More often than not, we find ourselves dealing with problems and
improvement opportunities at our workplaces. But equally interesting, not everyone looks into these
issues from a more statistically-sound perspective. The result is that inevitably, decisions sometimes are made based on opinions, desires, misinterpretation of facts, and "gut feeling". As quality practitioners and as process improvement champions, we should always look for factual data analysis that support decision making. One of the simplest approaches we can utilize to
tackle unresolved and/or unknown problems is the development of a process
improvement team (PIT) with the help of simple and yet powerful basic quality tools.
If your organization is currently facing issues that have yet to be resolved, you
may find the information on the Seven Traditional Quality Tools of great relevance.
The Seven Traditional Quality Tools are:
Stratification: (some authors replace this quality tool with Flowcharts): the simple act of
segregating data in a meaningful way so that the user can properly study the
data collected. This technique allows the analyst to group different data into
homogeneous stratums. Many quality practitioners use this
quality tool as the very first step in a process improvement team (PIT) approach to problem solving.
Check-sheet: basic document that offers the analyst with the
opportunity of checking the number of occurred events. Imagine that a count on the number of complaints an airline customer
representative needs to log per day must be performed. Although it sounds like a rather
simplistic tool, the data collected through the check sheet can be of valuable
insight by for example, serving as an input to other quality tools (such as the Histogram).
Scatter Diagram: a useful tool to understand the
relationship between two variables. Questions associated with Scatter Diagrams
are: what happens to X when Y increases or decreases? How strong is the
relationship between the two variables? What is this relationship telling the
analyst? And what is true or false in the relationship? Example: the hotter
it is outside the more water one drinks. Is the opposite also true? (More on Scatter Diagrams on this blog, please check the archive on the right hand side bar).
Histogram: this bar-type chart measures the frequency in
which events occur. It is a very valuable tool when the practitioner needs to
study how often a certain event occurs, and how the repetition of such events
behave within a certain period of time, in other words, it studies the
distribution of data over a period of time. Think about a study in which you
need to understand when your peak sales occur more often. It also is a great
visual tool for those who are not very familiar with statistical analysis.
Control Chart: this line graph shows the user how the data behave over a period of
time (often continuously). The user can set up rules to identify abnormal
behaviours (e.g. out of limits or seven points climbing or descending in a row) and
analyze the process as it happens over time. This is a powerful tool that can
predict issues in many processes.
Ishikawa Diagram: also called “Cause and Effect” or
“Fishbone” diagrams. This graphical representation of the relationship between
the symptom of the problem and its various possible causes is a great way of
discovering more about the root cause of an issue. It helps the user in digging
deeper and truly analyzing the root cause of the problem. (More on Ishikawa
diagrams on this blog, please check the archive on the right hand side bar).
Pareto Diagram: a bar-type chart that helps the user in
identifying the critical few versus the trivial many (Pareto’s 80/20 rule).
Many times managers focus their energy on things that are problematic per se
but not of great impact at the bottom line (bottom line as not only financial
performance but also employee engagement, safety, and so on). The Pareto
diagram helps the analyst in focusing on what really matters.
The eZSigma Group has recently launched a course on the Seven Quality
Tools. Please visit the link below to learn more about this learning
opportunity.
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