How do we actually know if our Agile teams are doing well? Is gut instinct enough? Furthermore, in a rapidly growing organization such as Spotify, how can we ensure some sort of consistency in our baseline level of Agile knowledge across the technology, product, and design organization?
In an ideal Agile world, the Scrum team can complete all user stories tasks that it planned for the current sprint. The real world is however different. In this article, Scott Lively explains how to use the sprint data to modify the team behavior.
Velocity is one of the most common metrics used – and one of the most commonly misused – on Scrum and Agile projects. Velocity is simply a measurement of speed in a given direction, the rate at which a team is delivering toward a product release. As with a vehicle en route to a particular destination, increasing the speed may appear to ensure a timely arrival.
How can metrics be used safely in coaching Agile teams? The classic Goldratt quote “Tell me how you will measure me and I will tell you how I’ll behave” signals the danger of using metrics to manage or motivate employees. This presentation shows and suggests approaches to Agile metrics that avoid the common pitfalls and shows some practical dashboards and the resulting chaos or calm they caused.
This presentation by Grindr VP of Engineering, Lukas Sliwka, focuses on implementing Scrum metrics to drive high performance teams while building strong and innovative software engineering organization.
Story point is a arbitrary relative measure used by Scrum teams to define the effort required to implement one story. In this article, Mahfoud Amiour proposes an approach to measure the cost of story points implementation.
Even if Agile was initially considered as an anarchic approach due to practices like self-organization, the reality is that it requires a lot of discipline. Metrics is an important tool to assess the continuous improvement efforts of Scrum teams. However, setting a good metric program is not obvious. The book “The Agile Culture” contains interesting thoughts about what could make a metrics program fail.