SAP BPC NW 10.0 Rolling Forecast

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Author: Chief Architect:
Murugesan Annamalai Jothi Periasamy
SAP Project Manager/Lead SAP HANA/EPM/BI/EIM Community Leader
SAP EPM/BPC Solutions Lead SAP BPC/BOBJ/BI/MDM Domain Champion
MurugesanA@cloneskills.com 07/25/2013 joesaran@gmail.com, (916)-296-0228 - Cell
SAP BPC NW 10.0 |KNOWLEDGEBASE
(A SAP EPM Community Service)
Six Month Rolling Forecast - Implementation Guide

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CloneSkills, Inc., http://www.CloneSkills.com , Info@CloneSkills.com , 1.800.836.8959, Page - 2
Table of Contents
Executive Summary:........................................................................................................3
Business Scenario:...........................................................................................................3
Business Scenario – 1: .....................................................................................................5
Business Scenario – 2: .....................................................................................................6
Solutions Architecture: ....................................................................................................7
Solutions Building Blocks:................................................................................................9
Entity Structure: ............................................................................................................11
Product Hierarchy: ........................................................................................................12
Product Hierarchy – Sample: .........................................................................................13
Product Hierarchy – Sample: .........................................................................................14
List of Accounts: ............................................................................................................15
Dimension – ACCOUNT..................................................................................................16
Dimension – CATEGORY ................................................................................................17
Dimension – ENTITY ......................................................................................................18
Dimension – PRODUCT_ALLOC ......................................................................................19
Dimension – RPTCURRENCY...........................................................................................20
Dimension – TIME .........................................................................................................21
Configuration : ..............................................................................................................22
Planning :......................................................................................................................23
Rolling Forecast in Action : ............................................................................................24
Important Note : ...........................................................................................................43
Appendix – 1 : ...............................................................................................................83
Data Manager Script – Account :...................................................................................83
Data Manager Script – Product : ...................................................................................84
Logic Script for Account-Based Forecasting : .................................................................85
Logic Script for Account-Based Forecasting : .................................................................88
Logic Script for Product-Based Forecasting :..................................................................89
Logic Script for Product-Based Forecasting :..................................................................90
Disclaimer: ....................................................................................................................91
SAP Community Contributors: .......................................................................................92

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Executive Summary:
The purpose of this document is to demonstrate the implementation of six months
rolling forecast based on a real-life business scenario. In this demonstration, we are
using CPG (Consumer Packaged Goods) industry as a use case. The scope of this
documentation includes step by step implementation instructions to implement SAP
BPC modelling, SAP BPC design, SAP BPC technical build, SAP BPC logic script and
overall solution delivery approach & methodology on an SAP BPC NW 10 platform.
This document provides the essentials and adequate steps to implement the six
months rolling forecast business scenario and also it enables SAP BPC users to gain
deep knowledge on SAP BPC technical and functional competencies around business
forecast. Further, users should be able to customise this solution to meet their needs
to do any forecast (ex: sales forecast, revenue forecast, etc.) solution for any
industry.
It has been assumed that the user has basic knowledge and understanding on
business forecast and the SAP BPC NW 10.0 product.
Business Scenario:
CubeInsights, Inc. has been in retail business for about 20 years, and the company
has been growing big, and now they have their operations across the world.
CubeInsights, Inc. is selling almost 2000 (two thousand) consumer products at
various stores and they are posting their financial transactions in 52 (fifty two)
currencies. To support the increasing demand and customer growth, CubeInsights,
Inc. is interested in forecasting their sales revenue and sales volume at Product
levels. CubeInsights, Inc. is currently using spread sheet for their next 6 (six) month
rolling forecast and they are using their past six months actuals as a baseline for the
forecast. While forecasting, the company wants to consider the forecast values as

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well for forecasting for the preceding months if actuals are not available within those
preceding six months.

