Dirty Data Is the Hidden Cost of ERP Projects

In ERP projects, processes, modules or software vendors do not unlock success.
The real key is often hidden in a place that is overlooked. DATA!

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For ERP systems to produce correct and consistent results, they are directly proportional to data quality.
The more solid your core data is, or the more reliable the sources from which data is collected, the more accurate and meaningful the output the system will deliver to you.

But the downside is this:
Before starting the project, most organizations forget to assess data quality.
And because they do not plan how much effort and cost to spend on this during the project, they experience major miscalculations.
In the end they face unexpectedly extended timelines, increased consultant time and internal resource depletion.

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So what should be looked at?

✅ From item masters to product structures,
✅ From accounts receivable to chart of accounts,
✅ From time studies to routing structure,
✅ From warehouse, shelf and department layout to purchasing–sales variety…

The more organized your structure is in this and many similar core data areas, the faster, more solid and lower-cost your ERP transition will be.
If not? That is when the chain of hidden costs begins…

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ERP consultants play a very critical role at this point:
They guide data preparation, show gaps, and describe how it should be set up in the system.
But data quality starts with the organization's own preparation, not with the consultant.

The more accurate, up-to-date and owned the data you start with, the more solid, fast and low-cost the project will progress.

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Moreover, it is not only the initial data; how the data will be set up in the ERP system also requires a separate preparation process.

📌 Companies, plants, branches, dealers…
How will they all be positioned within a single database?
How will the data be linked to each other?
How will data ownership and authorizations be defined?

All these decisions determine the future resilience of the ERP.

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Another critical issue is the quality of data collection from the field.
However well you transfer the initial data, if the operational data coming from the field is wrong, the system still fails.
Whether manual entry or IoT integration, correct data is needed first for correct results.

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ERP systems work with relational data logic.
Therefore:

📌 Data must be linked to each other,
📌 Arbitrary updates must not be made on it,
📌 Consistency must not be broken.

Because data consistency is equivalent to efficiency in ERP systems.

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The real question that should be asked before technical infrastructure in ERP projects is:

"Are we moving to ERP because of inefficiency,
or is our data gap making us inefficient?"

Because the outputs expected from the system are nothing but a reflection of the inputs you give.