The last post got way too long, and I wanted to get it out there. But of course, there are afterthoughts.
At a level higher than simple process chaos, overburden hits the entire organization when perceived demand is significantly greater than perceived capacity.
As I noted in the earlier post, segregating what should be routine from the true exceptions goes a long way, especially when there is work to continuously improve execution of routine things. This results in less capacity being used to process routine, and therefore, more capacity available to handle the true emergent stuff.
The next phase is to repeat the process, step by step, on the exceptions. Identify what makes them exceptions. Is there another process that can be isolated and segregated? Can you move something from “exception” to “routine” in some way?
Then look at what is left.
About 20 years ago, Philip Agre wrote a seminal PhD Dissertation at M.I.T. called “The Dynamic Structures of Everyday Life.” If you can find it, read it. This work was a major contributor to turning the science of symbolic artificial intelligence on its head. One of his conclusions was that almost everything we do is routine, and we do non-routine things in routine ways.
This thinking applies to complex, one-of-a-kind process situations. What “experience” brings to the table is knowing what things, that we know how to do routinely must be done; in what order; to gain control of the uncontrolled; and get the desired outcome.
In our heads, this is much messier than we want to believe it is. Fundamentally what we do is to try something we believe will have a certain effect, then see what effect it actually has. If the effect is the one we predicted, then we are one step closer to control and the stage is set for the next action; if not then we learn what did not work, gain a bit more understanding and try something else.
This is also how we build that thing called “experience” step by step, stretching our understanding, moving what we do not know into what we do. We do this as individuals, but it is only a truly exceptional organization that can do it as an institution. Learning is a process of prediction, testing and comparison.
The objective in these situations is to move an unknown, uncontrolled situation gradually toward familiar ground and make it into something routine.
Steven Spear quoted a health care worker that summed it up pretty well: “Air goes in and out, blood goes round and round. If either of those is not happening, we have a problem.” And in the most extreme medical emergency, the first steps are always to stabilize vital signs so that the patient will live long enough for the caregivers to understand the problem and develop countermeasures.
This is still, however, a customized sequence of tasks that should, themselves, be routine. Only the macro level varies. The more that can be done to stabilize the delivery of treatment to the patient, the less harried people will feel. They should not worry about the small things so they can pay attention to the big things.
The weak points in a complex system are the interconnections. People are not sure who should do, or has done, what. There are repeated transfers from one caregiver to another, often with far less than complete information – leaving it to the next caregiver to assess the situation all over again. Every time this happens presents an opportunity to overlook or misinterpret something that is already known.
By working very hard on execution of the things that should be routine, that much more mental capacity is made available to care for the patients. This means attacking ambiguity where ever it is found.