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Business Scenario – 1:
CubeInsights, Inc. is manufacturing and selling consumer products to it's
customers through it’s various entities.
The company wants to make rolling-forecast of Profit & Loss(ACCOUNT based)
for one of its’ entities – Unites states, in local currency.
The forecast has to be for the following Profit & Loss accounts for the product
- Eau De Lacoste 1 OZ:
o Third Party Sales
o Intercompany Sales
o Material Cost
o Labor Cost
o Personnel Cost
o Travel & Entertainment
o Advertising & Promotion
o Financial Income/Expense
o Clearing Account
The forecast period is : Feb 2013 to Jul 2013.
For the rolling forecast, the company wants to use it’s past six months’ Profit
& Loss data(ACTUALS). The past six months are : Aug 2012 to Jan 2013.
Rolling forecast for each month has to be the average of the preceding six
months’ Profit & Loss(ACTUALS) data.
Within the preceding six months, if ACTUALS – Profit & Loss data, are not
available for a particular month, then forecast values for that month are to be
considered.

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Business Scenario – 2:
CubeInsights, Inc. is manufacturing and selling consumer products to it's
customers through it’s various entities.
The company wants to make PRODUCT based rolling forecast for one of its’
entities – Unites States, in local currency.
The forecast has to be for the revenue generated from products sold.
And, the forecast has to be for the following products:
o Head & Shoulder Shampoo 10 OZ
o Pantene Shampoo 12 OZ
o Lemon Fresh Shampoo 8OZ
o Olay Base Moisturizer 6 OZ
o Olay Age Protect 6 OZ
o Olay Natural White
o Wella – ProSeries Care
The forecast period is : Feb 2013 to Jul 2013.
For the rolling forecast, the company wants to use it’s past six months’
product’s revenue data. The past six months are : Aug 2012 to Jan 2013.
Rolling forecast for each month has to be the average of the preceding six
months’ product’s revenue data.
Within the preceding six months, if ACTUALS – product’s revenue data, are
not available for a particular month, then forecast values for that month are
to be considered.

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Solutions Architecture:
The solution makes use of SAP BW server which is using SAP HANA as database
server to store data. SAP BPC 10 NW server is sitting in between SAP BW and the SAP
BPC’s various front end tools – MS Office Tools and the web browser.
Data from various data sources can be uploaded into SAP HANA database. This data
is then processed by SAP BPC server through SAP BW and then shown through MS
office client and web interfaces.
Besides this, SAP BW server can also be accessed through SAP GUI – a Windows
Client, but It is not advisable to change the data through SAP BW.

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Solutions Building Blocks:
CubeInsights, Inc’s entities are exporting past sales revenue and sales volume data to
SAP BW. These data are then transferred to SAP BPC cube. Business users can now
forecast sales revenue & volume for the next six months for an entity, using SAP BPC
NW 10.
# Solution Building Blocks System/Infrastructure Technical Details
1 Environment : ENV120_JUL28 SAP BPC SAP BPC Server
2 Model : ROLLING_FORECAST SAP BW Real-Time InfoCube Model Type - Financial
3 Dimension : ACCOUNT SAP BPC Dimension Dimension Type – A
4 Dimension : CATEGORY SAP BPC Dimension Dimension Type – C
5 Dimension : ENTITY SAP BPC Dimension Dimension Type – E
6 Dimension : PRODUCT_ALLOC SAP BPC Dimension Dimension Type – U
7 Dimension : RPTCURRENCY SAP BPC Dimension Dimension Type – R
8 Dimension : TIME SAP BPC Dimension Dimension Type – T
9 Six Months Rolling Forecast SAP BPC Data Manager Package.
This is used to run the
logic script which makes
ACCOUNT based rolling
forecast.
10 Six Months Rolling Forecast Product SAP BPC Data Manager Package.
This is used to run the
logic script which makes
PRODUCT based rolling
forecast.
11 RF_SIXMONTHS.LGF SAP BPC Logic Script. This is used
to calculate ACCOUNT
based six months rolling
forecast.
12 RF_SIXMONTHS_PROD.LGF SAP BPC Logic Script. This is used
to calculate PRODUCT
based six months rolling
forecast.
13 SixMonthsRollingFcst.xlsx SAP BPC Input Form as well as
Report. The work book

