Using EPM Foundation Data Enhancement Tools

This chapter provides an overview of the EPM Foundation data enhancement tools and discusses how to:

• Set up value objects.

• Define Data Manager rules.

• Define Data Manager rule sets.

• Rename Data Manager rules.

• Associate Data Manger rules sets with a job.

• Run the Data Manager engine.

• Define Allocation Manager rules.

• Define Allocation Manager rule sets.

• Rename Allocation Manager rules.

• Associate Allocation Manager rules sets with a job.

• Process allocations.

Understanding Data Enhancement Tools

This section discusses:

• Data Manager.

• Allocation Manager.

• Data Manager and Allocation Manager integration.

• Mathematical model for Data Manager and Allocation Manager rules.

Data Manager

The Data Manager is a flexible tool that enables you to:

• Move data into the performance journal table (PF_JRNL_F00).

• Organize the output from any PeopleSoft Enterprise Performance Management engine to create rows of data with multiple dimensions.

• Create reporting categories (dimensions) that represent groups of information for reports, such as business units, customers, products, channels, accounts (revenue, expense, and so on), and departments.

Note these key features of Data Manager:

• You can use Data Manager to consolidate or aggregate data and eliminate redundant rows.

• You can run Data Manager using different rules to organize and create multiple dimensions for direct costs and revenue data.

Data Manager supports the following methods for moving data:

Data Manager and the Profit Manager

Data Manager works with the Profit Manager tools by moving data to the performance journal table (PF_JRNL_F00). The Profit Manager tools verify this data (PF_EDIT engine) and post the data to the performance ledger (PF_POST engine). They also unpost data, if necessary (PF_UNPOST engine) and can clean up the performance journal table ( PF Journal Cleanup engine). The Profit Manager includes tools for balancing and reconciling your data.

The performance ledger, PF_LEDGER_F00, is a useful table for reporting because it contains all of the performance fact data. The facts have been allocated across several dimensions of your choice (typically channel, product, customer, and department). Having all of this information organized in a single table makes it easier for you to query and create reports.

The Profit Manager tools are described in later in this PeopleBook.

See Setting Up and Using Profit Manager.

Data Manager Setup

To set up the Data Manager, you need to:

1. Define the necessary metadata (including tablemaps, datamaps, constraints, and filters).

   The system uses datamaps and constraints to point to the appropriate tables.

2. Define Data Manager rules, including the method by which you want to move, aggregate, or create multidimensional data, as well as the sources and target of the process.

3. Create a Data Manager rule set that contains one or more rules.

4. Set up job metadata and jobstreams.

5. Associate the Data Manager rule set with a job.

6. Run the Data Manager engine.

Allocation Manager

Allocation Manager is a tool that enables you to distribute revenue, expense, and statistical amounts across business units, departments, and other dimensions. For example, you can allocate budget planning to detail levels to perform detailed budgeting. The type of allocation method that you select determines the output.

The following table lists the types of allocations that are supported by the Allocation Manager and describes each allocation type:

Allocation Manager Dimensions

Due to platform limitation issues on DB2 UDB for OS / 390 and z/OS (the index size is limited to 255 characters) and Oracle (which requires 30 columns in an index) the predelivered index is on the first 10 dimensions. However, based on your requirements and the database platform, you can increase the maximum number of dimensions in the Allocation Manager to 28. The records that need to be modified for index changes include PF_AL_CALC_T, PF_AL_DIFF_T, PF_AL_DIV_T, PF_AL_SRC01_T, PF_AL_BAS02_T, and PF_AL_TOTAL_T.

To increase the number of dimensions:

1. Open each of the above records in the Application Designer.

2. Open the relevant subrecord.

   The delivered unique index is shown on the fields PF_AL_DIM1 to PF_AL_DIM10.

3. Depending on the number of dimensions you are adding, modify the index by adding the extra dimensions as keys.

   For example, if you want to use 15 dimensions then modify the index to include PF_AL_DIM11 through PF_AL_DIM15 and build the record. Alternatively, you can add a custom index on the table, using the Add Index feature.

Note. You can also apply these steps to Data Manager.

Allocation Manager Setup Steps

To set up Allocation Manager, you need to:

1. Complete your metadata setup, including the datamaps setup for the source, basis, and target definitions.

2. Define Allocation Manager rules, including the method, source, basis, and target definitions.

3. Create an Allocation Manager rule set that contains one or more rules, and define post-processing routines for the rule set.

4. Set up job metadata and jobstreams.

5. Associate the Allocation Manager rule set with a job.

6. Run the Allocation Manager to process the allocations.

Mathematical Model for Data Manager and Allocation Manager Rules

The rules for Allocation Manager and Data Manager represent mathematical operations to be performed on the data you specify. Although Allocation Manger and Data Manager use different terminology, they perform similar calculations. For Allocation Manager, you must specify a source, basis, and target for the operation. For Data Manager you must specify two sources (source 1 and source 2) and the target.

