Business Process Intelligence (BPI) is one of the emerging technologies in the knowledge discovery and analysis area. BPI deals with a series of techniques from discovering knowledge to analyzing the discovered knowledge in BPM-supported organizations. By means of the BPI technology, we are able to provide the full functionality of control, monitoring, prediction, and optimization of process-supported organizational knowledge. Particularly, we focus on the focal organizational knowledge, which is so-called the BPM activity-performer affiliation networking knowledge that represents the affiliated relationships between performers and activities in enacting a specific business process model. That is, in this paper we devise a statistical analysis method to be applied to the BPM activity-performer affiliation networking knowledge, and dubbed it the activity-performer correspondence analysis method. The devised method consists of a series of pipelined phases from the generation of a bipartite matrix to the visualization of the analysis result, and through the method we are eventually able to analyze the degree of correspondences between a group of performers and a group of activities involved in a business process model or a package of business process models. Conclusively, we strongly expect the effectiveness and efficiency of the human resources allotments, and the improvement of the correlational degree between business activities and performers, in planning and designing business process models and packages for the BPM-supported organization, through the activity-performer correspondence analysis method.