When we were developing the Professional Scrum with Kanban guide and class, Daniel Vacanti kept insisting I inspired the Work Item Aging flow metric we introduced. I was complimented, but didn’t recall the exact reference. Well, it turns out I did write and talk about this. Here's the original article, slightly refreshed. I hope you'll enjoy the historical perspective.
I’m a great fan of using Cycle Time charts to explore specific cycle times and reduce variation / continuously improve a Kanban System. A constant pattern I'm seeing is that finding out that there was an exception based on Cycle Times is too late. Why is that? Because a classic Cycle Time chart looks at the history - the action is over…
A couple of months ago, I read about “average cycle time in column” in the GSK R&D Case Study by Greg Frazer.
This was the seed for the idea that, perhaps, using the historical cycle-time data in columns/lanes, a current prediction of the final cycle time can be calculated for each in-flight card in the system.
This prediction can then be traced on an SPC-like chart, and exceptions can be identified more clearly (see illustration below for an example)
This reminds me of charts used to track “Due Date Performance” on releases/milestones - sometimes called Slip Charts.
I see capabilities such as identifying struggling work items based on exceptions from “average time in lane” and overall exceptions in predicted cycle time, key to taking the “early feedback and action” one step forward and making kanban something project managers swear by.
Update: At the time I wrote this article back in 2010 no tool supported this view. I’m glad to report that over the years, tool vendors listened and provided a variety of ways to identify aging work items. Actionable Agile Analytics has a robust Work Item Aging report,. Planview Leankit has filters that can highlight aging work. Tools like JIRA, Trello, and ADO can highlight aging work items visually using an indication of each day in progress.