REPLY Definition of root cause (SD6838)

[SDMAIL Jack Harich]

Posted by  Jack Harich <register at thwink.org>


SDMAIL Bill Braun wrote:
> Posted by  Bill Braun <bbraun at hlthsys.com>
>
> Jack writes, "Thanks. I don't understand what you mean by "pump 
> different content through it." What is "it"? What is "pump"? What is 
> "different content"? Also, I don't know what you mean by "the 
> structure is just fine."
>
> I interpret the model to mean that the dynamic hypothesis is 
> understood to be a function of exogenous parameters, not current 
> policies. 
Hi Bill,

Have you read the Dueling Loops paper? I noticed that you are not using 
any of the key phrases from the paper. Perhaps to save time you looked 
only at the diagram titled The Leverage Points of the Dueling Loops at 
the bottom of 
http://www.thwink.org/sustain/articles/005/DuelingLoops_Paper.htm. I can 
understand. We are all pressed for time.

On page 2 the paper says "There are two feedback loops in the human 
system that, in the large, affect citizen’s lives more than anything 
else. They are the loops that politicians use to gain supporters." Thus 
the human system is the model boundary. Sterman defines exogenous 
variables as arising "from outside the boundary of the model." (page 95) 
Thus all the variables in the model are endogenous.

Perhaps you feel that constants or lookup tables are automatically 
exogenous?

Regardless of the terms used, the key distinction that Sterman tries to 
make is that one should not omit important variables from the feedback 
influence of a model, if they are significantly affected by that feedback.

If you read the paper, you will see that the structure of the model is a 
reflection of current policies, ones that are extremely common in 
political systems of all kinds. Something is wrong in the current 
policies. The model is an attempt to find out what.

> By "just fine" I meant that the policies explicit in the model are 
> taken to be OK as is, no changes are required or needed. 
I'm lost here. "The policies explicit in the model" are NOT okay. That's 
the problem!

The purpose of serious problem solving models is ultimately to allow 
decision makers to change their existing policies. Looking at popular 
high quality models, like Forrester's urban decay model, the Club of 
Rome's World3 model, and Jack Homer's and CDC's diabetes epidemic model, 
we see that in all cases the problems are caused by bad policies. (A bad 
policy includes no policy.) The purpose of these models is to help us 
discover good policies. Not perfect policies, just ones good enough to 
solve the problem.

> By different content, I meant that all that is required to achieve 
> desired results is to change the values of the exogenous parameters 
> (which you identified as as the high leverage points), which in the 
> context of the model, means that people only need to autonomously 
> behave better than they are at present (their behavior is an 
> independent variable).
>   
If you read the full length version of the paper, figure 18 on page 17 
shows a subsystem that allows decision makers to "push" on the high 
leverage point of "general ability to detect political deception." The 
model in The Leverage Points of the Dueling Loops diagram is not the 
final model. Figure 18 shows how this subsystem has been added, so that 
the amount of Ability to Detect Deception is no longer a constant. It is 
now a stock, with multiple inputs that affect its growth rate. The stock 
is now in the path of model feedback loops.

Thus the model never implies that "people only need to autonomously 
behave better." It shows that in the normal course of political system 
behavior, people's ability to detect political deception goes up and 
down. The key point, emphasized in the caption to figure 18, is that 
"This simple subsystem imitates how society reacts when corruption rises 
above an unwritten, culturally defined critical point. This reaction is 
part of a cycle that never ends, because presently there is no formal, 
enduring mechanism in governments to keep Ability to Detect Deception 
permanently high."

I apologize that the full length paper is so long, at 29 pages. But I've 
found that a shorter presentation leaves out crucial details, and does 
not allow key subjects to be covered in the depth they require.


