Demand Planning Sap

8/3/2019 Demand Planning Sap

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Demand Planning

Functions in Detail

SAP Advanced Planner & Optimizer


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Contents

SAP AG q Neurottstrae 16 q 69190 Walldorf q Germany


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Demand Planning qDecember 1999

Copyright 1999 SAP AG. All rights reserved.

No part of this brochure may be reproduced or transmitted in any form or for any purpose without the express permission of SAP AG.The information contained herein may be changed without prior notice.

Some software products marketed by SAP AG and its distributors contain proprietary software components of other software vendors.

Microsoft, WINDOWS, NT, EXCEL, Word and SQL-Server are registered trademarks of Microsoft Corporation.

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Design: SAP Communications Media


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Contents

Demand Planning

1 Demand Planning: State-of-the-Art Forecasting

1 Introduction

2 Overview of SAP Advanced Planner & Optimizer

3 The SAP Business Framework

4 Benefits of SAP Advanced Planner & Optimizer4 Key Features of SAP Advanced Planner & Optimizer Demand Planning

5 The SAP APO Demand Planning Architecture

5 An Integrated Demand Planning Solution

6 Demand Planning Features and Functions

6 Data Storage and Representation

6 Planning Environment

9 Consensus-Based Forecasting

9 Multiple Views11 Causal Analysis

11 Multitier Forecasting

11 Statistical Forecasting Toolbox

12 Forecast Accuracy Analysis

13 Conclusion


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You can find this and other current literature on our home page in themedia centers for each subject at:

http://www.sap.com


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Demand Planning: State-of-the-Art Forecasting

IntroductionProblems and Challenges of the Supply Chain

The hallmarks of todays business environment are

volatile demand, decreased customer loyalty, shorter

product life cycles, and tougher global competition. To

survive, organizations need an information infra-

structure that allows them to make accurate decisions

in real time and to make customer satisfaction a top

prior ity, while still remaining competitive and profitable.

The stakes are high. Miscalculations in forecasting thatresult in excess inventory can prove fatal. Failing to

meet promised delivery dates can drive away

customers. To handle these challenges, manufacturers

are tur ning to new, advanced planning and scheduling

techniques that generate optimized executable plans

in response to r apid changes in supply or demand.

Data-Driven Process

Huge amounts of data drive these planning and

scheduling processes. Much of it comes from the

organization itself, but other data comes from outside

the organization from suppliers, partners, and even

customers. Unlike the data models used by existing

Enterprise Resource Planning (ERP) systems, supply

chain decision support systems require a new breed

of memory resident data model that can handle vast

amounts of complex data in real time. Until now, if

you wanted an end-to-end solution, you had to

integrate specialized software with your existing ERP

system and built custom interfaces to handle outside

data sources. This can work, but only at an enormously

high cost.

The SAP Supply Chain Management Solution

SAP has introduced the Supply Chain Management

solution to meet the challenges of managing the entire

supply chain from end to end. The SAP Advanced

Planner and Optimizer ( SAP APO) is an important part.

With SAP APO, SAP has combined the ERP execution

power of the SAP R/3 System with advanced data

analysis and supply chain management tools.

Robust Integration Layer

Because SAP has built a robust integration layer

between SAP APO and the underlying execution system,

SAP APO can gain immediate and seamless access to

Online Transaction Processing (OLTP) business data.

While the data objects contained within SAP APO are,

in most instances, structurally optimized instances of

OLTP data, they remain synchronized through a series

of real-time triggers and messaging, a task that is

seamlessly accomplished through the integration

services of the Business Framework. SAP refers to this

technique as semantic synchronization. The SAP APOserver also integrates with the SAP Business Information

Warehouse using this same mechanism providing

unprecedented access to vital business decision data.

Advanced Optimization Techniques and Technology

In addition to highly specialized data objects, SAP APO

uses a library of advanced optimization algorithms and a

high performance, memory resident data processor to

perform planning and optimization. You can configure

SAP APO to provide task-specific, industry-specific, and

company-specific optimization, automated decision, andreal-time event notification to the underlying business

processes.

This brochure provides an introduction to SAP APO

and discusses in depth Demand Planing, one of the

SAP APO components.