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in the input form/report
is used to accept past six
months data for
ACCOUNT and PRODUCT
based rolling forecast.
And, also to show the
subsequent six months’
ACCOUNT and PRODUCT
based rolling forecast
data.
14 /CPMB/FX_RESTATMENT SAP BW Process Chain. This is
used to run the logic
scripts which are used to
calculate ACCOUNT and
PRODUCT based six
months rolling forecast.
This is an existing
process chain and for
demo purpose, this is
being used in this Rolling
Forecast planning
solution. This process is
NOT performing any
currency conversion
here.

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Entity Structure:
The following picture shows the entity structure for the main group – CubeInsights,
Inc. The main group has invested in its’ subsidiaries – US, Singapore and Germany.
While US has invested in Canada with 70% stake and Singapore in India with 80%
stake, Germany has invested in UK with 20% stake. As for the main group of
CubeInsights, it has 80% stake in the US subsidiary, 80% stake in the Singapore
subsidiary and 90% stake in the German subsidiary.

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Product Hierarchy:
CubeInsights, Inc. is producing and selling the CPG industry products to the outside
world. The following diagram shows the product hierarchy. At the hierarchy, Product-
Family is at the top. Each Product-Family has various Groups under it. And, each
Group consists of Products. And, each Product consists of SKUs.

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Product Hierarchy – Sample:
The following diagram shows a sample product hierarchy used in the solution. Here,
there are two product families – Personal Care & Household Care. Under the Family
– Personal Care, there are five Groups, and the Group – Beauty & Grooming, is
having six products. And the product – Shampoo & Conditioner, is having 3 SKUs. For
more details, refer to the diagram below.

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Product Hierarchy – Sample:

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List of Accounts:
CubeInsights, Inc. is using the following accounts to keep track of CPG product sales:

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Dimension – ACCOUNT
The following screen shows the dimension members from ACCOUNT dimension :

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Dimension – CATEGORY
The following screen shows the dimension members from CATEGORY dimension :

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Dimension – ENTITY
The following screen shows the dimension members from ENTITY dimension :

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Dimension – PRODUCT_ALLOC
The following screen shows the dimension members from PRODUCT_ALLOC
dimension :

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Dimension – RPTCURRENCY
The following screen shows the dimension members from RPTCURRENCY dimension :

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Dimension – TIME
The following screen shows the dimension members from TIME dimension :

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Configuration :
Step # 1 : Login to BPC NW 10 server and launch BPC web administration
client.
Step # 2 : Create and configure the dimensions needed(ACCOUNT, CATEGORY,
ENTITY, PRODUCT_ALLOC, RPTCURRENCY & TIME).
Step # 3 : Create and configure the model – ROLLING_FORECAST.
Step # 4 : Create an input form to accept the ACTUALS data for account-based
forecasting.
Step # 5 : Develop logic script to make account-based forecast based on the
ACTUALS.
Step # 6 : Create and configure a data manager package to run logic
script(created at Step # 5) to forecast sales based on accounts.
Step # 7 : Create an input form to accept the ACTUALS data for product-based
forecasting.
Step # 8 : Develop logic script to make product-based forecast based on the
ACTUALS.
Step # 9 : Create and configure a data manager package to run logic
script(created at Step # 8)) to forecast sales based on products.

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Planning :
Step # 1 : Open the input form(created at Step # 4) and key-in ACTUALS data
for six months for account-based forecasting. Save the data.
Step # 2 : Run the DM package create in Step # 6. This, in turn, runs the logic
script, developed in Step # 5 under Configuration section, to calculate the
forecast values for the accounts.
Step # 3 : Verify the results in the input form opened in Step # 1.
Step # 4 : Open the input form(created at Step # 7 under Configuration
section) and key-in ACTUALS data for six months for product-based
forecasting. Save the data.
Step # 5 : Run the DM package create in Step # 9. This, in turn, runs the logic
script, developed in Step # 8 under Configuration section, to calculate the
forecast values for the products.
Step # 6 : Verify the results in the input form opened in Step # 4.

