How to Implement the Linear Regression Technique in SAP Integrated Business Planning for Demand

  • by Manish Thukral, Principal Consultant, Infosys Technologies
  • Rahul Patil, Senior Consultant, Infosys Technologies
  • April 21, 2017
SAP Integrated Business Planning for demand is the equivalent of SAP Advanced Planning and Optimization (SAP APO) Demand Planning. While SAP APO has an out-of-the-box forecast model that uses a linear regression technique to forecast, SAP Integrated Business Planning does not have it. The purpose of this article is to understand the solution approach to forecast based on linear regression in SAP Integrated Business Planning. The approach for doing linear regression in SAP Integrated Business Planning is to use the multiple linear regression as an alternative solution.
Learning Objectives

Reading this article, you’ll learn how to:

  • Create a data model that includes creation of attributes, master data, time profile, planning area, key figures, and planning levels
  • Create a forecast model for linear regression in generating a forecast
  • Execute a statistical forecast using the SAP Integrated Business Planning add-in for Microsoft Excel user interface
  • Validate the forecast results
Key Concept

A forecast model is the configuration that defines the following parameters that are used during a statistical forecast engine run: general parameters, preprocessing steps, forecasting steps, and postprocessing steps. In the forecast steps, algorithms and variables are defined for use in linear regression-based forecasting.

Statistical forecasting is a demand planning process to predict the numbers of anticipated sales in a future time horizon based on past data. In forecasting there are different methodologies to arrive at forecast numbers. One of them is regression analysis of the past data points of a variable based on what forecast numbers are calculated. There are two types of variables. One is an independent variable and another is a dependent variable.

In regression analysis the linear relationship is established between dependent and independent variables to consider the impact of the independent variable on the forecast. If there is one independent variable used in forecasting method, then that method is called a simple linear regression. If there are multiple independent variables, then that method is called multiple linear regression. SAP Advanced Planning and Optimization (SAP APO) has two different forecasting models, one for simple linear regression and another for multiple linear regression. SAP Integrated Business Planning provides a built-in forecasting model for multiple linear regression only, but there is no forecast model based on the linear regression method.

We show the use of a multiple linear regression model with one variable to work as a simple linear regression model in SAP Integrated Business Planning.

Log in to the SAP Integrated Business Planning cloud and open the Model Configuration group of apps. To complete this step, click the triangle to the right of Communication Manager in the menu bar and select Model Configuration from the drop-down list of options (Figure 1).


Figure 1
Select Model Configuration in the main SAP Integrated Business Planning apps screen

This action displays the screen shown in Figure 2.


Figure 2
Model Configuration apps

In Figure 2, click the Configuration tile to open the Configuration app shown in Figure 3. Model Configuration apps help you create a planning model in SAP Integrated Business Planning. A planning model describes what are the planning levels, input—output information, how data is stored, and calculation.


Figure 3
Configuration showing links for planning model entities

Manish Thukral

Manish Thukral is is a certified SAP SCM consultant with more than 10 years of hands-on experience in the SAP Supply Chain Management (SCM), SAP Advanced Planning and Optimization (SAP APO), and SAP Integrated Business Planning suite of products, such as SAP APO Demand Planning (DP), SAP APO Supply Network Planning (SNP), Core Interface (CIF), Global Available to Promise (GATP), SAP Integrated Business Planning for demand, SAP Integrated Business Planning  for supply, SAP Integrated Business Planning for  sales and operations planning, and SAP Integrated Business Planning Supply Chain Control Tower. He has experience with multiple full life-cycle implementations and multiple projects.

Manish also is an APICS certified consultant with experience in functional areas of production planning, warehouse management, inventory management, demand planning, supply planning, sales and operations planning, and available-to-promise spanning across apparel, consumer packaged goods (CPG), fast-moving consumer goods (FMCG), and pharmaceutical industry sectors.

 

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Rahul Patil

Rahul Patil is a SAP Certified Associate, Strategic Planning (DP/SNP), working as a senior consultant with the Infosys Supply Chain practice. He has more than 10 years of experience with more than eight years in SAP Supply Chain consulting focusing on Supply Chain package implementations in industries such as fast-moving consumer goods (FMCG), pharmaceutical, and manufacturing. He has worked in projects such as rollouts, support, and upgrades for SAP Advanced Planning and Optimization (SAP APO), SAP APO Demand Planning (DP), SAP APO Supply Network Planning (SNP), SAP APO Production Planning and Detailed Scheduling (PP/DS) modules and SAP Integrated Business Planning for demand and SAP Integrated Business Planning for supply modules.

He also holds APICS CPIM Certifications in Basics of Supply Chain Management, Master Planning of Resources, Detailed Scheduling and Planning.

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