Planning Your Data Conversion

This section provides an overview of history data and discusses how to:

  • Protect history data.

  • Identify the data that you need.

History is the period-by-period data produced during periodic processing. Periodic processing produces history for the following functions:

Type of Function

Functions That Create History

Accrual Functions

  • Service

  • Cash balance accounts

  • Employee accounts

Consolidations Functions

  • Consolidated earnings

  • Consolidated hours

  • Consolidated contributions

You can view and modify history for the consolidations functions on the pages in the Review Consolidation Results (CONS_HOURS_HIST) component.

You can view history for the accrual functions on the pages in the Review Plan History (PLAN_HISTORY) component.

The history for the accrual functions includes balances for the end of each period. The balances are the accumulation of credits across periods. The consolidation functions do not need balances.

When working with accruals, you can avoid loading the entire period-by-period history and instead load startup balances. A startup balance is the accrual as of a date that you specify.

History data is always loaded into tables that are specific to functions. Startup balances are always loaded into the PA _STRTUP_HISTO table.

Periodic processing has two modes:

  • Normal mode.

    In Normal mode, the system adds new history to the existing rows.

  • Delete and Rebuild mode.

    In Delete and Rebuild mode, the system deletes all existing history and recalculates data throughout the employee's entire career. This can be useful in certain situations. For example, if you discover a problem with your calculation rules, you can correct the rules and recalculate everything at once.

    However, Delete and Rebuild mode is risky. If you load history data as part of your data conversion, the system does not have the source data to replace those rows. For example, if you load consolidated earnings but not the raw payroll data that was the source for the consolidated data, the system removes the consolidated data and cannot recreate it because of the missing source data.

Warning! If you load history for a function, take security measures to ensure that people do not have access to the Delete and Rebuild mode during periodic processing.

The service function always runs in Delete and Rebuild mode. This is necessary because ongoing events affect past service accruals. For example, previously accrued service can be forfeited after a break in service. Never load history for service. Always use startup values or load the job history that is the source data for the service calculation. If you load service history instead of the actual job history (hires and terminations, leaves and returns, and other relevant events), the entire history disappears the first time that you run the service function during periodic processing. The lack of a complete job history compromises the system's ability to produce accurate service information.

Raw payroll data is used in consolidated data. Consolidated data is used in various functions, including service, cash balance accounts, and employee accounts. The consolidated earnings history also supports final average earnings and social security calculations.

Loading both raw payroll data and consolidated payroll history is redundant. Similarly, loading both consolidated contributions history and a startup balance for employee accounts is redundant. The system never uses the consolidated contributions information before the as of date for the employee accounts starting balance.

When planning your data conversion, you can decide which data to load. Payroll data offers the greatest level of detail and thus increases flexibility for recalculation. Starting balances provide the least amount of detail and flexibility. Consolidated data is in between the two.

When you use consolidated earnings for final average earnings or social security, you cannot use startup balances. In these cases, you must use raw payroll data or consolidated data.