> Alternately stated, I take Jack to be saying that (based on my 
> understanding of the model, and I may be wrong) the structure of the 
> problem focus is OK as is, and the root cause is defined as exogenous 
> parameters (having been identified as the high leverage points).
>
> I am clarifying, not arguing, my point. I am still curious about my 
> interpretation of exogenous parameters as high leverage points. I can 
> think of any number of situations where it would be easy/convenient to 
> say, "behave better" and the problem would be solved.
>
> Jack inquires into my post on root cause and exogenous variables. 
> After some thought, I think my question is generic.
>
> To what degree ought we think of an exogenous parameter as a root 
> cause and/or as a high leverage variable, and correspondingly 
> construct models based on that?
>
> If such thinking is sound, why build models in the first place? I 
> think I would be left with advising a client, "Bill Braun, who is not 
> under your control or influence, is behaving badly. If you can get him 
> to stop (paradox intended), your problems are solved."
>   
Thanks for explaining. I feel your frustration. There are many business 
and social problems that we'd like to see solved. In some cases we can 
see a solution what would seem to work. But when we "push" on the system 
to implement a preferred solution, little happens. We can usually see 
this will be the case, so we don't bother to try.

Here's where I'm coming from. Every problem solver(s) has some small 
amount of force they can exert on a system, in an attempt to change it 
to preferred behavior. If their force is applied to a low leverage 
point, solution failure is likely, because the force is too small. (The 
force is the amount of effort to prepare and implement a change.) But if 
they push on a point with high enough leverage, they will prevail. In 
difficult problems, the HLPs are hard to find. This is made much easier 
by finding the root causes first.

That's why we build simulation models: to soar past the constraints of 
intuition.

Or, if one discovers a variable is exogenous and should be part of a 
model's feedback loops, then it needs to become endogenous.

SDMAIL John Gunkler wrote:
> Posted by  "John Gunkler" <jgunkler at sprintmail.com>
>
> Fred Nickols writes, about the example (from
> http://www.systems-thinking.org/rca/rootca.htm) of the plant manager 
> who finds oil on the floor,
>
> "I'll wager that aficionados of root cause analysis (RCA) would 
> indicate that the plant manager needed to go at least one or two steps 
> further and determine why he was pressing everyone to be so cost 
> conscious."
>
> And I, being one such aficionado, might reply much in the light of 
> Gene Bellinger's suggestion at the bottom of the cited webpage:  to 
> wit, that maybe we should not look for root causes but, instead, for 
> "actionable causes" that "I can act on that will provide long term 
> relief from the symptoms, without causing more problems that I have to 
> deal with tomorrow."
>   
Yes. That's why I define the characteristics of a root cause as:
(1) It is clearly a major cause of the symptoms.
(2) It has no productive deeper cause.
(3) It can be resolved. Sometimes it’s useful to include unchangeable 
root causes in
your model for greater understanding. These have only the first two 
characteristics.

The word "productive" was added as a result of this thread. The word 
allows you to stop asking why at some appropriate point in root cause 
analysis. Otherwise you may find yourself digging to China.

"Actionable cause" is a nice phrase. This idea is incorporated in my "It 
can be resolved."

Now then, what happens if it's too expensive to resolve directly? It 
remains a root cause. You then have to resolve it indirectly. This can 
be done by seeing that the root cause variable affects, and then 
introducing forces that negate that influence.

> In that light, if the manager can simply change his own behavior 
> without further analysis, and if that change in behavior resolves the 
> problem without creating more, then no further analysis is warranted.  
> I notice, too, that simply being put under pressure to reduce costs 
> should not be enough to prevent the plant manager from changing -- 
> after all, if his bonus depended upon cost savings, he has just 
> discovered that certain actions led to the opposite result and is 
> fairly confident that a change in his behavior would lead to a higher 
> bonus.
>
> If, on the other hand, the pressure on the manager was of a different 
> sort that prevented him from simply changing the way he pursued cost 
> savings (such as being held to very short-term accountabilities), then 
> further analysis might be useful and, indeed, another deeper cause and 
> corrective action might be preferable.
>   
Yes. A fine educational example.

Thanks for this,

Jack
Posted by  Jack Harich <register at thwink.org>
posting date  Tue, 25 Mar 2008 18:53:17 -0400