Mastering the basics of delivery is fundamental to building consistency and dependability.
It’s difficult to stay on top of delivering consistently and dependably when you’re trying to accelerate and scale-up. However, the marginal gains that come from teams continuously adapting the basics will support their transition from chasing their tails to delivering software repeatedly and predictably.
Quantifying agile delivery practices also increases the ability to advocate delivery success to non-tech leaders and host objective discussions within teams about what improvements can be made.
Visualising the rate of sprint completion and sprint stability over time tells a real story of delivery maturity and what may be holding teams back.
Completion rate indicates how well a team is executing their planned work. Visualising this data over multiple sprints quickly highlights a team’s predictability.
In this case, teams are completing approximately 50% of their planned work over their two-week sprints. This increases by an additional 10% when teams break down their work into smaller pieces and estimate how long it will take them; evidence of a practice that could benefit all teams.
Mid-sprint scope change
Constant scope change mid-iteration leaves teams spinning their wheels, disrupting their focus and preventing them from building delivery momentum.
For an average 10 day sprint in this example, there are two active days (indicated by the spikes) where new work is introduced. On Day 2 of the sprint, new work (stories, tasks etc) is added, ‘forgotten work’ from stakeholders pressuring the team to accept more than what was originally planned.
We see in this same example another spike of work after the planned completion date on Day 13 (this team’s sprint overrun by 40%, or 4days). Umano surfaces that this spike in activity is not driven by new work but by re-work; bugs.
Accepting both types of unplanned work into the sprint indicate scope creep, and are the beginning of a downward spiral of never completing work as planned, ultimately leading to unhappy teams.
This is post is part of Umano’s 2019 case study “Software Delivery Drivers”. To get a copy of the full case study complete the form below and we will email a copy to you.