# CONDA-PM--A Systematic Review and Framework for Concept Drift Analysis in Process Mining
###### Abstract  
Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts. m 2020202029 June 20  
in which the process is changing while being analysed_. Research on concept drift addresses the need for monitoring business process changes. Moreover, concept drift allows making a decision about a change, for example, whether to accommodate it or reject the change in case it violates the process specification. Many factors may affect this decision making process. For example, an incremental drift can be easier to trace back and mitigate its effects than a sudden drift. This way, the type of drift may affect the choice whether to propagate the drift and incorporate it as a part of the business process. Another example regards how the granularity level at which the drift occurs may affect the decision, as a drift at the process type level would affect more process instances than a drift at the process instance level. Ignoring concept drift detection and localisation widens the gap between the intended process and its actual execution. It further complicates the monitoring of running processes and makes results of process analyses outdated. Predicting the future outcomes or activities of a process instance (i.e., predictive monitoring) yields unreliable results if the prediction model is built upon assumptions that may change during process execution. Therefore, it is essential to obtain an understanding of what shall be considered as a concept drift, how to detect a concept drift, and which techniques are available for this detection. Despite its recognition as one of the major challenges in process mining [1], there is a lack of in-depth research on concept drift analysis and monitoring. As explained in this article, concept drift analysis has several dimensions for example, directions, handling modes, process perspectives, and themes. We argue that there is a lack of studies providing a comprehensive view of the problem along with its solutions. Furthermore, the purpose of this systematic literature review (SLR) is to clarify the confusion of the terms used in current studies and to clarify what is meant by concept drift analysis. We study how current approaches to concept drift analysis contribute to this topic and to what extent the various dimensions of the problem are covered by current research, the SLR discusses the advantages and shortcomings of each approach and systemically compares these approaches. Based on our conclusions from the SLR, we propose the CONDA-PM framework. CONDA-PM is a four-phased framework that may guide process mining practitioners in assessing the maturity level of a concept drift analysis method.