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Showing posts from 2015

What is Flow Debt?

+Daniel Vacanti's excellent treatise on Actionable Agile Metrics [vaca] introduces a term that may be unfamiliar, even to those with an interest and experience in managing flow systems. The term is Flow Debt - for a definition and explanation read on.

My own particular interest in flow systems is the management of agile software development teams, usually using some variant of Scrum and/or Kanban, and other agile practices such as test-driven (or automated-test intensive) build-test-deploy processes. However the discussion is relevant in many other domains, such as one I've recently been involved in discussing, the flow of patients through diagnosis, treatment and convalescence in healthcare systems.

In managing these systems we need ways to look at the mass of data that emerges from them to focus on the useful information rather than the noise; information in particular that indicates when intervention is appropriate to improve flow, and when the attempt would be as futile as…

Beyond Control Charts and Cumulative Flow Diagrams

Control Charts (CCs) and Cumulative Flow Diagrams (CFDs) are powerful ways to display information about a flow system, such as a Scrum or Kanban development process. Unfortunately the very fact that the charts display so much information means that it is often difficult to extract specific information from them. That is why it's useful to also plot some of the key attributes of the systems on their own - this allows us to look at these aspects specifically, alongside the rawer view of the data that you get from CCs and CFDs.

The graphic on the right shows a number of diagrams all of which were derived from very simple data about each item that flowed through this system:
when it arrived into the system; when it departed the system; andwhether the item was "delivered" or "discarded".Note: I use the term "discard" here as a general term to include an exit from the system at any point in the system and for any reason. It includes aborting/abandoning the …

Postscript on Throughput and Delivery Rate

Most people use Throughput and Delivery Rate in Kanban systems as synonyms - including myself up to this point. I've changed my view however.

The canonical form of Little's Law in Kanban is as follows:
Delivery Rate = WiP / Lead Time    [ande] even though these days I more frequently express it this way:
Throughput = WiP / TiP Surely these two ways of writing the equation are entirely equivalent aren't they? Well maybe not.
Note: All these terms are defined in my Glossary Proposal (which has recently been updated to include the definition of Throughput). Feedback, comments and references to publications using the terms defined are welcomed and encouraged. Throughput is the term +Daniel Vacanti uses (among many others), particularly in his excellent new book Actionable Agile Metrics [vaca], and it got me thinking about one of the problems with using Delivery Rate: what about the items which are not delivered but are discarded? If there are a significant number of these Little&…

Little's Inequality

The interesting thing about Little's Law, in spite of its very general applicability, and in certain cases mathematical certainty, there are many cases when it simply does not hold true. In those cases it's not so much Little's Law as Little's Inequality. Could the fact that specific instances of data do not follow Little's Law actually give us useful information about our Kanban and Scrum systems and point to the right kind of interventions to manage and improve their flow? That's what this blog is about.

In 1961 John Little published his proof of this general queuing theory equation [litt]:
L=λWL is the average number of items in the queue, λ is the average arrival rate, and W the average wait time Since that time Little's Law has found numerous applications in the study of general flow systems from telecommunications to manufacturing, including in Kanban systems. Because throughput or delivery rate is the more significant attribute for management of such …

Glossary Proposal

One of the problems Kanban practitioners have faced over the past several years is the lack of agreement of the terminology to use to describe flow systems. This in turn has led to confusion in both those learning the method and those implementing tools to support it. This blog has made a few previous attempts to disambiguate common terms (see discussions of Cycle Time for example). Mike Burrow's Glossary of Terms, [burr] reproduced on the Lean Kanban University site [lkun] is also very useful, though it does not give guidance on which terms to use when applying Little's Law to sub-processes in a more complex Kanban system.  This article is another foray into this minefield and is principally a proposal for the definitions of commonly used terms relating to Little's Law, particularly seeking terms applicable in complex flow systems and sub-processes within such systems. It is an invitation to others in the community to endorse these definitions, or propose alternatives. Let…

Growing Kanban in Three Dimensions

Kanban systems can work at different scales and in widely different contexts. Indeed any organisation that delivers discrete packages of value ("work items") and which is interested in maximising the value and timeliness of its delivery, can analyse and improve its performance using the Kanban method. 
Kanban systems can grow - in fact in most cases it's much better that they grow than a massive process change is made suddenly across a whole organisation. "Big bangs" tend to be quite destructive, even if they could clear the way for something new. There are three dimensions in which Kanban systems grow:

Width-wise growth: encompassing a wider scope of the lifecycle of work items than the typical "to do - doing - done" a single division of the process. It can cover from the idea to real value - or "concept to cash", though cash may come before or after the realisation of real value.Height-wise growth: by considering the hierarchy of items tha…

Earned Value Management and Agile Processes

I've recently been working with a client whose customer requires project reporting using Earned Valued Management metrics (EVM). It made me realise that, since they are also wishing to use agile methods, a paper I wrote back in 2008 could be relevant to them, and maybe a few others. When I looked for it online it was no longer available, so I thought I'd remedy that here. You can access the paper by clicking this link: EVM and Agile Processes – an investigation of applicability and benefits.

EVM is a technique for showing how closely a project is following both its planned schedule and planned costs. It's a superior method to simply reporting time and cost variance, since if the project has slipped but also underspent you cannot tell from the simple variances the degree to which the underspend has caused the slippage. EVM's cost efficiency and schedule efficiency (nothing to do with efficiency by the way!) can tell you this.

However agile methods do not have a fixed sc…

Does your Definition of Done allow known defects?

Is it just me or do you also find it odd that some teams have clauses like this in their definition of done (DoD)?
... the Story will contain defects of level 3 severity or less only ... Of course they don't mean you have to put minor bugs in your code - that really would be mad - but it does mean you can sign the Story off as "Done"if the bugs you discover in it are only minor (like spelling mistakes, graphical misalignment, faults with easy workarounds, etc.). I saw DoDs like this some time ago and was seriously puzzled by the madness of it. I was reminded of it again at a meet-up discussion recently - it's clearly a practice that's not uncommon.

Let's look at the consequences of this policy. 

Potentially for every User Story that is signed off as "Done" there could be several additional Defect Stories (of low priority) that will be created. It's possible that finishing a Story (with no additional user requirements) will result in an increase in…