Results for “mrpbv_forecast_consumptions”

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Overview

MRPBV_FORECAST_CONSUMPTIONS is a read-only view owned by the APPS schema in Oracle E-Business Suite 12.1.1 and 12.2.2. It resides in the MRP (Master Scheduling/MRP) product family and exposes the linkage between forecast consumption activity and the sales orders that consumed those forecasts. Forecast consumption is the process by which firm demand — typically booked sales order schedules — reduces or offsets forecasted demand within a planning horizon, preventing double counting of demand during MRP and MPS planning runs. The view is a reporting and diagnostic layer over the MRP_FORECAST_UPDATES table, joining it outward to sales order headers and lines and to the MTL_DEMAND_OMOE demand table so that planners and supply chain analysts can reconcile which sales order quantities consumed which forecast entries and when.

Because the view is declared WITH READ ONLY and contains a security predicate referencing FORUPD.ORGANIZATION_ID, it is intended strictly for query and reporting use rather than for data manipulation. It is not itself a base table, and no DML should be attempted against it.

Underlying Base Objects

The view is defined over four primary data sources and references several supporting packages. The driving table is MRP_FORECAST_UPDATES (exposed via a synonym), which stores forecast update and consumption records keyed by UPDATE_SEQ_NUM and LINE_NUM. MTL_DEMAND_OMOE, the Oracle Materials demand table synonym, is joined on the outer side (DEMAND_ID and USER_LINE_NUM) to identify the demand record created by the sales order. SO_LINES_ALL and SO_HEADERS_ALL are outer-joined through DEMAND_SOURCE_LINE and HEADER_ID respectively, providing the sales order context.

• MRP_FORECAST_UPDATES — driving table of forecast consumption/update records.
• MTL_DEMAND_OMOE — demand records linked to the forecast update.
• SO_LINES_ALL / SO_HEADERS_ALL — sales order line and header detail.
• Supporting packages — INV_DECIMALS_PUB, INV_SALESORDER, MRP_OE, and OE_INSTALL (PACKAGE objects referenced in the dependency chain).

The outer joins (indicated by the (+) syntax) mean forecast update rows are preserved even when no matching demand or sales order line exists, which is important when reconciling orphaned or partially processed consumption records.

Key Columns

• SALES_ORDER_SCHEDULE_DATE — the schedule date of the consuming sales order quantity.
• SALES_ORDER_QUANTITY — the quantity of sales order demand applied against the forecast.
• FORECAST_CONSUMED_DATE — the date on which the forecast was consumed.
• FORECAST_QUANTITY_CONSUMED — the forecast quantity offset by firm demand.
• DEMAND_CLASS — classification of the demand driving consumption.
• FORECAST_ENTRY_ID — identifier linking back to the originating forecast entry.
• SALES_ORDER_LINE_ID — the sales order line that consumed the forecast.
• LAST_UPDATE_DATE, LAST_UPDATED_BY, CREATION_DATE, CREATED_BY — standard audit columns.

Common Use Cases and Queries

Typical uses include auditing forecast consumption after an MRP or MPS planning run, reconciling sales order demand against forecast entries, and diagnosing consumption discrepancies between planning outputs and booked orders.

A representative query listing consumption by date follows:

• SELECT sales_order_schedule_date, sales_order_quantity, forecast_quantity_consumed, demand_class FROM apps.mrpbv_forecast_consumptions WHERE forecast_consumed_date >= SYSDATE - 30;

A second query groups total consumed quantity by sales order line to identify high-consumption orders:

• SELECT sales_order_line_id, SUM(forecast_quantity_consumed) consumed FROM apps.mrpbv_forecast_consumptions GROUP BY sales_order_line_id ORDER BY consumed DESC;

Because the view enforces read-only access and organization-level security, it is suitable for custom reports, BI Publisher data sets, and ad hoc planner analysis without risk to transactional data integrity.