Not all kanban is alike

In the series of “not all work is alike” and “not all change is alike” I could not resist the temptation to write a blog titled “not all kanban is alike”. Mainstream kanban systems (which I will refer to as delivery kanban) as we know them today are mainly focussed on improving fitness for purpose of service delivery. I have a firm believe that the scope of Kanban systems is much wider if we also take Discovery Kanban systems into account. I intentionally use the word system to stress the fact that what I am talking about here is more than just kanban boards and visualisation with sticky notes. Kanban systems have a set of properties that make them systems. Both mainstream kanban and Discovery Kanban share a set of properties. They are also fundamentally different. Below you can find an overview of how mainstream and Discovery Kanban are similar but different Kanban systems. The comparison should be relatively self-explanatory. If something needs some more explanation, please leave a comment.

Delivery Kanban Discovery Kanban
Purpose Improving fitness for purpose of service delivery Improving the fitness for purpose of organizations in an uncertain and changing business landscape
Assumption Demand is established and there is more demand than capability Demand can stagnate or be disrupted requiring not just delivery against established demand but also timely  creation of new demand
Who pulls Workers pull the work Workers pull work, Customers pull product
What is visualized Work More than work alone: opportunities, options, risks, issues, learning, improvement, …
What is limited Work in progress Unvalidated assumptions as well as work in progress
What is managed Flow of work Flow of work as well as flow of customers; being in the flow (balance discovery and delivery)
What is measured Fitness criteria of service delivery: Lead time, due date performance, quality, etc. Fitness criteria of delivery and discovery: cycle time, AARRR or other innovation accounting metrics, etc. as well as service delivery criteria
Feedback loops Internal feedback loops at different  levels in the organziation Customer feedback loops as well internal feedback loops
Change Evolutionary change Mixed change approach
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Not all change is alike

After the opening session at the Kanban Leadership retreat in Portugal it is clear that change is again a big topic at the retreat. Mike Burrows’ session proposal is on visualising change (have a look at his recent blog post). Pawel Brodzinski’s proposal is on investigating what the preconditions are for using Kanban successfully, and how to avoid cargo cult when introducing Kanban (a recent blog post of Pawel). The Kanban Method, as a method of change, in itself seems to be perceived as a change that may lead to resistance and all the side-effects that go along with it.

My own proposal is a call for a finer grained understanding of what change is – and a recognition of the fact that not all change is alike – as a prerequisite for both visualisation and understanding the pre-conditions for any type of change. In plain language this latter means that change is in the eye of the beholder. As a community we can discuss at length why or why not certain changes are difficult to accept or not. The truth of the matter is that the only group of people that can reasonably give an indication of how “difficult” or not a change is, is the group of people that is subject to the change. All change contains an internal tension. Acceptance of the change calls for respect for the identity, absorption capacity, needs and wants of the ones that are subject to the change. Deep systemic improvements may call for divergence and substantially moving away from the status quo.

Thomas Kuhn in his ground breaking work “The Structure of Scientific Revolutions” has made a very detailed analysis of “change” in the history of science. His work can teach us some important lessons.

Kuhn makes a distinction between two types of change. The first type of change is revolutionary change. It is the type of change that involves a certain sort of reconstruction of group/community/organizational commitments as it challenges the prevailing climate, involving an unfamiliar perspective of both problems and solutions. Revolutionary change is sometimes also called paradigm breaking change as it challenges the existing paradigm that is shared by a group of people.

The second type of change that Thomas Kuhn points out is cumulative change. Cumulative change stays in line with existing commitments and the prevailing climate. It is also sometimes called paradigm consistent change.

Between the two types of change, revolutionary change is the one that is least understood (although it may be the one that is most talked about). Revolutionary change needs not be a large change, nor does it need to seem revolutionary to those outside of a single community. Often revolutionary change is mistakingly associated with crisis. This does not need to be the case. This brings us to a second distinction that we can make in the nature of a change: is the change imposed upon us, or is the change a change that we are initiating ourselves? Or as shown in the picture below: is it pro-active or reactive.

The above analysis can be used as the basis for a framework for making sense of change. In fact I use such a sense-making framework when I introduce change in a group of people. The change is broken down into smaller parts that then can be analysed with the above framework. It gives me an indication of how the change is perceived by those that are confronted with it. It allows me to adapt the order and strategy for introducing the change in that group of people.

Since every organisation is unique the sense-making framework is best tuned to the specifics of the organisation. Not every organisation uses the same terminology, for example, and you do not want to let this get in the way (in the above framework, for example, the reader might prefer another terminology). This can be done by means of a workshop to construct archetypical changes based on stories of the participants. Doing so makes the participants aware of the fact that not all change is alike and that different types of changes require a different strategy. The different types of strategy for the different types of change deserves a separate discussion. I just want to note here that in my opinion pro-active change is best served by an evolutionary approach (as advocated by the Kanban Method).

“Not all change is alike” is one of the principles of Discovery Kanban. Discovery Kanban calls for an approach that includes sense making and visualisation of change. In subsequent blogs I will go deeper into other aspects and principles of Discovery Kanban.

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Visual project management

I did a webinar for LeanKit where I explore the why-how-what of Visual Project Management.

Below you can find a link to the slides.

Posted in agile entrepreneurship, change, Discovery Kanban, intrapreneurship, kanban, Lean, OODA, Uncategorized | Tagged , , , , , | Leave a comment

A serendipitous rediscovery

When I met Sean Murphy of SKMurphy at the Lean Startup conference in Dec of last year I could not have imagined that this encounter would put an overlooked topic back on our agenda. Sean and I got into a conversation after I had mentioned the use of the Kanban Method as a way of introducing lean startup principles into the enterprise. Sean was triggered by this remark and during a conversation afterwards, without knowing Patrick was my co-founder, he referred to Patrick’s work on Discovery Kanban. Speaking of serendipity …Since that conversation we have had several skype calls with Sean that helped us to advance with our Discovery Kanban Method.

As a result we are rebranding the lean-adaptive blog towards Discovery Kanban. Patrick has presented some of our new insights at the London Lean Kanban Day 2014.

 

Stay tuned …

Arlette

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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.

Reference:

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

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