Improving Supply Chain Risk Management by Introducing Performance Measurement Systems
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Supply chain risk management (SCRM) is a topic that gains more and more interest from both the academic and practitioner’s perspective. The reason for this is the increased complexity in the global supply chain (SC) networks and many managers do not realize the risks they build in their SC by the continuous search to cut cost and decrease tied up capital. One problem with SCRM is that it is hard to measure the performance of it and if it is really beneficial to work with it. The objective for this master thesis is to investigate how companies can evaluate and thereby improve their SCRM efforts by connecting the field of SCRM to the field of performance measurement systems (PMS). First, a thorough literature search was conducted where the current literature about SCRM and PMS was examined to understand what the literature recommends. This was followed by a multiple case study including semi-structured interviews with SC managers at eight companies to get the practical aspect of the problem.The results of the research show that companies work with SCRM in many different ways. The companies that have advanced furthest are the ones that have connected their SCRM to existing key performance indicators (KPIs) and because of that they have been able to measure the results of their SCRM efforts. The top-performers had a comprehensive understanding of their risk drivers and risks that affected their SC, which was consistent with the literature. Connecting the SCRM to the PMS, the companies can better monitor how the SCRM affect the performance goals for the SC performance. Then the next step is then to connect key risk indicators (KRIs) to the key KPIs that will give managers longer time to react to potential risks. Only one company in the study had accomplished this, hence, there is a great space for improvements for many companies.
Place, publisher, year, edition, pages
2013. , 62 p.
Examensarbete INDEK, 2013:116
supply chain risk management, performance measurement systems, key performance indicator, key risk indicator
Other Engineering and Technologies
IdentifiersURN: urn:nbn:se:kth:diva-124091OAI: oai:DiVA.org:kth-124091DiVA: diva2:632754
Subject / course
Industrial Economics and Management
Master of Science in Engineering - Industrial Engineering and Management
Angelis, Jannis, Ass Prof
Engwall, Mats, Prof