Data makes the world more visible.
At the end of March, I embarked on a personal initiative at the J-School to quantify as many of our processes as possible. My working thesis: if we can generate enough data about a system, and have a framework to understand it, we can be far more effective in what we do. Quite possibly way over 5-6%.
My motivations to blog about this are largely because I’m making this up as I go along. I’d like to regularly publish metrics we produce, how we interpret those metrics, what actions we take, and the results that come from our actions. If this initiative incurs the effectiveness increases I hope it does, there will be lessons others can steal.
Our most active spreadsheet right now tracks how our web team executes projects. Specifically, these data points:
- Project initiation date
- Original deadline
- Actual completion date
- Client
- Priority (high, medium, low)
- Project manager
- Estimated hours to complete
- Estimated number of staff required
- Number of milestone (deadline) shifts
- Actual hours to complete
- Actual number of staff required
- Short text explanation by the project manager of why the project ended up as it did
- Link to a debrief or recap if there is one
Tracked projects range between 1 and 20 hours, and we have 94 logged since March 31st. We use Basecamp extensively. Time on tasks is tracked using its time-tracking functionality, and then we spend a minute adding everything up at the very end of the project.
Next up: figuring out how to interpret the data. I hope the data will give us visibility into:
- Whether we’re meeting our stated hour requirements and deadlines
- Where we spend most of our time
- Which clients we’re spending the most time with
- What types of projects we’re not able to deliver on deadline and on budget, and why
Reviewing what we have to date, the post-project explanations are already proving valuable in identifying the trends of what makes a project successful versus going off the rails.