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Trying To Do Our Very Best
We now
know how some of the mismeasure, frustration, and sometimes despair arises as
we try to manage that relatively recent invention; the serial process – the
manufacturing process. We recognize,
often intuitively, that we are trying to optimize according to some
reductionist/local optima approach but that we are actually bound by the
process dependency and variation of our system. But what does it mean to optimize? Surely this means to do our very best. In fact, for everyone to do their very
best.
Doing
our best is such an important concept in process improvement that we will
deal with it in detail in this section.
Therefore, this section is really about people. Let’s start once again with our simple
departmentalize model, this is most likely to reflect the reality of most
people and most systems at the start of an improvement process.
 Now ask yourself;
where are the most likely areas for conflict in this system. Are they within departments or between
departments? Sure, we seem to
understand frustration within our own departments, and between our own
actions and our own measures, but conflict seems to be reserved most often
for the interface between departments.
Within
a department it seems that we have sufficient control to try and achieve the
results that we desire, we might call this a span of control or a sphere of
influence (1). At the interface
between departments the control passes from one group or manager to another,
we lose direct control and another takes it up. We could call these interfaces transfer
points (2). Let’s add this to our
diagram.
 Still, just
passing control can’t be reason enough for conflict. So why is there conflict?
The
response might be something like; “well we certainly try to do our best, but
some of those other people in that other department, well, we’re not so sure
about them.”
Oops, I
think that it is time for a reality check.
Reality Check
Try one
day to ask a diverse group of people; people from more than one department or
people from more than one organization, if there is anyone present in that
group who leaves home in the morning with the intent of not doing a good
job. Of course no one would admit to
such a thing openly. But watch the look
of indignation on peoples’ faces that you should have even have asked such a
question. This is the proof that
people do intend to do a good job.
Sure, everyone knows someone else who doesn’t want to do a good job,
but no matter how many times you repeat this experiment you won’t find that
someone. You will be left with the inescapable
conclusion that indeed everyone does want to do a good job. In fact, their best.
We need
to add, of course, that whether everyone wants to do a good job and whether
everyone actually does a good job is another matter. Whether someone doesn’t do a good job might
not be a matter of competence for instance, it might be a matter of
alignment, or focus, or one of a number of other things.
So I
think we can safely say that everyone
wants to do their best, according to their current view of what is best. And maybe those words; “according to their
current view of what is best” are more telling than we suspect. Nevertheless, it would appear that the
conflict that occurs at transfer points is not due to one group or manager
doing well and another group or manager doing less well; it is because both
groups are doing their very best according to their map of reality.
Conflict arises not because people are failing to do their best, but
because everyone is doing their best.
It is
the map of reality that we need to look at in order to understand why there
is conflict. But, first, let’s have a
look at some pre-suppositions that are useful to know.
Some Pre-Suppositions
It is
useful to keep in mind some pre-suppositions about human behavior when
considering improvement initiatives (3, 4).
In any improvement initiative we are going to come up against
situations where it appears that the initiative is not being
supported. When that happens we need
to run these pre-suppositions past our minds as a test against the situation.
(1)
All behavior has positive intent.
(2)
People make the best
decision they can at the time.
(3)
People respond to their map of reality and not reality itself.
(4)
There is no failure, only feedback.
This
will help us to reframe the problem so as to see it from the viewpoint of the
people who appear not to support the initiative. Their behavior will be positive from their
viewpoint, even if it doesn’t’ appear positive from our viewpoint or the
viewpoint of the system. If we can
develop an understanding of their viewpoint and thus their map of reality
then we are in a much better position to do something about it. Always ensure that there is adequate
feedback. Management who perceive a
problem but fail to provide the necessary feedback to staff rob the staff of
the opportunity for self-improvement.
Feedback
Let’s expand on the concept of feedback for a
moment. Margaret Wheatley has
characterized feedback in the following terms (5). Feedback is self-generated, an individual
or system notices whatever they determine is important for them and they
ignore everything else. Feedback
depends upon the context, the critical information is being generated right
now, failing to notice the "now," or staying stuck in past
assumptions, is very dangerous.
