Reducing cycle time is a recurrent concern in the field of business process management. Depending on the process, various interventions may be triggered to reduce the cycle time of a case, for example, using a faster shipping service in an order-to-delivery process or giving a phone call to a customer to obtain missing information rather than waiting passively. Each of these interventions comes with a cost. This paper tackles the problem of determining if and when to trigger a time-reducing intervention in a way that maximizes the total net gain. The paper proposes a prescriptive process monitoring method that uses orthogonal random forest models to estimate the causal effect of triggering a time-reducing intervention for each ongoing case of a process. Based on this causal effect estimate, the method triggers interventions according to a user-defined policy. The method is evaluated on two real-life logs.
翻译:缩短周期时间是业务流程管理领域一个经常性的问题,根据程序,可以触发各种干预措施,以减少案件的周期时间,例如,在交付到交付过程中使用更快的航运服务,或打电话请客户获取缺失的信息,而不是被动地等待。每种干预措施都有成本。本文件处理确定是否和何时触发时间减少干预措施以最大限度地实现总净收益的方式减少干预措施的问题。本文件建议采用规范流程监测方法,使用随机森林模型来估计为每个进行中的流程案件触发时间减少干预措施的因果关系。根据这一因果估计,该方法根据用户定义的政策触发干预措施。该方法以两种实际生活记录为基础进行评估。