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Identification and classification of Human Error in process model development

机译:过程模型开发中人为误差的识别与分类

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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.
机译:流程模型捕获有效的知识管理(km)的重要公司专业知识。但是,许多流程模型与企业现实不匹配,因此无法满足预期目的。人为错误是这些不一致的主要来源,可能会妨碍流程实施和维护以及持续改进努力。本文介绍的方法占员工的更积极参与,以进一步提高公元港的经济效益。为此目的,进行了过程建模中的人为误差分析。从64个科目的数据源的结果表明,对于活动水平的遗漏和错误执行的误差比具有理论知识和经验丰富的建模者的主题相当高。然而,可以得出结论,即使对于经验丰富的建模者来说,复杂的建模情景也容易造成谬误,从而代表企业实践中模型不一致的可能源。

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