Over the past 15 years of working with various agile techniques, practices, frameworks, and strategies I’ve found that there is one thread that ties them all together. They are all focused on improving our ability to learn and to apply that learning to our future work.
This post is aimed at a fairly niche audience so if you aren’t trying to make sense of poor data out of some ticketing system then you might want to skip this one.
One of the key practices supporting continuous improvement is making your work, and how you do the work, visible. This starts by tracking the progress of that work in a highly visual way, often by using a kanban board. Once that work is being tracked we can begin to gather that data and start to gain insights into where our biggest opportunities for improvement are, often by using the metrics defined in The Three Flow Metrics (Plus One).
Some of the best indicators of team performance are the flow of both new information into the team and of value out of the team. If we can improve visibility into these indicators, and therefore the opportunities for the team to improve the way they work, it becomes possible for the team to support their organization in ways they couldn’t before. There are three standard metrics that are core to understanding the effectiveness of any flow-based system. The relationship between the three metrics is defined by Little’s Law. When applied to the systems used to enable knowledge work the law is usually restated in terms of Throughput, Work In Progress (WIP), and Cycle Time.