sap performance management for financial services

SAP Performance Management for Financial ServicesContent
1 SAP Performance Management for Financial Services. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Environments and Roles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1 Analysis Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Execution Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Modeling Environment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Allocation Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8 Calculation Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Calculation Unit Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Check Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Collection Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60 Conversion Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65 Derivation Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Description Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72 Editor for Data Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Environment Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73 Field Sets Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Funds Transfer Pricing Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87 Intragroup Transaction Elimination Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Item Form Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Item Report Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Item Reconciliation Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Join Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Lookup Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Management of Unassigned Items Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Mapping Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Model Table Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Model View Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Model Writer Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Transfer Structure Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 View Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Remote Function Adapter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Result Group Write Adapter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Planing Engine Write Adapter Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Valuation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
2.4 Application Monitor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 2.5 Integrate Data Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
2 C U S T O M E R SAP Performance Management for Financial Services
Content
2.6 Environments and Calculation Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
3 Best Practices for a Model Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 3.1 Integrate Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 3.2 Collect Source Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .169 3.3 Enrich Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 3.4 Create (Cost) Drivers and Calculate FTP Rates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 3.5 Execute Allocations/Calculations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Manage unassigned items. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Checks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
3.6 Transfer Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172 3.7 Reporting, Analysis and What-if Simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .173
Update / Reconciliation Postings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
4 APPENDIX. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
SAP Performance Management for Financial Services Content C U S T O M E R 3
1 SAP Performance Management for Financial Services
Powered by SAP HANA, SAP Performance Management for Financial Services enables banking and insurance companies to maintain and execute complex allocation and funds transfer pricing models. This allows you to create the data foundation for flexible, near real-time, high-speed profitability analysis for insurance and banking products. The solution provides a configurable framework to create allocations down to single contract or coverage level.
It supports the following scenarios:
Modeling and execution of cost and revenue allocation and calculation models to determine profitability. For example, at individual contract level or at product, channel and customer level.
Modeling and execution of funds transfer pricing models to determine financial asset profitability. For example, at individual contract event level, at position level, product level or G/L level.
Item reporting and output analysis at granular level or aggregated results for the following: Reporting and analysis Simulation and what-if analysis Planning Measurement
The solution supports the integration of data sources, including the following: ERP data Core banking data Core insurance data Planning data Actuarial /risk data
SAP Performance Management for Financial Services comes with preconfigured calculations and models (sample content). This demonstrates the capabilities of the solution in an integrated environment and allows easy adaptation by the business department.
The following sections explain the main concepts, components and functions of the solution.
SAP Performance Management for Financial Services
2 Environments and Roles
SAP Performance Management for Financial Services is targeted toward the business user. It is designed to enable the business department (for example, Accounting and Controlling) to operate modelling, execution and analysis of cost and revenue data with minimal IT involvement. The solution is delivered with three preconfigured user roles and provides each of them with a specialized working environment optimized to support them in their main area of responsibility:
1. Modeling Environment Modeling users define and set up the data and calculation models, which are used to create the results for calculation processes such as simulation, planning, measurement, and analysis. The models usually include parameters to change assumptions easily later on and to make them reusable. The modelling environment allows users to access all of the features provided by the solution.
2. Execution Environment Execution users use the defined models and can change parameters that have been defined during modelling. Access to the execution environment allows users to execute the main functions of the model, including reports and controls, and to manage parameters.
3. Analysis Environment Analysis users use the results of the executed calculation models. Access to the analysis environment allows users to access all the analysis and reporting capabilities, including the creation of new reports and the individual layout customizing.
2.1 Analysis Environment
The analysis environment is designed for analysis users to access and analyze data using preconfigured reports, and to configure new report layouts based on the output of selected functions.
Example Example 1:
The modeling user has preconfigured an item report with 30 characteristics and 200 key figures to analyze the profitability of all assets. The user has selected the characteristics "Channel" and "Product Group" as analysis dimensions, and has given the analysis user the authorization to use this report by selecting the Analysis relevant checkbox for this function in the function tree on the left-hand side in the hierarchy. The analysis user can then do the following:
1. View the results of this report at any time and choose from the values of the analysis dimensions to slice and dice, for example, by choosing only the channel "Online" and the product group "Giro".
2. Use the other 28 characteristics for new filters and selections of the report to enable deeper analysis, for example, at customer, product, or branch level.
SAP Performance Management for Financial Services Environments and Roles C U S T O M E R 5
Example Example 2:
The modeling user has preconfigured a collection function containing 40 characteristics and 300 key figures as a result of allocation. The user has registered this function in the output template of the surrounding calculation unit to make this output available to the analysis user. The analysis user can then do the following:
1. View the results directly in the output set. Here the user can also download it into Microsoft Excel, if feasible.
2. Create their own report using this function as input, for example, by using the item report function.
2.2 Execution Environment
The execution environment is designed for execution users, who are in charge of running the solution. They can run preconfigured functions and also run a report. In addition, they can use parameters to control the execution of the model.
Example Example 1:
The modeling user has configured a profitability model that is to be executed by the execution user on a regular basis. The execution user enters the parameter (for example, Key Date or Fiscal Period) that influences the calculation runs of the profitability model.
Example Example 2:
The modeling user has configured a profitability model that is to be executed by the execution user on a regular basis, but is also intended for use in simulations. The execution user executes the model with different parameter sets for simulation purposes. The user enters or uploads parameters that influence the calculation (for example, specific interest rate curves or assumed business). The execution user then runs the profitability model and examines the results.
2.3 Modeling Environment
The modeling environment is used by modeling users to set up and change data and calculation models. This can be done by defining new models or by copying the sample content as a basis and then making adjustments. The modeling user has all authorizations and also defines what the execution user and the analysis user are allowed to do.
In the modeling environment, you typically start with the copy of an existing model, for example, the sample content shipped with the software. This is where all adjustments, changes, and enhancements are made to fulfill
Environments and Roles
individual customer requirements. The following functions can be used for the setup of data and calculation models:
1. Allocation Function to perform direct and indirect allocations
2. Calculation Function to perform mathematical formulas and sequences of interdependent mathematical formulas on data
3. Calculation Unit Function to encapsulate another group of functions and make them reusable
4. Check Function to perform various checks on calculated data
5. Collection Function to perform data collection from various functions into one combined output
6. Conversion Function to perform currency conversion
7. Derivation Function to perform if-then-else enrichments of data
8. Description Function to describe processes and topics used for the documentation of models
9. Editor for Data Function to enter tabular parameters and to manually upload data
10. Environment Function to register all required fields (characteristics and key figures) and the connection to the database
11. Field Set Function to group fields for a common purpose so that they have to be entered only once and can be reused in various other functions
12. Funds Transfer Pricing Function to perform funds transfer pricing rate calculations based on duration/matched maturity and on the net present value approach
13. Intra-Group-Trans. Elimination Function to perform the nivellation of intragroup transactions
14. Item Form Function to define formulas and how to calculate item sheets (for example, for P/L schemas)
15. Item Report Function to perform data preparation
16. Item Reconciliation Function to define reconciliation mappings to ensure data completeness between applications
17. Join Function to join two or more inputs based on at least one common field
18. Lookup Function to look up missing values in a lookup table and to transfer these values to the original table
19. Management of unassigned Items Function to define suitable allocation characteristics for fields that could not be allocated successfully
20.Mapping Function to map source fields to target fields
21. Model Table Data table to temporarily store custom data locally.
22.Model View View on an external data source, such as a database table or a view
23.Model Writer Function to store temporary data in a model table
24.Transfer Structure Function to perform a transfer from accounting-based data to costing-based data (also called denormalization)
25. View Function to project or aggregate data, including filtering options and formulas
26.Remote Function Adapter Function to perform an ABAP-based remote function call (for example, to reconcile aggregated P/L results with FI-GL)
27. Results Group Write Adapter Function to perform a write call to an RDL result group optimized for SAP HANA (for example, to store final detailed actual profitability results)
28.Planning Engine Write Adapter Function to perform a write call to a BW/BPC embedded InfoCube optimized for SAP HANA (for example, to store detailed planning profitability results) or DataStore objects (DSO).
