Automating data quality follow-up: who will fix the record?

The administrator can edit the record, and sales knows the answer

The data quality report once again lists customers without an assigned account manager. The data team sends the list to sales, sales sends it on to the CRM administrator, and the administrator asks whom to assign. The administrator can complete the record but does not know which account manager is right. The decision belongs to the person sales names.

The issue goes to sales with a question about the account manager, and to the administrator with a task to enter the decision. The manager sees whether sales has settled the assignment and whether the administrator has made the change. The issue also says why the fix is needed: customer service has to know whom to pass a customer's case to. When the next report lists the same customers, the employee sees this on the open case, without a new task carrying the same list.

A closed task says that an employee reported the work as done. Only the new check shows whether the gap has gone, and if not, the result returns to the same case.

What data quality automation costs and when it pays back

The count covers the work around a case: searching, reading, writing and passing things on. What stays is the time to check the result, 30% of today's work in this scenario. Before the quote we measure both times on 20 to 100 cases the team has already handled, in a free test that takes 5 working days.

A customer without an account manager is a case that lands in a general inbox and waits. In the trial we therefore count the data team's minutes and the number of records that came back in later reports before someone fixed them.

Check the action management in your current tool

Microsoft Purview lets you assign data quality actions to users and update their status. If the team uses a tool like this, agreeing who is responsible and how to work is enough. Integration makes sense when the report is produced in one place and the fixes are made in several other systems. Rules route the known types of error, and AI helps sort free-text descriptions of issues.

Start with an error that keeps coming back

The first scope covers one recurring group of problems. The team names the source of the check, the people who settle the correct data and the place where changes are made. We build this kind of system as part of our AI automations. For the free analysis, a description of one case from the last few weeks and the tools it went through is enough. You do not need to send confidential documents, and you get a written plan within 2 working days.