Feature Fitment Factor – Knowing if your sprint length is optimum

Organizations that have just embarked on the or rather specifically journey often struggle to decide the right duration of the for them. Typically 1-4 weeks is the general recommendation. This decision is rather tricky as there are several factors at play. Two weeks sounds a great idea in terms of early feedback and frequent deliveries. However in the early days of your scrum journey, there may be very limited ability to churn out features at this speed. The sprint length is decided then primarily by the time it would take for the team to be able to deliver a feature. It could anywhere between 3-6 weeks.

Once teams start working, its likely that this ability will improve and that will be reflected in the velocity. Because teams are able to finish features much faster, essentially their cycle time has improved, they are able to commit and deliver more features each sprint – resulting in the increased velocity.

When you are working in a startup or a small product development company, this is pretty obvious and teams would typically adjust their sprint length going forward to be shorter and shorter – stopping maybe at 2 weeks beyond which the sprint length is no more optimum and the overheads of  shorter sprint outweigh the advantages. They may eventually stop doing scrum and go into a more Kanban style or single piece flow approach.

However when you are a big enterprise with hundreds of scrum teams operating on different cadences the situation is a bit different. You need some kind of a metric or leading indicator to see if the hundreds of team that you have are working at optimum sprint length. Is the time right for the team to shorten its sprint length?.

One simple indicator which I call Feature Fitness Factor can probably help in this.

Feature fitness factor =  Average cycle time of the features ⁄ Sprint Length

For example, if your average cycle time is 2.5 weeks and sprint duration is 3 weeks, then your Feature fitness Factor would be approx 0.8.

  • Factor < 1
    • probably its time to consider shortening the sprint length. There is a window of opportunity to optimize things further. Depending on what this number is may give you an indicator what can be the potential sprint length
  • Factor > 1
    • Indicates probably work often spills over and is done in more than one sprints. Is there really value in having a shorter sprint? Could increasing it be more logical? Maybe the shorter sprint is causing pressure on the team further inhibiting their ability to deliver. It could be impacting quality as well.

What we need is essentially a Big Visual Information Radiator that indicates whether the sprint length is optimum for a given point of time. Feature fitness factor essentially tries to answer that question.

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