Figure 1: SAP APO Overview


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Overview of SAP AdvancedPlanner & Optimizer

The SAP Advanced Planner and Optimizer builds on

the SAP Business Framework to improve informationflow by incorporating real-time collaborative decision

suppor t, advanced planning, and optimization into the

SAP R/3 System. SAP APO uses a powerful memory

resident analytical engine and highly specialized, highly

configurable data objects that offer major new

components:

n Supply Chain Cockpit

n Demand Planning

n Supply Network Planning and Deployment

n Production Planning and Detailed Scheduling

n Global Available-to-Promise

Supply Chain Cockpit

Graphical Command Center

The Supply Chain Cockpit component is a graphical

instrument panel for modeling, navigating, and

contr olling all the links in the supply chain. It gives

you a complete view of the entire length of the supplychain. Its the command center the cockpit from

which you manage your supply chain.

Using the Supply Chain Engineer, you can build an

elaborate graphical representation of even the most

complex supply chain. Once you have built a map of

the supply chain, you can select any part of it and zoom

in to a detailed level. Using a series of event triggers

and alarm conditions, the Alert Monitor can

automatically identify problems in the supply chain. It

can also monitor material, capacity, transportation,

and storage constraints, and it can handle such metr icsas delivery performance, cost flow, and throughput.

Demand Planning

Accurate Forecasting

The Demand Planning component is a toolkit of

statistical forecasting techniques and demand planning

features that helps you create accurate forecasts and

plans. Demand Planning is tightly linked to the SAP

Business Information Warehouse, so you can use

advanced Online Analytical Processing techniques todrill down to detailed levels of data and analyze

historical, planning, and business intelligence.

Because it integrates such a wide set of data, Demand

Planning gives you a sound understanding of all the

factors that affect demand, delivering context-based

demand planning, which raises forecasting to a new

level of sophistication and accuracy. Like the Supply

Chain Cockpit, Demand Planning uses the Alert

Monitor to report exceptions, like orders that exceed

forecasts or orders that fall short of forecast and

therefore may lead to excess inventory if production

is not adjusted accordingly.

Using Demand Planning, you can:

n Perform co llaborative forecasting

You can collec t for ecas t data from multiple

sources and store it in a common repository so

planners from marketing, sales, logistics, and even

third-party vendors and suppliers can work

together on a consensus forecast.

n Manage product life cycles

You can manage the life cycles of your products

according to such factors as product supersession,

substitution, and cannibalization.

n Plan promotions

You can model promotional demand based on

profitability goals, product availability, and

historical patterns. You can even predict how price

increases or decreases will affect future demand.

nForecastnewproductdemandYou c an de velop accu rate forecasts for new

products based on models from similar products,

demand h istories, and other factors. You can

monitor the launch of a new product and the end

of a products life using point-of-sale data.

n Performcausal analysis

You can identify and predict how such factors as

demographic changes, environmental variables,

and social or political factors affect demand for

your products. You can analyze actual demand

using a variety of tools, such as multiple linearregression, and incorporate causal factors such

as price.

Supply Network Planning and Deployment

Model Your Entire Supply Chain

Using the Supply Network Planning and Deployment

component you can develop a model of your entire

supply network and all of its constraints. Then, using

this model, you can synchronize activities and plan

the flow of material along the entire length of the supplychain. This allows you to create feasible plans for

purchasing, manufacturing, inventory, and trans-

portation and to closely match supply and demand.


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Drawing on data in liveCache, a high-performance

memory-resident technology, and using algorithms,

user-developed rules, and policies, the Deployment

component helps you dynamically rebalance and

optimize your distr ibution network. It also helps you

dynamically determine how and when to distribute

inventory.

Using the Supply Network Planning and Deployment

component, you can:

n Model plans at aggregate and detailed levels

n Perform what-if analysis

n Dynamically match supply and demand using

product substitutions

n Use vendor-managed inventory techniques

n Determine the optimum distribution of supply to

meet short-term demand

Production Planning and Detailed Scheduling

Generate Production Plans Rapidly

The Production Planning and Detailed Scheduling

component is an integrated set of tools that helps you

respond rapidly to changing market conditions. Using

this component, you can generate production plansand schedules that optimize resources. The com-

ponent offers optimization based on state-of-the-art

methods, such as the theory of constraints and

optimization librar ies. Using this component, you can:

n Perform forward and backward scheduling on

multiple levels

n Perform detailed capacity planning and material

planning simultaneously

n Synchronize schedules and make scheduling

changes at multiple levels of the bill of materials

( BOM)

n Use what-if scenar ios to simulate actual conditions

and consider the effect of various constraints

n Perform interactive scheduling and plan optimization

using a Gantt chart

n Integrate sales and distribution backorder

scheduling into the manufacturing process

Global Available-to-Promise

Match Supply and Demand with Global Available-to-Promise

The Global Available-to-Promise ( ATP) component

uses a rules-based strategy to ensur e you can deliver

what you promise to your customers. Global ATP

performs multilevel component and capacity checks

in real time and in simulation mode to ensure that

you can match supply and demand. You can also

per form these ATP chec ks against aggregate d,

memory-resident data for even better performance.

