Agile Production Support: Final brush strokes

There is no perfect software. At least I have never seen it. Bugs and minor feature changes are indications people are using your software.

Real users hit a system in ways that no control group can, and on non-critical applications, this is the best way to test your software. Let people use it and see what happens.

This is goes in line with the agile philosophy of release early and often. Get your application out there as fast as you can, so you can mold the finishing touches around the real users experience rather than a faux-environment.

There is some conversation about what is and what is not a “bug” in the software world. That is not a conversation I would like to partake in here, so lets call both bugs, integration items, minor feature enhancements, and things that fall through the cracks of development “tweaks.” It doesn’t matter what the nature of origin is, these are all things that must get done.

After the release of one of our products, a load of tweaks came in from the customer. As proud craftsman, we decided tweaks were our responsibility, and we would take them on in addition to our normal iteration. So we started to do them, to the detriment of our iteration. As a result, we accomplished only about half of our iteration’s velocity.

The next iteration, much to our surprise, we were twice as busy with production support. This is about the time that a developer looses a little faith. What did we miss? Is this high quality software we are writing? So we lost even more velocity when it came to iteration 2 after the release. Also, the customers were now unable to accurately plan new features moving forward due to an unstable velocity.

It is so hard to predict or estimate production support and tweaks. However, we needed to be able to so that the production support didn’t leave such a footprint in the project. It felt and looked like we were not getting very much done, even though we were working harder than usual.

It was the time being put into a vacuum and being unaccounted for that was troubling the project. It also had a negative effect on team morale.

The Production Support Card

We came up with a card, we call the “Production Support Card.” The amount of the iteration’s velocity this card took up was calculated by the amount of time we spent on production support the previous iteration averaged with the amount of time allocated for that iteration (sound like a familiar formula?).

It is added as a card to the next iteration. If the developers only spend 6 of the 10 points on production support, it is expected that they will complete 4 points worth of stories, which are automatically entered in the iteration.

For the first iteration where it becomes apparent that we need a production support card, we set the point value of the card at 0 and track how much time we spend, bumping out the least important stories if needed.

So, what does this tracking buy you, if you have to spend the same amount of time on tweaks? First, it allows transparency to the customer about what you are working on that week. When they see your normal velocity of 20 points turn into 5 points, they have a right to be worried.

When you say, in a defeated voice “we were fixing bugs,” they also have a right to worry about the stability of the code you have been writing, even though this spike in minor changes to the application is a part of the normal process.

Second, it raises the moral of the team, because they are working towards a specific goal, to remove the production support cards from the iteration. Also, we get the satisfaction of maintaining a velocity in points, which is something we know so well it is hard to work without.

It takes a few iterations, and the team squeezes the life out of the production support card, putting you back on track. After those iterations, the footprint goes from sasquatch to mini-me.

It also helps the customer plan around production support. Their time lines and release dates are made from a projection of feature difficulty to development’s velocity.

Over a long period of time, the velocity normalizes, and it hurts the projections to have hiccups. If you have production support data, you can predict about how much time around a release you will loose on the initial release of brand new development.

Paul Pagel, CEO and Co-founder

Paul Pagel has been a driving force in the software craftsmanship movement since its inception.