29.Valuation Function to perform comprehensive calculations with different valuation methods (for example, interpolation or discounting).
2.3.1 Allocation Function
Context
The Allocation function is used to distribute key figures from a higher level entity to a lower (more granular) level entity based on a distribution base.
The entity from which key figures are distributed is known as the sender. The sender key figures represent the values to be allocated by the allocation function.
The entity that receives the distributed key figures is known as the receiver. One or more key figures from the receiver constitute the distribution base or bases.
The following types of allocation are available:
1. Generic: The system uses direct allocation logic if the sender and receiver have common characteristics. Otherwise, the system uses indirect allocation logic.
2. Indirect: Distributes key figures from the sender to the receiver using a distribution base on the receiver side. 3. Direct: Distributes key figures from the sender to the receiver according to characteristics from both sides
and based on the distribution base on the receiver side. 4. Global Expense Indirect: Follows the logic of an indirect allocation. It also includes offset records. 5. Global Expenses Direct: Follows the logic of a direct allocation. It also includes offset records.
If the system does not find any matching characteristic values (no receivers are found for a given sender record) when you use Direct allocation or Indirect allocation (if some characteristics are marked as ‘self’ ), the sender records that do not match become ‘unassigned items’. You can process this in the Management of Unassigned Items function.
Prerequisites
To be able to use this function, you must have configured the functions that provide you sender and receiver data.
Roadmap Step 1- Settings
1. Choose a sender type from the dropdown list (the default setting is Generic). 2. Choose a sender rule (the default setting is Key Figure). 3. If you have selected Fixed Rate as the sender rule, you can enter a percentage (the default value is “100”). 4. If you have selected Indirect as the sender type, you can add a receiver summary level.
1. Choose a field set from the Receiver Summary Level dropdown list. 2. You can also choose Field Sets directly. A dialog box appears. 3. In Roadmap step 1, select the field set that you want to use or create a new field set under Field Set
function. 4. To update the field set, go to Roadmap step 2. Here you can change the hierarchy by choosing Up or
Down. You can also add and remove fields. 5. Optional: You can also choose the following:
1. Include Sender Characteristics 2. Include Receiver Key Figures 3. Distribute empty characteristic values (set by default). 4. Include all Receivers 5. Aggregate Allocation Results by Receiver.
6. To save your changes, choose Save.
Roadmap Step 2- Sender
1. Choose an input function from the dropdown list. 2. Choose a view type from the dropdown list (the default setting is Projection). 3. For basic information about configuring views, see View Function [page 140] . 4. To generate, choose Generate. 5. For a preview, choose Test. 6. To save your changes, choose Save.
Roadmap Step 3 - Receiver
1. Choose an input function from the dropdown list. 2. Choose a view type from the dropdown list (the default setting is Projection). 3. For basic information about configuring views, see the View function. 4. Optional: To generate, choose Generate.
5. Optional: For a preview, choose Test. 6. To save your changes, choose Save.
Roadmap Step 4 - Tracing Factor
1. Configure the receiver rule. 1. Choose a receiver rule from the dropdown list.
1. Even will skip the next three steps. 2. Cost Driver will continue with the next step.
2. Choose a field as the distribution base. 3. To define a receiver summary level in the first roadmap step, choose a field as the summary level
distribution base. 4. Choose Handle Negative Tracing Factor from the dropdown list. The default setting is No (negative
unchanged). 5. Choose which values are to be adjusted from the dropdown list. The default setting is No Adjustment. 6. Optional: Choose Offset Record Aggregation. (Only for global expense allocations)
2. Configure the Cumulation. (Only for global expense allocations) 1. Choose Term from the dropdown list. 2. Enter a value in the Term Minimum Value field. 3. Enter a value in the Term Maximum Value field. 4. Choose Cumulation Counter from the dropdown list.
3. Configure Iteration. (Only for global expense allocations) 1. Enter a value in the Cycle Maximum Value field. 2. Choose Iteration Counter from the dropdown list.
4. To generate, choose Generate. 5. Optional: For a preview, choose Test. 6. To save your changes, choose Save.
Roadmap Step 5 - Unassigned Items
1. Choose Management of Unassigned Items. For basic information about configuring the management of unassigned Items, see Management of Unassigned Items Function [page 120] .
2. Optional: You can choose a rule set directly from the Rule Set dropdown list. 3. Optional: To update the list of unassigned items, choose Refresh. 4. Optional: Choose a field set. 5. Choose a run set. The default setting is Run Set. 6. To apply the selected rule set, choose Run. 7. To save your changes, choose Save.
Example Example: Generic Allocation
Generic allocation automatically determines whether direct or indirect allocation logic is to be applied during processing. This depends on the matching characteristics and key figures of the input data. If the sender and receiver have common fields, direct allocation logic is applied. Otherwise, indirect allocation logic is applied.
Example Indirect Allocation Table 1: Roadmap Step 1: Settings
Sender Type Indirect
Sender block size
Receiver Summary Level
Process Unassigned Items
Cost Center IT Cost
Contract Coverge Product Lowest Level DB
20150000 6981 224 100
20150000 6982 224 200
20150003 6985 238 100
20150004 6986 238 200
20150007 6989 238 400
Table 4: Roadmap Step 4: Tracing Factor
Receiver Rule Cost Driver
Summary Level Distribution Base
Adjust Value No Adjustment
Offset Record Aggregation X
Contract Coverage Product IT Cost
20150000 6981 224 20,000.00
20150000 6982 224 40,000.00
20150003 6985 238 20,000.00
20150004 6986 238 40,000.00
20150007 6989 238 80,000.00
Example Indirect Allocation using Summary Level Table 6: Roadmap Step 1: Settings
Sender Type Indirect
Receiver Summary Level FieldSet1 (see below)
Distribute empty characteristic values
>> Fields of FieldSet1
Table 7: Roadmap Step 2: Sender (data)
Cost center IT COST
Contract Coverage Product Channel Customer Lowest Level DB
Summary Level DB
Summary Level Distribution Base Summary Level Distribution
Handle Negative Tracing Factor No (Negative unchanged)
20150000 6981 224 92H2 DD 18,000.00
20150000 6982 224 92H2 DD 12,000.00
20150003 6985 238 CXH0 DD 27,500.00
20150004 6986 238 CXH0 DD 22,500.00
20150007 6989 238 92H2 AA 4,000.00
Contract Coverage Product Channel Customer IT COST
20150008 6990 238 92H2 AA 16,000.00
Explanation of Indirect Allocation on Summary Level:
Table 11: 1. The receiver’s records are grouped by the Summary Level fields used in Roadmap Step 1
Summary Level DB
20150000 6981 224 92H2 DD 60 3
20150000 6982 224 92H2 DD 40 3
20150003 6985 238 CXH0 DD 55 5
20150004 6986 238 CXH0 DD 45 5
20150007 6989 238 92H2 AA 20 2
20150008 6990 238 92H2 AA 80 2
Table 12: After step 1: there are 3 allocation groups for the summary level
Product Channel Customer Summary Level DB Additional Information
224 92H2 DD 3 A
238 CXH0 DD 5 B
238 92H2 AA 2 C
Table 13: 2. Allocation on summary level (not the expected result after allocation)
Part of the Receiver’s data Summary level Additional Information
Product Channel Customer Summary Level DB
Distribution % ALLO CATED IT COST
-
224 92H2 DD 3 30.00% 30,000.00 30% of the IT Cost (100,000)
Part of the Receiver’s data Summary level Additional Information
238 CXH0 DD 5 50.00% 50,000.00 50% of the IT Cost (100,000)
238 92H2 AA 2 20.00% 20,000.00 20% of the IT Cost (100,000)
Table 14: 3. Allocation on lowest level based on the summary level ALLOCATED IT COST
Part of the Receiver’s data Lowest level Additional Information
Product Channel Customer Lowest Level DB
Distribution % ALLO CATED IT COST
-
224 92H2 DD 60 60.00% 18,000.00 60% of Group A IT COST (30,000 * 60%)
224 92H2 DD 40 40.00% 12,000.00 40% of Group A IT COST (30,000 * 40%)
238 CXH0 DD 55 55.00% 27,500.00 55% of Group B IT COST (50,000 * 55%)
238 CXH0 DD 45 45.00% 22,500.00 45% of Group B IT COST (50,000 * 45%)
238 92H2 AA 20 20.00% 4,000.00 20% of Group C IT COST (20,000 * 20%)
Part of the Receiver’s data Lowest level Additional Information
238 92H2 AA 80 80.00% 16,000.00 80% of Group C IT COST (20,000 * 80%)
Table 15: 4. The following is the final Indirect Allocation Result - the sum of all IT COST records should be 100,000
Contract Coverage Product Channel Customer IT COST
20150000 6981 224 92H2 DD 18,000.00
20150000 6982 224 92H2 DD 12,000.00
20150003 6985 238 CXH0 DD 27,500.00
20150004 6986 238 CXH0 DD 22,500.00
20150007 6989 238 92H2 AA 4,000.00
20150008 6990 238 92H2 AA 16,000.00
Example Direct Allocation Table 16: Roadmap Step 1: Settings
Sender Type Direct
Sender block size
Distribute empty characteristic values
Product Channel Customer Premium
20150000 6981 224 92H2 DD 3
20150001 6983 224 92H2 DD 7
20150002 6984 238 CXH0 DD 50
20150005 6987 238 CXH0 DD 50
20150006 6988 238 92H2 AA 10
20150009 6990 238 92H2 AA 40
Summary Level Distribution Base Summary Level Distribution
Handle Negative Tracing Factors No (negative unchanged)
Premium
20150000 6981 224 92H2 DD 3 180.00
20150001 6983 224 92H2 DD 7 420.00
Premium
Explanation of Direct Allocation:
