(P4): Advocacy Cycles

A small boy walking down a two-track with a small stream of water. He is dragging a stick through the water.

Everything operates in cycles. If you understand the cycles of the system you are trying to change, you can make use of that for improving the effectiveness of advocacy tactics.

A basic cycle of those systems we seek to change is the balancing of exploration and exploitation in seeking valued system outcomes. A simple abstract example will illustrate what this means.

Predators must find food (exploration)  and they must eat it (exploitation). Finding food uses calories, which increases the urgency of the exploitation side of the cycle. Eating food does not by itself help the predator to find more food. So the animal must balance the amount of time spent looking for food with the necessity of eating it. You can think of this as an example of a strategy for dealing with the uncertainty of the future and the scarcity of resources.

Because all kinds of complex adaptive systems face this same environmental demand, their system flow is a cycle. What is important to the system varies depending on where they are in this cycle. In bureaucracies, over time and aging, exploration is entirely reduced to acquiring funding, and exploitation is reduced to internal competition over the control of funding.

For an advocacy example, State Rehabilitation Services Agencies commonly experience high demand for their supports despite chronically low funding. One impact of this is that available support monies fall off more quickly during a fiscal year than the passage of time would suggest they should. So, it’s easier to get expensive supports in the first quarter and much harder to get them in the last quarter of the agency’s fiscal year. There are many variations of this kind of insight:

  • Pushing for a summer hearing in a special education case. The district may have to pay overtime for witnesses from their district to testify in the hearing.
  • Policy change advocacy in the weeks leading up to funding decisions for the supports system. Systems try to avoid scandal when their funding is at stake.
  • Kicking the system when it’s down (say, from a political fight)
  • Etc.

We don’t tend to think of such opportunities as a part of a larger cycle, but they are.

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(P4): The OODA Loop

Complex Diagram of the OODA Loop. See description through link below diagram.

OODA Loop Diagram Long Description

The OODA loop (see picture above) was created by John Boyd to help explain why some fighter pilots were much better than others in aerial dogfights. His basic premise was that you could win if you made good decisions faster than the other pilot. This was oversimplified over time to mean just faster decisions, without the part about better decisions.

The most important part of the OODA loop for advocates is the “Orient” phase. Successful use of the Orient Phase requires not especially the observation of where the opponent is, but rather a deep understanding of how your opponent thinks about reality. What does your opponent value? What risks are paramount in their thinking? After all, you want to know where your opponent is going. As Wayne Gretzky said, “I skate to where the puck is going to be, not to where it has been”.

For example, in an advocacy negotiation over, say, a complex support for a student, the Orienting Framework of a typical ISD or special education administrator focuses on cost, required program resource commitment (including staff, skills, general availability), precedent (will hundreds of other students/families request the same service if we support this student?), and the political consequences of agreement to the requested support from other staff, other parts of the education system, and the general public.

While it might seem as though these concerns are matter-of-fact, they are not. Underlying all of them is the decision-making rationale AND fear-driven concern for personal and system liability if things go sideways for some reason. Because the fear of such liability is never entirely rational (we can’t know the future), the Orienting Framework is sensitive to surprise, regardless of its source.

The use of the OODA Loop as a tactic in disability rights advocacy is often about producing novel challenges to the system as it is now and as it thinks/feels now. Thus, a successful challenge to a system with a novel destabilization requires that you have a clear understanding of how your target thinks and feels.

These challenges don’t have to be radical or revolutionary. They must, however,  be initiatives that the system hasn’t run into before.

Often, there also need to be several destabilizations. A bad habit of naïve advocates is to create a destabilization (say, a complaint) and then sit around waiting for a response. Delay (because it requires nothing but avoiding action) is always available as a default response for the system you are challenging, and it is used as much as possible by that system.

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(P3): The Ways of System Aging

The Panarchy Cycle; alpha-phase: reorganization; K-phase: Conservation & Stabilization; Omega phase: Release (Creative Destruction); r-phase: Exploitation & Growth; Poverty Trap (between alpha-phase and r-phase) is Insufficient Resources for starting New Growth; Rigidity Trap (between K-Phase and Omega Phase) is Holding on to old systems.

All CAS age (even us, or maybe especially us!). But seeing aging in a CAS is tough. There is no perfect way to describe such aging, but it is important to grasp the general contours if we are to make use of aging in our advocacy efforts.

