I was collecting metrics for an IT infrastructure development project recently and once again saw how metrics, rewards related to metrics, team learning and constant improvement produce unintended results. In this occasion the results are fairly positive, so no disasters waiting.
The project is run on three week sprints by two vendors located on three continents. Agile principles are followed as much as they can in such setting - as you can imagine, no daily scrums with about 10 timezones to cover.
There is contractual aspect to the metrics. The project invoicing is made dependent on sprint completeness reaching a certain limit for each sprint and both vendors separately. That makes metrics that much more interesting, as there is quite a lot of interest on that specific metric.
Such a metric also affects team dynamics. One would hope for a unified crew pulling together, solving problems and addressing issues. In practice the incentive and goal is to make sure the invoicing approval is secured, and that is clearly visible. In this regard, completeness as an invoicing criteria fails the project and team effort unless the goal and the metric is shared between the whole crew.
This obviously is different from most situations you'd see on a sailing vessel.
Completeness is defined as "deliverables produced in a sprint / deliverables planned in a sprint", and the produced refers specifically to what was planned. This makes good sense on paper, and is a fairly good start.
Team's development is visible in other metrics much better than completeness. A few illustrations about six consecutive sample sprints may be helpful. First, completeness and planned velocity:
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| Left axis: Agile points. Right axis: Completeness, %. |
As you recall, completeness is based on the tasks and deliveries included at the start of sprint. Anything else is excluded. This results in emphasis on predictability and also sets an upper bound for team's metrics - the "best" one can do is 100%.
That 100%, the perfect plan, is subject to a continuous discussion about how hard should one try. 100% completion, everything is done, looks good on a report, and is a sensible goal for a certain sized system. However, 100% also implies that the envelope was not pushed, that the IT system is flawless at release, and could also be taken as lack of ambition.
The team in this project has worked together for more than a year, and is improving at a reasonable rate. This is not visible at all in the completeness metric, as can be seen in the grey line above (note the axis on the right). Please note the growing trend of the orange line, axis on the left.
Looking at planned and actual velocity, the picture changes somewhat:
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| Unit: Agile points. Can't be compared between teams or projects, but are consistent for one team in subsequent sprints. |
There is one more view, which is accuracy. It would be great to know how much work there is, and when do we arrive - the infamous "Gimme a Latest Estimate" (read this about that folly). Most interesting - this happens:
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| Accuracy. Positive indicates larger delivery than planned, negative smaller. |
As the speed and ambition level rises, accuracy goes from substantial over delivery to small miss. In absolute terms such a graph indicates an accuracy of about 10% for any given sprint, without taking into account that all items are not equally relevant for business value earned metrics.
These and many other metrics can be collected and analyzed. In this case the biggest business emphasis is on completeness, and there is a conscious effort to keep that within parameters. Other aspects - improvement, speed, ambition - are side effects of how the project operates, and are of interest to analysts and skippers like yours truly.
Does this entry have a nautical aspect? Perhaps if one considers e.g. the constant improvement required to win events from entry level dinghy races to the America's Cup. Combining that with IT project metrics is a stretch, and best left alone.



