A New Copy!

Today we tackle Chapter 7 of  Daniel S. Vacanti’s Actionable Agile Metrics for Predictability: An Introduction (buy a copy today).  The chapter is titled, Conservation of Flow Part I.  The flow of work into and out of a process is incredibly important for establishing predictability.  Chapter 7 explains the concept of conservation of flow mentioned (almost in passing) in Chapter 6.

We begin with a reminder of Little’s Law Assumption One: the average arrival and departure rates have to be equal.  Vacanti uses an example that is near and dear to my heart, an airport.  If planes arrive faster than they depart, at some point all of the gates will be filled followed by the tarmacs, and if the scenario continues for too long the runways would be compromised.  The functionality of the airport would initially be stressed, then compromised, and in the end it would fail. This analogy holds for software development teams and organizations. Conservation of flow explains why committing to every request is a losing strategy for satisfying the need to deliver business value.

Vacanti suggests that one way of regulating arrival rate is to add an arrival column.  The arrival column contains only the work that has met the conditions of ready and the team has pulled to work on.  The arrival column should have a WIP limit.  Over any period of time, the work that enters the arrival column should equal the work that departs the process  (arrivals = departures). Remember the arrival column is not the backlog.

The arrival column establishes a crisp definition for arrivals.  Equally as important is having a crisp (Vacanti uses the terms clear and unambiguous) definition of when a piece of work leave the system or process.  This is often known as a definition of done.

In the text, Vacanti provides several excellent charts that show how variability in arrival or departure rates affect predictability (for example, see figures 7.6 and 7.7). For example, as arrival rates increase in relation to departures, WIP increase as does approximate cycle time.  Graphically, predictability occurs when the slope of the arrival rate and departure (completion) rate is the same.  This shows a steady amount of WIP and consistent approximate cycle time.  This scenario will generate a “pretty” cumulative flow diagram (CFD).  Vacanti admonishes the reader that a pretty CFD  is not a guarantee of a healthy system, but certainly a pretty decent start.

One of the benefits of re-reading a book like Actionable Agile Metrics for Predictability: An Introduction is that you immediately find nuances ideas that you have forgotten. This week I found myself discussing conservation of flow and drawing the relationship between WIP, throughput and approximate cycle time when discussing why starting more than can reasonably be finished in a two-week increment will lead to erratic results.

Previous Installments

Introduction and Game Plan

Week 2: Flow, Flow Metrics, and Predictability

Week 3: The Basics of Flow Metrics

Week 4: An Introduction to Little’s Law

Week 5: Introduction to CFDs

Week 6: Workflow Metrics and CFDs

Week 7: Flow Metrics and CFSs

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