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Experience Driven Process Improvemen

机译：经验驱动的流程改进

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摘要

The importance of process improvement and the role that best prac tice reference models play in the achievement of process improvement are both well recognized. Best practice reference models are generally created by experts in the domain who are external to the organization. However, best practice can also be implicitly derived from the work practices of actual workers within the organisation, especially when there is opportunity for variance within the work, i.e. there may be different approaches to achieve the same process goal. In this paper, we propose to support process improvement intrinsically by utilizing the experiences and knowledge of business process users to inform and improve the current practices. The main challenge in this regard is identifying the "best" previous practices, which are often based on multiple criteria. To this end, we propose a method based on the skyline operator, which is applied on criteria relevant data derived from business process execution logs. We will demon strate that the proposed method is capable to generate meaningful recommenda tions from large data sets in an efficient way, thereby effectively facilitating organizational learning and inherent process improvement.
机译：众所周知，过程改进的重要性以及最佳实践参考模型在过程改进中所扮演的角色。最佳做法参考模型通常由组织外部的领域的专家创建。但是，最佳实践也可以从组织内实际工人的工作实践中隐含地得出，尤其是当工作中存在出现差异的机会时，即可能有不同的方法来实现相同的过程目标。在本文中，我们建议通过利用业务流程用户的经验和知识来本质上支持流程改进，以告知和改进当前的实践。在这方面的主要挑战是确定“最佳”的先前实践，这些实践通常基于多个标准。为此，我们提出了一种基于天际线运算符的方法，该方法适用于从业务流程执行日志导出的标准相关数据。我们将证明，所提出的方法能够以有效的方式从大型数据集中生成有意义的建议，从而有效地促进组织学习和内在流程的改进。

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