In many companies, data quality is still viewed as an issue of oversight or compliance. It’s seen as a distant concern, tied to reporting, audits or annual closings. Yet this view overlooks a much more tangible reality: data quality influences the smooth running of daily operations, at every stage. And when that quality is lacking, it is users, processes and overall performance that suffer the consequences.
1. A single data error can block an entire workflow
In an ERP system, data flows from one module to another and triggers many operations: order validation, invoice generation, product receipt, payment execution. A single incorrect data point, such as an item code, project number, or VAT rate, can lead to an automatic rejection or halt the entire process.
This phenomenon, often invisible to non-expert profiles, causes cascading blockages: an order is not placed, a delivery is halted, an expense is misallocated. Over the course of a day, these disruptions directly interfere with the normal pace of operations.
2. Operations slowed by inefficient validation and checks
Incorrect or incomplete data forces teams to introduce manual verification steps. A poorly filled form, a missing reference, or a bypassed business rule forces users to pause their task, request clarification, or follow up with another department.
Validations are delayed, lead times are extended, and staff waste time on corrections rather than focusing on their core activities. This breakdown in workflow fluidity affects team responsiveness and the quality of service delivered to customers or internal stakeholders.
3. Employees forced to bypass the system
When a system fails to reflect operational reality, or when its data is seen as unreliable, users begin to develop their own working methods: local Excel files, parallel emails, multiple entries to get around blockages. While understandable, these practices create an informal, ungoverned and risky information system.
Over time, this makes processes more opaque, data less traceable, and the tools themselves less used. Data quality is no longer just a technical issue, it becomes a factor in eroding trust in the system.
4. Business teams focused on fixing rather than producing
Data errors consume significant time, often invisible, yet very real: checking allocations, chasing confirmations, manual validations, accounting adjustments, support calls… These tasks, outside the initial scope of a role, quickly become routine.
Instead of focusing on value-added activities, staff become managers of corrections. Operational efficiency takes a direct hit, and frustration builds in the face of recurring issues with no clearly identified owner.
5. Users lose confidence in the system’s reliability
When errors become frequent, users start to lose trust in the system. An inconsistent amount in a report, an unjustified alert, missing supplier information… Even minor incidents undermine the tool’s credibility and reinforce mistrust.
This lack of trust leads to minimal use of system features, over-reliance on support, and hesitation to treat the tool as a reliable source of truth. The ERP, meant to be the backbone of the information system, becomes a secondary tool—something to endure rather than control.
Conclusion
Data quality is not a remote issue reserved for management or support functions. It is an immediate operational performance lever, essential to the smooth running of daily activities.
Every day, in every task, the reliability of data determines workflow efficiency, responsiveness, and a team’s ability to do its job properly. That’s why it’s vital to move beyond the idea that data is a “technical concern” and recognise it for what it truly is: an essential part of doing good work.
👉 Our next article will focus on 10 Secrets to Improve the Quality of Data Entered in an ERP System
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