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Rolling Forecast in Action :
1. To resolve business scenario – 1, login to BPC 10 NW server as shown in the
screen.

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2. Launch BPC web admin. client.

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3. Create and configure ACCOUNT dimension as shown below:
Note : The property – IS_ACCT_FC, allows the accounts to be identified for
forecasting.

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1.1Populate the ACCOUNT dimension with members as shown below:

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4. Create and configure CATEGORY dimension as shown below:

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4.1 Populate the CATEGORY dimension with members as shown below:

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5. Create and configure ENTITY dimension as shown below:

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5.1 Populate the ENTITY dimension with members as shown below:

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6. Create and configure PRODUCT_ALLOC dimension as shown below:

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6.1 Populate the PRODUCT_ALLOC dimension with members as shown below:

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7. Create and configure RPTCURRENCY dimension as shown below:

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7.1 Populate the RPTCURRENCY dimension with members as shown below:

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8. Create and configure TIME dimension as shown below:

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8.1 Populate the TIME dimension with members as shown below:

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9. Create and configure the model – ROLLING_FORECAST, as shown below:

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10. Now, launch Excel add-in for MS Office:

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10.1 And, connect to model – ROLLING_FORECAST, as shown below:

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11. Create an input form, as shown below, to accept the ACTUALS data for account-
based forecasting:
Take note of the dimensions in the Page, Row and Column axis i.e.
- Page axis contains ENTITY, PRODUCT_ALLOC & RPTCURRENCY dimensions.
- Row axis contains ACCOUNT dimension.
- Columns axis contains TIME & CATEGORY dimensions.

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12. And, the final input form looks like the following:

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Important Note :
The input form has been designed in a separate tab in the Excel workbook. This tab
contains the input form for account-based forecasting for sales. Later, we will be
using the second tab to design the input form to forecast the sales based on the
product.
The input form calculates the forecast for the next 6 months(including the current
month). Current month and year is picked up by the form based on the server’s data
& time(which in this case is – 02/07/2013).
Whenever the input form is opened, it will show the forecast values for the next six
months(including the current server month). We need to clear all the values for
ACTUALS before calculating the forecast values.
TIME dimension members in the column axis are generated DYNAMICALLY i.e.
relative to the server’s data and time. The logic behind the dynamic generation of
the columns is in the hidden rows which we will see in the next step/screen.

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13. The screen below shows the input form, showing all the hidden rows. The hidden
rows contain the logic(both – Excel and EPM functions) to show the dynamically
generated TIME dimension values.

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The cell highlighted above is the central point which is driving the calculation of all
the TIME dimension values. The highlighted area at the top shows the Excel formula
used to generate the starting month and year for the forecast. All the other values
are derived using EPM function as shown below:

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14. The screen below shows how another TIME dimension value is calculated:

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14.1 The screen below shows how another TIME dimension value is calculated:

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15. Since the user has nothing to do with the logic, those rows are hidden and the
following screen shows how the form looks after hiding the logic rows:

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16. Now, key-in the ACTUALS data for account-based forecasting as shown in the
screen below:
Since the server data is 02/07/2013, key-in the 6 months values prior to Feb 2013.

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17. Now, go to logic script section of the BPC web admin client as shown below and
launch it :

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17.1 Launch the Scripts for ROLLING_FORECAST model.

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18. Create a logic script as shown in the screen below:
Since the ACCOUNT dimension has too many accounts, accounts are being filtered
based on the property – IS_ACCT_FC (Is account meant for forecasting?). Save the
script as RF_SIXMONTHS.LGF and close the workspace/tab.
When the script is run through data manager package, the script prompts the user
for input for ENTITY, PRODUCT_ALLOC & TIME member values. Based on that, the
script calculates the past 6 months’ average values to forecast for the next 6 months.
TIME input must be same as the server’s data and time values.