The following table lists the Data Manager and Allocation Manager terms and how they relate.

The sources of a rule use constraints to tell the Data Manager what is to be assigned and what basis to use. Use constraints to apply business rules to limit row selection. The target of a rule uses a datamap to tell the Data Manager where the rule should be located. The method that is applied to the rule determines the calculation that is performed.

Note. The explanation of the mathematical operations uses only Allocation Manger terms. Use the previous table to apply the Data Manager terms.

Understanding the Calculations Behind the Prorata and Spread Even Methods

The prorata and spread even methods perform the same calculation with the following exception: the prorata method uses measures from the basis table in the calculation, whereas the spread even method uses row counts from the basis to determine the ratio that is defined by basis measure ÷ basis total.

The prorata method performs the following calculation:

Source Measure * Basis Measure / Basis Total
Source Measure = Sum(Measures in source grouped by common dimensions and source mapped dimensions)
Basis Measure = Sum(Measures in basis grouped by common dimensions and basis mapped dimensions)
Basis Total = Sum(Measures in basis grouped by common dimensions only)

The spread even method performs the following calculation:

Source Measure * Basis Measure / Basis Total
Source Measure = Sum(Measures in source grouped by common dimensions and source mapped dimensions)
Basis Measure = Sum(Count of basis rows grouped by common dimensions and basis mapped dimensions)
Basis Total = Sum(Count of basis rows grouped by common dimensions only)

The following tables provide an example of the prorata method with one common dimension (unique dimension combinations).

Source:

Basis:

Target:

This table illustrates an example of the spread even method with one common dimension (unique dimension combinations).

Source

Basis:

Target:

Understanding the Calculations Behind the Arithmetic Method

The arithmetic method performs the following calculation:

Source Measure [Operator] Basis Measure
Source Measure = Sum(Measures in source grouped by common dimensions and source mapped dimensions)
Basis Measure = Sum(Measures in basis grouped by common dimensions and basis mapped Dimensions)
Operator = [Addition (+), Subtraction (-), Multiplication (*), Division (/)]

Allocation Using Fixed Percentages

In Allocation Manager, you can divide a quantity by predetermined percentages and allocate those amounts by using the prorata method in combination with the fixed basis option.

In the calculation that is performed by the prorata method, the basis determines the ratio by which the source is divided. A ratio is another way to specify a percentage. By controlling the ratio, you can allocate the source amounts by specified percentages, or a fixed percentage.

Source Measure * (Basis Measure / Basis Total)

or

Source Measure * (%Percentage)

Warning! The prorata method always allocates 100 percent of the source. You must use the correct percentages when defining the fixed basis.

Setting Up Value Objects

A value object provides descriptive information about fields and values. Value objects enhance the power of filters and can use constant strings to fill in target fields. Used in a filter, value objects play a role in the constraint's WHERE clause of a SQL command to enforce selection rules. There are two value object classes:

Note. PeopleSoft delivers predefined value objects with PeopleSoft Enterprise Performance Management. However, you might need to define your own using the Value Object page.

This section discusses how to define value objects.

Page Used to Set Up Value Objects

Defining Value Objects

Access the Value Object page.

Value Object ID	A unique identifier for the value object. All value objects are denoted in the system by a % at the beginning of the ID.
Field Type	Select the field type. Choices are: Amount, Basis Pts (basis points), Char (character), Date, Datetime, Number, and Rate.
Value Class	Select from the following: Meta Value: Meta values are meta SQLs that retrieve system dates, user IDs, and engine run control parameters. If you select this option, you must specify the state record and state record field. System Variables: System variables are values referencing system information (for example, the current date and time (%CurrentDateTime)). Fixed Value: Fixed values are user-defined strings of text or numeric values that might be useful in specifying the definition of an assignment object or rule. These are usually constants. If you select system variables or fixed values, the state record, state record field, quotes check box, and use tree check box are unavailable for entry. You must select the prompt table and enter a value.
State Record and State Record Field	For Meta Value, enter the state record and state record field.
Quotes	For Meta Value, select this check box for character strings. In most cases, you will not select this check box for numeric values.
Use Tree	For Meta Value, select this check box if you want to use trees. The Prompt Table field changes to a Tree ID field and you can select your tree ID.
Prompt Table	Use to select a prompt table as needed.
Value	For Meta Value, the value field is automatically populated based on the state record and state record field selections. For example, if you select EPM_CORE_AET as your state record and BUSINESS_UNIT as your state record field, the value field is populated with : %BIND(EPM_CORE_AET.BUSINESS_UNIT). For Fixed Value , enter a character constant in quotes or a numeric constant without quotes. For System Variables, enter the variable to use.
Meta Value	Displays the meta value for any meta value objects.