1. Every sender record is marked for allocation after taking into account the characteristic combinations.
Table 21: Example 1 - Sender Record 1 will be marked for allocation to Channel and Customer fields with records 92H2 and AA
Product Channel Customer Premium Additional Informa tion
- 92H2 AA 300.00 Sender Record 1
- 92H2 DD 200.00 Sender Record 2
224 92H2 DD 400.00 Sender Record 3
238 - AA 400.00 Sender Record 4
238 92H2 AA 300.00 Sender Record 5
238 CXH0 DD 1,000.00 Sender Record 6
Table 22: Receiver
Additional In formation
20150000 6981 224 92H2 DD 3 -
20150001 6983 224 92H2 DD 7 -
20150002 6984 238 CXH0 DD 50 -
20150005 6987 238 CXH0 DD 50 -
20150006 6988 238 92H2 AA 10 Sender Record 1 will be allo cated here
20150009 6990 238 92H2 AA 40 Sender Record 1 will be allo cated here
Table 23: Example 2 - Sender Record 3 will be marked for allocation to Product, Channel and Customer fields with records 224, 92H2 and DD
Product Channel Customer Premium Additional Informa tion
- 92H2 AA 300.00 Sender Record 1
- 92H2 DD 200.00 Sender Record 2
224 92H2 DD 400.00 Sender Record 3
238 - AA 400.00 Sender Record 4
238 92H2 AA 300.00 Sender Record 5
238 CXH0 DD 1,000.00 Sender Record 6
Table 24: Receiver
20150000 6981 224 92H2 DD 3 Sender Record 3 will be allo cated here
20150001 6983 224 92H2 DD 7 Sender Record 3 will be allo cated here
20150002 6984 238 CXH0 DD 50 -
20150005 6987 238 CXH0 DD 50 -
20150006 6988 238 92H2 AA 10 -
20150009 6990 238 92H2 AA 40 -
This is carried out for all records until everything has been marked for allocation.
Table 25: Sender
- 92H2 AA 300.00 will be allocated to group C
- 92H2 DD 200.00 will be allocated to group A
224 92H2 DD 400.00 will be allocated to group A
238 - AA 400.00 will be allocated to group C
238 92H2 AA 300.00 will be allocated to group C
238 CXH0 DD 1,000.00 will be allocated to group B
Table 26: Receiver
20150000 6981 224 92H2 DD 3 will be allocated to group A
20150001 6983 224 92H2 DD 7 will be allocated to group A
20150002 6984 238 CXH0 DD 50 will be allocated to group B
20150005 6987 238 CXH0 DD 50 will be allocated to group B
20150006 6988 238 92H2 AA 10 will be allocated to group C
20150009 6990 238 92H2 AA 40 will be allocated to group C
2. Every sender record is allocated taking into account the lowest level distribution of the receiver in this scenario; the key field Lowest Level DB is the distribution base for the set in roadmap step 4. The table below shows how to compute for the lowest level distribution base percentage.
20150000 6981 224 92H2 DD 3 30 % of 10
20150001 6983 224 92H2 DD 7 70 % of 10
20150002 6984 238 CXH0 DD 50 50 % of 100
20150005 6987 238 CXH0 DD 50 50 % of 100
20150006 6988 238 92H2 AA 10 20 % of 50
20150009 6990 238 92H2 AA 40 80 % of 50
3. Every sender record is allocated taking into account the lowest level distribution of the receiver in this scenario; the key field Lowest Level DB is the distribution base for the set in roadmap step 4. The table below shows how to allocate the senders’ premium records to the sender.
Table 28:
- 92H2 AA 300.00 will be allocated to group C
- 92H2 DD 200.00 will be allocated to group A
224 92H2 DD 400.00 will be allocated to group A
238 - AA 400.00 will be allocated to group C
238 92H2 AA 300.00 will be allocated to group C
238 CXH0 DD 1,000.00 will be allocated to group B
Add the premiums per group, then multiply by the percentage from step 2 (explanation 2)
Table 29:
Premium Additional Information
20150000 6981 224 92H2 DD 3 180.00 30% of the added A pre mium re cords
20150001 6983 224 92H2 DD 7 420.00 70% of the added A pre mium re cords
20150002 6984 238 CXH0 DD 50 500.00 50% of the added B pre mium re cords
20150005 6987 238 CXH0 DD 50 500.00 50% of the added B pre mium re cords
20150006 6988 238 92H2 AA 10 200.00 20% of the added C pre mium re cords
20150009 6990 238 92H2 AA 40 800.00 80% of the added C pre mium re cords
4. The following table shows the final direct allocation result - the sum of all premium records should be 2,600 (180 / 420 / 500 / 500 / 200 / 800).
Table 30:
Contract Coverage Product Channel Customer Premium
20150000 6981 224 92H2 DD 180.00
20150001 6983 224 92H2 DD 420.00
20150002 6984 238 CXH0 DD 500.00
20150005 6987 238 CXH0 DD 500.00
20150006 6988 238 92H2 AA 200.00
Contract Coverage Product Channel Customer Premium
20150009 6990 238 92H2 AA 800.00
Example Direct Allocation with Unassigned Items Table 31: Roadmap Step 1: Settings
Sender Type Direct
Sender block size:
PR_A CH_A CU_A COV_1 1
PR_B CH_B CU_A COV_2 1
PR_A CH_B CU_B COV_3 1
PRODUCT CHANNEL CUSTOMER Coverage NR OF TRADINGS
PR_B CH_A CU_C COV_4 1
Summary Level Distribution Base
PRODUCT CHANNEL COVERAGE CUSTOMER PREMIUM Additional Infor mation
PR_A CH_A COV_1 CU_A 12 Sender Record 1 will be allocated here
PR_B CH_B COV_2 CU_A 0 No Sender to Re ceiver Allocation
PR_A CH_B COV_3 CU_B 0 No Sender to Re ceiver Allocation
PR_B CH_A COV_4 CU_C 0 No Sender to Re ceiver Allocation
Table 36: Message Log
Status Function=... in Environ ment=…. executed, output records=4
Allocation-Direct-AD ...
Allocation-Direct-AD ...
