Book Review: Actionable Agile Metrics for PredictabilityPosted: April 30, 2015
Daniel Vacanti’s new book, Actionable Agile Metrics for Predictability, is a welcome addition to the growing canon of thoughtful, experience-based writing on how to improve service delivery. It joins David Anderson’s (Kanban: Successful Evolutionary Change for Your Technology Business) and Mike Burrows’s (Kanban from the Inside) books in my list of must-reads on the kanban method, complementing those works with deeper insight into how to use metrics to improve flow.
Daniel’s message about orienting metrics to promote predictable delivery and flow — which he defines as “the movement and delivery of customer value through a process” — is primarily grounded in his experience helping Siemens HS. He includes the case study (which has been published previously and is valuable reading in itself) at the end of the book, so he keeps the rest of the book free from too many customer references, though he’s drawing on the pragmatic experience.
As someone who for several years has been helping teams and organizations improve using the metrics Daniel talks about, I learned a tremendous amount. One of the reasons is that Daniel is particularly keen to clarify language, which I appreciate not only as a former English major (nor as a pedant!), but because it helps us carefully communicate these ideas to teams and management, some of whom may be using these metrics in suboptimal ways or, worse, perverting them so as to give them a bad name and undermine their value. Some examples: The nuanced difference between control charts and scatterplots and clear definitions on Little’s Law (and violations thereof), especially as related to projections and cumulative flow diagrams. I certainly gained a lot of new ideas, and Daniel’s explanations are so thorough that I suspect even novice coaches, managers, team leaders and team members won’t be overwhelmed.
As for weaknesses, I felt that the chapter on the Monte Carlo method lacked the same kind of depth as the other chapters. And I came away wishing that Daniel had included some diagrams showing projections using percentiles from scatterplot data. But those are minor plaints for a book that constantly had me jotting notes in my “things to try” list.
Overall, I loved how Daniel pulled together (no pun intended), for the purpose of flow, several metrics and tools that have often been independently implemented and used and whose purpose— in my experience — was not completely understood. The book unifies these and helps the reader see the bigger picture of why to use them in a way I had not seen before. If you’re interested in putting concepts and tools like Little’s Law, cumulative flow diagrams, delivery-time scatterplots and pull policies into action, this book is for you.
- The book has a very helpful and clarifying discussion of classes of service, namely the difference between using CoS to commit to work (useful) and using it to prioritize committed work (hazardous for predictability).
- It also had a particularly strong treatment of cumulative flow diagrams.
- Daniel does a lot of myth debunking, which I appreciate. Examples: work items need to be of the same size, kanban doesn’t have commitments.
- The tone is firm and confident — you definitely know where Daniel stands on any issue — without being strident.