In my previous post, Metrics for Successful Project Delivery, I mentioned that I am kicking off a series of posts that provide objectives and supporting metrics for managing the delivery of projects. The objective “maintain high project data quality” is a key objective to implement first. Without it, you cannot depend on any of the other metrics since people may not trust the data.
Data quality is affected by a number of factors. Time sheets are updated by team members, schedules are maintained by project managers, risks and issues may be updated by the whole team. This information is utilized to understand the health of a project. It needs to be entered accurately and in a timely fashion in order to have high data quality. This information is created and maintained by people. Simply by monitoring the quality of the data you can encourage (or discourage) behaviours such as entering time sheets on time.
The table below shows examples of metrics that drive project quality and the meaning of them based on people`s roles.
| Role | Context | Metrics |
| PMO Director | Stakeholders will only trust reports about the projects if they trust the data. | Number of project plans overdue to be published
Number of projects with hours scheduled in the past
Number of project with overdue timesheets |
| Project Manager | The project manager produces much of the data that drives other metrics | Number of hours overdue for publishing the project plan
Number of unscheduled hours
Number of resources late on time submission |
| Team Member | Teams members are “end points” of measurement for tasks within projects. | Number of days late on providing schedule updates. |
The final step in implementing the objective is to create a key performance indicator from the metric. This involves taking the actual value and comparing it to the target value. The table people shows an example for one of the metrics.
| Number of hours overdue for publishing the project plan (target) | Indicator |
| 0 | Green |
| < 4 | Yellow |
| > 4 | Red |
Implementing the objective “maintain high project data quality” is the foundation for ensuring all other objectives for delivering projects have strong supporting metrics.