Error cause analysis

The root cause analysis is one of the most important instruments of corporate management . It includes the recording of errors , their causes and the statistical evaluation of this data, which is followed by an assessment and derived measures to reduce errors (and reduce error costs ).

Basic procedure

One investigates which cause (s) had errors. The grouping of causes of errors can be useful. Then one looks for measures to reduce the number of errors and the error costs (e.g. process improvements, changed methodologies or changed use of technology or materials).

With a sufficiently large database, experience shows that the Pareto principle applies , according to which 20% of the causes of errors cause 80% of the errors. If these causes of errors are counteracted and the frequency of these (originally) 80% of errors is significantly reduced, positive company effects result. These usually not only include lower measurable error costs, but also an improved position on the market, employee motivation, etc.

The root cause analysis is an iterative process, so it does not stop with the decision on measures (see also Continuous Improvement Process ).

Typical errors and risks in the error-cause analysis

The cause of the error should be assessed in a suitable form by all those involved in order to achieve validity and acceptance of the interpretation and the derived measures. Last but not least, this is necessary for the collection of valid data.
The record of causes of errors should not be set up or operated with the aim of finding the culprit, but aiming at process improvement. Leading experts in quality management estimate that the ratio between system errors (or process errors, i.e. to be represented by management) to employee errors is 85 to 15 ( Joseph M. Juran ) or 94 to 6 ( William E. Deming since around the beginning of the nineties ), this approach seems appropriate. If this objective is not communicated openly, the validity of the data will suffer. B. more data are corrupted.