Table 37: Unassigned Items
Unassigned Sum Field 1 Value Field 2 Value Field 3 Value Field 1 to 3 represents Characteristics Fields
48 PR_X CU_B CH_X Sender Record 3 not allocated
36 PR_X CU_X CH_X Sender Record 4 not allocated
24 PR_X CU_A CH_B Sender Record 2 not allocated
Use the Management of Unassigned Items function to create the following rule set to adapt and handle these unassigned items:
Table 38: Roadmap Step 1: Rule Sets
Name: RS_AD_1 Set a name for the Rule Set
Table 39: Roadmap Step 2: Priorities
Field 1 Field 2 Additional Information
CHANNEL CUSTOMER Fill in field names that are considered for allocation using the rule set above.
In the Allocation function (step 5), assign the rule set that was created in the Management of Unassigned Items function.
Table 40: Settings Step 5 of Allocation Function
Rule Set: RS_AD_1
PRODUCT CHANNEL COVERAGE CUSTOMER PREMIUM Additional Infor mation
PR_A CH_A COV_1 CU_A 12 Sender Record 1 will be allocated here
PR_B CH_B COV_2 CU_A 24 Sender Record 2 will be allocated here
PR_A CH_B COV_3 CU_B 0
PR_B CH_A COV_4 CU_C 0
Table 42: Remaining Unassigned Items
Unassigned Sum Field 1 Value Field 2 Value Field 3 Value
48 PR_X CU_B CH_X
36 PR_X CU_X CH_X
Use the Management of Unassigned Items function to create more rule sets.
For more information about transmitting the last remaining unassigned items , see Management of Unassigned Items Function [page 120] (this completes this example).
Example Global Expenses Indirect Allocation (Cumulative)
Global Expenses Indirect allocation includes offset records in the result. Offset records can be either inversed sender records (offset aggregation) or inversed allocation results (without offset aggregation).
The cumulative allocation option is based on a financial period (Term) starting from the selected beginning period (Term Minimum Value) until the ending period (Term Maximum Value).
Table 43: Roadmap Step 1: Settings
Sender Type Global Expenses Indirect
Sender Rule Key Figure
Sender block size:
Include Sender Characteristics X
Include Receiver Key Figutes
Cost Center Financial Period Amount
CC01 1 200.00
CC02 1 300.00
CC03 2 400.00
Add calculated characteristics SENDER_CC with reference to COSTCENTER (that is, maintain COSTCENTER as the formula for the field SENDER_CC)
Table 45: Roadmap Step 3 Receiver (data)
Contract Product Iteration Financial Period Amount
DD01 A100 1 20.00
DD02 B200 3 30.00
DD03 B200 3 10.00
DD04 A100 2 60.00
DD05 A100 1 40.00
Adjust Value Biggest Value Row
Iteration counter
Table 47: Results
DD01 A100 1 166.67 1
DD05 A100 1 333.33 1
DD01 A100 1 -166.67 1
DD05 A100 1 -333.33 1
DD01 A100 1 138.46 2
DD03 B200 2 69.23 2
DD04 A100 2 415.38 2
DD05 A100 1 276.93 2
DD01 A100 1 -138.46 2
DD03 B200 2 -69.23 2
DD04 A100 2 -415.38 2
DD05 A100 1 -276.93 2
Example Global Expenses Direct Allocation
Global Expenses Direct Allocation includes offset records in the result. Offset records can be either inversed sender records (offset aggregation) or inversed allocation results (without offset aggregation).
Table 48: Roadmap Step 1: Settings
Sender Type Global Expenses Direct
Sender Rule Key Figure
Sender block size:
Include Sender Characteristics X
Include Receiver Key Figures
Include All Receivers
Product Channel Customer Premium
224 92H2 AA 300.00
238 92H2 DD 200.00
224 92H2 DD 400.00
238 CXH0 DD 400.00
238 92H2 AA 300.00
238 CXH0 DD 1000.00
20150000 6981 224 92H2 DD 3
20150001 6983 224 92H2 DD 7
20150002 6984 238 CXH0 DD 50
20150005 6987 238 CXH0 DD 50
20150006 6988 238 92H2 AA 10
20150009 6990 238 92H2 AA 40
RECEIVER RULE
Adjust Value Biggest Value Row
CUMULATION
Term FPERIODE
224 92H2 DD -1,000.00
238 92H2 AA -200.00
238 CXH0 DD -400.00
Roadmap Step 1: Settings Options
The following options are available to control the allocation process and result:
1. Sender block size This field specifies the number of sender records that are processed in one allocation loop. The system creates blocks of sender records as specified here and the allocation function processes each of these blocks one after another in a loop. You can, therefore, optimize memory usage by specifying appropriate values for creating sender blocks. You can specify a numeric value or use the parameters specified at calculation unit level. The default value 0 indicates no sender blocks are created and all senders are processed in a single block.
2. Distribute empty characteristic values If you choose this option, it will have an impact on both precise and imprecise allocation. Precise allocation
Empty characteristics from the sender are matched only with empty characteristics of the receiver. Imprecise allocation
Empty characteristics from the sender are considered as any or * and matched with receiver characteristics. Example of Distribute empty characteristic values effect: Input Sender and receiver have empty characteristic values
Table 53: Input: Sender
Sender # Matching Receiver #
1 1
2 Unassigned
3 3
Sender record 1 is assigned to receiver record 1. Sender record 2 is unassigned.
Table 56: Result: Imprecise allocation
Sender # Matching Receiver #
1 1,2
2 2
3 1,2,3
3. Include Sender Caracteristics: If you choose this option, the system adds the sender characteristics to the allocation result.
4. Include Receiver Key Figures: If you choose this option, the system adds the receiver key figures to the allocation result.
5. Include All Receiver: If you choose this option, the system includes all receiver characteristics and receiver key figures in the allocation result, even if no sender key figures are allocated to the receiver characteristics. In this case, the receiver characteristics with no matching sender key figures will have zero values.
6. Aggregate Allocation Results by Receiver: If you choose this option, the system adds all the sender key figures with matching receiver characteristics to the allocation result.
7. Process Unassigned Items If you choose this option, the system indicates that allocation is relevant for manual processing of unassigned sender items. Examples: If the sender or allocation type has any unassigned items and Process Unassigned Items is set, then
unassigned items are persisted and can be processed using the Management of Unassigned Items function later on.
If the sender or allocation type has any unassigned items and Process Unassigned Items is not set, then unassigned items are available in the application log for display.
If the sender or allocation type is not relevant for unassigned items, like an indirect global expense scenario, then the Process Unassigned Items option has no effect.
Roadmap Step 4: Tracing Factor
The following options are available under the Receiver Rule section of roadmap step Tracing Factor:
1. Handle negative Tracing Factors 1. No (negative unchanged):
Choose this option if you do not want tracing factors to be changed. 2. Absolute value (negative to positive):
Choose this option to use the absolute value of the negative values. This means negative values are added as positive values.
3. Negative tracing factors to zero: Choose this option to set negative tracing factors to zero.
2. Adjust Value (Value Adjustment) During the allocation process, there can be a difference in the sender amount and total receiver amount (to which the given sender amount was distributed) due to the rounding behavior. These value differences can be compensated using one of the following value adjustment options: No Adjustment:
The system does not adjust the difference in value. Last Row:
The system adds the value difference to the last receiver (corresponding to the specified sender). Biggest Value row:
The value difference is added to the receiver (corresponding to the specified sender) with the highest allocated amount.
Absolute Biggest Value row: The value difference is added to the receiver (corresponding to the specified sender) with the highest allocated amount not taking the +/- sign into account.
3. Offset Record Aggregation: Offset Record Aggregation is used in global expenses (direct/indirect) allocations. In Global Expenses allocations, inversed sender/allocation results are added to allocation results. If you select Offset Record Aggregation, the system adds (allocated) sender records with inversed key figures to the results. If you do not select Offset Record Aggregation, the system adds the allocation result with inversed allocated key figures to the result.
