Generating Forecasts for Inventory Planning Optimization Cloud Service-Demand Forecasting

The same forecasting interface described in the previous section for MFP is also used to generate the base demand and initial forecasts for Inventory Planning Optimization Cloud Service-Demand Forecasting (IPOCS-Demand Forecasting). Demand and forecasts must be generated in AI Foundation as part of your Forecasting implementation. The general workflow is the same, but the forecasting levels and methods used will vary depending on your implementation needs. For example, your IPOCS-Demand Forecasting forecasts may be at an item/location/week level of granularity instead of higher levels like MFP requires. You will also use other forecasting methods such as Causal-Short Life Cycle instead of the MFP default method (Auto ES).

IPOCS-Demand Forecasting directly integrates the demand and forecast parameters between AI Foundation Cloud Services and PDS tables using the RAP data exchange layer (RDX) as needed. Outputs from the forecasting engine will be written to tables prefixed with RSE_FCST_*. Outputs from IPOCS-Demand Forecasting back into the data exchange layer will be in tables prefixed with RDF_APPR_FCST_*. For more details on importing the forecasts after they are generated, refer to the IPO Demand Forecasting Implementation Guide.