| Summary: | Risk management is one of the critical issues in supply chain management. Supply chain disruptions negatively impact on the performance and the business continuity of a firm, and the disruptions should be managed proactively if possible. One of the approaches for supply disruption management is to raise the level of inventory: supply disruptions can be reduced by simply increasing the safety stock level. However, inventory costs will be increased at the same time. Therefore it is assumed that having extra safety stock when and where needed is better than keeping a high safety stock all of the time.
In this thesis, the concept of dynamic inventory management by supplier behavior monitoring is suggested and explored. Key to the concept is the assumption that out-of-control situations at a supplier can be causal triggers for stockouts, and that these triggers can be potentially predicted by using statistical monitoring tools. In the suggested approach, the statistical process control approach of using run tests is employed to monitor and evaluate the supplier behavior. The supplier’s yield rate is monitored as the performance measure, and the receiver’s safety stock level is increased when the supplier’s performance is detected to be potentially out-of-control (or about to reach an out-of-control situation). The simulation results under different yield rates indicate that stockouts can be reduced by monitoring the supplier behavior and dynamically adjusting inventory policy when production capacity is relatively loose and enough variability can be seen in the performance measure.
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