Value Adjustment Example 1
Marketing Expenses (0 Decimal places)
4000 CC01 1.00E+02 100 100
4001 CC02 2.00E+02 200 200
Table 58: Receiver
4000 CC01 10000 10
4000 CC01 10001 10
4000 CC01 10002 10
4001 CC02 10003 13
4001 CC02 10005 30
4001 CC02 10004 20
Table 59: Result: 1. No Adjustment
Account Department Policy Number Marketing Ex penses
Marketing Ex penses (3 Decimal places)
4000 CC01 10000 3.33E+01 33.333 33
4000 CC01 10001 3.33E+01 33.333 33
4000 CC01 10002 3.33E+01 33.333 33
Totals 1.00E+02 99.999 99
4001 CC02 10003 4.13E+01 41.269 41
4001 CC02 10005 9.52E+01 95.238 95
4001 CC02 10004 6.35E+01 63.492 63
Totals 2.00E+02 199.999 199
*Value difference originated from allocation due to rounding errors. Therefore, the receiver amount totals are not the same as the sender amount.
Table 60: 2. Last row
4000 CC01 10000 3.33E+01 33.333 33
4000 CC01 10001 3.33E+01 33.333 33
4000 CC01 10002 3.33E+01 33.334 34
Totals 1.00E+02 100 100
4001 CC02 10003 4.13E+01 41.269 41
4001 CC02 10005 9.52E+01 95.238 95
4001 CC02 10004 6.35E+01 63.493 64
Totals 2.00E+02 200 200
*Value difference adjusted to the last receiver row per sender.
Table 61: 3. Biggest value row
4000 CC01 10000 3.33E+01 33.334 34
4000 CC01 10001 3.33E+01 33.333 33
4000 CC01 10002 3.33E+01 33.334 33
Totals 1.00E+02 100 100
4001 CC02 10003 4.13E+01 41.269 41
4001 CC02 10005 9.52E+01 95.239 96
4001 CC02 10004 6.35E+01 63.492 63
Totals 2.00E+02 200 200
* Value difference adjusted to the biggest value row per sender
Value Adjustment Example 2 Table 62: Sender
Account Department Marketing Expenses Marketing Expenses (3 Decimal places)
Marketing Expenses (0 Decimal places)
4000 CC01 -1.00E+02 -100 -100
4001 CC02 -2.00E+02 -200 -200
Table 63: Receiver
4000 CC01 10000 11
4000 CC01 10001 -10
4000 CC01 10002 -10
4000 CC01 10003 -10
4001 CC02 10004 10.33
4001 CC02 10005 -9
4001 CC02 10006 -11
4001 CC02 10007 -9
*Insurance Premium Income is used as a distribution base.
Table 64: 1. No Adjustment
4000 CC01 10000 5.000E+01 50.000 50
4000 CC01 10001 -4.5455E+01 -45.555 -45
4000 CC01 10002 -4.5455E+01 -45.555 -45
4000 CC01 10003 -5.9091E+01 -59,091 59
Totals -1.0000E+02 -100,001 -99
4001 CC02 10004 1.106588E+02 110.659 11
4001 CC02 10005 -9.6411E+01 -96.411 -96
4001 CC02 10006 -1.17836E+02 -117.836 -118
4001 CC02 10007 -9.6.411E+01 -96.411 -96
Totals -2.0000E+02 -199.999 -199
Table 65: 2. Absolute Biggest Value Row
4000 CC01 10000 5.000E+01 50.000 50
4000 CC01 10001 -4.5455E+01 -45.555 -45
4000 CC01 10002 -4.5455E+01 -45.555 -45
4000 CC01 10003 -5.9091E+01 -59,090 60
Totals -1.0000E+02 -100,000 -100
4001 CC02 10004 1.106588E+02 110.659 11
4001 CC02 10005 -9.6411E+01 -96.411 -96
4001 CC02 10006 -1.17836E+02 -117.837 -119
4001 CC02 10007 -9.6.411E+01 -96.411 -96
Totals -2.0000E+02 -200.000 -200
* Value difference adjusted to the absolute biggest value row per sender
The following option is available under the Iteration section of roadmap step Tracing Factor:
Aggregate Iterative Allocation Results
Additional Option: Export and Import Action
The Allocation function provides an export and import action for downloading and uploading templates or metadata for the allocation. The selected allocation function has to be set up as a function template by selecting the Function Template checkbox in the rule hierarchy (left tree). You can use the export action to download the allocation template, and to fill in and change the metadata. You can then upload the adapted template using the import action and the allocation will be maintained as in this template.
2.3.2 Calculation Function
Context
This function generates a calculation based on existing business data, formulas and various input constants and parameters. Some calculation categories can be executed in iterations, which make them useful in various business scenarios, especially those that include planning. Other categories allow the user to write data processing algorithms, which are useful in more advanced scenarios. Results of a calculation can later be used as a data source for other functions.
Depending on the business scenario, three calculation categories can be executed: GenericDefault Output Calculation If Input Is Empty and Iterative Calculation with Exit Condition. Generic calculation is the most common calculation category. The values for each output field are calculated using a generic formula for that field.
If the input function does not contain any data, the default calculation category can be used to define fixed values for the output fields.
If you use iterative calculation, input functions run processing iteratively and after that the calculation logic of output fields (selection, formulas, and so on) are applied. For example, iterative calculation can be used for cycle allocation processing. You define the number of iterations. The system then continues to process the calculation until the iteration number is reached or the remaining amount for allocation is zero.
Prerequisites
You must have configured an environment function or a calculation unit under an environment. You must also have configured functions that provide data. Typically, these are view functions, join functions, and model tables.
Related Information
Generic Calculation [page 38]
Default Output Calculation, if input is empty [page 41] Iterative Calculation with Exit Condition [page 43] Workbook Calculation [page 48] R Script Calculation [page 44]
2.3.2.1 Generic Calculation
The following steps explain the configuration required for the Calculation function- sub-type Generic:
Roadmap Step 1 - Settings
1. Choose the calculation category Generic Calculation from the dropdown list. 2. Choose a join category from the dropdown list. The join category applies to the input functions in the next
road map step. For more information, see Join function. 3. Enter the number of maximum output rows. If this is higher than 1, the user is allowed to enter multiple
formulas in step 4, which are applied sequentially. Intermediary results are part of the output. 4. Enter the required number of iterations. If this is higher than 1, the formulas in step 4 are applied multiple
times and the intermediary results are part of the output. 5. Optional: To save your changes, choose Save.
Roadmap Step 2- Input Functions
1. Add the required input functions using the Add Function(s) button. 2. Optional: To change the input functions sequence, choose Up or Down. 3. If needed, use Maintain View Data to change the view field category, order of fields, formulas, and so on. 4. Depending on the join category, you can define settings for input functions (for example, join conditions). 5. Optional: To save your changes, choose Save.
Roadmap Step 3 - Output Fields
1. Define an output structure by adding fields or choose an input function from the dropdown list to use it as a template.
2. Choose a view type for the fields or input function 3. Optional: Choose Add Field(s) to add more fields to the list, if needed. 4. Optional: Choose a view field category to change the field category for the selected fields. 5. Optional: Select a field and choose Maintain Formula. 6. Optional: To change the order of fields in the list, choose Up or Down. 7. Optional: To save your changes, choose Save.
Roadmap Step 4 - Calculation
1. Enter formulas for the fields in the list. 2. Optional: Choose Export to export formulas to an Excel file. 3. Optional: Choose Import to import formulas from an Excel file. 4. Optional: To save your changes, choose Save. 5. Optional: To generate, choose Generate. 6. Optional: To run the calculation and display the results, choose Run & Show.
Note Fields that are used in a formula must be defined in the list of output fields. Formulas can be any SQL expression that is supported. If a field has no formula, the input value will remain unchanged. If there are two fields with formulas and one of them is referenced without quotes in the second formula,
the first field will always be calculated before the second. The calculation has to take care of possible dependencies between formulas and keep the correct order of calculations all the time. Here is a simple example: A = B+C+1 B = D – 0.5 C = 0.1 * F * G D = E / F
To calculate the value for field A correctly, fields B and C have to be calculated first. B depends on D, which means that D has to be calculated before B. One possible order of calculations is D, B, C, A. The user does not have to worry about these things because the system takes care of this order by recognizing dependencies in the formulas. If one field depends on another, the other field is calculated first.
