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Managing Quality Without Data: Don’t Try This At Home November 16, 2012

Posted by Tim Rodgers in Management & leadership, Quality.
Tags: , , ,

I know from experience how hard it is to measure, analyze, improve, and control quality in a high-stakes or high-volume production environment. There’s never enough data, and there’s constant pressure to draw conclusions and make decisions. What can we do to fix this defect? Did the process change work? When can we get the line running again? Sample sizes are usually too small to determine whether differences are statistically significant. One data point on a run chart will be taken as evidence that things are trending in the right direction. One defective product chosen at random “proves” that the whole batch is bad.

It’s worse when there’s no data at all, by which I mean the lack of a reliable source of objective, unfiltered, and unbiased data. You can’t run an effective quality system without links to the factory’s internal information systems: ERP, MRP, and other shop floor control and measurement systems. Data that’s automatically collected and reported in the course of normal production is less likely to be manipulated to make the situation look better (or worse) than it is. Data that’s manually collected is acceptable but less trustworthy, unless repeatability and reproducibility has already been established for operators.

There are too many people and constituencies with a vested interest when it comes to quality, people who want to believe that quality is always good, or at least good enough. It’s not fun for anyone when the production line is down or field failures are up. It’s easy to discount or ignore data as outliers when they don’t fit the desired story. There are also real situations where data may be suppressed or even fabricated. I think you’re better off with no data than with data that’s been compromised, but of course the better solution is to improve data integrity before making any changes to improve quality.



1. Fred Schenkelberg - November 16, 2012

Happens all too often, unfortunately, then they balk when the data doesn’t agree with what the results should be…

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