Aging applies as much to advocacy organizations as it does to those organizations that are the object of our advocacy efforts. The Panarchy Cycle is as good a model for system aging as I have found, and it has the advantage of “face” usefulness. It is important to remember in what follows, however, that we can do things to change the path of aging in a CAS. If I develop arthritis in my hip and it gets bad enough, I might have a hip replacement surgery. If that surgery is successful, the quality of my life can take a huge leap. But, despite the improvement in my day-to-day activities, I am still aging.

The Panarchy Cycle is usually described as four repeating steps:

1.Reorganization

2.Exploitation and Growth

3.Conservation and Stabilization

4.Release or Creative Destruction

A commonly used example of these steps is a forest system after a large-scale fire:

1. The “empty” landscape after the fire becomes populated by weeds and other fast-growing plants and small animals and micro-organisms.

2. As the landscape becomes denser with life, fast growth is gradually replaced by plants and animals that can store resources and more easily alter the forest to fit their needs.

3. Eventually, the forest becomes stable and many of its possibilities for novelty are locked up in resources controlled by subsystems of large tree species, symbiotic relationships, organizing of resource flows like water, animal families and reproduction, and so on.

4. The CAS organization becomes increasingly brittle and subject to easier breakdown.

The two big drivers of the development of enabling relationships in the CAS are the “poverty trap” in the early development of the system, when it is tough to use resources because they must be changed (the enabling relationships must be created) by those organisms that participate in early development, and the “rigidity trap”, when most resources are already tied up in some subsystem, and organisms have set patterns for their use and reproduction. Rigidity is defended and becomes brittle and opens the forest to disturbances that cause some level of cascading breakdown in the system’s ability to adapt to further disturbance.

It is often difficult for us to accept this kind of aging cycle in our own organizations or those we target for advocacy because it seems as though the problems we experience would be easy to fix if we just go ahead and fix them. This apparent ease of problem-solving is based on our false idea that the organization is a machine or a computer.

The isolated problem is often easy to fix. But fixing the problem also changes the CAS in long term ways that are hard to see, by destabilizing some enabling relationships and generally making enabling relationships harder to create. This is the unavoidable burden of unintended consequences.

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(P3): The Ways of Governing Constraints

A female soldier doing orthopedic rehabilitation under PT supervision.

Governing Constraints create possibility spaces by eliminating large swaths of possibility that are irrelevant to the meaning of the governing constraint. When there is more than one governing constraint in an organization, the governing constraints create a complex possibility space that permits much more complex possibility choices.  When the CAS is working the way it is supposed to, the multiple governing constraints also allow the populating of the space by more complex enabling relationships. In turn, this drives a more complex CAS development process and a more complex aging process.

But the interaction of multiple governing constraints is, well, complex. Multiple constraints can undermine or enable each other, and the choices made by participants in an organization can produce extremely different organizational behavior. The three governing constraints of any advocacy organization or the usual organizations that are subject to advocacy (Mission, Reproduction, and Hierarchy) frame but do not determine that behavioral path.

The primary result of the Hierarchy Constraint is a massive reduction in the possibilities of enabling relationships. The best example of this is the aphorism about bureaucracies, “Anything not required is forbidden”. Hierarchy is a societal choice, not an objective law of physics. It hinges on the belief that the universe is mechanical, and that restricting choice improves the causal power of the mechanical links that supposedly guarantee outcomes.

The staff will be flogged until morale improves, etc.

Hierarchy can be based on logical relationships or power relationships. Logical hierarchies are not used to run organizations. The use of a power hierarchy always reduces the possibilities in the space created by Mission and Reproduction.

The Mission, at least in new systems, is the best statement of what the system can create. The relationship between Mission and Reproduction is complicated by the way that a complex adaptive system ages.

If a system ignores Reproduction to maximize it’s Mission, the system will run out of resources to realize the Mission. If the system maximizes reproduction at the expense of the Mission, then the system will become like a zombie, focused exclusively on more resources, with no regard for Mission outcomes.

Because human systems are made up of humans, it is always possible to change the relationship between Mission, Reproduction, and Hierarchy, creating a new complex possibility space. But it becomes more difficult to change these relationships as the system ages, and the likelihood of some kind of system collapse (not required to be total) increases.