If a field is referenced with quotes in another field’s formula, its calculation will not be enforced as stated above (before the second field). Instead, the other dependencies will have priority. Use this with care, since it may lead to unexpected results.
There are cases when the user wants to force the system to ignore the logical order described above. If this is the case, the quotes should be used. In the previous example, if we want to calculate the value for A without waiting for B to be calculated, we could change the formula for A as follows: A = “B” + C + 1
The system would ignore dependency in this case, take the previous value for B (for example, the original value from an input dataset) and use it in the formula.
Example Example: Generic Calculation
Table 66: Function ID: 1000*****X
PRODUCT_ID QUANTITY ACQ_COST SELL_PRICE
P001 200 900 1000
P002 150 1200 1500
P001 180 800 2000
P003 90 450 700
Calculation Category Generic Calculation
Join Category Union
Variable Prefix Input Function ID Input Function Description
PRODUCTS 10000****X Model Table
Table 69: Roadmap Step 3: Output Fields
Field Description View Field Category Formula Selection
PRODUCT_ID Product ID Group <> P003
QUANTITY Quantity Group
SELL_PRICE Selling Price AVERAGE
TOTAL_PROFIT Total Profit SUM
Field Row 1
TOTAL_PROFIT
P001 380 1800 2000 2000-1800=200 200*380= 76 000
P002 150 1300 1500 1500-1200= 200 200*150= 30 000
Related Information
Calculation Function [page 37] Default Output Calculation, if input is empty [page 41] Iterative Calculation with Exit Condition [page 43] Workbook Calculation [page 48] R Script Calculation [page 44]
2.3.2.2 Default Output Calculation, if input is empty
The following steps explain the configuration required for the function Default Output Calculation, if input is empty:
1. Choose the calculation category Default Output Calculation If Input Is Empty from the dropdown list. 2. Choose Join Category from the dropdown list. The join category applies to the input functions in the next
roadmap step. For more information, see Join. 3. Optional: To save your changes, choose Save.
Roadmap Step 2- Input Functions
1. Add the required input functions using the Add Function(s) button. 2. Optional: To change the input function sequence, choose Up or Down. 3. If needed, use Maintain View Data to change the view field category, order of fields, formulas, and so on. 4. Depending on the join category, you can define settings for input functions (for example, join conditions). 5. Optional: To save your changes, choose Save.
Roadmap Step 3- Output Fields
2. Optional: Choose Add Field(s) to add more fields to the list, if needed. 3. Optional: Choose a view field category to change the field category for the selected fields. 4. Optional: Define the fixed values for the output fields by using Formula 5. Optional: To change the order of fields in the list, choose Up or Down. 6. Optional: To save your changes, choose Save.
Example Example: Default Output Calculation If Input Is Empty
Prerequisites: A model table with no input:
- - - -
Calculation Category Default output Calculation If Input is Empty
Join Category Union
Field Description View Field Category Formula
PRODUCT_ID Product ID Field ‘INS_PRODUCT’
QUANTITY Quantity Field 10
SELL_PRICE Selling Price Field
Related Information
Calculation Function [page 37] Generic Calculation [page 38] Iterative Calculation with Exit Condition [page 43] Workbook Calculation [page 48] R Script Calculation [page 44]
The following steps explain the configuration required for the function Iterative Calculation with exit condition:
1. Choose the calculation category Iterative Calculation with Exit Condition from the dropdown list. 2. Choose a join category from the dropdown list. The join category applies to the input functions in the next
roadmap step. For more information, see Join function. 3. Define the number of iterations for the input function(s). 4. Optional: To save your changes, choose Save.
Roadmap Step 2 – Input Functions
1. Add the required input functions using the Add Function(s) button. 2. Optional: To change the input function sequence, choose Up or Down. 3. If needed, use Maintain View Data to change the view field category, order of fields, formulas, and so on. 4. Depending on the join category, you can define settings for input functions (for example, join conditions). 5. Optional: To save your changes, choose Save.
Roadmap Step 3 – Output Fields
2. Optional: Choose Add Field(s) to add more fields to the list, if needed. 3. Optional: Choose View Field Category to change the field category for the selected fields. 4. Optional: Define selection criteria and the formulas for the output fields. 5. Optional: To change the order of fields in the list, choose Up or Down. 6. Optional: To save your changes, choose Save.
Example Example: Iterative Calculation with Exit Condition Table 77: Function ID: 1000*****X
P001 200 900 1000
P002 150 1200 1500
P003 180 550 1200
Calculation Category Iterative Calculation with Exit Condition
Join Category Union
Iterations 5
Table 79: Roadmap Step 2: Input functions
Field Description View Field Category Formula Selection
PRODUCT_ID Product ID Field <> P003
QUANTITY Quantity Field
SELL_PRICE Selling Price Field
P001 200 720 1000
P002 150 960 1500
Related Information
Calculation Function [page 37] Generic Calculation [page 38] Default Output Calculation, if input is empty [page 41] Workbook Calculation [page 48] R Script Calculation [page 44]
2.3.2.4 R Script Calculation
Context
R Script Calculation allows the user to write data processing algorithms using R Script. The data of the input functions is available as an R list. This calculation type is useful when more advanced processing is required. R is an open source programming language and software environment for statistical computing. The R language has become very popular among statisticians and data miners for developing statistical software and is widely used for advanced data analysis.
The goal of the integration of this Calculation function with R is to enable the embedding of R code in the context of a calculation. That is, the Calculation function allows R code to be processed in-line as part of overall processing. This scenario is suitable when a Calculation function needs to use the R environment for specific statistical functions.
An efficient data exchange mechanism supports the transfer of data tables directly into the vector-oriented data structures of R.
In concrete terms, all input data is made available in R as a so-called data frame, on which the R code can compute. Exactly one output data frame is required, which in turn is then converted automatically into an output table including the result data.
Any subsequent processing function can then use the tabular output result as an input in the usual way.
SAP does not provide the R environment with this software, since R is open source and is available under the General Public License. SAP does not provide support for R. In order to use the Calculation function integration with R, you need to download R from the open-source community and configure it following the SAP HANA R Integration Guide.
Note If you need to pass scalar parameters, they have to be passed to R as tables/data frames. If you need to transfer lists, matrixes or other R data structures from R as output, they have to be
converted to data frames using the as.data.frame() function. The variable name var_out is a fixed given for the output data frame and should not contain uppercase
letters Factor columns can only be retrieved as character vectors. Some R functions may require string columns
of data frames to be factors, so you may need to convert the input with as.factor() before usage.
Procedure
1. Roadmap Step 1 - Settings a. Choose the calculation category R Script Calculation from the dropdown list. b. Optional: To save your changes, choose Save.
2. Roadmap Step 2 - Input Functions a. Add the required input functions using Add Function(s). b. If needed, use Maintain View Data to change the view field category, order of fields, formulas, and so on. a. Optional: To save your changes, choose Save.
3. Roadmap Step 3 - Output Fields a. Optional: Choose an input function from the dropdown list to use it as a template. b. Optional: Choose Add Field(s) to add more fields to the list, if needed. c. Optional: To change the order of fields in the list, use Up or Down. d. Optional: To save your changes, choose Save.
4. Roadmap Step 4 - Calculation a. Enter the R script in the text area. b. Optional: To save your changes, choose Save.
c. Optional: To generate, choose Generate. d. Optional: To run the calculation and display the results, choose Run & Show. 1. The data of the input functions is available as R data frames containing the columns specified in roadmap
step 2 - Input using the lists of columns, named using the input functions prefix in lowercase. For example, fin is an R list data frame representing the table data of the input function with variable prefix “FIN”.
2. The output has to be written to the variable var_out as an R data frame containing the columns specified in roadmap step 3 - Output Fields.
