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Improving Predictability - Average Arrival and Departure Rates

In a previous post I introduced the four assumptions behind Little’s Law and the idea that they are critical to understanding and improving your system’s predictability. If you haven’t read that post I encourage you to go back to understand the background. As a reminder, the four assumptions are listed below.

Improving Predictability

Little’s Law is an equation that frequently appears in discussions of Kanban systems. While initially formulated as a part of queueing theory to describe the length of time people would spend in stores it has since been applied to many other contexts from manufacturing to knowledge work (particularly Kanban for the purposes of today’s conversation).

Getting Kanban metrics from the Jira API

If your team is using Jira then at some point you’re going to want to look at some flow metrics to see how you can improve. You’ll very quickly discover that Jira only provides two charts out of the box and that neither one is terribly useful. The cumulative flow chart has known bugs and the control chart is both difficult to read and has problems of it’s own.

The cost of interruptions, and how to reduce it

Interruptions can be a significant source of waste. By their nature, interruptions cause a context switch as we lose track of what we had been working on to focus on the interruption. There is a significant cost to that context switch as it takes time and effort away from the task at hand. There is also a real impact on quality as mistakes are far more likely to happen when we’re distracted.

Massively overburdened with WIP

About once a year I run across a team that has at least ten times as many items on the board as there are people on the team. The worst I’ve ever seen was a team of ten people with 227 items in progress.

Flowing value

In Kanban we often talk about flowing value through the system and yet that’s somewhat misleading. The reality is that we can’t know whether a work item is valuable until we’ve actually finished the work and made it available to our customers.

Classes of service

Many Kanban teams use classes of service to help model their workflow. We’re going to talk about how they work, where they are valuable and why you should avoid them wherever you can.

“We tried Kanban and it didn’t work”

I sometimes run across teams that say “we tried kanban and it didn’t work”. When I hear this, I’m always genuinely curious and ask for more details about what they’d done and what specifically didn’t work for them.

Waste: Psychological Distress

One of the more subtle forms of waste is psychological distress. When we are afraid or anxious, our sympathetic nervous system activates to prepare us for one of fight, flight or freeze. All good responses in a survival situation.

Understanding waste in the system

In Kanban, we are always trying to optimize for efficiency, effectiveness and predictability. Waste in the system is something that hurts all three of these objectives and is something we want to remove or reduce wherever possible.