The Psychology of Quality and More
How to measure
When taking measures, there are several approaches which can help to ensure that the right data is selected and collected in a way that helps with the subsequent analysis.
When investigating a problem, a single general measurement is often insufficient and can cloak useful information. By measuring the situation in a number of different ways (stratifying or segmenting it), one or more 'cuts' may reveal new information that will allow specific corrective action to be identified, as in Fig. 1.
Common measurements used in stratifying data include:
Fig. 1. Significant stratification in a Scatter Diagram
For example, a customer support organization counts the number of calls about each product, and find that a heater product is receiving a very high call rate. They have identified a problem, but cannot find out why without making more measurements. They therefore stratify the calls by taking intrusive measures, asking customers questions about suspected causes, such as the type of problem (failure, cutout, etc.), customer (age, occupation, etc.), how they are using the product (indoors/outdoors, hours of usage per day, etc.) and so on.
In order to know exactly how a set of measured items behaves, they must all be measured, such as when determining the distribution of the values of a batch of electrical resistors. However, this is seldom possible, for several possible reasons:
In such cases, a limited sample may be measured, from which the characteristics of all other items (the population) are deduced. In order to be able to do this reliably, there are two factors that must be taken into account:
Fig. 2. Using a sufficient sample size
Most tool descriptions identify the size of samples that need to be taken to ensure a representative sample, so knowledge of statistics is not essential, although a deeper understanding in this area (or access to someone with this knowledge) can be very useful.
For more information on sampling calculations, go Google!
When actually measuring data, it is important that the accuracy of the data is maintained through careful measurement and accurate instruments. This is best achieved through the use of a clearly defined data collection process.
It is usually useful to collect not only the data that is to be used, but also information about the situation in which it was collected. This may include:
Where the data is to be collected by hand, then a Check Sheet may be designed to ease both the recording and interpretation of data.
A variable often overlooked when recording data is the person doing the job. The best way of reducing any potential variation from this source is through training. This need not be complex or long, but it should be enough for the person to understand how to use any instruments, operate any machines and reliably record all requisite data. It can help if they know how the information is likely to be used afterwards, as a fear that the information may be used to their disadvantage can tempt them to tamper with it.
And the big