Defining Data Manager Rules

This section provides an overview of Data Manager rule methods, lists prerequisites, and discusses how to:

• Define a Data Manager rule.

• Define sources.

• Define the target.

• Review and define the source 1 and source 2 columns.

• Review the mapped common dimensions.

• Review the generated SQL.

Understanding Data Manager Rules and Methods

Data Manager rules use metadata to specify the source and the target tables for moving, aggregating, or creating multidimensional engine output.

Most rules have two sources: the measure to be assigned (for example Activity-Based Management indirect costs, revenue amounts, or inventory quantities) and the basis for the assignment (for example, per cent sales by region, product, or channel). Another datamap is selected as the target of the rule.

Data Manager rules define three things: source tables, targets, and the method that you want to apply to the data from the source tables as it moves to the target. These methods are:

• Copy method.

• Arithmetic method.

• GL Mapper method.

• Spread even method.

• Prorata method.

• Tree aggregation method.

Copy Method

The copy method moves data from the source to the target, but does nothing to the data. You would typically use multidimensional data as the source.

An example of this method would be the copy of REVENUE_F00, which is already attributed to the customer, product, and channel dimensions, to PF_JRNL_F00. In this move, no spreading of the revenue amount from the source to the target occurs.

In addition, this example shows that you can also use the copy method to generate aggregate amounts since more than one row of data might exist in source 1 for a customer/product/channel intersection. The copy method allows this type of aggregation by using the sum column on the Define Target page.

Source 1 datamap definition:

• DIMs: CUST_ID, PRODUCT_ID, CHANNEL_ID

• MSR: MONETARY_AMOUNT

Define Target page:

• Target fields of CUST_ID, PRODUCT_ID, CHANNEL_ID mapped to corresponding source 1 fields

• Sum check box selected for MONETARY_AMOUNT and mapped to source 1

Source 1 data:

Target results:

Arithmetic Method

The arithmetic method applies an arithmetic operation (for example, add, subtract, multiply, or divide) to combine amounts in the sources that are grouped by common dimensions and source (or basis) mapped dimensions.

GL Mapper Method

The GL Mapper takes data from the general ledger tables and maps it to performance data. It populates the temporary table GLSTG. From GLSTG, you can use the copy method to move data directly to the performance journal or apply other methods to enrich your data.

For example, let's say that source 1 looks like this:

If you map 100 percent of the amounts from source accounts 110 and 111 to performance account 100000, the target would look like this:

Spread Even Method

The spread even method adds a dimension to your data, and spreads the fact amount evenly across the dimension. For example, you have revenue for three products as follows:

Source 1:

Source 2:

The target looks like this:

The amounts for product are spread evenly across the customers.

Prorata

The prorata method adds an additional dimension to your data and divides the amount across that dimension based on the percentage of the total amount. For example, you have revenue for three products as follows:

Source 1:

You also want to attribute that revenue to customers. The revenue by customers is:

Source 2:

The target looks like this:

The amounts for the products are prorated based on the percentage of total for each customer (C1 has two-thirds, or 66.67 percent, and C2 has one-third or 33.33 percent).

Tree Aggregation

In the tree aggregation method, measures are aggregated based on a tree hierarchy. The node names act as the dimension. For example, assume you have the following data for individual customer IDs.

Source 1:

Assume you have the following customer location tree structure.

Source 2:

Sample customer tree

The system rolls up the source data (customer IDs) to the next level up (regions) summarizes it, and reduces the number of rows. In the target table, the customer ID is now the tree node at the desired roll-up level.

This is how the target looks:

Prerequisites

Before setting up your Data Manager rules, you must:

• Complete set up of your metadata (tablemaps, datamaps, and constraints).

• Define any value objects on the Value Object page.

See Also

Setting Up and Working with EPM Foundation Metadata

Setting Up Value Objects

Pages Used to Set Up Data Manager Rules

Defining a Data Manager Rule

Access the Data Manager Rules - Define Rule page.

Method	Select the method for the rule you are defining. Options are: Arithmetic, Copy, GL Mapper, Prorata, Spread Even, and Tree Aggregation. See Understanding Data Manager Rules and Methods. Note. If the method is changed after the target fields have been populated, some fields might be reset to blank. This occurs if the current method has a source 2 and the new method does not. All source 2 fields that were mapped in the Data Manager Rules component are reset. The system displays a warning message. For a method of Arithmetic, select the operation to use: Addition (+), Division (/), Multiplication (*), and Subtraction (–). For a method of Prorata, the system prorates measures in source 1 across all common dimensions based on source 2 numbers. For a method of Spread Even, the system spreads source 1 measures evenly across all common dimensions based on source 2 numbers. For a method of Tree Aggregation, the system copies data elements from the source to the target based on the source 2 tree structures.
Save As	In correction mode, click the Save As button to access the Copy Rule page on which you can enter a new rule ID to which you want to copy the rule information. Enter an effective date as today's date. Click OK to save the changes and return to the Define Rule page.
	Click the Compilebutton on this page or other pages in the component to build the Data Manager rule. Review the generated SQL on the Data Manager Rules - SQL page.