Global ATP maintains simultaneous, immediate access

to product availability along the supply chain, so you

can be confident that you can meet your delivery

commitments.

Global ATP draws on a number of criteria to arrive ata commitment, including:

n Productsubstitution

If a finished pr oduct or component is not available,

the system automatically selects a substitute using

rules-based selection criteria.

n Selectionofalternativelocations

As with product substitution , Global ATP can

sour ce mater ials from alternative locations. You

can also integrate this logic with the product

substitution r ules.

n Allocation

You can allocate pr oducts or components that are

in short supply to customers, markets, order s, and

so on. The ATP calculation and r esponse take these

allocations into consideration.

The SAP Business Framework

Integrate New Technology and Legacy Systems

SAP APO is a separate SAP solution with its own release

cycle. It is a Business Component of the Business

Framework, SAPs strategic product architecture,

which is designed to facilitate the seamless and rapid

integration of new business functions and information

technology into existing environments. The Business

Framework provides an open architecture, allowing

its basic elements, the Business Components, to

operate through standardized Business Application

Programming Interfaces ( BAPIs) . Each of the SAP APO

components, such as Demand Planning, can be

implemented as a stand-alone product or as an inte-

grated part of the Business Framework.


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Benefits of SAP AdvancedPlanner & Optimizer

SAP APO provides a number of benefits, including the

following:

n Completeness

SAP APO supports all of the key supply chain

planning and optimization functions and processes

traditionally found in stand-alone advanced

planning and scheduling solutions.

n Performance

The SAP liveCache memory resident computing

technology enables forecasting, planning, and

optimization functions to be executed in real time.

n Independence

SAP APO performs planning functions and

processes outside of the OLTP system, ensuring

greater flexibility and high availability of the

SAP APO server.

n Openness

SAP built SAP APO to function in heterogeneous

environments. It interoperates with SAP R/3, third-

party, and legacy OLTP systems.

n Integration

SAP APO is seamlessly integrated with the

R/3 System so you can integrate all the links in

your supply chain. A robust and sophisticated

integration layer facilitates the use of SAP APO with

additional optimization and forecasting

algorithms.

Key Features of SAP AdvancedPlanner & Optimizer

Demand PlanningA Ready-to-Run Solution

SAP APO Demand Planning is a state-of-the-art, ready-

to-go demand planning solution. It includes a data

mart based on the star schema and an easy-to-use front

end with powerful planning and analysis tools. You

can implement SAP APO Demand Planning quickly,

simply, and cost-effectively.

SAP APO Demand Planning is integrated with the

R/3 System and the SAP Business Information

Warehouse. Data can be automatically transferred

between SAP BW and SAP APO Demand Planning.

SAP APO Demand Planning uses multidimensional datastructures that support many different levels and

dimensions. Using tree selection and drill-down

capabilities, you can navigate through these multi-

dimensional structures.

SAP APO Demand Plannings decision-support tools

allows you to perform what-if analysis and online

simulation to create, store, and compare different

planning versions. In Release 2.0 the Notes Management

tool enables the documentation of planning activities by

multiple users.

Best-of-Breed Solution

SAP APO Demand Planning embodies all of the

advantages of a best-of-breed demand planning solution

with the following features:

n Multilevel planning

n Life cycle management

n Promotion planning

n Causal analysis

n Multitier forecasting

n Phase-in and phase-out forecasting

n The Statistical Forecasting Toolbox

n Forecast accuracy reporting.

Internet Communications

Using the SAP APO OpenForecast tool, you can

collaborate with your business partners using Internet-based interfaces and technology; share event

information, such as promotions and store openings;

and compare and r esolve variances within forecasts.

It supports supply chain par tnerships, such as Vendor-

Managed -Inventor y ( VMI) , Efficient Consu mer

Response (ECR), and Collaborative Planning,

Forecasting and Replenishment ( CPFR).


