6D root cause analysis of flow in knowledge work

I have been working on a little framework for analyzing why work is, or is not, flowing. The result can be seen below. It takes the form of an Ishikawa, or fishbone, diagram.

Screen Shot 2013-11-17 at 15.41.41

The purpose is to look at a situation and use the framework to identify causes of why work is not flowing.

The Ishikawa diagram above, nicely complements the 4L root cause analysis that I posted before. The 6D framework can be used at the team level; the 4L framework at the value stream level.

I am putting it on the blog mainly to get feedback. Do you find it useful? How do you find the categories? Let me know.

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A careful analysis of work organization underlying Scrum and Kanban

The Scrum vs Kanban discussion is quite a debate with many different viewpoints including the viewpoint that it is a pointless debate. I personally think that something useful can be extracted. In order to do so we need to look inside the Scrum box and inside the Kanban box, and analyze the underlying models of organizing work. By analyzing the underlying models of work we can start thinking outside the box and think up novel ways of organizing knowledge work.

Our starting point of analysis is work organization in lean manufacturing (and the Toyota Production System in particular). It is a good starting point because it is a point of reference for many people. Note however that we will not stop here as our ultimate goal is work organization of knowledge work.

The Toyota Production System (TPS) has two distinct ways of organizing work:  continuous flow (implemented in work cells) and level pull (implemented with kanban and demand leveling). Both ways of organizing work complement each other. A critical concept to tie both ways of working together is the pacemaker. Let’s review each of these concepts. (Because of space limitation our review will be very compact. I recommend the excellent book of Taiichi Ohno, Toyota Production System, for a more in-depth explanation.)

In its ideal state, continuous flow (sometimes also referred to as single-piece-flow) means that items are processed and moved directly from one processing step to the next processing step, one work item at a time. Each processing step produces a work item just before the next processing step is ready with processing the previous item. Continuous flow is implemented in work cells (or cells in short). A cell is an arrangement of processing steps next to each other through which parts are processed in continuous flow. Cells may be operated by multi-skilled workers as different machines are operated by a single operator.

Ideally, product flows continuously all the way from the raw material to the customer. In reality however, for any manufacturing process of reasonable complexity, upstream processes that feed activities downstream may be disconnected. The extent of continuous flow may be limited for several reasons such as: unreliable equipment, equipment that cannot cycle fast enough, equipment that is designed for batch. From a flow perspective this means that you need a place to focus. That place is the ‘pacemaker‘, the most important segment of your value stream. It is the process (or segment) where the product takes it final shape for the external customer. For the upstream processes the pacemaker sets the pace in line with the rate of customer demand. While the pacemaker process is organized as continuous flow, material is pulled from upstream processes making use of a kanban system. To avoid uneven demand for the upstream processes, demand leveling is performed. Without demand leveling, upstream processes would suffer really uneven demand.

Despite the fact that the work organization around continuous flow/work cells and level pull/kanban comes from manufacturing it is a point of reference for many in the lean agile community. Knowledge work is different from manufacturing. In terms of work organization, there is one particular difference that is of interest to us. It is the (obvious) fact that knowledge work is cognitive work (or at least mostly cognitive). More specifically, knowledge work is situated in the realm of socially distributed cognition where depending on their organization, groups may have cognitive properties that differ considerably from the properties of individuals (btw. Edwin Hutchins, Cognition in the Wild is a source of inspiration in this context). An important point to remember.

Also for knowledge work we can analyze the different ways of organizing work. Again, we identify two types of settings. The first is one where work takes place in a carefully organized task setting. The task setting provides a context in which to perform the work. The task setting might include a mix of tasks that are sequentially constrained (sequential control of activity) and tasks that are sequentially unconstrained. Groups that work in a carefully organized work setting are often called crews – like the crew of an airplane, or the crew on board of a army vessel. Another typical example of a carefully organized task setting is work that is organized around a workflow; or closer to the world of software development, a group that is organized around a knowledge discovery process as described by David Anderson.

The second way of organizing knowledge work is one where a task setting is absent. It is the case where the constraints between tasks are yet unknown. It typically entails a group of people with multiple skills that continuously need to co-ordinate their actions to meet a challenge or solve a problem. A good example is a group of people that swarm on a problem as exemplified in this Apollo 13 movie clip.

The above analysis of organizing knowledge work might seem both different and similar to the analysis of how work is organized in the Toyota Production System. Let’s examine the difference/similarities as they are of most interest to us.

