BPR-L digest 186

Forwarded to: imail[CSG-L@VMD.CSO.UIUC.EDU]
          cc:
Comments by: Paul George@Eng@Columbus
Comments:

[Paul George 940926 10:30]

An interesting simulation that might be recastable in formal PCT terms. To my
limited understanding it seems to map to the reorganization phenomenon.

Comments?
   -------------------------- [Original Message] -------------------------

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                            BPR-L Digest 186

Topics covered in this issue include:

  1) Dynamic Computer Model of Resistance to Change
        by PeterVS1@aol.com

----------------------------------------------------------------------

Topic No. 1

Date: Sat, 24 Sep 94 22:16:06 EDT
From: PeterVS1@aol.com
To: BPR-L@duticai.twi.tudelft.nl
Subject: Dynamic Computer Model of Resistance to Change
Message-ID: <9409242216.tn52083@aol.com>

Resistance to Change
A STELLA Model of a Complex System

by Peter von Stackelberg

One of the most difficult problems organizations face is dealing with change.
In the rapidly changing, highly competitive business environment of the
coming century, the ability to rapidly and effortlessly change will
distinguish the winners from the losers. Many businesses will founder,
however, because they find themselves unable to constantly adapt to the
environment within which they exist.

Resistance to change is an on-going problem. At both the individual and
organizational level, resistance to change impairs concerted efforts to
improve performance.

The relationship between individual and organizational resistance to change
is important. An organization is a complex system of relationships between
people, leadership, technologies and work processes. From this interaction
emerges organizational behavior, culture and performance.

These emergent properties and behaviors are tightly linked in two directions
to the lower level interactions.

Organizational resistance to change is an emergent property. Individual
resistance to change can give rise to organizational resistance. A
self-reinforcing loop of increasing resistance can develop as individuals
create a environment in which resistance to change is the norm. That
environment in turn encourages increased resistance to change among
individual employees. The self-reinforcing nature of this loop can be
tremendously powerful, defeating repeated attempts to break out of it.

Understanding the dynamics of resistance to change is critical to turning
around individual and organizational resistance to change. The creation of
adaptive organizations requires a greater understanding of the systems
dynamics involved. The model of resistance to change described here was
developed in order to help better understand those dynamics.

Basic Assumptions of the Model

The logic and basic assumptions used to develop this model of resistance to
change are:
1. Humans build mental maps which are, in effect, their reality.
2. Changing a mental map causes a negative feeling best described as
discomfort or pain.
3. The greater the pain, the greater the resistance to making mental map
changes.
4. The greater the resistance, the fewer the number of mental map changes.
5. Humans experience dissonance when their mental maps are not synchronized
with their external environment.
6. Changes in the external environment increase the dissonance.
7. Increasing dissonance reduces resistance to changing the mental map.
8. Changing a mental map decreases dissonance as the internal and external
realities are brought into closer synchronization.

The STELLA Model

This model was developed using STELLA. This Macintosh-based software is used
to create and run dynamic systems models using a graphical user interface.

Conditions Under Which the Model Was Run

The model was run using three different conditions:
* No change (other than the initial change event) occurs.
* A constant rate of change occurs.
* Change occurs as a series of crises.

Results of "No Change" Run

When the model was run so that no changes other than the initial change event
occurred, there was a rapid fluctuation at the start of the run associated
with that change event. However, the system quickly stabilized into an
equilibrium in which resistance rose and remained high. Pain associated with
mental map changes showed an almost instantaneous jump at the start of the
run, then dropped rapidly to remain low during the balance of the run. Mental
map changes dropped rapidly from a high at the beginning of the run and
remained low throughout the balance of the run.

Results of "Constant Change" Run

When the rate of change in the system was constant, the dynamics were
different from the run in which no change occurred. Initially the system
experienced a number of fluctuations but within a short period of time
settled into a stable pattern in which resistance to change fell even as the
total number of change events (but not the rate of change) increased. What is
particularly interesting about this run is that both pain and dissonance
increase, although they rise relatively slowly in comparison to the number of
change events.