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The SAP APO Demand Planning Architecture

SAP APO Demand Planning is composed of three

layers:

n Graphical user interface

n Planning and analysis engine

n Data mar t

The graphical user interface contains the planning

views. The planning and analysis engine contains the

Online Analytical Processing processor, the Business

Planning Library, and the Statistical Forecasting

Toolbox. The data mart contains infocubes, the time

series catalog, and notes. The data mart stores different

data types in different database structures using arelational database.

Figure 2: SAP APO Demand Planning Architecture

An Integrated Demand Planning Solution

Seamless Integration

You can directly link SAP APO Demand Planning to

SAP R/3, the SAP Business Information Warehouse,

and any legacy or external systems for a completely

integrated system. This integration provides a

continuous planning cycle in which actual data, such

as orders and shipments, flows from SAP R/3 to SAPAPO Demand Planning, and demand data, such as

price information, flows from profit-based

promotional planning in SAP APO to SAP R/3.

Ready Access to Data

The SAP Business Information Warehouse is a product

that combines state-of-the-art demand planning

techniques and state-of-the-art data warehousing

features in one consistent model. Its integration with

Demand Planning means accurate decision-support

information is always at your fingertips.

Easy Data Transfer

The APO Demand Planning data mart uses InfoCubes

that have the same data structures as those that are

used in the SAP Business Information Warehouse.

It is therefore extremely easy to transfer data between

the two applications.

This integration provides many benefits. For example,

you can stor e syndicated point-of-sale data, such as

AC Nielsen data, in the SAP Business Information

Warehouse. You then analyze this data in SAP APO

Demand Planning and determine which of it should

be used in causal analysis. You cr eate consensus

forecasts in SAP APO Demand Planning and transfer

them to the SAP Business Information Warehouse,

where users can work with them to create the reports

and ad hoc analyses that drive the business.

You can use the SAP Business Information Warehouseto pull data from multiple heterogeneous data sources

into the data mart.

Integrate the Sales Force and Forecasting

You can integrate the sales force into the forecasting

process by using the SAP Mobile Sales solution on a

laptop. You can download account data from the data

mart into the laptop and then use SAP Mobile Sales on

the laptop to enter sales figures for the accounts offline.

When youre finished, you can upload the data back

into Demand Planning to update the sales figures in

the data mart.

Figure 3: SCM Cycle


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Demand Planning Features and Functions

Data Storage and RepresentationMultidimensional Data Storage

SAP APO Demand Planning allows you to view data,

plan from many different perspectives, and dr ill down

from one level of detail to the next. To make this

possible, SAP APO Demand Planning stor es data in a

multidimensional form in the SAP APO Demand

Planning data mart.

InfoCubes

An InfoCube is a multidimensional data structure andthe primary container of data used in planning,

analysis, and reporting. InfoCubes contain two types

of data: key figures and characteristics. Key figures

are quantifiable values, such as sales in units.

Characteristics determine the organizational levels at

which you do aggregation and reporting. Typical

characteristics for sales are products and customers.

Figure 4: Example of an InfoCube

Hierarchies and Networks

Develop Aggregation Hierarchies

The hierar chical relationships of characteristics play

an important role in planning and reporting. In

SAP APO, you model hierarchies and networks as

combinations of characteristic values. For example,

products are generally grouped into product family

hierarchies. Demand Planning allows you to model a

hierarchy over the value domain of one or more

character istics. You can use these hierarchies as the

basis for aggregation, disaggregation, and drilling

down. They provide the ability to plan and view data

at varying levels of detail.

Time Series Management

Reusable Time Series

Times Series Management is based on catalogs. In each

catalog, you can store time series data with related

attributes, such as promotional patterns and life cycles.

SAP APO Demand Planning allows you to reuse timeseries, which saves time and ensures consistency. For

example, you can r euse a past pr omotional pattern to

estimate the impact of a future promotion of the same

type.

Notes Management

Maintain an Audit Trail

The Notes Management tool maintains all notes entered

by planners. The notes d iscuss planning data, such as

promotions and consensus forecasts. You can use thenotes to create an audit trail of all demand planning

activities, which is especially helpful when multiple

sources and people are involved, such as in consensus

forecasting.

Planning Environment

Easy Data Access with Planning Books

You access the information in InfoCubes and Time

Series Management using planning books and reports.

Using slice-and-dice techniques, you can define how

information is displayed in a planning book. Demand

Planning provides you with a uniform planning

Incorporate Business Rules

The aggregational behavior o f key figures must follow

business rules. Key figures, such as sales, might be

summed by product and time. SAP APO Demand

Planning allows you to model these properties.

