Problem definition: Data errors in business processes can be a source for exceptions and hamper business outcomes. Relevance: The paper proposes a method for analyzing data inaccuracy issues already at process design time, in order to support process designers by identifying process parts where data errors might remain unrecognized, so decisions could be taken based on inaccurate data. Methodology: The paper follows design science, developing a method as an artifact. The conceptual basis is the notion of data inaccuracy awareness – the ability to tell whether potential discrepancies between real and IS values may exist. Results: The method was implemented on top of a Petri net modeling tool and validated in a case study performed in a large manufacturing company of safety–critical systems. Managerial implications: Anticipating consequences of data inaccuracy already during process design can help avoiding them at runtime.

问题定义：业务流程中的数据错误可能是异常的来源并阻碍业务成果。相关性：本文提出了一种在流程设计时分析数据不准确问题的方法，以便通过识别可能无法识别数据错误的流程部分来支持流程设计人员，从而可以根据不准确的数据做出决策。方法论：论文遵循设计科学，开发一种方法作为人工制品。概念基础是数据不准确意识的概念——判断真实值和 IS 值之间是否可能存在潜在差异的能力。结果：该方法在 Petri 网建模工具之上实施，并在一家大型安全关键系统制造公司进行的案例研究中得到验证。管理意义：