For work that takes place in an organized task setting the principles of pull can be applied (similar to the TPS concept of pull). Work items flow between activities within the constraints imposed by the task setting (e.g. sequential constraints). Work in progress can be limited on an activity basis creating pull between activities. As the understanding of the work and the task setting evolves the work can be incrementally improved and adapted to changing circumstances. A perfect match for applying Kanban for knowledge work (which is similar but also different from the TPS concept of kanban).

What about work where the task setting is absent? In agile teams, swarming is a familiar example of work where the task setting is absent. Another interesting example is given by James Shore and Arlo Belshee in a presentation on Single Piece Flow where a multi-skilled group of people act as a work cell processing one work item at a time (similar to the TPS concept of single piece flow in a work cell). The work cell swarms each work item and only proceeds to the next work item when the previous one is done, really done. The absence of the task setting is exemplified by the “detective blackboard” in the presentation. The detective blackboard acts as a shared workspace between the group members. In knowledge work, cells need a shared representation of their understanding of the problem they are solving and the co-ordination needed to solve the problem (so cells in knowledge work are similar but also different from TPS cells).

A cell that is exploring a new demand acts as a pacemaker in knowledge work. The pacemaker is driven by external customer feedback: Are there customers for the product? Is the product solving a customer problem? Etc. The cell’s purpose is to produce hypotheses of customers and demand and to validate these hypotheses (accidentally this is exactly what is covered by discovery kanban). As demand is being established and the product is becoming more feature rich, the pacemaker can pull in work from upstream groups that provide e.g. development or maintenance services. Just like in TPS the pacemaker ties the concepts of cells and pull together.

I am convinced that I have only scratched the surface here. Different questions remain. The concept of pacemaker and how to level demand for upstream development teams, still needs deeper explanation. Still, I hope that I have convinced the reader that thinking in terms of underlying models of organizing work (e.g. cells, swarming, pull, pacemaker) opens up new pathways for organizing knowledge work. Personally the more I am working with the underlying models of organizing work, the less I feel the need to think in terms of Scrum or Kanban “boxes”. I am really looking forward to feedback and discussion.

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Using narrative to research Kanban implementations

Update to this post (Oct. 30, 2013)

During the months after this blog post, Arno Korpershoek and myself have worked on an implementation of a narrative research tool (as described in the blog post) for lean agile organizations based on Cognitive Edge Sensemaker. The purpose is to allow practitioners to share stories about their experience with lean and agile. You can go and have a look and leave a story (if you want) on the narrative research tool website.

How deep is your Kanban?

The Kanban community holds the idea of evolutionary change very dear. The Kanban core practices play a central role in the sense that they are said to catalyze change, allowing a lean agile organization to emerge.Given the importance of the core practices, it is to be expected that people ask the question of how to “measure” a Kanban implementation against the core practices.

Kanban spider

Such measurements are being developed in the Kanban community. Typically, each core practice is considered a dimension against which to measure according to a certain scale of shallow to deep implementation. The above is a typical spider diagram visualization of this. The size and shape of the area in the middle of the spider diagram are a visual representation of the depth of the Kanban implementation for the team that is measured.

The most important reason for measuring a Kanban implementation seems to be a genuine concern for improvement. Measurement can help a team to identify “gaps” or opportunities for improvement. More importantly, it can help to identify other teams with similar or different profiles in the context of experience sharing.

Narrative research

Despite all good intentions, “measurement” of teams is a very thorny issue. We all know that measurement engenders all kinds of dysfunctional behavior. Quantification leads to unwanted outcomes, the environment is treated as unvarying, the context is not taken into account (one-size-fits-all), and it narrows the focus to that what is measured. Most important it may lead to cargo cult as every team aspires to conform to the ideal. In the wrong hands, it can turn into a tool that completely goes against the grain of evolutionary change that is held so dear.

The risk of a one-size-fits-all approach can kill the team diversity that is so crucial to improvement. Teams with different levels of sophistication in their Kanban implementation act as gradients for improvement. Just like a hang glider that needs pressure differences to keep going, improvement and learning needs different teams that perform at different levels of sophistication of implementing Kanban to keep on going. The wrong approach to measurement can take all the pressure differences away leaving no room for learning.