The Online Analytical Processing pr ocessor guarantees

that all business rules ar e met and that the computed

views present valid results from a business point of view.

The InfoCubes allow you to stor e multiple key figures,

such as order s, shipments, POS, and r elated forecast

components, as well as plans and causal factors.

InfoCubes also share master data and descriptive text,

which are stor ed in separate tables.


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environment that supports full multilevel planning with

top-down, middle-out, and bottom-up reconciliation

strategies. Within this planning environment, you can

use a wide range of demand planning and forecasting

techniques.

Business Planning Library

Library of Powerful Planning Functions

The Business Planning Library is a collection of

powerful planning and analysis functions. Using these

functions, you can convert the data contained in the

InfoCubes into relevant business information.

Demand Plannings rich planning and forecasting

functions are based on the Statistical Forecasting

Toolbox and the Business Planning Library. Thesefunctions include:

n Aggregate functions

Aggregate functions include SUM and AVERAGE.

The information content of many types of data is

greater when viewed on an aggregate level. For

example, product sales are most useful when

viewed on a regional or national level.

n Disaggregate functions

Disaggregate functions include disaggregation

based on quotas, proportional distribution, andequal distribution. In many cases, planning results,

such as forecasts and promotions, are output on

an aggregate level and must be disaggregated to

the detailed level.

n Comparison functions

Comparison functions include difference, ratio,

percent, and so on. These functions are essential

for determining the difference between forecasts

and actual results so you know quickly how far

forecasts deviate from your actual results.

n Financial functions

Financial functions include conversion from units

into revenue, cur rency conversion, and business

period conversion.

n Time-series functions

Time-series functions include the time-phased merge

of time series, time series averages, and time-series

weighted averages. Time-series functions work with

planning techniques, such as composite forecasting.

Planning Books

Easy-to-Use Planning Books

A planning book is an easy-to-use tree control for

selecting data and a frame with a grid and a chart.

The tree control in the planning books allows you to

explore data easily and to change the perspective of

the view by simply clicking the mouse. Tree control

provides all data from the various dimensions and

hierarchies that matches the given set of selection

criter ia. For example, you can initially select a general

view, jump to a view that is more detailed, and then

jump again to a more aggregated view.

Jump Between Data Views

You can a lso jump to a data view for completelydifferent planning issues. For example, a sales

manager examining sales forecasts can look at sales

for a particular continental region, such as Europe,

and then drill down to sales for individual countries

within Europe. The manager can stay at this level of

detail, but switch views by displaying sales according

to product group.

The planning books grid displays selected data, such

as forecast components and planning versions, using

slice-and-dice functions.

You can specify which unit of measure and calendar

to display and used for planning, and calendars allows

you to mix multiple per iods of time. For example, you

can start with weeks, change to months, and change

again to quar ters. You can total row and column with

a mouse click, and these totals remain fixed as you

scroll through the grid.

You can make adjustments on the basis of absolutes

and percentages. If you change data on one level of

aggregation, the system automatically updates the data

on other levels of aggregation. The same is true ofdisaggregation changes. You can also fix the values of

certain data elements during the reconciliation

process.

Graphical Data Display

The grid is directly linked to a chart, which displays

information from the grid in user-specific graph

modes. You can also adjust values directly in the chart.

If you edit data either in the grid, the system

automatically updates the data in the chart, and vice

versa so you never need to worry about inconsistentdata.


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Customizable Planning Books

SAP APO Demand Planning Books are highly

configurable. You can easily change the properties of

the grid and the chart, and you can save different

settings as profiles so the system works the way youdo, not the other way around.

You can run online simulations from the time that data

is uploaded into the p lanning book until the changes

are saved. This allows you to see the effects of different

judgmental techniques on the forecast.

Preconfigured Planning Books for Quick Starts

SAP APO Demand Planning comes with preconfigured

planning books for promotional planning, causal

analysis, statistical forecasting, life cycle management,and so on, so you can get star ted r ight away. You can

also use these as guides for customized planning

books.

