Effective supply chain management is a difficult multifaced task: keeping inventory policies balanced and cutting operational costs, including transportation, production, and distribution expenses. That’s why drugstores executive management decided to rent new facilities for its cold chain.
This problem can be solved by following the steps below:
- Greenfield Analysis
- Multi-Echelon Greenfield Analysis
- Safety Stock Estimation
- Risk Analysis
With the aid of Greenfield Analysis we found the optimal number of regional sites and their locations (considering the maximum distance between drugstores and facilities). We also found the optimal location for the distribution center, whereupon we performed Safety Stock Estimation, which helped us configure inventory policies with the optimized safety stock.
All this, however, is not enough for effective supply chain designing. Supply chain operations are tightly connected to risks and uncertainties, which must taken into account while designing supply chain. This complicates the planning process and sets high standards for the agility and robustness of a supply chain. The risks must be estimated to design the network, define policies, and figure out how to act in case of an emergency.
We consider a supply chain in England comprising:
- 100 drugstores located in the largest cities
- 3 suppliers of medications in Lincoln, Sudbury, and Amesbury
- DC located in Milton Keynes
- 6 regional sites
Demand for the following medications is of periodic nature:
- Stomachic medications
- Cardiac medications
- Reliever medications
- Neurological drugs
- Cold medicines
Drugstores are supplied in a certain order, which allows the trucks to fetch orders for several destination points and follow the route, visiting customer per the specified order. Once the final destination point of the milk run has been served, trucks head to the positioning regional site.
What will happen if the river Thames floods, agreement with the supplier terminates, or demand changes?
If you want to see the effect of a stochastic parameters on the supply chain, you should run the Variation experiment.
In addition to parameter variation, you can also assess particular “what-if” scenarios to stress-test the supply chain in emergency situations.
As a result we quantified the risks. This will allow you to design a network that minimizes possible expenses and increases supply chain resilience.
The History by Replication page shows daily service level per replication. As you can see, Replication 9 has the worst service levels per day.
At the same time, the total costs in Replication 9 was minimal.
Based on the results of current the experiment run we can assume that the required service level may be maintained by increasing the expenses for the critical elements of the supply chain.
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