Glider that uses thermals

Narrative research (or narrative inquiry) is an alternative that needs to be seriously evaluated in the Kanban community. Narrative inquiry is a form of qualitative research that emerged in the field of management science and later also developed in the field of knowledge management. It uses stories as the central unit of analysis. It is the stories, such as the two examples below, that provide a context to any quantification of a Kanban implementation. Numbers derive meaning from the context that is set by the stories that are told by the individuals and team(s) that implement Kanban.

Story 1: We are a maintenance team that maintains a large application. Our customers are users from the following  units in the business:= HR, Finance, etc. Customers expect timely delivery of changes to the application and a stable application.

Story 2: We are innovating our product to cope with disruptive changes in the market. We are still exploring what our potential customers want and the business model to capture the value.

So how do the Kanban core practices fit in the narrative research? As a coach I have had the privilege to witness how the Kanban core practices are key to phase shift an organization into a different regime of higher performance. I am sure other coaches have had similar experiences. The Kanban core practices are modulators; i.e. a forces or factors that trigger a change in the “leanness” or “agileness” of a team. They are not just independent and linear dimensions. They influence each other and are influenced by the emergence of a lean-agile organization.

Core practices as modulators As such, it is a good idea to let the individuals and teams signify their stories with an identification of the strength or direction of the modulator/core practice. To avoid “cargo cult”/”conformance to the ideal” we prefer however to use a signification based on equal opposite ends rather than the traditional negative – positive extremes. The picture below shows an example on the basis of “Implement feedback loops” core practice.

Implement feedback loops signifier

The design of the signifier is such that both ends of the scale are equally positive/neutral or negative. In the example above, both types of feedback loops are seen to be equally neutral.

A signifier set design based on equal opposite ends avoids the risk of conformance to the ideal. However, designing a signifier set with equal opposite ends can sometimes prove to be a difficult exercise; especially for the Kanban core practices. The reader might, for example, have different concerns with the example above: Are the opposite ends really equal?  Are these the right opposite ends? I do think that the leaders in our community can agree upon a signifier set that is suitable. The exercise of building it could have a value in itself.

Fitness landscapes

I conclude this blog with an indication of how the results of a narrative inquiry are visualized and used. The figure below shows a fitness landscape. (NOTE: This is not a fitness landscape that has been constructed based on a narrative inquiry. Still it does fine for illustrating how a large quantity of stories that have been signified can be visualized.)

Fitness Landscape

Fitness Landscape

The fitness landscape shows plateau’s of stable implementations; outliers; and peaks of instable implementations. It can guide us to the places where we need to make an intervention and places that we can learn from.

For constructing such a landscape we need to have a large enough quantity of stories. This may be beyond what is possible for small organizations; it might even be beyond the possibilities of larger organizations. My personal opinion is that this presents an opportunity for LKU, Limited WIP society or other to serve the Kanban community. A collection of Kanban implementation stories signified at the source of collection can prove to be an invaluable asset for the community.


Dave Snowden’s work on narrative research has been very influential. See the Cognitive Edge website for more information.

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Managing risks and options with discovery Kanban

At the London Lean Kanban day last month I gave the following presentation on discovery kanban.

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Lean Kanban Europrean Tour 2012 – Resilient change

Here’s the slides of my presentations at LKNL2012 and LKFR2012:

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Resilience, Adaptability and Transformability with Kanban


“Imagine you are on a boat docked in a calm harbor and you want to quickly carry a brim-full cup of water across a stateroom without spilling. Now imagine the same situation but with the boat in rough seas. In harbor, the solution is simple: just walk quickly, but not so quickly that the water spills. At sea, speed is a secondary concern; now the real challenge is to maintain balance on an abruptly pitching floor. The solution now is to find secure handholds and footholds and to flex your knees to absorb the roll of the boat. In harbor, the solution is a simple optimization problem (walk as fast as possible but not too fast); at sea the solution requires you to enhance your ability to absorb disturbance-that is, enhance your resilience against the waves.” From: Resilience Thinking: Sustaining Ecosystems and People in a Changing World by Brian Walker PhD, and David Salt

Resilience is the capacity of a system to absorb disturbance while undergoing change and still retain essentially the same function, structure, identity, and feedbacks. Eco-systems exhibit resilience: e.g. the capacity of a forrest to recover from a fire; the human body exhibits resilience: e.g. the capacity to maintain body temperature under varying conditions; as do many other systems.

The current economic, political and ecological climate, requires organizations to exhibit higher degrees of resilience.  They are forced to change their focus from maintaining efficiency of function towards that of maintaining existence of function (as illustrated with the water cup in the opening story). This has been a main driver of change in organizations for the last decade and will remain so for some time.

