Purpose – The purpose of this paper is to present a generic framework to assess and simulate outsourcing risks in the supply chain. Design/methodology/approach – This combination approach involves a qualitative risk analysis methodology termed as the supply chain risk‐failure mode and effect analysis (SCR‐FMEA) which integrates risk identification, analysis and mitigation actions together to evaluate supply chain outsourcing risk. The qualitative risk assessment will allow risk manager to provide a visual presentation of imminent risks using the risk map. Monte Carlo simulation (MCS) on the imminent risks of delivery outsourcing using the Milk‐Run system is adopted. Findings – With basic statistical concepts, key performance variables and the risk of delivery outsourcing are analyzed. It is found that a newly implemented delivery outsourcing arrangement on the Milk‐Run system reduces the average customer lead‐time and total cost. However, a certain extent of risk or uncertainty can still be detected due to the presence of variation. Research limitations/implications – This paper reveals that company can manage the risk by adopting a systematic method for identifying the potential risks before outsourcing and MCS can be applied for examining the quantifiable risks such as lead time and cost. Practical implications – The paper provides a generic guideline for practitioners to assess logistics outsourcing, especially for logistics management consultants and professionals for evaluating the risk and impact of outsourcing. It is believed that the proposed risk assessment framework can help to analyze the operational cost uncertainty and ensure the stability of the supply chain. However, the limitation of this research is that the full spectrum of outsourcing risk, especially the non‐quantifiable risk may not be analyzed by MCS. Originality/value – This paper proposed an integrated framework which combines qualitative and quantitative method together for managing outsourcing risk. This research provides a standardized metric to quantify risk in the supply chain so as to determine the effectiveness of outsourcing.
Industrial Management & Data Systems – Emerald Publishing
Published: Apr 20, 2012
Keywords: Risk management; Outsourcing; Monte Carlo simulation; Risk map; Failure mode and effect analysis