Dr. Russel Ackoff spoke often of how we were prepared to
deal with the real world in school. We were usually presented with a “case
study.” We would then busy ourselves in reading and developing ideas around the
case study. We would then turn in or present the case to the teacher for a
grade. Ackoff noted that in the real world, problems do not come in the form a
case study, but as a “mess.” Part of our journey is understanding the mess and
developing a statement of the challenge. Laurence J. Peter warns us in the quote:
“Some
problems are so complex that you have to be highly intelligent and well
informed just to be undecided about them.”
The challenge before most of us trying to make improvements
is the complexity of environment in which we are working. Systems that are not
closed but open systems that are dynamic accompanied by influences for which we
may or may not be aware. Ramo (2016) draws the distinction between complicated
and complex systems:
Complicated mechanisms
can be designed, predicted, and controlled. Jet engines, artificial hearts, and
your calculator are complicated in this sense. They may contain billions of
interacting parts, but they can be laid out and repeatedly, predictably made
and used. They don’t change. Complex systems, by contrast, can’t be so
precisely engineered. They are hard to fully control. Human immunology is
complex in this sense. The World Wide Web is complex.
Complicated systems have the property of being closed
systems, while complex systems operate in an open environment that is very
dynamic. Many of us working to make improvements in our organizations can
relate readily to the idea of complex system. Into this fray, many of us are
given problem solving methods that are linear. We are presented with the idea
that if we follow the method, we will be led to a solution. Dr. Jeff Conklin
presented some research around the so-called “Waterfall” method commonly used
to develop software. Figure 1 describes this method:
Figure 1: Waterfall Method of Problem Solving
In this method, we are to gather data, analyze the data,
formulate a solution and implement the solution. How does the real world react
to this linear path? Conklin then presented the experience of one designer
following the method. Figure 2 describes how the perception of the designer
vacillates from problem to solution over the course of using this method:
Figure 2: Waterfall Method with One Designer
Conklin referred to this vacillation as a “wicked journey.”
If you have worked on an improvement effort of any complexity you can
appreciate this journey. One day filled with hope and a solution, the next day,
frustrated by an unintended consequence of your change, you are now faced with
the challenge to adapt to the new circumstances you are facing. More work to do!
Life would be good if we could handle complex challenges by
ourselves (the lone designer) as in Figure 2. Complex challenges usually require
subject matter knowledge of other people. What happens as we add other people?
Do they share our perceptions of the problem and solution? Figure 3 describes
the journey with two designers:
Figure 3: Waterfall Method with Two Designers
From Figure 3, we can readily see the perceptions between
the two designers track at times and are very different at other times. For
improvement teams, we usually have 3-5 people on a team. Conklin refers to this
addition of people as “social complexity.” Personality intelligence tells us
that people are very different. Their perceptions of the same events, data,
etc. may be very different given how they learn and their subject matter
knowledge.
We had an improvement team in an international tech company
that used a method called Understanding,
Develop Changes, Test Changes and Implement Changes (UDTI). Within each of the defined phases the
Plan-Do-Study-Act (PDSA) cycles were utilized. The team referred to their
journey as “wicked.” Figure 4 describes this team’s journey:
Figure 4: Using UDTI with PDSA Cycles to Make an Improvement
In following the PDSA cycles in the figure, you can imagine
the frustration of the team in PDSA 12 when a rush to implementation led to
failure and required a visit back to the “Understand” phase. After this
learning, testing was always done before implementation. The six cycles of
implementation at the end were the spread of known changes to other regional
groups.
What is the downside of the vacillation between the stages
of the linear method? When an improvement team discovers an unintended
consequence of a test, they must go back to a prior stage of the linear model,
many see this as a failure. Experienced
people with improvement efforts understand that when addressing complex
challenges, learning and unlearning are natural parts of the journey. However,
the same organization that used the UDTI method had one team in Europe that
eliminated all the failed PDSA cycles of the improvement journey, forcing a
perfect match to the method. Unfortunately, this sort of practice, while
helping self-esteem has nothing to do with the science of improvement.
People who use such linear methods often discuss the
vacillation of the hopeful path. One of my colleagues is looking for the first
project of any complexity that follows such a method. So far, we have not found
one. Margaret Wheatley once commented on why the myth of success with linear
methods continues: “After the fact, people usually report their journey by the
prescribed method, thereby reinforcing their use.” Dr. Jeff Conklin and the
UDTI team have given us some insight into use of such methods as they encounter
a world of complexity. Hopefully, we won’t be surprised when the real world
does not cooperate.
In Part 2, we will examine some methods based on the science
of improvement. The importance of questions in addressing complex systems and
help in addressing the social consequences of technical change.
References:
1.
Conklin, Jeff, Wicked Problems and Social
Complexity (2008); This paper is Chapter 1 of Dialogue Mapping: Building Shared
Understanding of Wicked Problems, by Jeff Conklin, Ph.D., Wiley, October 2005.
For more information see the CogNexus Institute website http://www.cognexus.org. © 2001-2008
CogNexus Institute. Rev. Oct 2008.
2.
Ramo, Joshua Cooper. The Seventh Sense: Power,
Fortune, and Survival in the Age of Networks (p. 137). Little, Brown and
Company.
3.
Leadership and the New Science, Margaret
Wheatley, Berrett Koehler Publishers, San Francisco, 1992. Note: In searching
this book, we were not able to locate the quote from Wheatley. In communication
with her staff, we were told to attribute. The reader may find this reference
useful. Find Part 2 here
Acknowledgment
Jesse Trevino and Jane Norman offered comments to make this
more readable. Many thanks. Ron Moen added suggestions for including Deming’s
concepts of enumerative and analytics studies. Bruce Boles, Jonathan Merrill
and Dave Hearn reviewed. Many thanks to all for the help!
