Results for “mrp_bis_forecast_wb”

AI-generated from documented ETRM metadata — verify critical details on the linked pages.

Overview

MRP_BIS_FORECAST_WB is a summary table owned by the MRP schema within Oracle E-Business Suite Release 12.1.1 and 12.2.2. It resides in the Master Scheduling/MRP product family and is classified as a VALID table object. The table serves as a pre-aggregated reporting substrate that stores forecast and actual demand values consumed by Oracle Discoverer workbooks, enabling planners and supply chain analysts to compare committed forecasts against realized order and shipment activity without querying high-volume transactional tables directly.

From a data modeling perspective, the heuristic Data Vault classification mined from the foreign key structure is standalone. This classification indicates that MRP_BIS_FORECAST_WB does not participate as a hub, link, or satellite in a normalized Data Vault model, but instead behaves as a denormalized reporting fact table. Where Data Vault principles are applied, this object would most naturally map to a reporting satellite or materialized aggregate of the forecast and actual-demand business process, retained as a convenience layer for analytical consumption rather than as a system of record.

Key Information Stored

The table contains 48 documented columns. The most operationally significant attributes cluster into dimensions, measures, and audit metadata.

• ORGANIZATION_ID, ORGANIZATION_CODE, ORGANIZATION_NAME — the inventory organization dimension identifying where the forecast applies.
• FORECAST_SET, FORECAST, FORECAST_DESCRIPTION — the forecast set and forecast name hierarchy used to group planning scenarios.
• UPDATE_TYPE, DEMAND_CLASS — distinguish how demand entered the plan and its demand classification.
• INVENTORY_ITEM_ID, ITEM_NUMBER, ITEM_DESCRIPTION — the item dimension.
• CATEGORY_SET_ID, CATEGORY_SET, CATEGORY_ID, CATEGORY, PRODUCT_FAMILY_ID, PRODUCT_FAMILY_NUMBER — item grouping and product family dimensions used for rolled-up reporting.
• CUSTOMER_ID, CUSTOMER, CUSTOMER_CLASS — the customer dimension.
• SHIP_ID, SHIP_TO_ADDRESS, SHIP_TO_CITY, SHIP_TO_STATE, SHIP_TO_ZIP — ship-to geography.
• BILL_ID, BILL_TO_ADDRESS, BILL_TO_CITY, BILL_TO_STATE, BILL_TO_ZIP — bill-to geography.
• FORECAST_DATE — the time dimension bucket for the row.
• FORECAST_QUANTITY, ORDER_QUANTITY, SHIPPED_QUANTITY — quantity measures for forecast, ordered, and shipped demand.
• FORECAST_AMOUNT, ORDER_AMOUNT, SHIPPED_AMOUNT — corresponding monetary measures.
• CONFIDENCE_PERCENTAGE — planner-assigned forecast confidence.
• LAST_UPDATE_DATE, LAST_UPDATED_BY, CREATION_DATE, CREATED_BY, LAST_UPDATE_LOGIN, REQUEST_ID, PROGRAM_APPLICATION_ID, PROGRAM_UPDATE_DATE — standard EBS audit and concurrent-program provenance columns.

The metadata does not document a surrogate primary key or unique index for this table. No single column is formally identified as a primary key; composite business keys spanning organization, forecast, date, item, and customer are the practical grain identifier. BILL_ID is the only documented foreign key, referencing IGS_FI_BILL_ALL, linking the summary row back to a bill-to party record in the Financials interchange schema.

Common Use Cases and Queries

Typical usage centers on forecast-versus-actual variance reporting, forecast accuracy measurement, and demand planning dashboards. A representative query aggregates forecast, order, and shipped quantities by item and forecast month:

• Forecast accuracy: compare FORECAST_QUANTITY against SHIPPED_QUANTITY by FORECAST_DATE, INVENTORY_ITEM_ID, and ORGANIZATION_ID to compute bias and MAPE.
• Product family roll-ups: group by PRODUCT_FAMILY_NUMBER or CATEGORY to evaluate forecast performance at aggregate planning levels.
• Customer and geography analysis: join on CUSTOMER_ID or inspect SHIP_TO_STATE to identify regional demand patterns.
• Confidence-weighted pipelines: weight FORECAST_AMOUNT by CONFIDENCE_PERCENTAGE for weighted demand views.
• Refresh lineage: use REQUEST_ID and PROGRAM_UPDATE_DATE to audit which concurrent program populated the summary and when.

Because the table is a summary artifact rather than a transactional source, queries should filter on ORGANIZATION_ID and FORECAST_SET to avoid cross-scenario contamination.

Related Objects

The documented relationship data identifies BILL_ID as a foreign key to IGS_FI_BILL_ALL. Additional dependencies are inferred from the domain and column structure:

• IGS_FI_BILL_ALL — joined on MRP_BIS_FORECAST_WB.BILL_ID = IGS_FI_BILL_ALL.BILL_ID, providing bill-to party detail.
• MTL_SYSTEM_ITEMS_B — joined on INVENTORY_ITEM_ID for item master attributes.
• MTL_PARAMETERS — joined on ORGANIZATION_ID for organization context.
• MRP_FORECAST_SETS — joined on FORECAST_SET for forecast set definitions.
• MRP_FORECAST_DATES — joined on FORECAST_DATE for planning calendar alignment.
• MRP_FORECAST_ITEMS — the transactional forecast detail underlying these aggregates.
• OE_ORDER_HEADERS_ALL and WSH_DELIVERY_DETAILS — sources for order and shipped quantity reconciliation.

These relationships make MRP_BIS_FORECAST_WB a bridge between planning entities and analytical reporting layers, though only the BILL_ID linkage is formally documented as a foreign key.