So our edited take on the well know phrase above adds a little bit of detail to what normally reads…the tough get going… They get going to find some sort of control over their situation. The reason for this is that we equate control with understanding, and at the heart of tough situations is a lack of understanding, a sense of not knowing quite what to do. The actual saying does not say what to get going to, yet for some convoluted reason we tend to get going toward control. And control in organizations typically means using some sort of highly practical and data driven methodology. Things like Six Sigma, Lean Manufacturing, some version of TQM or any number of policies or systems designed to control things. The problem is that these methodologies and systems only create a certain level of control and do very little to create understanding, let alone control over the key element of any of these systems….. the people that make them work. What would happen if, when the tough got going, they looked for understanding rather than assuming it came with control.
There is one basic flaw to every one of the methodologies like Six Sigma and there have been many of these types of methodologies (remember Taylorism). That flaw is that they create the thinking that people operate from the same causality as nature and machines. This is flaw of logic, not an ethical or moral flaw, although the consequences of this flaw may create ethical and moral atrocities. Virtually all systems thinking based methodologies create this logical flaw in thinking.
Nature and machines operate from a causality called formative. Formative causality means that something ‘behaves’ based on its inherent design properties. The seed of an oak tree produces an oak tree, not a willow tree and a clock tells time, not your future. The formative causality of nature is magnitudes more complex than machines but it is still formative. People as well, from a biological perspective, physically grow to become people by this same causality (although there are even some questions about this now), but from a behavioral perspective they operate from two different types of causality:
Rational causality is simply behavior caused by individual choice and transformative causality is behavior caused by interaction between people where that interaction causes the behavior of those involved (often unpredictable behavior).
Methodologies such as Six Sigma function on the basis of formative causality and do what they are designed to do when done well. The problem is we take what they can do too far and assume they can control the behavior of people. And when the going gets tough we want that control, so we ramp up the expectations of what things like Six Sigma can do and follow our flaw of logic to one of two common end points. Those being there is something wrong with the system we are using (so let’s find something better than Six Sigma – I’m sure there is one being developed right now), or more commonly, there is something wrong with the people using the system.
If you decouple control from understanding you will use things like Six Sigma to create a system that can be controlled by formative causality, and be very clear what that is, typically the machines or work flow to be used. This is the control part. Then you will go and talk to people, interact with them to try and understand the rational causality that may be driving their behavior and you will stay open to the transformative causality that may create behavior you could not have predicted. This is the understanding part. When we think and act in this way we have realistic expectations of the methodologies we are using. We also enhance our accessibility to the possible options that may arise in our interactions with the people charged with making the system work. And if done knowing that all of formative, rational and transformative causality are at play, you will not feel like you are in control to the extent you might like to feel. And that is a much more accurate picture of reality than what any systems thinking methodology typically leads us to believe.
So when the going gets tough and we toughies get going, let’s try getting going to both control and understanding. Use systems thinking methodologies as they should be and then go interact with people to move forward together. And just keep in mind; interacting together is not a humanistic, nice or even good thing to do. It is the logical thing to do.
An interesting perspective on a phenomena I had observed but not hitherto rationalized. I would be interested to know who the author is and what academic sources support this theory.
Hello David… thanks for your comment and interest. The main influence for me regarding this post and perspective is the work of Ralph Stacey and colleagues at the Universtiy of Hertfordshire, UK. Of course we all put our own spin on things. Here is a link to their blog which contains further information and posts – http://complexityandmanagement.wordpress.com/ This work challenges much of the dominant thinking about how organizations operate and I have found it very helpful in the work our organization does. Our web site is http://www.tmsamericas.wpengine.com
Thank you. I have Ralf Stacey’s book Complexity and Organizational Reality (but not yet read it in its entirety) and admire his work. I was interested to know the source in case other writers had come to the same conclusion.
It is useful to know the author of an article in case one wants to quote it. I have passed Tom’s article to colleagues some of whom share these ideas but for others it is not pursuasive. I guess it has a lot to do ones weltanschauung!
There is one point I wished to challenge and it was the point made about systems thinking based methodologies creating this logical flaw in thinking. I am no expert in systems thinking but from what I have read, I found nothing to suggest that they are based on thinking that people operate from the same causality as nature and machines. On the contrary, interaction between people (parts of the systems) is one of the tenets of systems thinking. Maybe it is in deriving the “methodologies” from an understanding of the properties of social systems that such mistakes are made.
Specifically to your question of the author of the post; it is Tom Gibbons – co managing director of TMS Americas.
Hello David, Tom here and I show up as tmsamericas when I comment here so all those ones have been mine.
I think you bring up an interesting point and the post represents my experience of course. For me one of the key elements of systems thinking methodologies is the requirement of a ‘system’ of some sort. These methodologies then require you to act on that system by being separate from it to analyze it and adjust it so the system will produce what it is designed to produce. At its simplest this is formative causality and works well with hard engineering and the technical parts of Lean or Six Sigma for instance. Systems methodologies that include the people element, such as soft systems try and bring in the element of rational causality but typically end up in the same place, which is some element of control and predictability through design, or expanding the system to ever greater boundaries, what Stacey refers to as infinite regress.
If we try and incorporate transformative causality then the basic uncertainty of human interaction needs to be recognized. I do not see this in the systems methodologies that I have worked with over the years.
What I do find is that people working with systems methodologies and are doing great work are not really following the methodology as it is defined. There is constant improvisation and a recognition that much is being made up as things naturally emerge.
I would agree with you when you say ‘Maybe it is in deriving the “methodologies” from an understanding of the properties of social systems that such mistakes are made.’ I think the wonderful lesson from systems thinking, that relationship is critically important, is too often lost in the drive to find a methodology that operationalizes this in the form of some level of predictability and control.