Defining Sources

Access the Data Manager Rules - Define Source 1 page and the Data Manager Rules - Define Source 2 page.

Source 1	Select the constraint to tell the Data Manager what to assign. The constraints you define can limit the row selection. You can also define constraints to have no criteria, in which case they pull all the data. Most rules have two sources, with the exception of the copy and GL Mapper methods, which only require one source. Source 1 contains the measure to be assigned (for example, the Activity-Based Management costs), while source 2 contains the basis for the assignment (for example, spreading those costs either evenly or prorating them over customers). For the GL Mapper method, the source constraint must be GLM_LEDGER_ALL. This constraint must be built on the primary table of the LEDGER_VW tablemap. Note. To review the primary table of the LEDGER_VW tablemap, click the View/Edit Constraint link to navigate to the Constraint page. On the Constraint page, click the View/Edit Datamap link. For the tree aggregation method, a source 1 mapping field displays next to the Source 1 field. The Data Manager uses this field in conjunction with the tree node field to determine the join criteria in the SQL.
Source 2	Select the constraint to tell the Data Manager what basis to use. For the tree aggregation method, select the tree you want to use for aggregation. When you select the tree, the Tree Viewer opens and enables you to drill down to the tree level you require. You can also review the tree node information. Click the Select button on the Tree Viewer page to select the tree level. Note. You do not need to specify a source 2 for the copy or GL Mapper methods.
View/Edit Constraint	Click the link to view or edit the selected constraint. This option transfers you to the Constraint page for that constraint.
Update	Click the Update button to view an updated list of the source 1 or source 2 assignment values. You must be in correction mode to click this button.

Note. If you change a source constraint after the populating the target fields, the target fields that were mapped to source fields will not be lost so long as the datamap is the same.

Defining the Target

Access the Data Manager Rules - Define Target page.

Target	Select the datamap to use as the target for the processed data. The system populates the Target Object Field Map grid with target fields based on the datamap you select. The system handles the mapping of all the fields except for the department and product fields, which you can only map to the source 1 department or product, a fixed value, or a meta value. For the GL Mapper method, the target is GLSTG. Warning! For the prorata and spread even methods, each target field must map to a source 1 field, source 2 field, or value object. The system issues a warning message if any dimensions exist on the datamap that are not mapped to a target field.
Prorata Measure	For a method of Prorata, select the measure to use for the prorata calculation. Only source 2 fields that are defined as measures on the datamap display in the prompt list.
Measure	For a method of Arithmetic, select the measure to use. The values in the list box are based on the selected source 2 constraint.
Target Description and Metadata Type	The system populates these fields based on the datamap you select as the target. The target description comes from the datamap definition.
RvrsSign (reverse sign)	Select to reverse the sign of the amount when the data is copied to the target table. Check boxes are available in this column only for target fields that are defined as a measure on the target datamap.
Sum	For a method of Copy, select this check box to total the amounts when the source 1 data is copied to the target table. Check boxes are available in this column only for target fields that are defined as a measure on the target datamap.
From	This field can be: Source 1: Data is copied from the source 1 table to the target field. Fixed Value: A constant value is inserted into the target field. Meta Value: A meta value is inserted into the target field. Sys Var: (system variable) A system variable is inserted into the target field. Note. For the GL Mapper method, you can only specify the From field for the department and product ID.
Source Description	If the value in the From field is Source 1 or if the value is mapped from source 1, a list box of the fields that were defined in source 1 is available. If the value in the From field is Source 2 or if the value is mapped from source 2, a list box of the fields that were defined in source 2 is available. If one of the value object types is specified for the value in the From field, the drop-down list box contains the objects that correspond to the specified value object class.
Prorata	For a method of Prorata, select this check box for any measures you want to use for the proration. You must select at least one measure field for prorata.
Arithmetic	For a method of Arithmetic, select this check box for a field in which you want to use in the arithmetic operation that is specified on the Data Manager Rules - Define Rule page.

Target Definition for the Copy Method

When you are setting up the target field map for the copy method:

• If you select a target measure field that is mapped to a source 1 field for a sum operation, all other measures that are mapped to source 1 fields must also be selected for a sum operation.

• If you select the sum check box for any of the fields, you can map only key source 1 fields.

