Predictive Process Monitoring

Francescomarino, Chiara Di; Ghidini, Chiara

doi:10.1007/978-3-031-08848-3_10

Cited by 45 publications

(13 citation statements)

References 48 publications

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“…The PPM research pillar includes 22 surveys [71,72,116,141,154,157,160,167,207,211,216,222,247,256,273,275,281,286,290,297,316,318]. Similar to the surveys in the remaining event prediction pillar, the scope of the existing 22 surveys is limited.…”

Section: Related Surveysmentioning

confidence: 99%

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas

Benzin¹,

Rinderle-Ma²

2023

Preprint

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Event prediction is the ability of anticipating future events, i.e., future real-world occurrences, and aims to support the user in deciding on actions that change future events towards a desired state. An event prediction method learns the relation between features of past events and future events. It is applied to newly observed events to predict corresponding future events that are evaluated with respect to the user's desired future state. If the predicted future events do not comply with this state, actions are taken towards achieving desirable future states. Evidently, event prediction is valuable in many application domains such as business and natural disasters.The diversity of application domains results in a diverse range of methods that are scattered across various research areas which, in turn, use different terminology for event prediction methods. Consequently, sharing methods and knowledge for developing future event prediction methods is restricted. To facilitate knowledge sharing on account of a comprehensive classification, integration, and assessment of event prediction methods, we combine taxonomies and take a systems perspective to integrate event prediction methods into a single system, elicit requirements and assess existing work with respect to the requirements. Based on the assessment, we identify open challenges and discuss future research directions.

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Section: Related Surveysmentioning

confidence: 99%

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas

Benzin¹,

Rinderle-Ma²

2023

Preprint

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“…Process mining in RPA processes is not very typical at the moment, however, it can be applied to automated processes for RPA (Egger et al, 2020;Průcha, 2021), where duration rates, bottlenecks and deviations can be identified. With advanced methods of process mining such as predictive process monitoring, enhancing the process data with data from other systems, root-cause analysis and online monitoring, it is possible to gain more valuable insights about the behavior of RPA processes including information why an RPA bot fails, whether the bot fails when executing a particular variant and whether RPA bots can keep up with the queue of cases (Burattin, 2022;Di Francescomarino and Ghidini, 2022;Fahland, 2022;Van Houdt and Martin, 2021). The use of statistical methods in process mining represents the core of process mining.…”

Section: Variability and Spc In Process Miningmentioning

confidence: 99%

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Průcha

2023

SSRN Journal

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“…For instance, organizational mining techniques were developed to focus on resources employed within the process [53]. Moreover, these additional data attributes also play a fundamental role in decision mining [18,47] (see [17]) and predictive process monitoring [19] (see [20]).…”

Section: Additional Data Attributesmentioning

confidence: 99%

Foundations of Process Event Data

Weerdt

Wynn

2022

Lecture Notes in Business Information Processing

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Process event data is a fundamental building block for process mining as event logs portray the execution trails of business processes from which knowledge and insights can be extracted. In this Chapter, we discuss the core structure of event logs, in particular the three main requirements in the form of the presence of case IDs, activity labels, and timestamps. Moreover, we introduce fundamental concepts of event log processing and preparation, including data sources, extraction, correlation and abstraction techniques. The chapter is concluded with an imperative section on data quality, arguably the most important determinant of process mining project success.

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Predictive Process Monitoring

Cited by 45 publications

References 48 publications

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Foundations of Process Event Data

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