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Traditionally, organizations focus on the mean or average
performance over a period of time and ignore the variation
in performance, whereas customers experience the variation.
What does it mean when a courier agency says "On an average,
we deliver goods on the same day as committed"? It probably
means that a good 50% of the customers get it earlier and
another 50% get it later than committed. It could +/-5 days
or +/-50 days - both give an average of zero delay (defect).
With that kind of variation around the mean (which in this
case is zero delay) it would be impractical to predict the
exact date of delivery. So, shouldn't organizations focus
on consistency and the drivers of consistency? Six Sigma is
all about eliminating variation and ensuring consistency,
so processes become predictable.
Six Sigma is methodical,
data based and uses a set of statistical tools towards identifying
and controlling the key causal variables of variation.
Sigma is a Greek word and
a statistical symbol for standard deviation, which is a measure
of variation. The number of 'Sigmas' (as in Six in Six Sigma)
is an indicator of process performance - a measure that doesn't
just address the performance averages, but also variation
in process performance. Every output that falls outside of
the acceptable level (specification limits) is a defect and
higher the Sigma level, lesser the defects.
So, we say, a Six Sigma process would produce
only 3.4 defects per million outputs from that process!
Six Sigma philosophy has also been used
by organizations to facilitate a culture change … towards
more objective and data based problem solving and decision
making.
Thus Six Sigma is much more than a mere
statistical tool for quality improvement - It's a way of doing
things in organizations that have deployed Six Sigma successfully.
The Six Sigma process follows, what is popularly
known as the DMAIC Model.
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