Companies that frequently use robotic process automation often encounter difficulties in maintaining their RPA portfolio. To address these problems and reduce time spent investigating erratic behavior of RPA bots, developers can benefit from exploring methods from process sciences and applying them to RPA. After a selection process, we examine how variability and deviations impact robotic process automation. Indicators of statistical dispersion are chosen to assess variability and analyze RPA bot behavior. We evaluate the performance of RPA bots on 12 processes, using statistical dispersion as a measure. The results provide evidence that variability is an undesirable form of erratic behavior in RPA, as it strongly correlates with the success rate of the bots. Importantly, the results also show that outliers do not affect the success rate of RPA bots. This research suggests that variable analysis can help describe the behavior of RPA bots and assist developers in addressing erratic behavior. Additionally, by detecting variability, we can more effectively handle exceptions in RPA.

经常使用机器人流程自动化的公司在维护 RPA 产品组合时经常会遇到困难。为了解决这些问题并减少花在调查 RPA 机器人不稳定行为上的时间，开发人员可以从探索过程科学的方法并将其应用于 RPA 中受益。在选择过程之后，我们检查可变性和偏差如何影响机器人过程自动化。选择统计分散指标来评估变异性并分析 RPA 机器人行为。我们使用统计离散度作为衡量标准，评估 RPA 机器人在 12 个流程上的性能。结果证明，可变性是 RPA 中一种不受欢迎的不稳定行为形式，因为它与机器人的成功率密切相关。重要的是，结果还表明异常值不会影响 RPA 机器人的成功率。这项研究表明，变量分析可以帮助描述 RPA 机器人的行为，并帮助开发人员解决不稳定的行为。此外，通过检测变异性，我们可以更有效地处理 RPA 中的异常情况。