The concept of resilience is often depicted as a basin of attraction (see figure below). Under normal conditions, the system operates within the basin of attraction. Given enough disturbance the system can be moved beyond the threshold into another basin of attraction – the system has changed identity. In the case of the human body, if we move the body temperature beyond the threshold point (e.g. below 35°C), the human system is moved from the “life” basin of attraction to the “death” basin of attraction. Or in the case of a lake we may have a basin of attraction (the “good” basin of attraction) in which there is clear water and fish, and a “bad” basin of attraction where the lake is filled with algae due to the disturbance by nutrient pollution.

The stability landscape of a system. The basin of attraction define the main resilience parameters: L = Lattitude (how much the system can be changed); R = Resistance (how easy or difficult it is to change the system); Pr = Precariousness (how close the trajectory of the system is to the threshold )

To what degree does a software development, product development or other team exhibit resilience? Under what disturbances will a team lose it’s identity? I.e. when will a team start disintegrating, letting go of it’s normal practices, stop functioning and start trashing? At what point will the team stop feeling like the team? Under which disturbance? And which teams exhibit more resilience than other teams?

Let’s start with the disturbances. Typical disturbances include:

  • interruption of work
  • too much work
  • changing priorities
  • bugs
  • unclear requirements
  • information arriving too late
  • estimates

Many teams are so overwhelmed by these disturbances that their identity is one of firefighting, multi-tasking, and fixing problems. They are operating in a bad basin of attraction that they can not escape from. Resilience capacity is low, as small disturbances can have dramatic effect on the functioning of the team.

Kanban’s evolutionary change process allows teams to climb out of the bad basin of attraction. The Kanban core properties “visualize, limit WIP, manage flow, make policies explicit, collaboratively improve” help teams to build their resilience capacity. Resilience capacity depends on 3 main factors that are all 3 addressed by Kanban’s core properties and principles:

- Variety: the variety that is present/allowed in the system – the system needs variety to deal with the variety in its environment (requisite variety) – Kanban allows variety in the work items within a team and variety in the policies and processes across teams.

- Modularity: a modular system is more resilient than a highly connected system where disturbances freely propagate – Kanban promotes modularity of work within a team and modularity across teams

- Leadership: as humans are part of the systems we are talking about, leadership is required to respond to changing conditions – Acts of leadership are an integral part of Kanban

Beyond resilience adaptability and transformability are crucial properties. We leave those for a future blog post.


Adaptability is the capacity of actors in a system to influence resilience. This amounts to the capacity of humans to manage resilience.


The capacity to create a fundamentally new system when ecological, economic, or social (including political) conditions make the existing system untenable.

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When change is the bottleneck

A couple of weeks ago I was doing an in-company Kanban workshop. I knew the team that participated in the workshop from before. I had been working briefly with them a few years ago. From the moment people started coming in, I realized that I had to be careful. The team showed many signs of “a bad history of change”. They had been going through several change initiatives, many, if not most, without success or perseverance.

One clear signal was from the body language of one participant. Leaned back in his chair, chin in the air, I really saw him thinking … “here we go again, yet another *wise guy* that is going to tell us how we need to do our work”. Other signals were what others were talking about. Yeah, we do scrum … but we don’t have a stand-up meeting. Yeah we have a project life-cycle (that we need to comply to), but we do not follow it. Etc. Many changes had been pushed onto them. Perseverance in the change had been lacking.

A few years ago I was not able to interpret the signals that this team was sending out. Since then I have been exposed to explicit change methods (i.e. Accelerated Implementation Method, “AIM”) and the Kanban change approach. When it comes to change their seems to be 1 fundamental law:

    • The success of a change initiative highly depends on the success of past change initiatives

In other words, if you have failed at implementing change in the past, you will have a high risk of failing to implement change in the future. And, the more failed changes, the harder it becomes.

For this organization, change really is the bottleneck. Yes, they need to fundamentally improve their performance; but yes they also need to be careful that this does not turn into a YAFCI – Yet Another Failed Change Initiative.

Kanban, in this light, is not just an evolutionary change approach. When done properly, Kanban evolutionary change actually helps the organisation to build a capacity for future change. By insisting on small steps and being persistent, the organisation can build a platform of successful change. The organisation starts with small changes and grows the capability to take on bigger changes in the process. Respect and persistence are the key words.

In the end we had a good workshop. I showed respect for the team, they showed respect back.

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