Spare Parts Management? Why Tables are Becoming a Bottleneck

From Tablesheet to Scalable Solution: Why Excel Does No Longer Make the Cut

A missing spare parts number. A machine that is not running. And a team search for the right reference in five different Excel files. It is at this point whether your spare parts management grows with you – or whether the table turns into a risk.

 

Excel as a Starting Point – Simple, Familiar, Free

Excel is in most companies the natural first step. Every professional knows the tool, it does not require an additional license, and new tables are created within minutes. For a moderately sized spare parts management tied to a single location, this runs like a well-oiled machine. The entry investment is low, the result seems clear at first glance. This familiarity is the reason why Excel stays the first choice in many business departments.

This even applies to companies were spreadsheets are far from today’s state-of-the-arts. A IDC survey tasked by Kinaxis from December 2023 demonstrates this. 37 % of German companies continue to trust exclusively in Excel concerning hteir supply chain and inventory planning.¹ Some companies combine Excel with individualized custom solutions.¹ Spare parts constitute a portion of this planning, at times even its most essential part. It should be of little surprise why barely any company starts with a PIM system. The shift is almost always reactive – as the answer to a concrete problem, not the planned fist step.

 

The Turning Point: When Excel becomes the Bottleneck

The turning point rarely emerges abruptly, it comes to be stepwise: A second affiliate, a new product line, more languages in the catalog. Every additional dimension increases table complexity – not linearily but exponentially. What started with a single file turns into ten files with ten diverging versions.

Three triggers occur particularily frequent in practice:

1. Growing varient diversity making individual tablesheets unclear.
2. Multiple company locations each maintaining their own version independently of one another.
3. Increasing record-keeping and documentation requirements that Excel cannot cover by design.

As soon as two of these three factors come together, the table becomes a bottelneck rather than solution path.

To product management teams, this often becomes apparent first in small ways: An inquiry by the service team that nobody can answer right off the bat because the current table version is unlcear. A single incident is no reason to be alarmed. If this repeats weekly, it has grown into a symptom.

 

The Greatest Weakspots of Excel in Spare Parts Management

Missing Standardization and Classification

Excel does not know your consistent product language. Every specialist names columns, attributes, and spare parts numbers based at their own discretion. Similar spare part numbers will be confused, variants wrongly assigned, attributes written differently. “V2A” in one column, “Stainless Stell V2A” in another – both referring to the same material.

Classification standards like ETIM or ECLASS solve this problem structurally. ECLASS is a cross-industrial standard with a four-level hierarchy and a register of more than 23,000 attributes.² Spare parts are hereby classified by their unique identifiers – independent of who manages its data or in what language. Individual departments do no longer need to invent their own system since everybody speaks one and the same data language. This pays dividens especially when catalogs are distributed internationally.

For data management teams, this classification is more than a technical extra. It is the very foundation for all subsequent automation. Without a uniform structure, no data record can be validated reliable, no attribute can be filled automatically, no report can be cleanly evaluated. Those who postpone the classification only delay it until the next assortment expansion.

 

No Pattern Recognition and Duplicate Control

Excel does not validate data records automatically for redundancy. If spare parts are registered twice – deviating slightly in spelling or filed under a different spare parts number – this will often remain undetected. The consequence: contradictory data record, doubled orders, false availability information.

Manual data maintenance intensifies this risk with each newly added table row. Without automatic qualiy validation, the error maring grows in proportion to the data quantity. What is still managable given 200 articles becomes a structural problem in the face of 20,000 articles. And nobody in the team will catch on until the error becomes noticeable to service or the customer.

 

Missing ERP Integration and Loss of Information

There is a glaring gap between Excel file and ERP system in most companies. Data is exported, manually adjusted, and then re-imported – and at each of these steps, there is a risk of transmission errors. A transition between formats is enough to make prices, inventory, or specifications no longer match.

The lack of a system costs more than just time. It destroys traceability. After the fact nobody can reliably state which version of which table was used as the data foundation at what point in time. For IT personnel, this translates into an additional risk: each manual interface is a potential source of error that cannot be automatically covered by any monitoring.

 

Liability Risks in Company Audits

For audits, traceability matters. All logs on who edit what spare parts data and when must be flawless. Excel files do not offer this traceability and, thus, auditability by design. Changes can be overwriten, versions can go missing, and responsibilities are unclear.

For product management teams, this will be quick to turn into a libability risk – not because of errors in the data but because its history cannot be proven. An audit trail, which structured systems offer out-of-the-box, can provide exactly this proof without additional expenses in daily business.

 

The Consequences of Unstructured Spare Parts Data

Idle Costs and Production Losses

Missing or wrong spare parts data has an direct impact on production. The Siemens Report “True Cost of Downtime 2024” judges annual costs caused by unplanned standstills for Fortune-Global-500 companies to be around 1.4 trillion US dollars – this equals 11 % of their total revenues this year.³ Accordingly, an hour of unplanned standstills in the automotive industry costs roughly 2.3 million US dollar.³

Furthermore, the report renders explicit a connection that concerns product management. Complex supply changes delay recovery time after an incident because spare parts are less accssible. Those who do not find the right reference straight away in emergency cases prolong the standstill. This time is irreversibly lost. Time that would have been valuable for other departments.