• If you do not select the sum check box for any of the fields, you can map any source 1 fields to any target fields.

  This might result in duplicate data when you run the Data Manager engine. This is because you are not grouping the data by the key values.

• You can use expressions for your mappings.

Target Definition for the Prorata Method

When you are setting up the target field map for the prorata method:

• Only three mapped measures are allowed.

• The source 1 and source 2 datamaps must both have at least one key field that is marked as a dimension.

• All non-measure target fields can be mapped only to source 1 or source 2 fields that are marked as dimensions (keys) on the datamap.

• All measure target fields can only be mapped to source 1, fixed value, or meta value fields.

• At least one measure target field must be marked for prorata.

• If a target field is mapped to a source 1 field, it must be marked for prorata.

Target Definition for the Spread Even Method

When you are setting up the target field map for the spread even method:

• Only three mapped measures are allowed.

• The source 1 and source 2 datamaps must both have at least one key field that is marked as a dimension.

• All non-measure target fields can only be mapped to source 1 or source 2 fields that are marked as dimensions (keys) on the datamap.

• All measure target fields can only be mapped to source 1, fixed value, or meta value fields.

  Data Manager uses all the source 1 mappings for the spread even calculation.

• At least one measure target field must be mapped to a source 1 field.

Target Definition for Tree Aggregation Method

When you are setting up the target field map for the tree aggregation method:

• Each target field must have a source 1 field, tree node, or value object to which it is mapped.

• Only one target field can be mapped to the source 2 tree node.

  This tree node field is used in conjunction with the source 1 mapping field for join criteria in the SQL.

• You must have at least one non-measure target field mapped to source 1.

• If the target field is mapped to source 2, you can select from all the fields for that source.

  If a target field is mapped to source 2, the only selection available is Tree Node.

See Also

Setting Up Value Objects

Reviewing and Defining the Source 1 and Source 2 Columns

Access the Data Manager Rules - DataSet for Source 1 page and Data Manager Rules - DataSet for Source 2 page.

Select

Select this check box to include the dimension or measure.

Note. The DataSet for Source 2 page does not display for the copy or GL Mapper method.

Reviewing the Mapped Common Dimensions

Access the Data Manager Rules - DataSet for Common DIMs page

This page shows the common dimensions that exist between source 1 and source 2. A dimension is common if it has a matching description in the source 1 and source 2 datamap fields.

For the prorata method, the page also shows the prorata measure marked as Sum.

Note. Common dimensions are very important. They determine the join criteria for the method. The criteria are based on the datamap, so always review this page to ensure the results are calculating as you expect.

Reviewing the Generated SQL

Access the Data Manager Rules - SQL page.

Once you have compiled a rule using the Compile button, review the generated SQL statement.

All %Bind and %SQL objects are resolved at run-time. There is only one SQL statement that is generated for each method.

A copy of this SQL is stored in the SQL repository with the SQL object ID prefix that is shown in this component. A sequential number for each SQL statement completes the SQL object name for the repository.

Defining Data Manager Rule Sets

You must define a Data Manager rule set for any Data Manager rules that you want to process. You can also use rule sets to combine multiple rules in one run of the Data Manager engine. Rules in a rule set are run in the order shown on the Data Manager Rule Sets page. The first rule must complete successfully before the second rule starts. The system places the data from the first rule in a temporary table (assigned by the engine) that will be the source of the second rule, and so on.

Note. A rule must be in a rule set, even if only one rule is processed.

This section discusses how to set up Data Manager rule sets.

Pages Used to Define Data Manager Rule Sets

Setting Up Data Manager Rule Sets

Access the Assignment Rule Sets page.

RuleSet	A unique identifier for this rule set definition.
Sequence	Enter a number, such as 100, for the first rule ID in the rule set. The next rule ID to run would have a sequence of 200. The actual sequence number is not important; it represents the order in which you want to process rules. The sequence must be unique.
Rule ID	Select the Data Manager rule to include in the rule set. You create the rules using the Data Manager Rules component.

Click the Notes tab to enter a more detailed description of this rule set.

Renaming Data Manager Rules

This section discusses how to rename a Data Manager rule.

Page Used to Rename Data Manager Rules

Renaming a Data Manager Rule

Access the Rename Data Manager Rule page.

SetID and Rule ID	Select the setID and rule ID for the rule you want to rename.
Search	Click the Search button. The search populates the grid with the names of the Data Manager rule sets that is affected by this rename.
Rename	To proceed with the renaming process, click the Rename button and enter a new name for the rule. Every instance in which the original rule name is used is changed to the new name.

Associating Data Manager Rule Sets With a Job

The next step in the Data Manager process is associating the rule set with a Data Manager job. Each unique run of the Data Manager engine is given a job ID. You must establish an association to the rules and the actual job that will run them on the Job Association page. When the jobstream that contains the defined Data Manager job ID runs, it uses the setup on the Job Association page to find the Data Manager rule set to execute.

