Prescriptive Process Monitoring

Prescriptive process monitoring (PresPM) aims to optimize business processes by recommending timely interventions during execution to improve outcomes, such as preventing negative events or enhancing performance. Current research heavily utilizes reinforcement learning (RL) and causal inference (CI) to learn optimal intervention policies, often incorporating techniques like conformal prediction to manage prediction uncertainty and resource constraints. This field is significant for its potential to improve efficiency and effectiveness in various domains by automating decision-making within dynamic processes, with a current focus on rigorously evaluating and comparing different approaches using real-world datasets.