Cynefin Framework: Unordered Systems


In my last post, I discussed the right-hand side of the Cynefin Diagram, the Ordered Systems. Today, I’ll discuss the left-hand side of the diagram, the Unordered Systems.

We hear a lot about chaotic systems these days, but Chaos is always a short term event. Chaos produces Novel Actions, stuff we can’t predict, and our best response is to act according to our values (not our past practice), see what happens, and support the best of the novelty that appears. It is difficult to have an effective change strategy in a genuinely chaotic situation. But, engagement by your organization or group will let you learn what you can from the turbulence.

Complex systems are largely the place where advocacy groups plot and execute their change strategies. Most typical organizational planning is focused on the Complicated Realm, however, and we often try to make our interactions as part of complex systems change fit the logic and “predictability” of the complicated realm.

This is a mistake, and continuing to interpret the complex as complicated (and amenable to procedurally focused planning and execution models) is a strategic error, weakening our change strategies and constraining the possibilities for real change.

In this complex realm, your organization or group and your change target become part of a single system that is changing together or coevolving. The longer you pursue change in a particular target, the deeper the coevolutionary relationship becomes. Put simply, you change the target and the target changes you.

Part of the change in you involves the learning you acquire about your target, which in turn is largely a result of the responses that your target uses to blunt or counter the change strategy you are implementing. Ideally, your learning from this coevolutionary relationship improves the effectiveness of your change strategy for this effort and for future ones.

In advocacy organizations, people who have been around for a while and have created and experienced change efforts against a target will often recognize a pattern in a current change effort that has either appeared before or which is a variation of one they have worked on in the past. This recognition of a pattern doesn’t dictate a specific advocacy action but provides a guide for creating a customized response to the current circumstances of the advocacy effort. Interestingly, efforts (I have seen many) to identify such patterns and make them explicit so they can be shared  with people who haven’t experienced them are largely failures. The pattern is best recognized and used in a real situation, and it is hard to pull out in the abstract (say for an advocacy manual); it is also hard for new advocates to grasp the importance of the pattern outside a real change situation. This is clearly different from the Complicated System where you can create a user’s manual for each component, and reuse already existing explicit information (from blueprints, procedures, experts, etc.) to solve a very specific problem.

In complex systems advocacy, you should try probing the target for its range of responses so that you can learn more about how it views your change effort, and how sophisticated its experience really is in the current engagement. Which is another way of saying that the success of your advocacy depends on your ability to learn from your current engagement with a specific target.

I know that the above is a mouthful. In my next post, I will use concrete examples from actual advocacy efforts to show how important this coevolution with our change target is, and better illustrate the weakness of a “complicated system, detailed planning, measurable outcomes” approach.

Interventions in Complex Systems


Cynefin Framework: Ordered Systems


The right side of the Cynefin diagram represents ordered systems. Most of the time, even when a system is clearly unordered, we try to interpret it and change it as though it were ordered. I will go into more detail about how poorly such an approach to change can work in the next post.

Simple Systems

The lower part of the diagram covers what Snowden calls simple systems. As a very simple example, consider a form that your organizations submits every month or every quarter because the form is required for you to maintain some employee benefit. Basically, filling in the form assures some agency of government that you are doing the same thing you were the last time you submitted the form, and the form, signed and sent, makes you liable if you aren’t doing things right.

You update each time if there is anything that is actually new. A more involved version of this same concept of a simple system would be tweaking a personnel policy because of a change in your organization or the rules regarding such policies. Most of the time, with a little effort, you can figure out what needs to be tweaked, make the changes, and be done with it.

Snowden describes these activities as “Best Practices”. There is a right way to perform these actions and once you figure it out, you can pretty readily keep doing it right. You identify the task (Sense), you connect what you Sense to a task you have more or less done before (Categorize), and you Respond with the appropriate output.

Much of day-to-day work for most people falls into this kind of system.

Complicated Systems

Systems are called complicated because they have lots of parts. Think of an airplane, like a 747, or a computer. When a complicated system is being designed, the relationships between the parts need to be rigidly constrained. We don’t want the wing of a 747 to suddenly decide that it needs to be somewhere other than remaining attached to the plane. Also, while the parts are optimized for being a part of the 747, they are not necessarily optimized for what they could be if they weren’t part of the 747. It is a bad idea to have one part that will last forever and another connected to it that fails with great regularity. In complicated systems, parts and their maintenance are often tailored to each other so that failure of the system as a whole won’t occur.

Much of the design of our organizations and change groups become complicated in this sense over time, as we get bigger and have more complicated constraints (laws, audit requirements, 3rd party contracts, etc.). These design changes are usually done because they can’t be avoided, and we tend to add the changes and make some adjustments in the rest of our organization or group to accommodate them. It is like trying to remodel the 747 while it is flying.  Optimization doesn’t enter into our organizational results because we have to keep the doors open while we design and make the changes. After such changes, organizations usually go through a process of running into “pain points” that didn’t exist before the change. We muddle with these to make them work as well as we can, but some aspects of such change will show up in employee stories about the problems in the organization for years. Some will even outlive the employment of every person who participated in the original change.

If a change is particularly difficult (say, rewriting your retirement plan to make it compliant with a new Federal law), you might hire an expert to help plan and implement the change (say to draft a compliant plan which you can then tweak to fit your organization). Even though you end up with a plan, it had to be created part by part in the same way that you would design or build that 747.