Note. Each time that you run a Enterprise Performance Management engine , it must have a unique job ID. These jobs must then be run in a jobstream.

This section discusses how to define rule sets to be run for a given job.

Prerequisites

Before you can associate rule sets with job, you must:

• Set up the Data Manager job ID.

• Set up a jobstream for the job ID.

See Also

Streamlining Processing with Jobstreams

Pages Used to Associate Data Manager Rule Sets With a Job

Define Rules Sets to be Run for a Given Job

Access the Job Association page.

Job ID	Select the job ID. The job ID was created in the job metadata and represents a unique instance of a Data Manager engine in a jobstream.
Ledger ID	Select a ledger ID. This is required for the Profit Manager. See Processing and Posting Journals.
Sequence	Enter a number, such as 100, for the first rule set in the job association. The next rule set to run would have a sequence of 200. The actual sequence number is not important; it represents the order in which you want to process rule sets. The sequence must be unique.
Rule Set	Select the rule set or rule sets to include in the job. You create rule sets on the Data Manger Rule Set - Assignment Rule Sets page.

Click the Notes tab to enter a more detailed description of this job association.

Running the Data Manager Engine

As a last step, you run the Data Manager engine in a jobstream. As you run the jobstream:

• Use the Process Monitor to verify the status of your job.

• Review the results by querying the target table for the Data Manager rules that you have run.

• Review any error messages using the Error Messages component.

See Also

Running Jobstreams

Viewing Engine Messages

Defining Allocation Manager Rules

This section provides an overview of fixed source and fixed basis options in allocations, lists prerequisites, and discusses how to:

• Determine the list of dimensions to use.

• Create a list of sources.

• Define an Allocation Manager rule.

• Define the allocation rule source.

• Define the allocation rule basis.

• Review common dimensions.

• Define the target.

• Assign residual amounts.

• Specify offset target information.

Understanding the Fixed Source and Fixed Basis Options

You use datamap metadata to define the tables that contain the source, basis, and target for you allocation in the Allocation Manager rule. However, in some cases you might not have source or basis data stored in tables in your database. To accommodate this situation, we deliver a set of metadata (the FIX_BASIS datamap, and PF_AL_FIX_SOURCE and PF_AL_FIX_BASIS constraints) that point to the fixed source and basis table (PS_FP_AL_FIX_BASIS). You can tailor this table by adding your organization's dimensions to it on the Fixed Dimensions page. Use the Fixed Dimension page to list the dimensions and assign prompt tables and trees and select values for each dimension.

Note. Fixed source and basis is used with the Allocation Manager only. It is available with all methods except period-based allocation.

Note. Before you create an Allocation Manager rule to associate with a setID, create a PF_AL_FIX_BASIS and PF_AL_FIX_SOURCE filter and constraint for that setID. You can model the setup for the PF_AL_FIX_BASIS and PF_AL_FIX_SOURCE filter and constraint using the sample data under the SHARE setID.

Warning! For period-based allocations, the Merge engine (PF_MERGE) moves data directly from the temporary table to the target table without using the edit process.

Prerequisites

Before setting up your Allocation Manager rules, you must:

• Complete the setup of your metadata (tablemaps, datamaps, and constraints).

• Define any value objects on the Value Object page.

See Also

Setting Up and Working with EPM Foundation Metadata

Setting Up Value Objects

Pages Used to Define Allocation Manager Rules

Determining the List of Dimensions to Use

Access the Fixed Dimension Setup page.

Dimension Name	Each dimension on this page is based on the FIX_BASIS datamap. This datamap is delivered with your system and consists of a generic table into which you can enter your organization-specific information. You can define a maximum of 12 dimensions for this datamap. PeopleSoft delivers this datamap with several dimensions; however, you can create more, if necessary.
Lookup Table and Lookup Tree	For each dimension, assign either prompt tables, trees, or both to select values.
Refresh	Changes to the FIX_BASIS datamap do not automatically display on this page. Click the Refresh button to update the page with any additions or deletions to the datamap.

Note. You can only change dimensions. Do not change attributes or the measure.

Creating a List of Sources

Access the Allocation DataMap Setup page.

DataMap Code	This code identifies the datamap. Note. You must create the datamaps before using the Datamap component.
Target	If selected, the target indicates that the datamap can be used as a target. This check box is only an indicator. This is defined as part of the datamap definition.
	Click the Select Dimensions button to access the Select Dimensions page on which you can specify the metadata types (Attribute, Dimension, or Measure) for the dimension fields in your datamaps. When you are done, click OK to save your changes and return to the Allocation DataMap Setup page.

