Quality Tool – Histograms-

<p><strong>Variation</strong></p>

<p>We are all aware that variation is everywhere. It is inevitable in the output of any process &ndash; manufacturing, service, or administrative.</p>

<p>We also know it is impossible to keep all factors, in a constant state, all the time. This is one of the key challenges for a quality improvement team. More specifically, to reduce variability.</p>

<p>A Histogram is a graphic summary of variation in a set of data. The pictorial nature of the histogram enables us to see patterns that are difficult to see in a simple table of numbers. Histograms enable quality improvement teams to diagnose problems with a x-ray vision.</p>

<p>At a macro level, there are three important characteristics of a histogram:</p>

<ul>
<li>The centre</li>
<li>The width</li>
<li>The shape.</li>
</ul>

<p>These three characteristics also point quality improvement teams to the COPQ resident in a process.</p>

<p><strong>Histograms and Limits of Acceptability</strong></p>

<p><img alt="" src="http://sureshlulla.com/blog/wp-content/uploads/2020/10/Quality-Capsule_-Inside-Article-Diagram-016.png" /></p>

<p><strong>Potential Pitfalls</strong></p>

<p>There are three important pitfalls that a quality improvement team should be aware of when interpreting histograms:</p>

<ul>
<li>Before stating your conclusions from the analysis of the histogram, make sure the data is representative of typical and current conditions in the process.</li>
<li>Do not draw conclusions based on a small sample. As a rule of thumb, use a sample of 40 for each histogram you wish to construct.</li>
<li>Remember that your interpretation of the histogram is only a hypothesis that requires additional analysis and direct observations of the process in question.</li>
</ul>

<p><strong>Insight</strong></p>

<p>A histogram is usually a bell shaped curve. What we end up seeing is a result of sorting the good from the bad. Examples: truncated histograms; bi-polar histograms; etc.</p>

<p>Look carefully for the phantom bell shaped histogram. Establish the Cost Of Poor Quality (COPQ) that you are unknowingly burdened with. Refer&nbsp;<a href="http://sureshlulla.com/2020/07/29/how-to-assess-cost-of-poor-quality/">Quality Capsule #4</a></p>

<p><strong>Next</strong></p>

<p>In my next edu-blog, on Wednesday 28 October, I will introduce Scatter Diagrams. This is an effective quality tool for bi-variate analysis. It quantifies a cause-effect relationship..</p>