Statistical Aspects of Target Setting for Attribute Data Monitoring

We consider early warning systems (EWS) for monitoring multi-stage data, in which downstream variables undergo changes associated with upstream process stages. In such applications, the EWS monitoring arm acts as a search engine that analyses a number of data streams for each monitored variable, as the problems of change detection and identification of the change-causing stage are handled jointly. Given massive amounts of data involved in analysis, it is important to achieve an acceptable balance between false alarms and sensitivity requirements, by focusing on changes of practical significance. The role of the target-setting arm of EWS is to ensure and maintain this balance via suitable selection of control scheme parameters. In this paper, we discuss principles of developing and managing targets, with examples from a supply chain operation.