The Cost to serve experiment is used to estimate and provide detailed statistics on all costs incurred in the process of delivering the demanded product from its initial source to its final destination within the specified period. The data on the collected costs is available in the Cost to Serve statistics.
The Cost to serve experiment is most commonly used for the following purposes:
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Baseline scenario comparison:
- By comparing the transportation costs between the baseline and optimized scenarios, it becomes possible to evaluate the current supply chain performance and understand the way optimization changes the cost structure.
- The experiment allows you to analyze costs at each supply chain link to determine if the process has improved or worsened.
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Input data and result validation:
- Statistics help to spot cost-related issues (when the resulting data differs significantly from the expected value).
- Analysis helps to ensure that model inputs are accurate and reliable.
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Price / Discount analysis:
- Analyze potential price adjustments and areas, in which they might be made.
- Results can highlight discount possibilities based on the costs incurred in each part of the supply chain.
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