A three-year old drowning victim is alive and thriving today because someone in Switzerland cares about systems. Atul Gawande, surgeon, polymath, and author of The Checklist Manifesto, recounts the tale as the second of four BBC 2014 Reith Lectures on the future of medicine. The podcast of “The Century of the System” is well worth 40 minutes of your time.
Gawande’s central point is that the power of design, coordination, and collaboration trumps heroics. This is so terribly hard to pull off because it runs against the stories of heroics that so capture our imagination and our egos. How we get to good designs in a world that honors heroes is the challenge.
Systems in the real world are messy and complex. There’s a reason that Aldo Leopold was so cautious about interventions:
“The last word in ignorance is the man who says of an animal or plant, “What good is it?” If the land mechanism as a whole is good, then every part is good, whether we understand it or not. If the biota, in the course of aeons, has built something we like but do not understand, then who but a fool would discard seemingly useless parts? To keep every cog and wheel is the first precaution of intelligent tinkering.” ― Aldo Leopold, Round River: From the Journals of Aldo Leopold
Feedback loops and interactions can be subtle and hard to see. This short video is a nice example of that complexity presented in an accessible and understandable way. It’s been making the rounds in various social media settings. I wanted to post it here so that I can find it and share it more easily.
Here is a brief clip from an interview Steve Jobs did in 1995 while he was at Next. It neatly captures an important attitude about dealing with complex systems:
Whenever you poke at a system, the system pokes back. If you grew up with siblings, you learned this at a visceral level.
Too many of us take a limited lesson from those experiences; we come to believe that we are powerless in the face of a larger, more powerful system (or sibling). The better lesson, which Jobs embodied in his life, is to seek places and directions to poke where your impact can be amplified.
I’m just wrapping up a course I’ve been teaching at DePaul’s School for New Learning on Understanding Organizational Change. I’ve grounded the course in a view of organizations as dynamic systems from the perspective of Jay Forrester, Donella Meadows, and Peter Senge. In the last few sessions, we’ve also been discussing the notion of Wicked Problems and the challenges they present in today’s organizational environment.
There is no definitive formulation of a wicked problem. In other words, the problem can be framed in many different ways, depending on which aspects of it one wants to emphasise. These different views of the problem can often be contradictory. Take, for example, the problem of traffic congestion. One solution may involve building more roads, whereas another may involve improving public transport. The first accommodates an increase in the number of vehicles on the road, whereas the second attempts to reduce it.
Wicked problems have no stopping rule. The first characteristic states that one s understanding of the problem depends on how one approaches it. Consequently, the problem is never truly solved. Each new insight or solution improves one s understanding of the problem yet one never completely understands it. This often leads to a situation in which people are loath to take action because additional analysis might increase the chances of finding a better solution. Analysis paralysis, anyone?
Solutions to wicked problems are not true or false but better or worse. Solutions to wicked problems are not right or wrong but are subjectively better or worse. Consequently, judgements on the effectiveness of solutions are likely to differ widely based on the personal interests, values, and ideology of the participants.
There is no immediate and no ultimate test of a solution to a wicked problem. Solutions to wicked problems cannot be validated as is the case in tame problems. Any solution, after being implemented, will generate waves of consequences that may yield undesirable repercussions which outweigh the intended advantages. (Offering Britney Spears a recording contract is a classic example).
Every solution to a wicked problem is a one-shot operation because there is no opportunity to learn by trial-and-error, every attempt counts significantly. Rittel explained this characteristic succinctly, with the example One cannot build a freeway to see how it works.
Wicked problems do not have an enumerable (or an exhaustively describable) set of potential solutions. There are no criteria that allow one to test whether or not all possible solutions to a wicked problem have been identified and considered.
Every wicked problem is essentially unique. Using what worked elsewhere will generally not work for wicked problems. There are always features that are unique to a particular wicked situation. Accordingly, one can never be certain that the specifics of a problem are consistent with previous problems that one has dealt with. This characteristic directly calls into question the common organisational practice of implementing best practices that have worked elsewhere.
Every wicked problem can be considered to be a symptom of another problem. This refers to the fact that a wicked problem can usually be traced back to a deeper underlying problem. For example, a high crime rate might be due to the lack of economic opportunities. In this case the obvious solution of cracking down on crime is unlikely to work because it treats the symptom, not the cause. The point is that it is difficult, if not impossible, to be sure that one has reached the fundamental underlying problem. The level at which a problem settles cannot be decided on logical grounds alone.
The existence of a discrepancy representing a wicked problem can be explained in numerous ways. The choice of explanation determines the nature of the problem s resolution. In other words, a wicked problem can be explained in many ways with each explanation serving the interests of a particular group of stakeholders.
The planner has no right to be wrong (planners are liable for the consequences of the actions they generate). Those who work with wicked problems (town planners, for example) are paid to design and implement solutions. However, as we have seen, solutions to wicked problems cause other unforeseen issues. Planners and problem solvers are invariably held responsible for the unanticipated consequences of their solutions.
The earliest blog posts were essentially pointers to ‘good stuff’ out there. Here’s such a pointer from last fall from my former partners and still good friends Paul Carroll and Chunka Mui. They’ve found two very worthwhile reads that I otherwise would have missed.
If you’re interested in the deep challenges of thinking strategically you would also do well to start paying attention to the work that Paul and Chunka are doing at The Devil’s Advocate Group. It’s a continuation of the work they did in creating Billion Dollar Lessons, which I reviewed here.
From time to time, I recommend Meadows’ article, Places to Intervene in a System. It’s a succinct summary of her long experience at finding leverage points for effective change in complex human and organizational systems. In this slim volume, she provides an accessible and understandable introduction to systems thinking in general and "Places to Intervene" takes its place as a penultimate chapter.
We spend our days surrounded by and embedded in multiple, complex, interacting systems: transportation, education, health care, our employers, our customers, our suppliers. The systems we encounter are those that by design and by adaptation have found stable ways to operate and to survive.
Thinking in Systems explains why systems work the way they do and why our intuitions about them are so often wrong. Feedback loops drive system behavior. Positive feedback loops give us population explosions and Internet billionaires; negative feedback loops let us steer cars or regulate the temperature in our offices. Unrecognized feedback loops and lag times between action and response lead to most of the surprises we encounter with systems in the real world. What Meadows does here is make that all understandable and accessible with apt examples and clear explanations.