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(P3): How An Advocacy/Target System Evolves

The pattern problem: An example becomes a lesson; A lesson becomes a method; A method becomes a practice; A practice becomes a doctrine; A doctrine becomes death.

In 1981, I went to work for Michigan Protection and Advocacy Service as a field advocate in the counties around Michigan’s Thumb. About half of my work involved representing students and their families in special education disputes. Over the next four years, I got to observe first hand how my special education advocacy and the approach of the special education systems in my catchment area evolved. It was quite enlightening.

Initially, school districts viewed special education largely as a new program only partially paid for by the federal mandate (this remains true today). The important aspects of it to the district CAS were how to pay for it and what impact did it have on their previous model of education services. There was, early on, and continuing to this day, a constant source of tension between regular education and special education systems (SPED services receive roughly twice the funding per pupil than regular education receives). Demands by special education students for supports and services that were outside the ken of past education practice were either ignored or denied.

This framework was ripe for effective advocacy. In the first few years of special education advocacy, it was very easy to win programs, supports, and services because the district didn’t really think it had to do anything to win other than obstruct demands. Advocates had time to prepare, to deepen their understanding of the law at both Federal and State levels, and to become adept at using the state and federal rules in the negotiations.

This advantage, like all advantages in the competitive interaction between different CAS, didn’t last.

One set of changes that our effective advocacy triggered was a dramatic increase in the number of students and families that requested advocacy assistance. Since the MPAS budget didn’t increase based on demand, this resulted in less time and resources for pursuing advocacy outcomes. In turn, this made our interventions less effective, overall.

The other set of changes that our effective advocacy triggered was to be taken more seriously by the districts. They began to commit resources to fight our advocacy including, eventually, hiring attorneys on retainer to improve their obstruction.  This also meant that the cases would be more complex (basic failures of civil rights were avoided), requiring more time from advocates and less successful outcomes. The upshot of these various forces (including successful State efforts to eliminate large amounts of state funding for MPAS) was, over time, to dramatically reduce individual special education advocacy by our organization.

Similar shifts in response by the system took place at the State and Federal level. The current state of special education law is an extraordinarily rigid narrowing of the possibilities that seemed just over the horizon in the late ‘70s and early ‘80s. There have been some separate increases in advocacy effectiveness in ways other than the single student advocacy model of the early years, which I will talk about later.

This pattern of initial success followed by a slow steady reduction in advocacy effectiveness and the reduction of civil rights to rigid requirements is so common across all areas of disability rights that I think of it as a standard development pattern in the exercise of advocacy.

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(P3): Destabilizing Weak Constraints in Advocacy

Image of the Night King from Game of Thrones Series

  • I came to a stark realization: chronic surpluses could be almost as destabilizing as chronic deficits. –Alan Greenspan
  • One of the points about distractions is that everything they do is destabilizing.
    -Bruce Sterling
  • Yet, history has shown that if material force can defeat some ideologies it can no longer obliterate a civilization without destabilizing the whole planet.
    Abdelaziz Bouteflika

In a Complex Adaptive System (CAS), any form of interaction between the system and the outside world can be usefully viewed as a weak constraint and a potential target for destabilization. Obviously, some constraints are closer to the heart of your advocacy outcome than others.  But there are always more ways to go after a valued change than whatever works the first time we use it.

The biggest problem we advocates have in interacting with the CAS is that we settle on a technique or procedure that has worked for us in the past. This approach, while understandable, dramatically reduces the palate of ways we might destabilize the CAS for a valued purpose.

When we use the same techniques with the same CAS over and over, the CAS will adapt to them, making our advocacy more complex and expensive for us to use. Additionally, when the larger environment in which our target faces the same set of destabilization techniques, that larger environment will also adapt, narrowing the impact of our efforts to destabilize and making the outcomes we achieve more predictable, and, thus, more manageable by targets. Both the target and our advocacy become more rigid.

An example (in the next post) will give you the idea of how local, state, and national CAS and our advocacy approaches adapt over time to successful advocacy.

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(P2): Safe-to-Fail Experiments as Weak Constraints

Strange yellow and black bicycle with a perfectly square frame and no brakes.

The idea of Safe-to-Fail Experiments was developed by Dave Snowden as part of his Cynefin framework. The technique is a way to learn about a complex adaptive system without triggering unintended consequences that are out of your control (See the link above.) But the concept of using probes to learn about complex systems is useful in many other contexts, most notably, in social justice advocacy.

