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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

Prescriptive process monitoring: Quo vadis?

Kateryna Kubrak¹, Fredrik Milani¹, Alexander Nolte^1,2

¹Institute of Computer Science, University of Tartu, Tartu, Estonia.

Peerj. Computer Science

|October 20, 2022

Summary

This study reviews prescriptive process monitoring methods, which suggest real-time interventions to improve business processes. It proposes a framework to categorize these methods and identifies future research directions for enhanced applicability.

Keywords:

Business process Prescriptive process monitoring Process optimization

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Area of Science:

Business Process Management
Operations Research
Data Science

Background:

Prescriptive process monitoring aims to optimize business operations through runtime interventions.
Existing methods offer various approaches to prevent negative outcomes and improve process performance.

Purpose of the Study:

To systematically review and categorize existing prescriptive process monitoring methods.
To propose a framework for characterizing these methods based on key attributes.
To identify challenges and future research directions in the field.

Main Methods:

Systematic literature review (SLR) of prescriptive process monitoring methods.
Development of a framework for method characterization.
Analysis of identified literature based on the proposed framework.

Main Results:

The SLR provides a structured overview of current prescriptive process monitoring techniques.
A framework is proposed, categorizing methods by performance objectives, metrics, intervention types, modeling, data, and policies.
Key challenges and areas for future research are identified.

Conclusions:

The field requires further validation of methods in real-world scenarios.
Intervention types need expansion beyond temporal and cost factors.
Policy design should incorporate causality and second-order effects for greater effectiveness.