Advanced Macros

Quick and Easy Macros

You can use advanced macros to per form complex

spreadsheet calculations quickly and easily. The

macros are extremely flexible, so you can use them to

model your planning environment based on your

individual business tasks. Using the macro tool, you

can:

n Control how macro steps are processed usingcontrol instructions and conditions

n Build a macro consisting of one or mor e steps

n Control how macro results are calculated usingcontrol instructions and conditions

n Use a wide r ange of functions and operators

n Define offsets so that the result in one period isdetermined by a value in the previous period

n Restrict the execution of a macro to a specificperiod or periods

n Write macro results to a row, a column, or a cell

n Write the results of one macro step to a row,column, cell, or variable, and use them only insubsequent iterations, macro steps, or macros.

n Analyze forecasting or business data at a glanceusing special icons

n Create context-specific and user-specific planningviews

n Trigger an alert in the Alert Monitor to inform you

of particular business situations

Figure 5: Example of Planning Book Design with Advanced Macros


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Integration with Microsoft Excel

Use Familiar Tools

If you are already familiar with Microsoft Excel, you

can use Excel to edit data before transferring the

results back to the grid. You can also store the content

of the grid in Excel on a laptop. This allows you to

work in a familiar environment, which reduces errors

and training costs.

Consensus-Based Forecasting

Consensus Planning Drives the Business

SAP APO Demand Planning supports consensus-based

sales and operations planning. Its planning and

forecasting features allow you to create plans fordifferent business goals (such as a strategic business

plan, tactical sales plans, and the operative supply

chain plan) and integrate them into one consensus

plan that drives the business. The planning books and

repor ts help you gain consensus in meetings because

they allow you to see the effects of your decisions.

Multiple Views

View Data from Multiple Angles

The multidimensional data structure of the InfoCubesallows you to view past sales and forecasts in many

different dimensions, using varying units of measure

and degrees of granularity, including:

n Product levels for mar keting

n Sales areas and accounts or channels for sales

n Distribution centers and plants for operations

n Business units for finance

Consensus Plan

Create Multiple Versions of Plans

The forecasting techniques in SAP APO Demand

Planning allow you to create many planning versions

on any level and in any dimension using the same or

similar data. For example, you can maintain multiple

demand plans, such as a marketing plan, a sales plan,

and an operational plan, so you can tailor them to

individual situations and needs.

Synchronize Multiple Plans

Demand Planning can reconcile and combine different

plans on the same level and it can synchronize plans

created on different levels and different dimensions

so you can always arrive at a consensus forecast.

Multilevel Planning

Synchronize Forecasts and Promotions

Multilevel planning capabilities allow you to forecast

and plan on any level and in any dimension. Demand

Planning provides consistent planning capabilities that

synchronize forecasting and promotional data on any

level in real time. You can plan from the top down,

from the bottom up, and from the middle out. You

can base disaggregation of data on user-defined time-phased quotas, proportional distribution relative to

user-specified data streams, and equal distribution.

Life Cycle Management

Life Cycle Management is a function of both the

Demand Planning and the Supply Network Planning

components. In the demand planning process, the

planning strategies for a product depend on the stage

in its life cycle.

Analysis capabilities help you make decisions. DemandPlanning helps you answer questions like:

n Should a new product be introduced?

n When should a new product be introduced?

n How should a product be promoted during the

different stages?

n Should the pr oduct be eliminated, and if so, when?

n Should a follow-up product be introduced?

n Should a product be relaunched and when?

n Will introducing a new product cannibalize sales

of existing products?

Complete Life Cycle Management

Aproducts life cycle consists of different phases:

n Launch

n Growth

n Maturity

n Discontinuation


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In Demand Planning, you can represent the launch,

growth, and discontinuation phases by using phase-

in and phase-out pr ofiles. Aphase-in profile reduces

demand history by ever incr easing percentages during

a specified period or periods, thus mimicking the

upward sales curve that you expect the product to

display during its launch and growth phases. Aphase-

out profile reduces the demand forecast of a product

by ever decreasing percentages during a specified

period or periods, mimicking the downward sales

curve that you expect the product to display during its

discontinuation phase.

Create Forecast with Minimal Data

Some pr oducts do not have enough historical data to

provide the basis for a forecast. With likemodeling,you can create a forecast using the historical data on

a product with similar demand behavior. You can use

like modeling for new products and products with

short life cycles.

For any product, you can use a phase-in profile, a

phase-out pr ofile, a like profile, or any combination

of these.

Promotion Planning

Factor Price into Promotional Projections

Promotions of all kinds have a major impact on

consumer sales behavior. The impact of promotions

must be pr ojected separately from standar d forecast

components that are based on historical sales data.

