Why Master Data Is Not a Cleanup Project
Master data problems are often treated as cleanup work. Export the records, remove duplicates, fill missing fields, correct classifications, and the problem appears to be under control. That view is too narrow. In production systems, master data is not just content stored in tables. It defines how workflows behave, how interfaces interpret records, how reports classify reality, and how automation decides what to do next. 1. Clean Data Is Only a Moment in Time A cleanup project can improve the current state of the data. It can remove obvious errors and make a system look more consistent for a while. But clean data at one point in time does not mean the data is governed. If the creation process, change process, and ownership model remain unchanged, the same problems slowly return. This is why many cleanup initiatives feel successful during the project and disappointing six months later. The data was corrected, but the operating model that created the problem was left untouched. 2. Master...