Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Abstract

Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining cycle time of a given process case. These insights could be used to support operational managers in taking remedial actions as business processes unfold, e.g. shifting resources from one case onto another to ensure this latter is completed on time. A number of methods to tackle the remaining cycle time prediction problem have been proposed in the literature. However, due to differences in their experimental setup, choice of datasets, evaluation measures and baselines, the relative merits of each method remain unclear. This article presents a systematic literature review and taxonomy of methods for remaining time prediction in the context of business processes, as well as a cross-benchmark comparison of 16 such methods based on 16 real-life datasets originating from different industry domains.

Context-Aware Process Performance Indicator Prediction

“…the PPIs which are related with them are shown in Table 4 595 ( Figure 1, Step 6). We have selected a typical aggregation encoding described in [36] as one of the most used in literature to encode the process cases. Thus, all events since the beginning of the case are considered.…”

“…We have not divided the cases in the event log into different buckets. This technique is named Zero bucketing as defined in [36]. We have also incorporated the order of the events as a new attribute in all the logs (i.e.…”

“…As predictive algorithm we have used random forest [38] and extreme gradient boosting [39] as seen in previous works in the literature [3], [36]. article_create_time, ticket_create_time, diff, owner_id, priority, ticket_history_type,a_from) 6 .…”

Tratamento do impacto de casos >i<non-fitting>/i< em predição de tempo de resolução usando mineração de processos com múltiplos atributos

“…(MAGGI et al, 2014). Uma organização que tenha a capacidade de prever certas condições em seus processos durante a execução dos mesmos pode alertar suas equipes sobre situações específicas, tomar decisões mais embasadas sobre onde colocar o foco dos recursos disponíveis ou para a alocação de recursos adicionais, entre outras ações possíveis (VERENICH et al, 2019; AALST, 2016).…”

“…Vários trabalhos já se debruçaram sobre a tarefa de predição, usando técnicas de mineração de processo aliadas a técnicas específicas, notadamente para a predição do tempo total de execução de um caso. A revisão sistemática apresentada em Verenich et al (2019)é uma boa referência para identificar esses trabalhos. Entretanto, poucos deram algum focoà escolha dos atributos descritivos a serem usados pelo preditor (MARQUEZ-CHAMORRO;…”