A Systematic Literature Review to Identify the Challenges of Business Process Improvement and Process Mining Methodologies, and Develop a Data Mining Solution

Nowadays, organisations face a high volume of business processes (BPs) along with numerous process features. In the current situation, the problems related to processing information, such as higher dimensionality, complexity, changeability, and scalability issues, have created significant challenges for business process improvement (BPI) and process mining (PM) approaches. This paper contributes in two ways. At first, for the first time, a systematic literature review of the challenges of the two main approaches, including BPI and PM, is presented. These challenges are in accordance with the problems associated with the high volume of BPs in organisations. Second, this paper proposes a new model of applying data mining to improve BPs, supporting the two mentioned approaches and reducing the related challenges. To assess the applicability of the proposed model, an actual BP dataset was used in this work. In the end, the advantages of the proposed model over the BPI methodologies and PM approach have been established. The proposed model can significantly alleviate the challenges associated with organisations’ high volume of BPs. Of course, it is crucial to carefully consider and manage inherent limitations to better implement the proposed model. In addition, the literature review can reveal a broader issue for other researchers to investigate related topics. These topics are elaborated on in various parts of this paper, particularly in the section related to challenges and solutions in BPI and PM. Furthermore, practitioners can also consider the main issues discussed in this literature review to improve BPs in their organisations.