Most advocacy is premised on the idea that there are legal constraints on the behavior of target systems, and that these constraints can be used to change the behavior of the system. In other words, advocacy can use procedures repeatedly to create change. Implicitly, we only need to understand the legal constraint under which a system operates and the change procedures (complaints, lawsuits, etc.). We don’t need to understand the politics or history of the system we are trying to change, all of which are, of course, other kinds of constraints.

But we do need to appreciate these aspects of a system before we can hope to successfully change it. This is because even the most apparently logical procedural path of some bureaucratic machine is, as we all know, a little “Peyton Place”, more complex and messier than the bones of the procedure would suggest.  Which is to say, all bureaucracies are Complex Adaptive Systems using much of their available energy to prevent disturbance from creating change through forcing them to modify existing constraints.

From inside a bureaucracy (or any large organization, including for-profit corporations), creating change must involve experiments too small to trigger annihilation of the experimenters or the CAS, but enabling you to learn something useful about the systems dispositional trajectory, about its system of constraints.

Safe-To-Fail is also a useful tool for changing that most personal of CAS, yourself.

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(P2): Tinkering and Bricolage

A room full of various unexpected things for you to play with and make something new

Tinkering is standard behavior for anyone who is curious. Bricolage is a French word defining tinkering as finding a solution to a problem with whatever is in your immediate environment. Bricolage makes problem-solving local and personal and is more than just playing. Bricolage reliably produces solutions that are inexpensive, easier than managed solutions to implement, and well matched to the actual reality of the problem rather than the “planned” reality of the problem. In fact, in modern life, bricolage is a common response to solutions that are imposed by organized management.

I suspect bricolage was a primary way our hunter-gatherer ancestors engaged the problems of their daily lives. Adequate solutions would become part of a multi-generational exploration of what possibilities these solutions held, a kind of socially organized exaptive process. Bricolage speaks to the personal “engineering” drive we all have.

My father was an extremely capable chemical engineer who worked for Dow Chemical for 45 years. His primary focus over the course of his career was something called “process engineering”. His task was to take a reasonably successful research project and find out if the project had commercial potential. Researchers tend to think that you scale their successful research by simply making it a bigger version of what they used as their research methodology.

In reality, designing and building a commercial pilot that is a million times larger than the research process, respecting the physical environment of seasonal temperature changes, the length of pipes, the delivery of chemical components at the right temperature and with the catalysts and pre-product components at the right time, so the next step in the process can be successfully initiated, and so on. Process Engineering is a particularly large form of bricolage, and the difference between ideology (research) and engineering (bricolage) has many lessons for any attempt to change any CAS.

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(P2): Environmental Scanning

Wildly diverse images of pollen types in black and white

Environmental scanning is not monitoring. It is a deliberate activity designed to increase the possibility of surprise. It assumes you already have a commitment to changing your current view of reality by exposing yourself to what you couldn’t anticipate.

So, having a rigid procedure for environmental scanning won’t work. Over time, you’ll find less and less novelty and more and more repetition. You need an approach that has enough noise in its scan to produce stuff you didn’t expect or even know might exist.

I use a variety of ways of accessing information, including ones that I am uncomfortable with, or frankly disagree with, in order to maximize the possibility of surprise. This approach requires scanning a lot of useless crap. But I’ve gotten faster and more accurate in my scanning for crap over the years, so I still get a fair amount of surprise. I also add and subtract sources regularly to maintain the surprise. I use the criterion that a particular source is no longer surprising to me.

Since anybody’s experience of surprise is conditioned by the personal path they have followed in all its eccentricity and uniqueness, a useful environmental scanning approach will be customized to that anybody.  The vagaries and dynamic of our personal purpose and meaning will also influence what we find surprising, and that will change over time as we change. Our ecosystem always includes ourselves.

The way that this kind of environmental scanning helps us detect weak signals is best understood as similar to a kind of process called stochastic resonance. Stochastic resonance happens when you add noise to a weak signal. That part of the noise that matches some part of the signal will boost the “volume” of the signal. That part that doesn’t match will cancel out through interaction with other parts of the noise.

We often try to remove noise if we are dealing with a weak signal because we believe that will make the signal clearer. So it is surprising to find out that noise can help us understand weak signals. This reality is an interesting metaphor/framework for interaction with any CAS.

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