This need for real design is the reason why “Analyze” replaces “Categorize”.  The notion of problem solving rather than matching an exact solution is the reason why Snowden describes this quadrant as “Good Practice”. Nonetheless, understanding (making sense of) a complicated system can be achieved one piece at a time. Think of the metaphor of a “blueprint” (I’m old enough to remember when blueprints were blue). While you may not be able to get the whole of the 747 inside your head, you can go through the entirety of the plan by using the design documents and the narratives attached to them. Much of what we think of as funding proposals qualifies them as complicated systems. We are constructing them a piece at a time, and organizing them in a way that will show the proposal reviewers what we expect to happen and how we expect to make things happen. A blueprint. In fact, most strategic plans are also blueprints. This may seem obvious to you as you read that last sentence. But as I hope to show you in the next post, blueprints don’t work well with complex systems, and they don’t work period with chaotic ones.

Introduction Cynefin (video)

Advocacy and Sensemaking


Although we tend to think of advocacy as a kind of service, like other social services, it isn’t. The reasons why this is true have nothing to do with advocacy being “better” than other services. Rather, advocacy is different from standard services because it has a different relationship to the target of its actions than standard services. Along with this difference in target relationship, an advocacy effort uses a different nonstandard framework to make sense of a target and, for that matter, itself as an organization.

Sensemaking is a concept that developed in the 70’s, and it has gone through a variety of reformulations over the last few decades. For an advocacy organization, all the usual ways of making sense of their advocacy effort and their target certainly apply (identity, retrospection, and so on). But the relationship between an advocacy organization and the target of its change strategy requires a unique effort in sensemaking.

This is because the relationship between an advocacy organization and its change target is evolutionary. For typical social service systems, the relationship between the system and the person receiving services might well focus on changing the person, but the social organization expects to remain the same after the person has received services. Such organizations work very hard to stay the same after the delivery of services. In fact, this relentless focus on staying the same is one of the most criticized dimensions of working in social services.

I have looked for years to find a framework that respected this evolutionary relationship, and that allowed it to be understood in less abstract terms than a “coevolutionary change relationship”. I ran across the Cynefin Framework some time ago, and, although it is targeted at large enterprise and governmental initiatives, the model is a very useful one for understanding change efforts by small advocacy organizations, and informing our change efforts by making sense of targets. I am going to put together a few posts to introduce the model. This post will be an overview focused on the image above.

The first thing to recognize about what the diagram means is that it describes how we understand (make sense of) the target of our advocacy. That’s why the little area in the middle (disorder) is there. We often find ourselves facing an advocacy challenge on behalf of our constituents with no detailed understanding of how or why the particular challenge arose. In fact, initially, it is often unclear what the target of our change effort should be. We must “make sense” of the issue and potential targets to build a change strategy. The four categories that constitute the possible sensemaking, the meaning that the target has for us, with ordered systems on the right and disordered systems on the left. The red words are the actions we must take to build a useful understanding of each specific system type, and they are in the order we must take them.

I’ll give you two short videos, one very funny and the other a short, if challenging, introductory video to review before my next post:

How to organize a Children’s Party (3 minutes)

The Cynefin Framework (8 minutes)

Next time, I’ll talk about the Ordered side of the diagram.

Aging Orgs


From “Discovery Kanban”


All living systems age. Even organizations. This doesn’t mean that organizations die like human beings; but, there are lessons we can learn about how our organization evolves over time. In much the same way that our personal aging changes us irreversibly, so too does the passage of time alter the range and focus of our Mission 1 and Mission 2.

In the system theory framework, there are four general phases of “aging” in complex adaptive systems (including advocacy organizations):

“The Panarchy model suggests that systems follow a four-phase adaptive cycle of (1) “exploitation”…; (2) “conservation”…; (3) “release”…; and (4) “reorganization”….” From,  Cynefin, Panarchy, PDCA, OODA and value creation curves

  1. Exploitation: For advocacy organizations, exploitation is a way of thinking about the universe of possibilities that exist when that organization first begins its advocacy work. It is an unfortunate fact that oppression and marginalization of devalued communities creates a very large context in which advocacy can take place. The choices that an advocacy organization makes when it begins to interact with this universe of advocacy possibilities are usually a mix of the worst problems the community faces and the immediate resources that the organization has. Regardless of what drives the choices, these initial decisions create the learning environment for the advocates. This learning environment can have a profound effect on the development of the organization and its advocacy. So, for our goals, exploitation is really learning.
  2. Conservation: The most common way Mission 1 and Mission 2 interact is the use of M1 to generate resources that become the core of the organization’s strategy for Mission 2. In other words, the organization uses it’s core passion to generate resources to keep the organization going. “Resources” doesn’t just mean money. They include a governing board, reputation, social support, staff capabilities, and organizational infrastructure like equipment, fund-raising events, financial documents, and so on. Over time, what was done earlier in the development of resources constrains what can be done later. So Conservation doesn’t just mean saving. It also means the conservation of a path of organizational development. As useful as such an approach is, it reduces the flexibility of the advocacy organization.
  3. Release: Release in organizational terms means the breakdown of the organization’s ability to pursue its core mission (M1). This can happen because the organization has become a bureaucracy and only pursues its own maintenance (M2), because it has altered its core mission to something that no longer inspires support, or because it has become corrupted and is only a tool or opportunity for its staff and stakeholders to exploit for their own individual ends. Whatever resources remain are “released” into the environment, and abandoned or picked up by other organizations.
  4. Reorganization: The resources released during Phase 3 begin to reorganize themselves immediately. It is the reorganization that allows the possibility for exploitation or new learning.

In later posts, I will discuss each of these phases in greater detail. It is the case that advocacy strategy has to match not only the problems of a supported devalued community. That strategy has to fit the phase of the adaptive cycle in which the organization