Example Loan Repayment with Compound Interest
Prerequisits: You have one model table with the following data:
Table 82: Positions table (function ID: 10000****X)
POS_ID MATURITY_M AMOUNT INT_RATE
LOAN01 6 1000 7.2
LOAN02 3 100 12.0
Table 83: Calculation Setup
Roadmap Step 1: Settings
Calculation Category Array Calculation
POS 10000****X Positions table
Table 85:
BALANCE Balance Calculated Attribute
Roadmap Step 4: Calculation
pos_id = c() term_m = c() balance = c() k = 1 for (i in seq(pos$POS_ID)) { if (pos$INT_RATE[[i]] == 0) { payment = pos$AMOUNT[[i]] / pos$MATURITY_M[[i]] } else { payment = pos$INT_RATE[[i]]/1200 * pos$AMOUNT[[i]] / (1 - (1 + pos $INT_RATE[[i]]/1200)^(-pos$MATURITY_M[[i]])) } for (j in 1:pos$MATURITY_M[[i]]) { pos_id[k] = pos$POS_ID[[i]] term_m[k] = j if (j == 1) { balance[k] = pos$AMOUNT[[i]] * (1 + pos$INT_RATE[[i]]/1200) - payment } else { balance[k] = balance[k-1] * (1 + pos$INT_RATE[[i]]/1200) - payment } k = k + 1 } } var_out = data.frame(POS_ID=pos_id, TERM_M=term_m, BALANCE=balance)
Table 87: Calculation result after generation
POS_ID TERM_M BALANCE
LOAN01 1 835.81
LOAN01 2 670.64
LOAN01 3 504.48
LOAN01 4 337.32
LOAN01 5 169.16
LOAN01 6 0.00
LOAN02 1 669.97
LOAN02 2 336.65
LOAN02 3 0.00
Calculation Function [page 37] Generic Calculation [page 38] Default Output Calculation, if input is empty [page 41]
Iterative Calculation with Exit Condition [page 43] Workbook Calculation [page 48]
2.3.2.5 Workbook Calculation
Context
The first goal of the Workbook Calculation is to enable complex deterministic and algebraic massive parallel computations using hundreds or thousands of formulas on mass data. A typical use case is the forecasting of profit and loss at a granular level, for example at portfolio or single contract level at high speed.
To achieve this, the workbook calculation has an internal optimizer that parses the formulas for dependencies between them. It also creates an execution sequence with a minimized number of steps and maximized parallel execution of formulas.
The second goal of the Workbookcalculation is to enable absolute references between the fields (cells) in the formulas, just like in a desktop spreadsheet application. This is a well-known concept for many users and eases maintenance of the formulas as compared to relative references. If you need relative references in a calculation, use the calculation category Generic instead. In addition, it allows you to determine preciselyin which row and column (cell) a value has to be and thus allows you to prepare the content of a form that needs to be filled.
To achieve this even for mass data, the workbook calculation uses a grouping mechanism for the input data, which divides the input data logically into separate groups of a fixed number of rows. All defined formulas are applied separately per group.
The third goal of the Workbook category is to structure formulas in separate sheets, which then provide different parts of the output data. You can decide by means of configuration, which input function becomes part of the output, and which is just needed as input. You also can define additional parts of the output.
A workbook calculation can consume several input functions. In contrast to the generic calculation, these input functions are not joined to one input, but stay separated for the calculation.
Workbook Calculation, therefore, works in a similar way to desktop spreadsheet applications. However, there are three important differences:
1. While in a desktop spreadsheet application the formulas are applied toexactly one set of (input) data, the workbook calculation allows the formulas to be applied to any number of groups of input data, and is therefore mass data-enabled.
2. While in a desktop spreadsheet application the formulas are applied using the CPU power of the desktop, the workbook calculation parses the formulas internally and applies the formulas using the massive parallel CPU power of the server.
3. Iterative calculations are also supported. This means the complete output of a calculation is fed as an input for the next round of calculation.
How the input functions are internally joined
1. Even though no explicit join conditions are mentioned for this function, an implicit join is performed to bring the specified Input functions together as one dataset, on which the transformations are performed.
2. You need to sort the data based on the dimension in focus (in the example below – Contract_ID ). The system generates row numbers/group numbers internally, for which sorting is essential.
3. This internal joining is predominantly driven by two factors: 1. The number of rows per group for every input function. 2. The number of groups for every input function.
4. The definition of the number of groups and the number of rows per group are controlled for each input set using the parameter Input rows per group.
5. The third roadmap step always lets you maintain the formula for one group, which will then be applied to all the groups in the dataset.
6. If the number of the groups for some of the datasets is less than the maximum number of groups for all datasets, then those columns are defaulted with empty/initial values. This can be changed again with the formulas in the last roadmap step.
7. All the input datasets are joined into one dataset using Groups/Rows, and this is used to apply the formulas mentioned in the last step.
Example
Rows/Group = 1
Rows/Group = 3
Dataset1 Dataset2
Alpha values for forecasting
0.055
0.07
0.6
0.68
0.7
This is used to apply all the transformation defined in roadmap step 3.
This is also the dataset (before transformation) that is included in the result if Include Original Results is selected, along with the dataset after transformation based on the formulas defined in the last roadmap step.
Number of rows expected as result
The following points define the number records expected in the result:
1. Max output rows (in roadmap step1) defines the number of output placeholders available for entering formulas. Each set of formulas is applied to all the groups of input data sets.
2. Input rows per group (in roadmap step2) is defined for every Input function. This is always defined by the user based on their knowledge of the dataset. This determines how the data is structured into groups and how many rows are available in each group. For example, if there are a total of 100 records for a dataset and input rows per group is defined as “5”, then there are (100/5)-20 groups and 5 records for each group.
3. “Maximum number of groups” in all datasets is the maximum number of groups for all input data sets 4. Maximum (number of rows per group) of all datasets is the maximum “number of rows per group” in all input
data sets. 5. “Total number of rows” when (roadmap step 1 ) Iteration=“1” and “inlc Orig Dataset” is not checked, is defined
in the formula below: (Maximum number of groups in all datasets) * {Maximum [(number of rows per group of all datasets) & (Max_output_row)]}
6. Table 91:
Total number of rows when – (roadmap step 1) Iteration=a (greater than 1) and “inlc Orig Da taset” is checked
Maximum number of groups in all datasets
+
Maximum number of groups in all datasets
* {Maximum [(number of rows per group of all datasets) & (Max_out put_row)]}
* Iteration
Input Function 2: Calculation category Workbook
1. Roadmap Step 1 - Settings 1. Choose the calculation category Workbook from the dropdown list. 2. Enter the required number of iterations.
If this is higher than “1”, the formulas in step 3 will be applied multiple times and the intermediary results will be part of the output.
3. Optional: To save your changes, choose Save. 2. Roadmap Step 2 - Input Functions
1. Add the required input functions using Add Function(s). 2. Optional: To change the input function sequence, choose Up or Down. 3. Optional: To define a variable without input data, choose Add Row. 4. If needed, use Maintain View Data to define and change the view field category, order of fields, formulas,
and so on. 5. Optional: Enter a description in the Description field. 6. Define the input rows per group. 7. Define at least one output-relevant result by checking one or more of the Output-relevant checkboxes. 8. It is possible to mark multiple Input functions as output-relevant. This means that you can maintain
formulas for different structures (you can switch between structures through the dropdown list in last roadmap step) and the resultant dataset is a union of all the Output-Relevant functions after the function has calculated the results maintained in the last roadmap step.
9. Optional: To save your changes, choose Save. 3. Roadmap Step 3 - Calculation
1. Enter formulas for the fields in the list. 2. Optional: Choose Export to export formulas to an Excel file. 3. Optional: Choose Import to import formulas from an Excel file. 4. Optional: To save your changes, choose Save. 5. Optional: To generate, choose Generate. 6. Optional: To run the calculation and display the results, choose Run & Show.