Promotion-driven components are generated on top

of a baseline forecast. Demand Planning extends

classical volume-based pr omotional planning so that

you can take prices into account when doing

profitability analysis for promotional calendars.

You can plan pr omotions on any level, and you can

aggregate or disaggregate them using the Business

Planning Library.

Reporting capabilities allow you to track promotional

activities and related costs and, therefore, assess the

efficiency of your companys pr omotional campaigns.

Figure 6: Example of Promotion Planning.


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Promotion Patterns

Isolate Promotional Patterns

You can define prom otional uplifts in units or

percentages with promotion patterns. Using historical

sales or estimates, the system can automatically detect

a promotion pattern that occur red in the past. You

can archive a promotion pattern in a promotion

catalog, so you can reuse it if you repeat the promotion

at a later date. The promotion catalog has a copy

function that you can use to model like products,

like regions, and so on. Demand Planning provides

several techniques for estimating the effect of a

promotion, such as multiple linear r egression with or

without a trend or seasonality. Figure 7: Example of Multi-Tier Forecasting

Causal Analysis

Include Causal Factors in Forecasts

To predict consumer behavior, you must first

understand all the factors that influence it. With

Demand Planning, you can include all significant

causal factors in your models and deter mine how they

affect your customers behavior. Causal factors include

price, number of displays, number of stores,

temperature, and working days. You can even forecast

the unknown future of causal factors using Demand

Planning forecasting techniques.

Breaking down sales to determine the impact of causal

variables allows you to model the virtual consumer

and simulate sales development accor ding to the mix

of causal factors.

Use Proven Methods

Demand Planning provides the proven forecasting

method of multiple linear regression to model the

impact of causal factors.

Multitier Forecasting

Multitier forecasting integrates sell-in data, like point-

of-sale data, into the process of forecasting

sell-through data, like shipments. You can use a causal

model based on all significant causal factors to forecast

POS. You then use a second causal model to forecast

shipments. The shipment model uses past POS data

and the POS forecast as the main causal factor while

taking the time lag between POS and shipments into

account. You can also consider other causal factors,

such as forward buys and trade promotions.

Statistical Forecasting Toolbox

Multiple Tools for Multiple Forecasting Needs

Your companys product portfolio probably includes

a variety of products that ar e in different stages of their

life cycle and have different demand types.

Unfortunately, a single forecasting method that creates

accurate statistical forecasts for mature products,

slow-moving products, and hot new products does not

exist. Approaches that attempt to cover most of such

demand types are very complex and tend to be a black

box for planners. You have to use different methods

to get the right answers. Demand Planning offers a

toolbox of all practical, proven forecasting methods.

You can choose the best method for a specific type of

demand. Composite forecasting extends the idea of

picking the best method, allowing you to combine

forecasting methods.

The Statistical Forecasting Toolbox provides all the

tools you need to efficiently create accurate forecasts,

including data analysis using time series models and

multiple linear r egression.

Data Analysis

Identify Missing Values

With Demand Planning, you can identify missing values

and outliers in the data that drives the forecast and

adjust the data or the applied forecasting method. This

improves the quality of the statistical forecast.


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Intervene as Changes Occur

Structural changes in established patterns, such as

level changes, trend changes, amplitude changes, and

changes from unstable to stable behavior, must be

identified. By automatically detecting structuralchanges using a tracking signal, Demand Planning

allows you to take cor rective action. You can either

adjust the applied forecasting method, or you can

replace it with a mor e suitable method. You can

intervene manually, or the system can do it

automatically.

Time Series Models

Time series models are techniques that use past

sales to identify level, trend, and seasonal patterns as

a basis for creating future projections. The Statistical

Forecasting Toolbox provides all of the most important

models, such as naive models, moving average, simple

linear r egression, Browns exponential smoothing, and

Holt-Winters so you always have the right tool for the

job. For time series models with a linear trend, you

can apply a dampening of the trend. You can a lso

integrate life cycle patterns into the time series models

using special profiles.

Stochastic Models

Accurate Forecast with Sporadic Demand

When sporadic demands exist, the time ser ies models

always produce inappr opriate stock levels as a result

of the high mean absolute deviation from periods

without demands. The Crosten method accounts for

this inaccuracy by using exponential smoothing to

estimate the size of demand during per iods in which

demands occur as well as the demand frequency. The

final forecast values are determined by distributing

the size of demand according to the demand frequency.