Feedback changes; what an individual or system chooses to notice will
change depending on the past, the present, and the future. New and surprising information can get in,
the boundaries are permeable. Finally,
feedback is life-sustaining, it provides essential information about how to
maintain one's existence, it also indicates when adaptation and growth are
necessary.
So now we can see, for instance, why measurements cause frustration. They provide a formal but usually localized
feedback. Let’s show what we mean.
 Measurements provide a formal but localized feedback
loop that may directly contradict our informal feedback loop – what we see
and what we know is happening but which is not measured. However, there is a strong risk of a
“closed circuit” here. If our map of
reality is strongly reductionist/local optima, and so too are our
measurements, and thus also our formal feedback; then it is quite possible
that we won’t notice any disjoint between the formal and informal measures
until it is quite explicit. We won’t
notice until it is blindingly obvious and even then, maybe not. But people outside of the system will
notice the disjoint however because they are not bound to the same
assumptions. To break this closed
circuit we need to reframe the map of reality first, and then the
measurements.
Maps Of Reality
People
make the best decision they can at the time according to their map of
reality. For most people their map of
reality in their work environment is a reductionist/local optima one.
How do
we know this? Think back to your
response to the first diagram of our simple system when it was presented in
the introduction. It looked like this.
That this
diagram didn’t produce howls of concern indicates that for most people it is a
pretty fair representation of reality.
This is a model of the reductionist/local optima approach. In fact we are quite used to seeing our
world subdivided like this.
If our
own map of reality was different, then many people would have been searching
initially for something maybe more like the following view.
 This is a
systemic/global optimum view. This is not
to say that such a view or map isn’t possible, it’s just that for the
majority of us, given our experience and dare I say it – our training, this
isn’t the first thing that enters our mind.
If we
can be sure that people strive to do their very best within their department,
within their group, if we can be sure that workers concentrate equally on
everything everywhere within their area, and that managers concentrate on
everything in all of the departments under their control, then perhaps there
is a very real danger that we only know how to locally optimize? Perhaps there is a very real danger that we
can’t see or think in systemic/global optimum terms? Let’s investigate this thought a little
further.
Maybe Global Optimization Is Contrary To Human Nature?
Is
global optimization contrary to human nature?
Well, let’s test it. Let’s
return to our departmentalized version of our simple system, and let’s add
some responsibility or spans of control to it. Our basic level is that of a foreman, as we
might expect in a traditionally structured manufacturing organization. However, we could call them team leaders,
charge nurses, or whatever else is relevant.
As shown earlier there is a transfer point between each span of
control.
 Now consider,
for example, someone whose span of control, or sphere of influence, extends
beyond one department or section or company.
It’s more likely that person will see “a bigger picture” than other
people. That person’s local
optimization across their span of control is far more likely to approach the
global optimization of the system. The
larger the span the closer the potential for the local optimization to
approach the global optimization.
Let’s
draw this concept using our simple model of a system. Let’s draw in two supervisors where we
previously had 4 foremen. The 4
foremen report to two supervisors. The
number of transfer points drops as the span of responsibility grows.
 Cynics would
point out that “most bottlenecks are at the top”. However, this is unfair. People at the top usually can’t help but
see the global issues of the system.
So let’s modify our diagram to reflect this reality. Now we have one manager whose span of
control replaces the two supervisors who report to him.
 Actually we need
to modify this view the system as it is in reality – a system with one
weakest link. A system that looks more
like this.
 So, let’s
repeat. The people at the top usually
can’t help but to see the systemic/global optimum view.
So we
need to ask where, then, are they being let down?
Are they
let down by their subordinates? I
don’t think so. Well then, are they
being let down by their performance measurement system? In part, the answer to that must be
yes. In fact, we have seen already
that this is the case. We are trying
to understand the global issues while relying upon using local performance
measures – legacy performance measures from our reductionist/local optima
approach of the last several centuries past.
We can see the whole system and then we insist on breaking it apart
into sub-units again. Let’s draw what
we mean.
 Imagine the
subordinates’ point of view then; there should be no reason why they too,
cannot form a systemic view except for the imposition of a legacy measurement
system from the top down. After all;”
Tell me how you will measure me, and I will tell you how I will behave. If you measure me in an illogical way… do
not complain about illogical behavior (6).”
So if you measure me locally then that is how I will behave.