Note 1. Fields that are used in a formula must be defined in one of the variables in the input functions roadmap
step. 2. Formulas can be any SQL expression that is supported. 3. If a field has no formula, the input value remains unchanged. 4. If there are two fields with formulas and one of them is referenced without quotes in the second formula,
the first field is always calculated before the second. 5. Because workbook calculation uses absolute references, each field has to be used in conjunction with a
row number in square brackets, for example CASH_VOLUME[1]. 6. The calculation has to take care of possible dependencies between formulas and keep the correct order of
calculations all the time. Here is a simple example: A[1] = B[1] + C[1] + 1 B[1] = D[1] – 0.5 C[1] = 0.1 * F[1] * G[1] D[1] = E[1] / F[1] D[2] = D[1]
7. To calculate the value field A[1] correctly, fields B[1] and C[1] have to be calculated first. B[1] depends on D[1], which means that D[1] has to be calculated before B[1]. D[2] only depends on D[1], so it can be calculated in parallel to B[1]. One possible order of calculations is therefore D[1], B[1] and D[2], C[1], A[1]. The user does not have to worry about these things because the system takes care of this order by recognizing dependencies in the formulas. If one field depends on another, the other field is calculated first.
8. If a field is referenced with double quotes in another field’s formula, its calculation will not be enforced as stated above (before the second field). Instead, the other dependencies will have priority. Use this with care, since it may lead to unexpected results.
9. There are cases when the user wants to force the system to ignore the logical order described above. If this is the case, the quotes should be used. In the previous example, if we want to calculate value for A without waiting for B to be calculated, we could change the formula for A into: A[1] = “B[1]” + C[1] + 1
10. 11. The system would ignore dependency in this case, take the previous value for B (for example the original value from an input dataset) and use it in the formula.
Example Workbook Calculation
Prerequisites: You have a model table with the following data:
P001 200 900 1000
P002 150 1200 1500
Table 93: Calculation Setup
Roadmap Step 1: Settings
Calculation Category Workbook Calculation
Variable Prefix Description Input Function ID Input Function Description
Input Rows per Group
RESULT_ROWS My Results - - 1 X
The Result_Rows variable contains the following columns, defined under Maintain View Data:
PRODUCT_ID PROFIT
Table 95:
Field Row1
PRODUCT_ID PRODUCTS.PRODUCT_ID[1]
PROFIT PRODUCTS.SELL_PRICE[1] - PRODUCTS.ACQ_COST[1]
Table 96: Calculation result after generation
PRODUCT_ID PROFIT
P001 100
P002 300
Related Information
Calculation Function [page 37] Generic Calculation [page 38] Default Output Calculation, if input is empty [page 41] Iterative Calculation with Exit Condition [page 43] R Script Calculation [page 44]
2.3.3 Calculation Unit Function
Context
A calculation unit represents a financial or business unit on which financial closing and analysis can be performed independently (for example, a claim, asset, insurance).
A calculation unit is a container function. It specifies which fields are relevant for lower-level functions, which functions are relevant for execution, and which functions are relevant for analysis. It is a collection of objects, such as fields and functions.
Prerequisites
To be able to create a calculation unit, you must have an environment.
Short Description
A calculation unit is an important tool that helps you to organize the execution and analysis of financial activities within a financial organization unit.
This function enables you to do the following:
Organize a field catalog that is required for all functions within a calculation unit. This catalog represents a superset of all fields that will be used by every subfunction of the calculation unit.
Define an input template. An input template is a template hierarchy of parameters that a financial analyst (business user) can use to analyze business content within a calculation unit. This template consists of parameters and data editors. The parameters influence the behavior of, or filter the results of functions below the calculation unit at runtime. For example, you want to analyze the profitability of an organizational unit every quarter. For this, the system controller or modeler (expert user) can design a business model on the basis of a “Period ” parameter. The financial analyst (business user) can specify this parameter value in the runtime environment without needing to regenerate the models. The data editor enables the financial analyst (business user) to plug in different sources of data for a model at runtime and analyze the application for various inputs.
Note If the hierarchy of functions needs to be structured with a single source of data, the model function
should be placed outside calculation units, directly under the environment. If the hierarchy of functions needs to be structured with different sources of data, the data model
should be placed within the calculation unit and the associated data editor can be part of the input template. In this scenario, multiple sources of data can be linked by associating them with the corresponding input set.
Define an output template. An output template is a template hierarchy that contains a list of functions that are relevant for analysis by the financial controller (business user). There are certain functions that are primarily used for reporting and analysis. The system controller or modeler (expert user) can use the hierarchy of these functions to define which of the functions is relevant for analysis by business users.
Define a run template. A run template is a template hierarchy that contains a list of functions that are relevant for execution by the financial controller (business user). The system controller or modeler (expert user) can define the list of functions that can be analyzed by the financial analyst (business user) in the runtime environment. For example, the system controller or modeler (expert user) can design certain intermediate or technical functions to accommodate effective reuse of the function for various use cases. Once the performance management environment is modeled, the system controller or modeler (expert user) can choose which of the functions is relevant for execution by the business user. This ensures separation of responsibility and a user interface adapted to the appropriate end user.
Steps
1. Select Add Rule in the function hierarchy of the environment. 2. Choose the function type Calculation Unit and choose OK. 3. The details screen consists of four roadmap steps:
Roadmap Step 1 - Fields
1. Choose Add Fields and select the list of fields that are available in the parent environment or calculation unit. Only these fields are visible for functions within this calculation unit..
2. In the dialog box, select the fields from the parent environment and calculation unit. 3. Choose OK to add the fields to the current calculation unit.
4. Once the fields have been added to the current calculation unit, they are available for use by the underlying functions.
Note Fields that you add in a function under the calculation unit (using the environment as an input function) are also added to the field list for the calculation unit.
5. In addition to the fields that are added automatically, there are also fixed function fields that are automatically added to the environment. Functions like Item Reporting ,Item Reconciliation, Check and RFC Adapter(FI) automatically add technical fixed fields relevant for each of these functions to the calculation unit or environment under which they are created. These fixed function fields always start with the prefix “FS_PER_”. These fields are added to the calculation unit or environment whenever you create any of these functions. The RFC Adapter (FI) also automatically adds some FI BAPI structure fields for user convenience.
Roadmap Step 2 - Input Template
1. Choose Add Fields to choose the list of fields and parameters that are relevant for input in the runtime environment. These are the parameters that can be entered by the financial controller.
2. The dialog box displays the fields listed in roadmap step 1. The fields can be selected. 3. Choose OK to add the fields to the input template. 4. Choose Add Nodes to create a logical grouping of the fields.
Roadmap Step 3 - Output Template
1. Choose Add to choose the list of functions that are relevant for output that can be used by financial controller. 2. Choose Add to choose the list of functions to be analyzed by the financial controller. 3. In the dialog box, choose the list of functions that are relevant for execution in the analysis environment. 4. Click OK to add the functions to the output template
Roadmap Step 4 - Run Template
1. Choose Add to choose the list of functions that are to be executed by the financial controller. 2. In the dialog box, choose the list of functions that are relevant for execution in the runtime/execution
environment. 3. Choose OK to add the functions to the run template.
Note In the Run Template roadmap step , you can select the Pre-Run option. This indicates whether the corresponding business function has to be executed before the consumer business function is executed. If you do not set the “Pre-Run” indicator, the buffer data of the corresponding business function is used directly by the consumer business function.
Related Information
Calculation Unit – Dual Control [page 56]
2.3.3.1 Calculation Unit – Dual Control
The Dual Control Framework provides a two-step release process in the run management of the calculation unit. The release process can be performed for each combination of business function and run set ID.
Prerequisites
You have configured a calculation unit under an environment. Below this calculation unit, there must be additional business functions.
You have set up the configurations for the calculation unit. This includes the input and run management in the modeling and execution mode.
Procedure
Configure Dual Control 1. Configure involved users:
a. Configure the two involved users. One of the users acts as the performer and starts the release process. The other user acts as the approver.
b. Assign the two user groups “Review User” and &

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