare parts problem because they stock too little. They have a problem because they don’t know what they already have.”
The issue is not effort. Nor is it intent. It is visibility.
The hidden cost of “just-in-case”
Inventory is often treated as a safety net, something passive that sits on a shelf, waiting to be used.
In reality, it behaves very differently.
Every spare part requires space, handling, inspection, and administration. It must be counted, preserved, and occasionally replaced before it is ever used.
Over time, this creates a significant cost layer.
According to supply chain benchmarks, inventory carrying costs typically range between 20% and 30% of total inventory value per year.
This includes storage, capital costs, obsolescence, and operational overhead.
And yet, even with this investment, availability is not guaranteed.
If you're particularly interested into that topic, Reliability Expert Sanjib Das had crafted a fairly extensive list of all costs related to keeping inventory during an interview with SPARROW.
Where the system breaks down
To understand why, you have to look beyond the warehouse and into the data.
In most industrial environments, spare parts data has grown organically over years, often across multiple systems and sites. New parts are added under pressure. Descriptions vary depending on who enters them. Technical attributes are incomplete or missing. ERP systems make it difficult to identify whether a part is already in the system or not before creating a new one.
The result is a fragmented material master:
- the same bearing exists under different names
- identical parts are stored under separate IDs
- manufacturer references are missing or inconsistent
- equivalent components are not linked
From the system’s perspective, these are different items.
From the engineer’s perspective, they are often the same.
This disconnect has real consequences.
Companies unknowingly buy parts they already own.
Demand is split across duplicates.
Criticality becomes difficult to assess.
And when a failure occurs, the right part may be somewhere in the organisation, just not where or how it is needed.
Why more inventory doesn’t fix the problem
“Just-in-case” inventory assumes that risk can be managed by increasing availability.
But if the underlying data is unreliable, more inventory simply amplifies the problem.
More duplicates.
More complexity.
More capital tied up in the wrong places.
As Meir Veisberg explains:
“If your data is fragmented, scaling inventory doesn’t reduce risk, it scales inefficiency.”
This is why many organisations reach a point where increasing stock no longer improves reliability. It only increases cost.
A shift from reaction to structure
Leading industrial companies like Bayer are beginning to approach spare parts differently.
Not by asking how much to stock, but by asking:
Do we understand what we have?
Do we know what actually matters?
Are we managing inventory as a system or as isolated decisions?
This shift is less about tools and more about mindset. Bayer moved spare parts management from a reactive function to a structured capability. And it indeed led to inventory reduction, as Dirk Herbrich, Data Value Stream Lead for Acquire to Retire in CORE, Bayer AG, confirmed:
“If anybody in your organisation says there are no duplicates—bet €100 you’ll find some. At Bayer Berlin, we reduced materials from 63.000 to 48.000. That’s 20% duplication proven, not theoretical.”
Building the foundation: clarity in spare parts data
The first step is deceptively simple: create a clear and reliable view of the spare parts landscape.
This is where many transformation efforts begin.
With SPARROW.Clean, companies can analyse and structure their material master data at scale. Duplicate parts are identified, descriptions are standardised, and manufacturer references are restored.
What emerges is not just cleaner data but visibility.
For the first time, organisations can answer a basic but critical question:
Do we already have this part?
From intuition to decision-making
Once data is reliable, a second shift becomes possible.
Stocking decisions can move beyond experience and individual judgement.
Instead of relying on past incidents, companies can evaluate spare parts based on:
- failure probability
- lead time
- operational criticality
- cost of downtime
SPARROW.Plan supports this transition by embedding these factors into a structured decision framework.
The objective is not to reduce inventory at all costs.
It is to ensure that every stocked part has a clear reason to exist.
Seeing beyond the single site
The next layer of complexity appears in multi-site organisations.
Spare parts are often managed locally, with limited visibility across plants. As a result, the same components are stocked multiple times, without coordination.
At the same time, procurement tends to follow established sourcing paths, often relying heavily on OEMs.
Recent supply chain disruptions have highlighted the risks of this approach. According to Deloitte, 79% of organisations experienced supply chain disruptions in recent years, exposing the fragility of single-source dependencies.
With SPARROW.Pool, organisations can begin to treat inventory as a shared resource:
- identifying parts that exist across multiple sites
- enabling cross-plant availability
- reducing redundant stock while maintaining service levels
Inventory becomes part of a network, not a collection of silos.
From spare parts to resilience
What emerges from this shift is not just a more efficient warehouse.
It is a more resilient operation.
Spare parts are no longer managed as isolated items stored “just in case”.
They become part of a system that determines how quickly a company can respond when something goes wrong.
And that is ultimately what matters.
Conclusion
Most spare parts strategies don’t fail because of bad intentions.
They fail because decisions are made without a clear view of reality.
When the same component exists under multiple names, when stock is spread across sites without visibility, and when criticality is based on past incidents rather than actual risk, adding more inventory doesn’t solve the problem. It compounds it.
That’s why leading manufacturers are changing their approach.
Not by cutting inventory blindly, but by building the capability to decide:
- what truly needs to be stocked
- where it should be available
- and what can be sourced differently
As Meir Veisberg puts it:
“In most organisations, 20 to 30 percent of spare parts inventory is effectively invisible: duplicated, misclassified, or simply not trusted. Until you fix that, every inventory decision is made on shaky ground.”
Because in the end, downtime is rarely caused by a lack of parts.
It’s caused by not knowing which parts matter or where they really are.
And that’s a problem inventory alone will never fix.
