Facilitating business process improvement through personalized recommendation

Process improvement continues to be a high priority for organizations and hence organizations continually invest in expert advice and reference models. However, a valuable and often overlooked source of successful practice is the experiences and knowledge of individuals who perform various activities within the business process. In this paper, we promote the use of this existing knowledge to assist process users and designers towards process improvement. There are two main challenges in this regard: The identification of the so-called best practice and its recommendation to an individual user in such a way that it fits the individual user's current level of experience. In order to address the above challenges we take a design science approach towards the development of methods for multi-criteria based process ranking and personalized recommendation. The methods are evaluated using a real scenario and simulated data. Results of the analysis experiments indicate that the developed methods can assist in facilitating effective learning mechanisms within the organization's user base that may subsequently lead to process improvements