Oh my – projects create a lot of data. If you’ve been around projects for any amount of time (or read my previous articles on data management) then you’ll know that it’s really important what you do with that data.
By project data in this sense, we’re talking about the data about managing the project – the performance management data you collect and use to course correct. Your project might also create data as a deliverable, for example customer records or staff records, or financial data. But what we are talking about here is the performance management of the project – the kind of data that the PMO wants to audit from time to time to ensure you are sticking to the process.
Data validation tools
Data validation tools are what you can use (and they might already be set up in the system) to make it easier to ensure that the data meets certain criteria. Two easy ones are:
Data validation rules: Implementing built-in validation rules in your project management tools (e.g. ensuring budget figures are positive numbers or task deadlines are not in the past). That can prevent incorrect data entry or flag up when things look off.
Automated checks: Use software that automates validation processes, checking for discrepancies in data consistency, format, or compliance with predefined standards. For example, project codes might need to be 5 digits, or the project sponsor name might be chosen from a drop down list. These can be automatically checked at the point of entry by limiting the entries, or you can run reports in the background.
Auditing and monitoring
Audit logs: Enable audit logs in your project management tool to track changes made to the project data, including who made the change, what was changed, and when it was changed. Then you can trace discrepancies and identify the source. You might need PMO-level access to see the logs, but that’s OK, it’s normally the PMO team who would want to do the auditing anyway.
Data quality dashboards: Use dashboards that monitor the quality of project data. For example, what % of fields are filled in on a resource request? How many dependencies are in the average project schedule? How many risks haven’t been updated this month? This gives you insights into who is actually updating the project management software, and the quality of what they are putting in there.
Regular data audits
These are your normal project health checks or peer reviews, but in my experience they often stop happening after a brief fluffy of being booked in at the beginning of the year.
Periodic data reviews: The PMO can schedule regular data reviews to manually check the consistency and accuracy of project data, especially after major milestones or changes. As a project manager, you can also ask for a data review if you think it will help you maintain the accuracy and completeness of your data.
Cross-department audits: In larger projects, ask cross-functional teams (e.g. finance, operations, and HR) review project data for consistency and accuracy. Ideally, everything that’s held should be the same as what other departments are saying it is – in other words, data should align across departments. Check everyone is working off the same documents and schedules. You’d be surprised at how often one team is working off something that is out of date!
These are only a few strategies and ideas for auditing and validating the data in your project management systems – and they mostly require input from other humans on the team. If you are in a PMO role, try to build these into your annual cadence of checks and balances. As a project manager, do your best to stay on top of the data you create for performance tracking and keep everything as tidy as possible.
Posted on: March 17, 2026 12:00 AM |
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