See Also

Setting Up Datamaps

Defining an Allocation Manager Rule

Access the Rules - Method page.

Method	Select the allocation method. The method determines the calculation options, such as how to determine the source amounts going to the targets. The available methods are: Arithmetic, Copy, Prorata, and Spread Even.
Arithmetic Operation	For a method of Arithmetic, select the operation to use from Addition (+), Division (/), Multiplication (*), and Subtraction (-).
Period Based Allocation	This check box is only available for selection for the Prorata and Spread Even methods. Select to specify period-based allocation. Period-based allocation enables you to allocate from one period to one or more additional periods. For example, you may allocate quarterly source data into monthly target data based upon monthly basis data. To do this, a scenario ID must be specified for the basis on the Basis page. The scenario ID determines from which calendar to select the basis data. The calendar that is identified by the scenario that you selected on the Basis page determines which periods from the basis are used to perform the prorata or spread even processes. Note. Your source period must include one or more periods from the basis calendar. For example, if you source period is monthly, your basis cannot be quarterly.
Allocate Rounding Differences	For the Prorata and Spread Even methods, clear this check box to disable rounding. By disabling rounding, you can increase system performance. If rounding is disabled, the system rounds all amounts that are prorated or distributed to the closest whole number for each period. This takes considerably less time than it would using rounding. For example, it is more time consuming to spread an amount of 1,0000 evenly across twelve periods because the results equals 83.33333333333 per period.
Notes	Enter any notes to further describe the Allocation Manager rule.
Save As	In correction mode, click the Save As button to access the Copy Rule page, on which you can enter a new rule ID and copy the rule information. Enter an effective date. The system default is today's date. Click OK to save the changes and return to the Method page.
	Click to individually compile the Allocation Manager rule. You can also use Mass Compile. Note. You cannot use Mass Compile for allocation rules that are period-based or have the inter-business unit option selected. The system will skip these . You must compile these rules directly from the Allocation Manager Rules component.

Defining the Allocation Rule Source

Access the Rules - Source page.

You can either use a fixed source by selecting it from the Fixed Source page or enter a source.

Specifying a Fixed Sourece

The dimensions that you select appear in the Fixed Sources grid.

Specifying a Source

If you are not using fixed source, you must specify the source to use.

Defining the Allocation Rule Basis

Access the Rules - Basis page.

You can either opt to use a fixed basis or enter a basis.

Specifying a Fixed Basis

Tree Level

Select the tree level to which you want to resolve your allocation. Your options are: No Tree Allocation, Allocate to leaf level, or Allocate to next node.

Select the values for each of the dimensions that you selected on the Fixed Basis Dimension Setup page.

Specifying a Basis

Reviewing Common Dimensions

Access the Rules - Source to Basis Relationship page.

This page lists the common dimensions. Common dimensions are very important as they are used to determine the divisor, therefore the ratio, for the spread even and prorata methods. For all methods, they determine how the source and basis are to be grouped before applying any mathematical formulas. Select from which source to base dimensions by selecting the Use check box.

The system determines the common dimensions using the descriptions of the datamaps for the source and basis. It considers that any source and basis fields with the same description represent the same information and are therefore a common dimension if the fields are marked as dimensions on both the source and basis. When looking for common dimensions, the system ignores case and spaces at the beginning and end of the description.

Defining the Target

Access the Rules - Target page.

Assigning Residual Amounts (Optional)

Access the Rules - Residual page.

The following table provides an example of an arithmetic allocation rule in which the residual source amount is set up with a target department value of RES (Residual). DIV1, 2, and 3 use a total of 400. The residual amount is 600, so that amount is placed in the RES account.

Specifying Offset Target Information (Optional)

Access the Rules - Offset page.

This page enables you to calculate offset for the target balance. Offset accounts aid in balancing source transaction and budget entries. You can use offsets to balance ledgers.

The following is an example of an arithmetic method offset allocation account:

In this example, the offset account is equal to 400, which is the same total for Divisions (DIV) 1, 2, and 3.

Defining Allocation Manager Rule Sets

This section provides an overview of Allocation Manager rule sets and discusses how to

• Set up Allocation Manager rule sets.

• Define post-processing routines for an allocation rule set.

Understanding Allocation Manager Rule Sets

You must define an Allocation Manager rule set for any Allocation Manager rules that you want to process. You can also use rule sets to combine multiple rules in one run of the Allocation Manager engine. Rules in a rule set run in the order that is shown on the Allocation Manager Rule Sets page. The first rule must complete successfully before the second rule starts. The system places the data from the first rule in a temporary table (which is assigned by the engine) that will be the source of the second rule, and so on.

Note. A rule must be included in a rule set, even if only one rule is processed.

