So you’ve taken many steps to get to this point: Your firm has launched a PPM tool, and your staff is trained how to use it. You’ve built a base set of standards, and are beginning to reap the benefits of having all your data in one place, reporting your initiatives, and tracking how much they truly cost. You finally have an eye on things.
But now you want to investigate whether or not you have any more deep-seated issues within your organization.
One visual that will help significantly with this is a Stacked Resource Timeline.
Each of the 10 rows above were managed by the design team. The rows represent the estimated/baseline durations (the smaller bars underneath the larger bars), and the actual durations for the last 10 initiatives they participated in.
It gives us a very clear data point: The design team is, for some reason, ALWAYS underestimating their efforts, and incurring a schedule overrun.
This is a big problem. Not just for their team, but also because it probably has trickle-down cost ramifications for other teams or resources who are depending on design tasks being completed on time…or even sort-of-on-time, which they are not.
There is a LOT we can do with this information to attempt to try and dig into the root cause of the issue and resolve it, or to simply mitigate it by buffering the time and cost overruns that seem prevalent with this particular team.
Although these data might come from 10 different source files in the PPM tool/database, the only things we’re paying attention to here are the estimated/baseline durations, and the actual durations. To get it into OnePager in the above format, you simply need to make the baseline start and actual start dates match in a generic way.
You could copy/paste the tasks and actual/baseline durations into a new Project file, and then keep the actual/baseline start dates the same.
Here is what my datasheet looks like, to create the above example:
I used a Text column in Microsoft Project (Text1) to capture the value for the initiative/project, and a Number column (Number1) with a formula to capture the % miss value, based on the difference in the actual and estimated durations.
Here is the formula for the % miss value:
Do you have another way you think this would work better? We’d love to hear it!