Let’s be honest about it. In many cases, collecting data (especially when done manually) can be tedious and viewed by some as a ‘pain in the backside’. This is understandable to a degree but imagine a situation where after spending 6 weeks collecting data we find out that it is inaccurate, it can’t be used and is in effect a waste of time. This issue can be due to the fact that we put no thought or effort into how we defined the metric in question.
E.g., a Food Processing Company was trying to baseline the Cleaning in Place (CIP) Process. In order to understand if here a difference in the CIP time by shift, product type, CIP types, etc. they set about collecting data over a 6 week timeline to answer some of these questions.
When the Project Team examined the data after the 6 weeks, they found there were some major differences by shift and the other aforementioned factors. Importantly though, this was not due to a difference in performance but by how the Metric was being measured.
Unfortunately, it was then back to the proverbial drawing board!
The morale of the story is to agree on a very specific Operational Definition for a metric, include it on the Data Collection Sheet and even go as far as to give the Data Collectors a fictional pre-completed data collection form to use as a guideline.
Submitted by Éamon Ó Béarra, SQT Lean Six Sigma tutor
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