Why is data quality critical in process mining?

Data quality is critical in process mining primarily because inaccurate data can lead to misleading insights and ineffective improvements. In process mining, data serves as the foundation for analyzing business processes and uncovering inefficiencies. If the data is flawed, whether due to errors, omissions, or inconsistencies, the resulting analysis will be based on incorrect information. This can skew the understanding of how processes actually function, leading to misguided decisions based on erroneous conclusions.

For example, if the analysis based on poor data suggests that a particular process is performing well, when in reality it has significant bottlenecks, the organization might fail to implement necessary changes, resulting in continued inefficiencies. Consequently, maintaining high data quality ensures that the insights drawn from process mining are reliable, facilitating effective process enhancements and organizational improvements.