Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction

• URL: http://arxiv.org/abs/2105.07111v1
• Date: Sat, 15 May 2021 01:19:04 GMT
• Title: Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
• Authors: Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas, Marcello La Rosa
• Abstract summary: 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 random forest models to estimate the causal effect of triggering a time-reducing intervention.
• Score: 0.7837881800517111
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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