What are possible approaches to modeling a customer demand in time-series-based optimization with SAP IBP...

Time-series-based optimization in SAP IBP for Response and Supply balances demand and supply constraints over a horizon. Modeling customer demand involves prioritization and cost considerations.

Option A: Ensure discounting does not result in negative costs for each customer-product combinationThis is incorrect. Discounting (e.g., price reductions) isn’t a standard concept in time-series optimization; costs (e.g., non-delivery) are positive penalties, not negative adjustments.

Option B: Assign a high cost value (1 million or more) for non-delivery to priority customersThis is correct. In the optimizer, assigning high non-delivery costs (e.g., 1M) to priority customers ensures their demand is met first, a common prioritization technique in SAP IBP, per optimization documentation.

Option C: Ensure product prioritization with the combination of customer and productThis is correct. Time-series optimization can prioritize demand at the Customer-Product level (e.g., via demand priority rules or costs), ensuring key combinations are favored, per SAP IBP’s supply planning features.

Option D: Try to go as granular as possible with the customer productThis is incorrect. Excessive granularity increases complexity without guaranteeing better results; optimization balances granularity with performance, not mandating maximum detail.

Thus, B and C are valid approaches to modeling customer demand, per SAP IBP’s optimization capabilities.