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19. Now, return to logic script section of the main screen as shown below:

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20. Go to Home workspace/tab now, as shown below:

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21. Now, launch EPM add-in for Excel:

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22. Connect to ROLLING_FORECAST model:

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23. Go to Data Manager section:

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24. Click Organize menu:

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25. Click Organize Package List menu:

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26. Create Packages folder under ROLLING_FORECAST folder:

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27. On the right hand side, Right click and click on Add Package:

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28. Create a package with the following details:
Note : For demo purpose, I am using one of the existing process chains.

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29. Click on Modify Script button:

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30. Click on Advanced button:

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31. Code the section as shown within the RED coloured rectangle and take note of
the script file name(highlighted in GREEN colour, which we created a while ago):
Click OK button now.

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32. Click Save button now.

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33. Click Save button again in the following screen.

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34. Click Close button now.

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35. Go to EPM section:

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36. Open the input form we created earlier and take note of the 6 months ACTUALS
data we entered earlier:

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37. Go to Data Manager section:

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38. Click Run Package menu:

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39. Select the DM package we created earlier(Six Months Rolling Forecast) and Click
Run button at the bottom:

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40. Key in the inputs and click Next button. Take note of the TIME member
value(highlighted in GREEN colour) which matches the server’s Month and Year.

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41. Click Finish button.

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42. Click OK button at the prompt.

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43. Click View Status button.

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44. Check the Package Run status and close the screen.

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45. Go to the input form and click Refresh button.

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46. Verify the results.

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47. For product-based forecast(Business Scenario – 2), repeat all of the earlier steps.
The following screen shows the script needed to calculate the forecast:

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48. The following screen shows the results of product-based forecast of sales:

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Appendix – 1 :
Data Manager Script – Account :
The following script shows the Data Manager script which calls/runs the logic
script(RF_SIXMONTHS.LGF) which does the account based forecasting:

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Data Manager Script – Product :
The following script shows the Data Manager script which calls/runs the logic
script(RF_SIXMONTHS_PROD.LGF) which does the account based forecasting:

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Logic Script for Account-Based Forecasting :
The following screen shows the logic script(RF_SIXMONTHS.LGF) which makes the
account based forecasting:
RF_SIXMONTHS.LGF

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Logic Script for Account-Based Forecasting :
RF_SIXMONTHS.LGF
…

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Logic Script for Product-Based Forecasting :
The following screen shows the logic script(RF_SIXMONTHS_PROD.LGF) which makes
the product-based forecasting:

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Logic Script for Product-Based Forecasting :
RF_SIXMONTHS_PROD.LGF
…

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Disclaimer:
This description is a preliminary version and not subject to a license agreement or
any other agreement with SAP®. This document contains only intended strategies,
developments, and functionalities of the SAP product and is not intended to be
binding upon SAP to any particular course of business, product strategy, and/or
development. Please note that this preview is subject to change and may be changed
by SAP at any time without notice.
SAP/We assume no responsibility for errors or omissions in this document. SAP/We
does not warrant the accuracy or completeness of the information, text, graphics,
links, or other items contained within this material. This preview is provided without
a warranty of any kind, either express or implied, including but not limited to the
implied warranties of merchantability, fitness for a particular purpose, or non-
infringement.
SAP/We shall have no liability for damages of any kind including without limitation
direct, special, indirect, or consequential damages that may result from the use of
these materials. This limitation shall not apply in cases of intent or gross negligence.
The statutory liability for personal injury and defective products is not affected.

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SAP Community Contributors:
Author : Chief Architect :
SAP Project Manager/ Lead SAP HANA/EPM/BI/EIM Community Leader
SAP EPM/BPC Solutions Lead SAP BPC/BOBJ/BI/MDM Community Domain
Champion
MurugesanA@cloneskills.com joesaran@gmail.com, (916)-296 0228 - Cell
We always appreciate your help and support in growing SAP HANA/EPM/BI/EIM
community. Don’t hesitate to contact us for any of your needs, including:
Rolling Forecast
SKU-Level/Top-Down Planning
Consolidation
Planning
Budgeting
etc.

SAP BPC NW 10.0 Rolling Forecast

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