Espoused vs. Actual Decision Making was DT/furnace)

Richard Karash
Junior Member
Posts: 14
Joined: Fri Mar 29, 2002 3:39 am

Espoused vs. Actual Decision Making was DT/furnace)

Post by Richard Karash » Thu Nov 18, 1999 10:55 am

I think its a well proven fact that people often act at variance
with their stated descriptions of how they act and make decisions.

My work involves system dynamics and organizational learning. Heres
a very short piece Ive learned from the org learning side that
relates to this area:

Chris Argyris talks about peoples "espoused" theories for how they
act vs. their "theory in use" (how they actually act).

There are often big differences. A manager might say, "I value every
opinion" but then act to shut down others every day. Some of this is
unconscious; most of the time people are not even aware of the
differences... And, often are not even aware of their actions.

The causal chain is Thinking --> Actions --> Results.

Theres power in starting with data on results (or actions taken) and
working backwards, asking "What actions led to this result? What
thinking led to this action?" This produces surprises, illuminating
actual decision rationales or "theory in use." A related tool is
probing thinking about thinking (Argyris well known "Left-hand
column" exercise).

Argyris has very effective tools for bringing out the differences and
illuminating the theories in use.

In my work, I am trying not just to make a good model, but to make
the whole things a learning benefit for the decision makers. Putting
stated decision rationales in the model and checking match vs. data
is a sound approach. It should help illuminate the theories in use.
For decision makers to become aware of their theories in use -- this
can be a powerful learning moment.

Thereafter, they can be responsible for their decision making.
Without the ability to see the differences (tools and sensitivity)...
They cant be responsible, even if others try to hold them

-=- Rick

>Hines says, "I have noticed that its much easier to model after
>asking people how they really make decisions, than it is after simply thinking
>about either how they **ought** to make the decisions or how I **imagine** I
>might make the decision."
>Theres at least one more step worth considering. System participants bias
>their descriptions, too. After building a model of what the system
>says about decision-making, its worthwhile to compare model output with
>measured data.

Richard Karash ("Rick") | <>
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