1. A method, comprising operating a computer processor to perform operations comprising: accessing process execution data derived from audit logs generated during execution of instances of an automated business process comprising business process entities and defined by a directed graph of interconnected nodes representing respective activities, wherein the business process entities comprise services and resources, and each of the activities is defined by a respective service and is performed by a respective set of one or more resources; classifying the instances of the business process in accordance with a quality taxonomy defined by a set of quality categories each of which is associated with a respective condition on the process execution data and a respective quality score value, wherein the classifying comprises assigning the business process instances to respective ones of the quality categories based on application of the respective conditions to the accessed process execution data; building a predictive model comprising a respective set of predictive rules for each of multiple logical partitions of the directed graph defining the business process based upon the assignment of the business process instances to respective ones of the categories, wherein each of the predictive rules assigns a respective probability to each of the quality categories of the quality taxonomy for each of the business process entities that are invocable at the respective logical partitions of the directed graph, and each of the probabilities represents a likelihood that a given business process instance that invokes the respective business process entity at the respective logical partition of the directed graph will have an outcome corresponding to the respective quality category; and executing an active instance of the business process based on the predictive model.