Naturally, not all companies make the Fortune Global 500. The very same logic, however, still applies: The more unstructured the spare parts data, the longer the search will take should issues emerge and, consquently, the longer the standstill.

 

Time Loss and Inefficient Processes

The time loss beings long before the standstill – already in day-to-day business. This is revealed by a survey conducted by Lucid Software reveals in the year of 2025. More than 2,100 people were surveyed, including 272 from German offices. 49 % of the surveyed people spent one to two hours daily search for information.⁴ 39 % must re-create documents from scratch on a weekly basis because the current files cannot be found anywhere.⁴ As a result, German office workers hereby waste 300 hours per year.⁴

Applied to spare parts management, this means: Every minute spent on searching in dispersed tables is a minute that could have been better spent for product maintenance, sales, or serivce. Those who centralize data gain clarity. Those who gain clarity, in turn, win time for actual labor. Repeated searches turn into a one-time editing task.

 

Checklist: When does the Shift to a Central System Pay Off?

Seven Signs Indicating a Necessary Shift

The following seven signals speak for the shift to a structured system:

1. Multiple locations manage their own tables independently without central coordination.
2. Spare parts must be available in multiple languages and every translation is carried out manually.
3. The variant count grows faster than there is capacity for maintenance.
4. Support requests because of false or missing data increase visibly.
5. Duplicates and contradicting data records repeatedly surface despite internal controls.
6. A company audit is pending or long due.
7. The data volume grows significantly faster than the overview the team has of it.

If at least half of these points do concern you, it is worth taking stock. Not based on a gut feeling, but as a clear decision-making foundation that can be validated internally.

 

This is How a Soft Transition Succeeds

The shift does not succeed over night, and it does not have to. Instead of a big-bang change, a step-by-step migration is recommended. First, you prioritize critical data records – those with the highest potential for causing errors or the highest frequency of use. Subsequently, less pressing areas follow, one step at a time.

Accompanying change management assures your team’s acceptance. Not technology alone decides over the success of the shift, but also how well you integrate the professional personnel. Those who do the on-boarding early reduce resistance and accelarate the migration itself.

 

What a PIM System does Better Than Excel Excel

Central Data Management as the Single Source of Truth

A PIM system gathers all spare parts at a single places. No longer five tables for five truths, but one reliable source for sales, service, and product. This single source of truth guarantees that every channel – from internal ERP up to spare parts catalogs – receive the same consistent information.

For product management, this means less inquiries and feedback loops. For the marketing team, this means catalogs free of error across all channels. For ecommerce, to the extent that spare parts are also sold online, this means less abandoned shopping carts because of incomplete product information. For sales, one effect matters before anythign else: less total cost of ownership. Less manual workhours flow into data management.

 

Automatic Quality Assurance and ERP Connection

A PIM system checks data records automatically for duplicates, missing mandatory fields, and inconsistencies – before they enter production. It scans, validates, evaluates, and marks relevant data records as they emerge instead of making errors visible merely after the fact. Standardized interfaces for ERP replace manual export/import cycles through a continuous, auditable information flow.

The classification via ETIM or ECLASS hereby forms the basis for scaleability. Once cleanly integrated into the system, data must not be repeatedly copied for every location or every product line. Recurring manual effort turns into a reusable standard you only need to define once – future-proof for every subsequent assortment.

 

Next Step: From Managing to Orchestrating

Modern PIM platforms nowadays take this one step further. Orchestrate, agentic workflows take care of recurring validation steps automatically while people intervene were decisions do actually require proper judgement. Human-in-the-loop instead of full automation without control: the system recommends, people decide. This way, the product management team can keep track of what happens with which data record. From the classification to the release of the spare parts catalog.

 

Conclusion: The Right Time for Taking Inventory is Now

Excel was the right entry point. For an ever-growing spart parts assortment with multiple locations, increasing compliance requirements, and expanding variant diversity, however, it is no longer an apt solution. Missing standardization, no duplicate control, a lack of ERP integration, and liability rsiks because of aduits add up to form a risk that keeps growing with each and every data record.

The checklist provided in this article reflects whether the shift is already impending for your company. A well-structured, ERP-integrated product data management creates the foundation that Excel cannot over by design: standardization, traceability, and data quality. A foundation that grows with your assortment instead of slowing it down.

As a cloud-native PIM platform with AI in its DNA, ATAMYA connects the following components: central data management, automatic quality assurance, and smooth ERP connection. Not as a subsequent addon but fully built-in from the get-go. Your spare parts. Your strucutre. Your control over every channel.

Table of Sources:

¹ Source: IDC im Auftrag von Kinaxis, Dezember 2023, veröffentlicht auf Logistik Heute

² Source: ECLASS e.V.: An introduction to the Standard

³ Source: The True Cost of Downtime 2024

⁴ Source: Lucid Software (2025), zitiert nach: t3n: Verlorene Dokumente, langsame Prozesse: Warum deutsche Büros 300 Stunden pro Jahr verschwenden