Baseline vs Completed

Today I will describe one more report we’ve created in order to analyze how baseline hours refers to the actual time spent on the solution of the task. This information is rather useful. Baseline hours in our team are planned by a single manager and he does not know who will deal with each task. So, we have quite good point to compare members of the team.

First, let’s mention some metrics we’re operating in our everyday work:

  • Every developer has to close at least 7 hours each working day. This is controlling by daily management process and we have made it work.
  • The minimum number of hours developer closes a week is 35.
  • The minimum number of hours developer closes a month is 145.

While analyzing development time, we have to exclude hours spent on vacations, internal researches, meetings, etc – all activities that do not change code. In our case – that were not moved to the production environment.

In other words, it will be great to calculate how many baseline hours were moved to the production and how many actual hours were spent by each developer to achieve it.

For this purpose, the Baseline vs Completed report was created. Its main principles are the following:

  • Only implemented into production tasks are analyzed (how to find such task was posted in Deployment tab),
  • We analyze year period – in order to reduce the influence of vacations and time spent working under projects (when for several months the functionality is developed and tested – no deployments to production).
  • It was decided, that monthly average amount of baseline hours transferred to production must be more than 40. So, if developer has performance index more than 28% – we consider, that this is ok. We may be rethink this number in the nearest future, but today it’s 28%.

The first part of the report shows general pivot with average hours for the year.

TFS0018.1

While analyzing this report we can see:

  • Those who is working rather poor. They are located in the red area.
  • Those who spends much more time on the task than was planned. For example: developer monthly average baseline hours closed for the year is 91, but actually he has spent 142 hours to achieve such result. Basically this means, that developer remains after work to complete tasks in time.
  • Those who are doing much faster (baseline 146 only for 87 actual hours). Usually we have quality issues with fast done work.

The next part of the report shows average hours on a monthly basis:

TFS0018.2

This detailed report gives us possibility to go down to the lower level for further analysis. It’s quite simple and has the same principles as first pivot.

In our team we are looking at this report on monthly meetings where we discuss how we did in the last month. And usually we spend 5-6 minutes discussing its results and looking forward to correct “red developers”.

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