An operational support approach for Mining Unstructured Business Processes

Abstract

The refined process mining framework contains a set of activities that use extracted information from event logs, discovered models and normative ones. Among these activities, we find those dealing with running events in a Structured Business Process (SBP) context, which are the Detect, the Predict and the Recommend activities. These three activities are nominated as an operational support system that aims at detecting deviations, predicting events and recommending actions. In this regard, operational support systems perform well on SBP while, it stills a challenging task for an Unstructured Business Process (UBP). This puts forward the difficulty of predicting events and recommending actions for UBP, because of its complex structure. In this context, simplification and structuring operations must be applied. Therefore, the intervention of other process mining activities is required for business process simplification and structuring. To this end, we present an operational support approach dealing with UBP, using the refined process mining framework activities.

Complex Process Modeling in Process Mining: A Systematic Review

“…Because of its simple, scalable, and filtered directly-follows graphs (DFGs) based model generation, fuzzy miner remains the top choice for commercial process mining tools [61], [89]. However, DFG-based models fail to distinguish between a choice and a split construct [10].…”

“…The unpredictive behavior of process models resulted from the assumption that experiments conducted in a controlled environment will also work for real-world data. However, real-life process logs contained traces of flexible behavior, which allowed unpredicted results [9], [10]. Consider an example of an organization that asks its employees to achieve a particular target containing several activities with no restriction on the order of activities to follow.…”

Workplace performance measurement: digitalization of work observation and analysis

“…In Industry 4.0, ISs are used to analyze the course and support the implementation and improvement of business processes. Using process mining techniques based on the data collected in their event logs, it is possible to identify the course of the processes being carried out, and on this basis, compare them with the applicable standard and specify proposals for improvements allowing for the preparation of an improved standard (Badakhshan et al, 2022;Choi et al, 2022;IEEE Task Force on Process Mining, 2012;Lamghari et al, 2021;Lorenz et al, 2021;Mamudu et al, 2023). This is the scope of identification and analysis that fully covers earlier observation methods such as work sampling, snapshot observations, or work timing.…”

Unstructured Business Processes Improvement using Process Mining Techniques

“…These approaches are respectively validated in these publications (Lamghari et. al., 2020;Lamghari et. al., 2021;Lamghari et al, 2022).…”

“…Indeed, unstructured processes (knowledge intensive) are loosely defined and rely on access to readily available knowledge. The problematic is how to obtain a simplified and improved representation of UBP (Lamghari et al, 2021) using process mining techniques. The existence of structured processes (dataintensive) within the unstructured ones make process mining usable for both systems: data-intensive & knowledge intensive.…”