So
global optimization isn’t contrary to human nature, we naturally form a
systemic/global optimum view when our span of control allows us, but we are
hampered by the trap of reductionist/local optima performance measures. We need to apply our new measurement
process to the whole system. Let’s
draw this.
 We need to feed
back into the system the global outputs of the system in order to know what
actions to take locally. However, local
feedback into local actions was only part of the problem and so global
feedback into local actions can only be a part of the solution. Replacing the legacy reductionist/local
optima performance measures with our new systemic/global optimum measurements
– our fundamental measurements – is necessary but it is not sufficient. After all we have already deduced a
consistent and logical measurement system, so why then haven’t we applied it? Let’s have a look. Let’s look for the solution to the
remainder of this problem.
If Global Optimization Is So Natural – Why Aren’t We All Doing It?
In the
absence of a measurement system to support a systemic/global optimum view,
most people in a process will locally optimize – its human nature – the
belief that if everyone does his best, the net result will be the sum of all
of those efforts. In fact; “Companies who believe they have avoided the
pitfalls of performance measurement systems because they do not have a formal
system are in the worst case situation.
Everyone in the organization is defining what a good job is from their
local viewpoint of what good performance is locally (7).”
Previously we learnt to define; the system, the
goal, the necessary conditions, the fundamental operational measures, and the
role of the constraint. But what we
haven’t done yet is learn how to focus
on the constraints – and we need to do that in order to determine what a good
job is locally – this is the other part of the solution to the
problem. It is insufficient to
evaluate local actions in term of global feedback unless we know what it
means to do our best locally for the system as a whole. And as we have already learnt, “The key to
know what to do locally is the realization of the role the system constraints
are playing (8).” It is an absence of knowledge of a
focusing system that hampers us at present from implementing a
systemic/global optimum approach.
We will examine how to focus on the constraints in the next page on
the process of change.
In fact, once we know the role of the constraints,
and we can operate under a systemic/global optimum view, then we will be able
to remove the conflict that occurs at the transfer points between spans of
control. People being people will
still do their best, but now they will know for every area what that “best”
is for the system as a whole, rather than for their area under the former
assumption of an isolated and independent part. Again we will deal with this in detail in
the next page on process of change.
But did
you note something more important?
In our
previous example, although the people at the top formed a systemic/global
optimum view, nothing really changed – they really just applied their local
view to a broader canvas. That brings
us to a very important point, “all change – both individual and
organizational – requires a change in the meaning that the system is enacting
(9).” So, in effect, it is only a
change in meaning, a change in world view, a change in our map of reality. The people at the top didn’t abandon local
optimization. It’s just that their
span of control or sphere of influence grew sufficiently their “local” was
everyone else’s “global.”
Now, if
the people at the top can do that; why can’t anyone and everyone else. We have to replace the current map of reality
that says “I am my department,” to something like “I am a significant part of
the whole process.” Where everyone has
been let down in the past from making this transition was firstly the absence
of a systemic approach to measurements.
We have that now. All that
remains then is just to know where the constraint is in order to evaluate our
local actions according to these measures.
If There Is Conflict – There Is An Erroneous Assumption!
There can be no conflict in nature. "There must be an erroneous assumption
that we make about reality that causes a conflict to exist (10)." If we have conflict at transfer points then
there is an erroneous assumption somewhere (a common but erroneous map of
reality).
What is
the erroneous assumption? If we cast our
minds back to our simple model as it was first presented in the measurements
section we highlighted that the workflow wasn’t at all independent as we
might have first assumed. In fact, we
know that the workflow contains multiple dependencies and also variability. To some extent we might try to decouple the
dependencies by buffers of work-in-process – buffers everywhere. But we already know the cost of that. Lead times become too long and there always
seems to be some more urgent work that finds its way around those carefully
built buffers – and sitting in those buffers takes so long that lot’s of work
becomes urgent in any case. However,
the dependency is just as great within individual departments as it is between
different departments, so this can’t be the cause of conflict at transfer
points. Dependency doesn’t seem to be
the source of our erroneous assumption.
Maybe
it is variability then. We only need
to look at the success of total quality management (TQM) and total productive
maintenance (TPM) to see that reducing variability – both quality and process
variability – makes plants run much smoother, and produce much better
products too. However I have worked in
world-class precision manufacturing plants with TPM, ISO 9000, and ISO 14000,
and the conflict is still there and it starts right about where one foreman’s
area finishes and another’s starts.
