We’ve recently scoped several projects in Boulder. While scoping, several clients asked how we’re able to estimate a project’s cost with such confidence. I’ve thought about this a bit and I actually think this is pretty interesting and remarkably similar to something we’ve all been doing for a while: estimating user stories in Tracker.
Scoping a project is very similar to determining the number of points or weight you might assign to a user story or feature in an Agile backlog. Similar to measuring the relative size or complexity of a feature, we’re just measuring the relative size or complexity of the project against similar projects that we’ve completed. The important piece here is that we’re measuring against completed projects.
With stories or features you estimate size and then derive duration in order to achieve a running feature velocity. Feature velocity is essential and the key to predictability. Completing features and measuring their associated duration is the empirical data we use to determine when a future set of stories will be completed or delivered. When scoping a project we’re missing this empirical data, although we still need to actually provide a duration to calculate the project’s cost. So how do we estimate a project’s scope and cost?
Imagine estimating a feature that you just completed for another project. You’d probably be pretty close on the points assignment as well as confidence. Now apply this to a project. It’s becomes easier to scope a project when you’ve completed a few similar projects. The more projects the better the comparison and resultant estimate.
Completed projects are valuable because we know how long they took to complete. For example, client A’s CRM was roughly 1 pair for 2 months. Client B’s CRM required 2 pairs for 4 months. And client C’s CRM, the one we’re currently estimating, is slightly more complex than client A’s although much less complex than client B’s. We’ll likely estimate client C’s CRM at 2 pairs for 2 months.
It’s actually not all gravy. There are several risks that may increase a project’s scope. For example, if we’re up against an aggressive timeline, we may include an additional pair for a few weeks to help increase feature velocity. Similarly, if there are complex integrations, like a 3rd party billing system or external messaging subsystems, we may include an additional pair for a month.
During an initial scoping we help reveal or tease out high level risks and then prioritize theses risks against constraints like timeline and budget. The more similar the risks we’ve resolved on completed projects, the more confidence we have to estimate risks during a new project scoping. Again, pretty similar to how we estimate features in a backlog. We’re just estimating the size or complexity of risks against similar risks with known durations.
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