Karl Scotland – Using Agile to Deliver Value
Posts tagged Cynefin
The Science of Kanban – Introduction
Jan 30th
This is a write-up of a talk I gave at a number of conferences last year. I have split it into 5 parts.
Abstract
Science is the building and organising of knowledge into testable explanations and predictions about the world. Kanban is an approach which leverages many scientific discoveries to enable improved flow, value and capability. This article will explore some of science behind kanban, focussing on mathematics and brain science in particular, in order to explain the benefits of studying a system, sharing and limiting it, sensing its performance and learning in order to improve it. Readers will gain a deeper understanding of why and how kanban systems work so that they can apply the theory to their own team and organisation’s practices.
Introduction
Background
When I first started talking and writing about Kanban I was trying to articulate that Kanban is more than just using a card-wall. The kanban board is the visible mechanics of the system, but the goal is achieve a flow of value, and while time-boxes become optional, a cadence is required to understand capability. I referred to this triad of Kanban, Flow and Cadence as KFC (the irony being that fried chicken is not at all lean!) and that blog post from October 2008 remains the most popular I have written. While my language and thinking has evolved since then, I have realised that as I learn more about the science behind Kanban, much of it still maps back to those three core elements.
Kanban Thinking
This article will not describe how to design a Kanban system, but explores some of the science behind Kanban Thinking, an approach to creating a contextually appropriate solution.
Kanban Thinking is a systemic approach which places an overall emphasis on achieving flow, delivering value and building capability. The primary activities are studying, sharing, limiting, sensing and learning, and thus Kanban Thinking is itself a scientific approach.
Scientific Management
Frederick Winslow Taylor is generally credited with the development of Scientific Management in the late 19th Century by applying a scientific approach to improving manufacturing processes and publishing “The Principles of Scientific Management” in 1911. Given that we are now in the 21st Century, how relevant is scientific management to us today for software and systems development? Scientific management is considered to have become obsolete in the 1930s, yet I believe we can still apply science to understanding why and how differences in productivity exist. Scientific theory can be used to inform the practices we use, while our experiential practice can also inform and evolve the scientific theory.
Cynefin
Dave Snowden’s Cynefin model is a good example of balanced theory and practice. Cynefin suggests that there are different domains, and that we should act appropriately for each one. Thus depending on our understanding of the current context, we should apply scientific theory differently, and implement alternative practices appropriately. Thus scientific management can still be relevant for software and systems development if we apply a scientific approach contextually.
The manufacturing context was probably complicated at worst, with elements possible being simple. Thus Taylor’s approach to scientific management, with best and good practice, was appropriate. However, software development and knowledge work is often complex, so the appropriate approach is to allow emergent practice, using what Snowden calls probe-sense-respond.
Making an Impact
In a complex domain, not being able to predict or repeat cause and effect does not mean that a situation cannot be improved. It is still possible to understand the current state, and current performance, and known whether things are improving. Rather than simply reacting to the current state or attempting to predict or plan for a future state, having anticipatory awareness of the current state, with a view to exploring its evolutionary potential, allows the application of continuous experimentation to sense whether we are making an impact by improving outcomes for both the business and for the people.
I’ll cover some of the sciences that can be used to make an impact in the following future posts:
Cynefin, Agile & Lean Mashups
Jan 10th
2012 certainly started with a bang for me (lets hope it doesn’t end with a bang!). After a relaxing Christmas and New Year, I was up at 6am on January 2nd to head for Almens in the Swiss Alps, and an intense few days with Simon Bennett, Steve Freeman, Joseph Pelrine and Dave Snowden. We gathered at Joseph’s house to discuss a common interest, namely how do we apply complexity science, and in particular the Cynefin framework, to Agile and Lean development.
Early on, Simon suggested the name CALM, and it stuck almost immediately. I like it for a couple of reasons. Mashups invokes the idea of “a creative combination or mixing of content from different sources”. That’s exactly what we want to do, and its the creative aspect that particularly appeals to me. A Cynefin, Agile and Lean Mashup will inevitably be created contextually. CALM also subtly counterbalances the XP extreme notion. While that’s not an intentional focus, I find it a mildly amusing reference.
My interest in Cynefin began back in around 2004 when Dave first spoke at XPDays London, and while back then I wasn’t smart enough to realise the full implications, fortunately others like Steve and Joseph were. I met Dave again at ScanAgile in 2009 and last year at the LeanSSC and ALE conferences. Simon also gave a great talk linking Scrum and Complexity more concretely at Agile2011, and I that’s when I finally figured out how Cynefin could match my interest in exploring the underlying theories behind Agile and Lean, and more specifically Kanban Thinking.
My personal goal for being involved in the meeting was to move Cynefin, and complexity science, from being something which is used as a justification, to something which provides meaningful explanation, and ultimately to new application. To keep the industry advancing, and to be able to apply Agile and Lean principles in increasingly challenging organisations, we need theory informed practices, as well as learning from our current success by evolving practice informed theory. In other words we need to take a scientific approach, which ties in nicely with my recent presentations on the Science of Kanban, which should make it to a blog post soon.
The primary outcome of the CALM meeting was the creation of CALMalpha. This is a two day residential conference to be held on the 16th and 17th of February 2012 at Wokefield Park in the United Kingdom. The alpha represents the notion that this is an initial safe-to-fail experiment where we hope to explore the subject in more detail, as we seek to find coherence, coalescence and convergence around what we do in the future.
More detail, including prices and booking information, can be found on the eventbrite page. I hope to see you there!
