Managing supply networks: symptom recognition and diagnostic analysis with Web services

Abstract

As supply chain managers spend well above 60% of their total working time remedying disruptions along the value chain, they require the support of interorganizational information systems that allow them to focus their attention on the critical problems. In addition, each action they decide on needs to be aligned with the overall network strategy to sustain the supply chain's competitive edge. However, research has only been very limited in this area. Commercially available Supply Chain Event Management-suites are a first step into this direction but so far lack important aspects like diagnostic analyses and integration into existing management and controlling frameworks. Based on a network-wide capturing of performance measurement data and alerting mechanisms in case key figures or process metrics do not meet their targets or exceed pre-set limits, this paper describes a computerized symptom-to-therapy cycle starting with recognizing performance deviations all the way to diagnosing the underlying root causes and supplying management with possible reaction measures to steer clear of the problem. At FORWIN this concept has been realized in a web-based prototype that will be presented to show these principles work in practice. The modules for symptom recognition and diagnosis will be discussed in detail. The article concludes with a brief outlook on future research.

Compound Web Service for Supply Processes Monitoring to Anticipate Disruptive Event

“…In order to provide a SCEM solution, two contributions closely related with this work have been proposed: Speyerer [6] developed a prototype based on web services to detect the root cause of a disruption. After that the disruption has been detected and classified it is compared in the data base to identify the root cause.…”

Supply Chain Event Management System

“…Alarm system: Can systematically detect deviations in the schedule and notify the key employee (Hoffmann et al, 1999;Speyerer & Zeller, 2004;Teuteberg & Schreber, 2005;Zimmermann, 2006). Decision support system: Can detect deviation and find a solution that minimizes the disturbance impact on the SC.…”