Why poor ERP data quality is crippling mid-sized manufacturers
Many mid-sized industrial firms face persistent problems with data quality in their ERP systems. Despite heavy reliance on these systems, most businesses report incomplete, outdated, or incorrect information. This issue is now affecting core operations, from production to customer deliveries. Master data—covering product details, supplier contacts, and work schedules—serves as the foundation for ERP processes. Yet only a small number of companies consider their data quality to be excellent. The majority struggle with inconsistencies that create inefficiencies across the supply chain.
Poor data maintenance often leads to inventory shortages, production mistakes, and missed orders. Even minor errors in master records can disrupt workflows, reducing overall efficiency. With annual data growth exceeding 40%, unstructured governance leaves businesses with bloated, redundant datasets. Experts warn that simply buying new software is not the solution. A structured approach to master data management is essential for maintaining accuracy. Without it, companies risk worsening inefficiencies, regardless of their ERP investments.
The performance of an ERP system hinges on the quality of its underlying data. Firms that neglect proper data governance will continue facing operational disruptions. Addressing these gaps requires a clear strategy—not just technology upgrades.