After you define a rule set, you can create post-processing routines that further process the results of the rule set. You can also tie the routines to a particular rule set so that they automatically run when the rule set completes. The following sections summarize specific features of the post-processing routines.

Auditing Allocation Rules

This feature provides visibility into the inputs and rules that calculate your allocations. Runtime information, source data transformations, and basis data transformations are some of the data that is captured by the audit feature. The data is captured in logs and is stored in the corresponding data warehouse tables. The following table contains a complete list of delivered audit logs and the data warehouse table in which the data reside:

You can view the audit logs using PeopleSoft Query.

Merging Allocation Results to Permanent Tables

After an allocation rule set completes processing, the results are stored in a temporary target data warehouse table. This feature automatically loads the results that are stored in the temporary target table to a permanent non-journal target table—for example, PS_PF_AL_TGT.

Validating Journals

If you load your data to a journal target table, this feature ensures the journal dimensions have valid values. For example, you might create allocation rules at the beginning of the year. At the time of allocation rule creation, you specified account 100 as one of the target accounts for the allocation. Account 100 is a valid account. Suppose that during the year, account 100 is deactivated. If the allocation process is run and validate journal is checked, the process creates an error, as account 100 is no longer valid. Invalid journal dimensions are sent to the journal error table (PF_JRNL_E00).

Reversing Journals

If you load your data to a journal target table, this feature automatically reverses the journal entry. This process results in two journal entries: the original journal and another with all the amount signs reversed. In addition, you can specify whether you want to reverse a journal for the same or alternate accounting period.

Pages Used to Define Allocation Manager Rule Sets and Post-Processing Routines

Setting Up Allocation Manager Rule Sets

Access the Allocation Manager Rule Set page.

Ruleset ID

Displays the unique identifier for this rule set definition.

Rules in Rule Set

Defining Post-Processing Routines for an Allocation Rule Set

Access the Results Processing page.

Ruleset ID	Displays the unique identifier for this rule set definition.
Create Audit Trail	Select this check box to generate audit logs of the inputs and rules that calculate your allocations. Runtime information, source data transformations, and basis data transformations are some of the data that is captured by the audit logs. You can view the audit logs using PeopleSoft Query.

Options

Journal Options

The following table provides examples of the edit, validate, and post options used in combination with one another and the resulting output of the combination:

Please note that these are merely examples of edit, validate, and post option-combinations; you can choose a number of different combinations.

Renaming Allocation Manager Rules

This section discusses how to rename an Allocation Manager rule.

Page Used to Rename Allocation Manager Rules

Renaming an Allocation Manager Rule

Access the Rename Allocation Rule page.

SetID and Rule ID	Select the setID and rule to rename.
Search	Click the Search button. The system populates the Search Results grid with a list of the rule sets that affected by the renaming process.
Rename	To proceed with the renaming process, click the Rename button and enter a new name for the rule. Every instance of the original rule name is changed to the new name.

Associating Allocation Manager Rules Sets With a Job

The next step in the Allocation Manager process is to associate the rule set with an Allocation Manager job. Each unique run of the Allocation Manager engine is assigned a job ID. You must associate the rules with the actual job that will run them on the Allocation Manager Rule Set Job Association page. When the jobstream that contains the defined Allocation Manager job ID runs, it uses the setup on the Allocation Manager Rule Set Job Association page to find the Allocation Manager rule set to execute.

Note. Each time that you run an Enterprise Performance Management engine, it must have a unique job ID. These jobs must then be run in a jobstream.

This section discusses how to define Allocation Manager rule sets to be run for a given job.

Prerequisites

Before you can associate rule sets with job, you must:

• Set up the Allocation Manager job ID.

• Set up a jobstream for the job ID.

See Also

Streamlining Processing with Jobstreams

Page Used to Associate Allocation Manager Rule Sets with a Job

Defining Allocation Manager Rule Sets to Run for a Given Job

Access the Allocation Manager Rule Set Job Association page.

Job ID	Displays the unique instance of an Allocation Manager engine in a jobstream.
Ledger ID	Select a ledger ID. This is required for the Profit Manager. See Processing and Posting Journals.
Sequence Number	Enter a number, such as 100, for the first rule set in the job association. The next rule set to run would have a sequence of 200. The actual sequence number is not important; it represents the order in which you want to process rule sets. The sequence must be unique.
Rule Set	Select the rule set or rule sets to include in the job. You create rule sets on the Data Manger Rule Set - Assignment Rule Sets page.

Processing Allocations

As a last step, run the Allocation Manager engine in a jobstream. As you run the jobstream:

• Use the Process Monitor to verify the status of your job.

• Review the results by querying the target table for the Allocation Manager rules that you have run.

• Review any error messages using the Error Messages component.

See Also

Running Jobstreams

Viewing Engine Messages