A Literature Review on Predictive Monitoring of Business Processes

Oleme läbi vaadanud mitmesuguseid ennetava jälgimise meetodeid äriprotsessides. Prognoositavate seirete eesmärk on aidata ettevõtetel oma eesmärke saavutada, aidata neil valida õige ärimudel, prognoosida tulemusi ja aega ning muuta äriprotsessid riskantsemaks. Antud väitekirjaga oleme hoolikalt kogunud ja üksikasjalikult läbi vaadanud selle väitekirja teemal oleva kirjanduse. Kirjandusuuringu tulemustest ja tähelepanekutest lähtuvalt oleme hoolikalt kavandanud ennetava jälgimisraamistiku. Raamistik on juhendiks ettevõtetele ja teadlastele, teadustöötajatele, kes uurivad selles valdkonnas ja ettevõtetele, kes soovivad neid tehnikaid oma valdkonnas rakendada.The goal of predictive monitoring is to help the business achieve their goals, help them take the right business path, predict outcomes, estimate delivery time, and make business processes risk aware. In this thesis, we have carefully collected and reviewed in detail all literature which falls in this process mining category. The objective of the thesis is to design a Predictive Monitoring Framework and classify the different predictive monitoring techniques. The framework acts as a guide for researchers and businesses. Researchers who are investigating in this field and businesses who want to apply these techniques in their respective field

Comparative Evaluation of Log-Based Process Performance Analysis Techniques

Käesolev magistritöö võrdleb erinevaid protsessikaeve uurimustöid ning liigitab neid järgnevate näitajate põhjal: aeg, kvaliteet ja ressursikasutus. Magistritöö põhjendab protsessikaeve meetodite kasutamist ja nende pakutavat lisandväärtust. Pakume ühiseid mõõtühikuid ja parameetreid, mida saab kasutada protsessi tulemuslikkuse analüüsimeetodite hindamiseks. Lisaks eelnevale kirjeldab lõputöö kirjanduses esinevaid tarkvaralahendusi ja algoritme.This paper gives a comparative overview of process mining performance studies and clusters them based on proposed metrics: time, quality and resources. This thesis provides an explanation of reasons for using process mining performance techniques and shows what value they can bring. We provide common metrics and unit of measurement that can be used to evaluate process performance analysis methods. Also, the paper describes tools and algorithms that have been implemented in the literature

Sistema para la Integración de procesos de Negocio basado en situaciones contextuales. Caso estudio: Admisión Universitaria

El objetivo de este documento es presentar un sistema de integración de procesos basado en información contextual, aplicado a un caso de estudio relacionado con la admisión a programas de posgrado en una universidad pública. Se propone una metodología basada en fases, que buscan principalmente la captura, análisis y agrupamiento de procesos a partir de comparación semántica y sintáctica. Los principales hallazgos al aplicar la metodología de integración validan que las situaciones contextuales presentes en el dominio de ejecución del proceso, puede afectar su rendimiento una vez se le apliquen algunas actualizaciones

Towards a Framework for Context Awareness Based on Textual Process Data: Case Study Insights

Context awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it becomes essential to employ relevant text analytics techniques to increase the awareness of process workers, which is important for process execution. The present paper addresses this demand by developing a framework for context awareness based on process executions-related textual data using a well-established layered BPM context model. This framework combines and maps various text analytics techniques to the layers of the context model, aiming to increase the context awareness of process workers and facilitate informed decision-making. The framework is applied in an IT ticket processing case study. The findings show that contextual information obtained using our framework enriches the awareness of process workers regarding the process instance urgency, complexity, and upcoming tasks and assists in making decisions in terms of these aspects

A generic framework for context-aware process performance analysis

\u3cp\u3eProcess mining combines model-based process analysis with data-driven analysis techniques. The role of process mining is to extract knowledge and gain insights from event logs. Most existing techniques focus on process discovery (the automated extraction of process models) and conformance checking (aligning observed and modeled behavior). Relatively little research has been performed on the analysis of business process performance. Cooperative business processes often exhibit a high degree of variability and depend on many factors. Finding root causes for inefficiencies such as delays and long waiting times in such flexible processes remains an interesting challenge. This paper introduces a novel approach to analyze key process performance indicators by considering the process context. A generic context-aware analysis framework is presented that analyzes performance characteristics from multiple perspectives. A statistical approach is then utilized to evaluate and find significant differences in the results. Insights obtained can be used for finding high-impact points for optimization, prediction, and monitoring. The practical relevance of the approach is shown in a case study using real-life data.\u3c/p\u3

A generic framework for context-aware process performance analysis

Process mining combines model-based process analysis with data-driven analysis techniques. The role of process mining is to extract knowledge and gain insights from event logs. Most existing techniques focus on process discovery (the automated extraction of process models) and conformance checking (aligning observed and modeled behavior). Relatively little research has been performed on the analysis of business process performance. Cooperative business processes often exhibit a high degree of variability and depend on many factors. Finding root causes for inefficiencies such as delays and long waiting times in such flexible processes remains an interesting challenge. This paper introduces a novel approach to analyze key process performance indicators by considering the process context. A generic context-aware analysis framework is presented that analyzes performance characteristics from multiple perspectives. A statistical approach is then utilized to evaluate and find significant differences in the results. Insights obtained can be used for finding high-impact points for optimization, prediction, and monitoring. The practical relevance of the approach is shown in a case study using real-life data