So, enticing though the thought is; variability does not seem to be
the source of our erroneous assumption either.
In
fact, to understand the source of our erroneous assumption, and therefore
conflict, we must wait for the next section on process of change. But it was necessary here to clarify that
even though serial processes are characterized by dependency and variation,
these are not the cause of our conflict.
So, if leaders naturally see the broader system-wide
picture, why then do most of them, still resort to using local measures? The answer is that there hasn’t been until
recently a coherent methodology that would allow people to use global measures. We saw that coherent methodology as a
summary to the last section. Let’s
repeat it here.
(1)
Define the system.
(2)
Define the goal of the system.
(3)
Define the necessary conditions.
(4)
Define the fundamental measurements.
(5)
Define the role
of the constraint(s).
If you like, we have seen how most of these pieces
fall into place. Sure, just-in-time is
a system-wide approach and has been around for quite a while. But its applicability has been largely limited
to large scale repetitive processing (autos and consumer electronics). It certainly didn’t address the
measurements issue. Contribution
margin analysis did address the measurements issue and has been around for
quite a while too, but it doesn’t seek to identify the role of the
constraints. So we seem to have always
had bits and pieces, but not all the right bits and pieces in the same place
at the same time.
In fact, we have yet to address here the last step
of the methodology – the role of the constraints. We will do that in the next section –
process of change. If leaders have a
system-wide view and have sufficient systemic support from the fundamental
measurements and awareness of the role of the constraints, then what is there
to stop us from reframing the role of managers – and everyone else – from a
reductionist/local optima approach to a systemic/global optimum
approach? I think that the answer is
there is nothing to stop this whatsoever.
Summary
                   Global
optimization is natural; it isn’t contrary to human nature. Once a person’s span of control is allowed
to cover most of the system they can’t help but have a global perspective of
the system. In fact their “local” is
the system’s “global” perspective.
However, to date such a global perspective hasn’t been supported by a
systemic approach to measurements and therefore reductionist measures have
been imposed on subordinates.
Moreover, a failure to recognize the role of constraints within the
system has limited our ability to capitalize on the systemic perspectives
that we have been able to gain.
Many of
the pieces of the jigsaw are in place.
We need still to examine the process of change, and we still need to
answer the dilemma why people doing their very best results in conflict. This shouldn’t be so. The existence of conflict suggests we have
some as yet erroneous assumptions to resolve.
Let’s
then look at the process of change and try to resolve these issues.
References
(1) Dettmer, H. W., (1997) Goldratt’s Theory of
Constraints: a systems approach to continuous improvement. ASQC Quality Press, pp 67-69.
(2) Smith, D., (2000) The measurement nightmare: how
the theory of constraints can resolve conflicting strategies, policies, and
measures. St Lucie Press/APICS series
on constraint management, pg 137.
(3) Shearman, L., (2000) Why can't people be more careful. Safeguard Magazine, November.
(4) O’Connor, J., and Seymor, J., (1990) Introducing
neuro-linguistic programming: psychological skills for understanding and
influencing people. Thorsons, pg 114.
(5) Wheatley, M. J., and Kellner-Rogers, M., (1999) What
Do We Measure and Why? Questions About The Uses of Measurement. Journal for Strategic Performance
Measurement, June.
(6) Goldratt, E. M. (1990) The haystack syndrome:
sifting information out of the data ocean.
North River Press, pg 145.
(7) Smith, D., (2000) The measurement nightmare: how
the theory of constraints can resolve conflicting strategies, policies, and
measures. St Lucie Press/APICS series
on constraint management, pg x.
(8) Goldratt, E. M., In: Cox, J. F, and Spencer, M. S.
(1998) The constraints management handbook.
St Lucie Press, pg x.
(9) Wheatley, M.
J., and Kellner-Rogers, M., (1996) A simpler way. Berrett-Koehler, pg 100.
(10) Goldratt, E. M., (1999) How to change an
organization. Video JCI‑11,
Goldratt Institute.
This Webpage Copyright © 2003-2009
by Dr K. J. Youngman
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