What is a significant challenge faced during the implementation of process mining?

Integrating data from diverse systems is a significant challenge during the implementation of process mining. Organizations often operate with a variety of systems and databases that store process-related data. These systems may use different formats, structures, and access protocols, making it difficult to aggregate and harmonize data into a unified view for analysis.

Process mining relies heavily on extracting accurate and comprehensive data from all relevant sources to reconstruct and analyze processes effectively. If data integration is not executed properly, it can lead to incomplete or inaccurate process insights, which can undermine the value of process mining initiatives. Proper integration ensures that the analysis reflects the true nature of the processes being examined, allowing organizations to identify bottlenecks, inefficiencies, and opportunities for improvement.

The other options, while they may present challenges in their own contexts, do not directly pertain to the core requirements of successful process mining implementation. Creating new technologies from scratch is generally not necessary, as many tools are already available. Establishing clear benchmarks across industries can be complex but is not a core challenge of process mining itself. Developing personalized customer experiences, while important for customer relationship management, does not directly impact the execution of process mining initiatives.