Root cause analysis

The root cause analysis is one of the fundamental tools of corporate management. It includes the detection of faults, their causes and the statistical analysis of this data, in an assessment and derived measures for error is ( cost ) reduction connect.

Basic Procedure

By assigning errors to specific causes and the grouping of the causes of errors, measures to reduce the number of errors and thus the error cost can be derived.

With a sufficiently large data base experience, the Pareto principle, according to which 80 % of the errors on 20% of the causes of error are based applies. If this error causes technique or material used counteracted by process improvements, changes in methodologies or altered and the frequency of these (originally ) 80 % of the errors thus significantly reduced, resulting positive company effects. These include not only lower measurable error costs are generally, but also improved market position, employee motivation etc.

The root cause analysis is an iterative process that does not stop with the adoption of measures on (see a continuous improvement process ).

Typical errors and risks of root cause analysis

  • The cause of the error evaluation should happen in an appropriate manner by all stakeholders in order to achieve validity and acceptance of the interpretation and the derived measures. This is necessary for the acquisition of valid data does not last.
  • The cause of error detection should not be located or operated with the aim to find culprit, but aimed at process improvement. As leading experts of quality management estimate that the ratio between system failures (or process failures, ie the responsibility of the management), employee errors at 85 to 15 (Joseph M. Juran ) or 94 to 6 ( William E. Deming since about the beginning of the nineties ) is, this approach seems obviously appropriate. If these objectives are not communicated openly, the validity of the data will suffer because, for example, more data might be corrupted.
  • Quality management tool
  • Fault Management