Identification and classification of Human Error in process model development

Abstract

Process models capture important corporate know-how for an effective knowledge management (KM). However, many process models do not match with corporate reality and therefore cannot serve the intended purpose. Human Error is a major source for these inconsistencies that might hinder process implementation and maintenance as well as continuous improvement efforts. The approach presented in this paper accounts for a more active participation of employees in order to further increase the economical benefit of KM. To this purpose, a human error analysis in process modeling was conducted. The results derived from data of 64 subjects show that errors of omission and erroneous execution on an activity level are considerably higher for novices than for subjects with theoretical knowledge and experienced modelers. However, it can be concluded that even for experienced modelers complex modeling scenarios are prone to reasoning fallacies and thus represent a possible source for model inconsistencies in corporate practice.