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Overview
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Overview

The CEFV_CASH_FORECAST_CELLS view is a Business View owned by the APPS schema and delivered with the Oracle Cash Management (CE) module. It exposes the contents of the Cash Forecasting engine, presenting each individual forecast cell as a fully decoded, denormalized row. In the Cash Management data model, a cash forecast is structured hierarchically: a forecast header (CE_FORECAST_HEADERS) belongs to a forecast (CE_FORECASTS), which defines a series of rows (CE_FORECAST_ROWS) and columns (CE_FORECAST_COLUMNS). The intersection of a row and a column is a cell, physically stored in CE_FORECAST_CELLS and holding the forecasted amount for a given transaction type over a specific time period.

Rather than requiring report authors and integrators to resolve dozens of lookup codes, flexfield references, and join paths manually, CEFV_CASH_FORECAST_CELLS performs that work once. It translates lookup codes into meanings, resolves bank accounts, payment methods, receipt methods, payrolls, and accounting flexfield references, and attaches period start and end dates. This makes it the primary read-only interface for forecasting data used in custom reports, BI Publisher templates, Oracle Discoverer workbooks, and outbound integrations. Because the view exposes the FORECAST_DESCRIPTION column (sourced from FR.DESCRIPTION on CE_FORECAST_ROWS), users searching on "forecast_description" are typically looking for the descriptive text associated with a forecast row, which this view surfaces directly.

Underlying Base Objects

The view is defined over a mixture of base tables, synonyms, and other views. The core forecasting objects are CE_FORECAST_CELLS, CE_FORECAST_HEADERS, CE_FORECASTS, CE_FORECAST_ROWS, and CE_FORECAST_COLUMNS. These are joined on their respective primary keys (FORECAST_HEADER_ID, FORECAST_ID, FORECAST_ROW_ID, FORECAST_COLUMN_ID) to reconstruct the forecast hierarchy.

Supporting reference objects include CE_BANK_ACCOUNTS for bank account names and numbers, CE_LOOKUPS and AR_LOOKUPS for lookup meanings, GL_SETS_OF_BOOKS for ledger names, AR_RECEIPT_METHODS, HZ_CUST_PROFILE_CLASSES, and PAY_ORG_PAYMENT_METHODS_F for payment and receipt context, plus PO_LOOKUP_CODES, PAY_ALL_PAYROLLS_F, PAY_EXTERNAL_ACCOUNTS, HR_ALL_ORGANIZATION_UNITS, and HR_ORGANIZATION_INFORMATION. GL_PERIODS and GL_PERIOD_TYPES supply the period start and end dates, while GL_CODE_COMBINATIONS and GL_ENCUMBRANCE_TYPES provide accounting context. Notably, the join to GL_SETS_OF_BOOKS is an outer join (SB.SET_OF_BOOKS_ID (+) = FR.SET_OF_BOOKS_ID), preserving forecast rows that are not tied to a ledger.

Key Columns

  • FORECAST_CELL_ID — primary identifier of the cell row; the grain of the view.
  • MEANING (L1) — decoded transaction type (for example, PAY for payments or receipts).
  • START_DATE / END_DATE — period boundaries from GL_PERIODS for the forecast column.
  • AMOUNT — the forecasted amount held in the cell.
  • DESCRIPTION (FR.DESCRIPTION) — the forecast_description text describing the forecast row.
  • LEAD_TIME — lead time applied to the forecast row.
  • BANK_ACCOUNT_NAME / BANK_ACCOUNT_NUM — bank account context.
  • PAYMENT_METHOD and ORG_PAYMENT_METHOD_NAME — resolved payment method, conditionally decoded by transaction type.
  • CURRENCY_CODE (from the sets of books) and NAME for ledger identification.
  • CODE_COMBINATION_ID and associated flexfield key references.
  • CRITERIA1 … CRITERIA15 — user-defined forecast row criteria columns.
  • FORECAST_ID, FC.NAME, FC.DESCRIPTION — parent forecast identity and description.
  • CREATION_DATE, CREATED_BY, LAST_UPDATE_DATE, LAST_UPDATED_BY — audit columns.

Common Use Cases and Queries

The view supports reconciliation of forecasted versus actual cash positions, bank account liquidity reporting, and period-by-period cash projections. A frequent query filters on the forecast row description, which corresponds to the "forecast_description" search term:

SELECT FORECAST_CELL_ID, DESCRIPTION, START_DATE, END_DATE, AMOUNT, BANK_ACCOUNT_NAME
FROM   APPS.CEFV_CASH_FORECAST_CELLS
WHERE  UPPER(DESCRIPTION) LIKE UPPER('%:p_desc%')
AND    START_DATE BETWEEN :p_start AND :p_end;

Another common pattern aggregates forecasted amounts by transaction type and period to produce a cash-position summary:

SELECT MEANING, START_DATE, SUM(AMOUNT) TOTAL
FROM   APPS.CEFV_CASH_FORECAST_CELLS
WHERE  FORECAST_ID = :p_forecast_id
GROUP  BY MEANING, START_DATE
ORDER  BY START_DATE;

Integration use cases include extracting normalized forecast cell data into a data warehouse, driving cash application dashboards, or feeding treasury systems. Because the view resolves lookups and joins internally, and because the metadata confirms it remains VALID in the 12.1.1 and 12.2.2 schemas, it can be relied upon as a stable reporting interface as long as the underlying Cash Management forecast tables are populated.