Process Mining for Six Sigma

Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges the potential benefits of using process mining techniques in Six Sigma-based process improvement initiatives. However, a guideline that is explicitly dedicated on how process mining can be systematically used in Six Sigma initiatives is lacking. To address this gap, the Process Mining for Six Sigma (PMSS) guideline has been developed to support organizations in systematically using process mining techniques aligned with the DMAIC (Define-Measure-Analyze-Improve-Control) model of Six Sigma. Following a design science research methodology, PMSS and its tool support have been developed iteratively in close collaboration with experts in Six Sigma and process mining, and evaluated by means of focus groups, demonstrations and interviews with industry experts. The results of the evaluations indicate that PMSS is useful as a guideline to support Six Sigma-based process improvement activities. It offers a structured guideline for practitioners by extending the DMAIC-based standard operating procedure. PMSS can help increasing the efficiency and effectiveness of Six Sigma-based process improving efforts. This work extends the body of knowledge in the fields of process mining and Six Sigma, and helps closing the gap between them. Hence, it contributes to the broad field of quality management

Towards Smart Incident Management Under Human Resource Constraints for an IoT-BPM Hybrid Architecture

International audienceThe Internet of Things (IoT) is exploding, and this new technology affects all the layers in any enterprise architecture, from infrastructure to business. To survive this new evolution and make the most out of this paradigm shift, a communication channel must be created between Business Process Management (BPM) domain and IoT domain in order to bridge the gap between the business layer and the IoT physical layer. The allocation of business process resources to IoT events is an important step towards an end-to-end IoT-BPM integration approach to assist organizations in their scheduling and incident management journey. In this paper, we propose a combination approach which is based on (i) unsupervised machine learning algorithms to generate clusters of priorities, used to estimate incoming events priority, and to ensure a learning feedback loop that feeds forward insight to continuously adjust decisions made at each layer, and (ii) genetic algorithm (GA) to guarantee the assignment of the most critical IoT generated event to the qualified human resource while respecting several constraints such as resource availability and reliability, and taking into consideration the priority of each event that launch process instances. A case study is presented and the obtained results from our experimentations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions

How to Exploit the Digitalization Potential of Business Processes

Process improvement is the most value-adding activity in the business process management (BPM) lifecycle. Despite mature knowledge, many approaches have been criticized to lack guidance on how to put process improvement into practice. Given the variety of emerging digital technologies, organizations not only face a process improvement black box, but also high uncertainty regarding digital technologies. This paper thus proposes a method that supports organizations in exploiting the digitalization potential of their business processes. To achieve this, action design research and situational method engineering were adopted. Two design cycles involving practitioners (i.e., managers and BPM experts) and end-users (i.e., process owners and participants) were conducted. In the first cycle, the method’s alpha version was evaluated by interviewing practitioners from five organizations. In the second cycle, the beta version was evaluated via real-world case studies. In this paper, detailed results of one case study, which was conducted at a semiconductor manufacturer, are included

ChIP: a Choreographic Integration Process

International audienceOver the years, organizations acquired disparate software systems, each answering one specific need. Currently, the desirable outcomes of integrating these systems (higher degrees of automation and better system consistency) are often outbalanced by the complexity of mitigating their discrepancies. These problems are magnified in the decentralized setting (e.g., cross-organizational cases) where the integration is usually dealt with ad-hoc "glue" connectors, each integrating two or more systems. Since the overall logic of the integration is spread among many glue connectors, these solutions are difficult to program correctly (making them prone to misbehaviors and system blocks), maintain, and evolve. In response to these problems, we propose ChIP, an integration process advocating choreographic programs as intermediate artifacts to refine high-level global specifications (e.g., UML Sequence Diagrams), defined by the domain experts of each partner, into concrete, distributed implementations. In ChIP, once the stakeholders agree upon a choreographic integration design, they can automatically generate the respective local connectors, which are guaranteed to faithfully implement the described distributed logic. In the paper, we illustrate ChIP with a pilot from the EU EIT Digital project SMAll, aimed at integrating pre-existing systems from government, university, and transport industry