Most organizations have some version of a data quality framework . Fewer have one that works. The gap between having a framework and having a functioning one is wide, and it tends to widen quietly — through gradual neglect, accumulated technical debt, and the slow erosion of accountability that happens when no one is specifically paid to care. Here are seven signs that your data quality framework has stopped doing its job and what each one tells you about the underlying problem. 1. Your Quality Metrics Are Green but Business Complaints Are Constant This is the most common pattern and the most diagnostic. The data quality dashboard shows acceptable or good scores across completeness, accuracy, and timeliness dimensions. Meanwhile, the business analytics team regularly flags data problems, analysts spend significant time cleaning data before they can use it, and reports occasionally publish numbers that don't match reality.…