Predictive Monitoring of Heterogeneous Service-Oriented Business Networks: The Transport and Logistics Case

Abstract

Future service technology will provide an unprecedented access to operational data, which opens up novel opportunities for monitoring, controlling and managing service- oriented business processes. Amongst these opportunities, we consider predictive monitoring to be a major lever for increased efficiency, effectiveness and sustainability in future business networks. Predictive monitoring means that critical events, potential deviations and unplanned situations can be anticipated and proactively managed and mitigated along the execution of business processes. This paper demonstrates the potential of predictive monitoring in practice. We focus on transport & logistics as a major industry sector -- accounting for between 10% to 20% of a country's Gross Domestic Product. Based on widely adopted standards and real operational data, we empirically support the relevance of key issues faced in that industry sector, such as late cancellations of transport bookings and delayed deliveries. As a solution, we describe the design of a novel, cloud- and services-based collaboration and integration platform. Based on this platform we develop short-term prediction capabilities allowing to proactively manage and mitigate the identified issues in the transport & logistics industry, thus promising to increase business efficiency and sustainability.