Results of "Periodic Crisis" Run

The behavior of this system shows some very interesting behavior when it
undergoes change as a series of periodic crises interspersed with periods of
no change. After the fluctuations associated with the initial change event,
resistance to change drops and pain and dissonance rises as crisis after
crisis hits. The increments by which resistance drops and pain and dissonance
rises become smaller, however, even though the magnitude of each crisis
remains the same. This indicates that the system is adjusting to the crises
and is seeking an equilibrium.

However, the system is not able to absorb the shocks of crisis after crisis
indefinitely. What the graph shows is a broadening oscillation that appears
to become chaotic.

An attempt was made to determine if this behavior was in fact chaotic. To do
this, the initial conditions were altered for several runs. Specifically, the
magnitude of a single crisis that stressed the system was adjusted to see how
the system would react.

Interpretations

In spite of the limitations identified, this model does lead to a number of
useful insights into the nature of resistance to change.

Resistance to change within organizations tends to bring to the surface
considerable emotion. Those who resist change are often labeled as operating
from a different agenda, as stubborn or ill-informed, as lacking in
understanding, or in other negative, value-laden terms. One conclusion that
can be drawn from this model is that resistance to change is an inherent part
of the system's attempt to maintain a certain level of stability. As shown by
the run in which no change occurs, the "preferred" state of the system is to
come to an fixed state. There is a tendency for people within organizations
to attempt to halt external change so that their "internal" state does not
need to be changed.

Many organizations seem to lurch from crisis to crisis. The runs in which the
system was hit with periodic crises showed that at the onset of each crisis,
resistance dropped sharply and mental map changes jumped sharply. Then, after
the crisis passes, resistance levels out again and mental map changes stop
until the next crisis occurs. The model's reaction to crisis seems to be
supported by events within our organizations - crisis threatens, dramatic
action is taken and then everything settles back to "normal" until the next
crisis occurs. The conclusion one can draw is that crisis is needed to reduce
resistance to change and bring about significant changes in mental maps. The
impact of crisis after crisis is seen in the model's movement into chaotic
behavior as the stresses build in the system.

Another reaction to a constantly changing environment is to engage in
constant change. When this approach was modeled, resistance to change
decreased and mental map changes increased as change occurred at a constant
rate. From the organizational point of view, this approach is probably the
most conducive to long-term organizational health.

Conclusion

This model appears to be a realistic, though simplified, representation of
the psychology of resistance to change. The use of a dynamic model gives a
number of insights that would otherwise not be possible, the most dramatic of
which is the transition that this system makes from fixed to periodic to
chaotic behavior as stress is added to the system. This model points to the
underlying complexity and non-linear behavior of the systems associated with
change. This complexity and non-linearity needs to be addressed if efficient
and effective change efforts are to take place within organizations.

NOTE: This is an a summary of an article on organizational and individual
resistance to change. If you are interested in a full copy of the article
(including graphs from the model runs), please contact me with your mailing
address.

If you would like a copy of the resistance to change model that can be run
with the STELLA modelling language on the Macintosh, please send me a 3.5
inch diskette formatted for a Macintosh computer. You will need STELLA and a
Macintosh to run the model.

My address:

Peter von Stackelberg
Applied Futures, Inc.
1733 Woodstead Court, Suite 101
The Woodlands, TX
U.S.A. 77380

------------------------------

End of BPR-L Digest 186
***********************

<[Bill Leach 940928.17:43 EST(EDT)]

STELLA Model

Interesting and possibly even relevent however, I personally know nothing
of the STELLA Modeling language nor the structure or assumptions made in
the construction of the particular model.

While Peter's write-up sounds nice and "clean" it does not "sound" to me
at all like science. My impression is that he obtained some of the
results that he expected and concluded that his model "was right" and
then drew additional conclusing about people and organizations of people
from model results.

He even "opens" with "wisdom" that is filled with "buzz-words" that
convey no specific meaning.

He then makes an assertion with which I happen to believe that I agree
but as far as I know has no meaningful definition much less a proof
(resistance to change is a problem).

Unless I missed it, he did not in any way describe how he modeled any of
his "humans".

His "Basic Assumptions of the Model" help little in understanding in my
opinion but if one substitutes the word "conflict" for "discomfort",
"pain" and "dissonance", this fellow may be inadvertently stumbling upon
some PCT.

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