1 code implementation • 13 Jul 2023 • Mahmoud Shoush, Marlon Dumas
This paper argues that, in the presence of resource constraints, a key dilemma in the field of prescriptive process monitoring is to trigger interventions based not only on predictions of their necessity, timeliness, or effect but also on the uncertainty of these predictions and the level of resource utilization.
1 code implementation • 7 Mar 2023 • Zahra Dasht Bozorgi, Marlon Dumas, Marcello La Rosa, Artem Polyvyanyy, Mahmoud Shoush, Irene Teinemaa
Increasing the success rate of a process, i. e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal.
1 code implementation • 7 Dec 2022 • Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring methods seek to improve the performance of a process by selectively triggering interventions at runtime (e. g., offering a discount to a customer) to increase the probability of a desired case outcome (e. g., a customer making a purchase).
1 code implementation • 15 Jun 2022 • Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process's performance.
1 code implementation • 7 Sep 2021 • Mahmoud Shoush, Marlon Dumas
This paper proposes a prescriptive process monitoring technique that triggers interventions to optimize a cost function under fixed resource constraints.