Although I’ve
written about performance metrics in past postings, I want to expand upon what
I’ve previously written. Selection of
the right performance metrics is critical to the success of any organization,
no matter whether they produce products or deliver a service. There are three key objectives of performance
metrics as follows:
1.
First and foremost, performance metrics should stimulate the
right behaviors. Sounds simple enough, but unless the desired
behaviors are well thought out, it is very easy to go astray. For example, if your organization produces
products and uses the performance metric operator
efficiency, ask yourself what behaviors should you expect to see? Translated, efficiency deals with minimizing
waste and maximizing the capabilities of your human resources. From a Cost Accounting perspective, it is believed
that improving operator efficiency has a direct impact on the profit of a
company. So, if we increase operator efficiency,
then we should see a corresponding increase in profits……right?
The problem with operator efficiency as a performance metric is
that it doesn’t consider the impact on the total system. The behavior we typically see when using
efficiency as a metric is this. Because all of the process steps are encouraged
to “run to their maximum capacity” the total system is flooded with excess work-in-process
inventory which extends cycle times which negatively impacts on-time delivery. So do you think efficiency stimulates the
right behavior? The answer is, no it
doesn’t. But having said that, what if
we only measured the efficiency of the system constraint? What would happen then? We would indeed maximize the throughput of
the process because throughput is controlled by the system constraint. What about the non-constraint process
steps? Because we don’t want them to
outpace the constraint, they must effectively “slow-down” so as not to fill the
system with excess WIP. Their
efficiencies would deteriorate, but the profit of the overall system would
improve dramatically. This is directly
in contrast to what traditional cost accounting teaches. That is, as operator efficiency increases,
profits rise accordingly.
2.
Performance metrics should reinforce and support the overall
goals and objectives of the company. If the goal of any for profit company is to
make money now and in the future, then the selection of performance metrics
must directly support and enhance this goal.
3.
The measures should be able to asses, evaluate and provide
feedback as to the status of people departments, products, and the total
company. The right behaviors of people and
departments are critical to the achievement of the overall goal of the company,
but many times the metrics chosen encourage and stimulate the opposite
behaviors……just as I demonstrated with operator efficiency above. The fact is efficiency drives local
optimization rather than optimization of the total system.
When selecting
performance metrics, there must be criteria for selection of the correct ones…..right? Well, in fact, there are at least six key
criteria to consider when selecting effective performance metrics. Let’s look at these criteria and relate each
one to operator efficiency.
1.
The metric must be objective,
precisely defined, measurable and quantifiable.
There can be no ambiguity at all with the people or departments being
measured. For example, operator
efficiency is objective, well defined, measurable and quantifiable, so it would
seem to satisfy this first criteria…..right?
2.
The metric must be well within
the control of the people or departments being measured. For
example, when considering the metric operator efficiency, it clearly is within
the control of the people or department being measured, so it would seem that
it does satisfy this criteria…..right?
3.
The metric must be translatable
to everyone within the organization. That is, each operator, supervisor,
manager and engineer must understand how his or her actions impact the metric. For example, efficiency is definitely
translatable to everyone, so again, efficiency passes this litmus test….right?
4.
The metric must exist as a
hierarchy so that every level of the organization knows precisely how their
work is tied to and supports the goal and critical success factors of the
company. For example, if one of the critical success factors was “maximum
throughput” and efficiency was selected as one of the lower level metrics, what
would happen? That is, if it takes 5
minutes to process a part in an individual work station, then the maximum
amount of time for the part to be finished should be no longer than 5 minutes. And if you could somehow produce a part in 4
minutes, the efficiency of that work station could be above 100%. That would be great….right? But if the higher level metric was maximum
system throughput, would running each individual work station maximize system throughput
or would it “clog” the system with excess WIP and cause less than optimum
throughput? For this reason, efficiency
is not a good metric because it doesn’t have a positive effect on the system.
5.
The metric should be
challenging, yet attainable. Suppose
efficiency was selected as a metric. Is
maximum efficiency challenging and attainable?
The answer is no, if you want to optimize system throughput. Because of step 3 in Goldratt’s 5 focusing
steps (i.e. subordinate everything to the system constraint), non-constraints
can never be permitted to run as fast as they can or they will choke the system
with excessive WIP. The excessive WIP
extends cycle times, ties up cash unnecessarily, and all of the other reasons already
mentioned.
6.
The metric should lend
themselves to trend and statistical analysis and, as such, should not be “yes
or no” in terms of compliance. We could
definitely trend and perform statistical analyses on efficiency.
The point of
this posting is to demonstrate why it is so important to select the “right”
performance metrics. The success of
organizations is tied directly to the selection of metrics that drive optimal
behaviors. As Goldratt himself said, “Show
me how you measure me and I’ll show you how I’ll behave.” Take a look at the metrics your company is
using and see if they pass the metrics litmus test. If they don’t, then you have a problem.
Bob
Sproull