Finding Predictability in the Velocity

Being an independent contractor is exciting yet somewhat lonely, having to support myself and find every opportunity. I look to constantly improve my craft by finding others to collaborate with and have found those needs met by joining Rally. I now concentrate on improving my coaching and training practice with other coaches. We have a support system around us and I get to work with people who have different strengths and skills.

One of the clients I work with is a networking company. One of the teams I worked with had a difficult time establishing a consistent velocity. Forecasting when a release might be ready for system testing was difficult for this group. This holds back other groups who have to integrate with them at the system level.

Leaving Defects Unsized

The Product Backlog and historical velocity information showed me that the team was not sizing defects. When inquiring why that decision was put in to practice the answer indicated that story points were seen as a measure of value. After all, the team is only credited with the point value of a User Story when the Product Owner has accepted the work as done.

The group sees defects as having no value and show that the original story was not really completed. We discussed if User Stories can be in an accepted state when defects exist for them. We talked about how to apply a formula to recalculate velocity and accommodate for defects. It seemed to the team to be a lot of work with little reward.

When prompted, the team came to the conclusion that defects looked a lot like User Stories and that they could see the relative size of them in comparison to those stories. Someone noted that the expected/actual language of a defect matched up well to acceptance criteria.

We discussed what makes up the size of a story, like how complex it is, and how much uncertainty we have about it. User Story size seemed to us to be correlated to the amount of effort the team needed to invest to finish a story. I admitted to having thought about story points as a value metric and had changed my mind, I now thought that they related closer to the cost of an item.

The team talked about what they believed and concluded that it would be worthwhile to try estimating the size of defects and see what happened. They already met weekly to triage them. Defects were stack ranked with the rest of the Product Backlog. It seemed to the team that it would require minimal effort to size them as well.

The Effect of Sizing Defects

Velocity stabilized with the team keeping all the items including defects in the Product Backlog relatively sized. The total point increase of the Product Backlog confirmed what most people thought; the projected release date was further out than first promised.

The predictable velocity allowed this team to now reserve a certain amount of point capacity to invest in automation and other infrastructure. Preventing defects instead of merely fixing them reduced their cost of feature deployment. This could be seen by them in different ways, such as the reduction of defects backlogged and less time spent in triage.

Understanding velocity showed data to help the team decide if more features had to be cut to meet the date, if the date would have to move, or if more people needed to be hired. In the end the organization acted on all of these options.

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