Multiple Linear Regression

Causal techniques are based on relationships between

past sales and other causal factors. Multiple linear

regression allows you to estimate these relationships

by performing a least squares fit.

You can choose from a variety of options to model

linear and nonlinear trends, including seasonal

patterns, life cycle patterns, dummy variables, and time

lags. Using correlation analysis, you can correct

variables. The system provides several statistics,

including adjusted R-squared and Durbin-Watson.

Pick-The-Best Option

With the pick-the-best option, the system either runs

all of the available forecasting methods or uses the

planner-specified forecasting methods and applies the

best one. You can specify the horizon for the fit criter iabased on short-term, medium-term, or long-term

forecasting goals.

Composite Forecasting

Composite forecasting creates a weighted average of

the forecasts of multiple forecasting methods to create

one forecast. You can determine the weights as equal

(simple average) or using multiple linear regression

by taking the residuals of the multiple forecasts into

account. In addition, you can time-phase thecombination so that short-term and medium-term

forecasts are combined with respect to their horizons.

Forecast Accuracy Analysis

Track Forecast Accuracy

Forecast accuracy reporting helps companies assess

the accuracy of past forecasts and integrate this

knowledge into projections for the future. The primary

technique is to store a series of forecasts for a

particular period and to compare each deviation ofthis series to the actual values for the same period.

You can then project the deviation into the future. This

visualization of expected deviation not only places the

forecast in context, it also enables what-if planning.

For example, this enables a business to evaluate future

scenarios for maximum, planned and minimum

production volumes, stock, sales revenue, and cash

flow. The real impact of forecast accuracy reporting

is realized when you couple it with a simulation at the

significant nodes of the supply chain.

In Demand Planning, you can also measure theaccuracy of the forecast using the following forecast

errors:

n Mean absolute deviation ( MAD)

n Error total (ET)

n Mean per centage error ( MPE)

n Mean absolute per centage error ( MAPE)

n Mean square error ( MSE)

n Square root of the mean squar ed er ror ( RMSE)


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Real-Time Alerts to Exceptions

In addition, the SAP APO Aler t Monitor informs you in

real time via e-mail or an exception message in an

exception window if an exception occurs in Demand

Planning.

You can d efine exception conditions b ased o n

thresholds for special statistics, such as MAD and

tracking signals, so that the system alerts you if bias,

outliers, or trend changes occur or orders exceed the

forecast. This allows you to take action quickly when

it can do the most good.

Forecast accur acy repor ts show forecast er rors at any

level and dimension. They compare:

n Actual versus forecast

n Actual versus time-lagged forecast

n Actual versus different planning versions, such as

baseline forecast or consensus forecast

n Actual versus budget

You can sort reports by forecast er ror or restrict them

to products with a forecast er ror greater than a user-

specified thr eshold.

PerformancePerformance is of vital importance in any demand

planning solution if users are to benefit fully from

available information. Demand Planning ar chitecture

includes several features that ensure high

performance:

n Dedicatedserver

SAP APO resides on its own dedicated server. Like

the SAP R/3 System, there are a number of

configuration options to provide highly scalable

performance as the number of users increases.SAP APO takes full advantage of the flexibility of

SAP R/3s three-tier client/server technology.

All SAP APO server components can reside on

the same har dware system, or you can place the

database on a dedicated database server. You can

also add multiple application servers as the

number of users increases.

n Multidimensional datamart

The data mart is based on the star schema. The

star schema is a structure that suppor ts efficient

use of storage space and of CPU cycles,

minimizing query response time.

n Batchforecasting

You ca n upd ate long-running mass foreca st

updates as a batch process so you do not impede

online performance.

Conclusion

Demand Planning provides multiple benefits that help

you match supply and demand and manage the entire

length of your supply chain. Demand Planning is:

n A fast solution

Because Demand Planning is a component of the

SAP Business Framework, you can implement it

rapidly and at a low cost.

n An open solution

SAP APO Demand Planning does not limit you to

using SAP R/3 or R/2. Using open interfaces, you

can integrate SAP APO Demand Planning with non-

SAP data sources and non-SAP tools to create the

best solution for your business.

n A function-rich s olution

SAP APO Demand Planning has the tools you need

so you dont need to assemble them from multiple,

specialized software packages. Demand Planning

can improve forecast quality, model consumer

sales behavior and market dynamics, integrate

processes that drive the forecast, share

information, and enable collaborative forecasting

with business partners.

n An adaptable solution

If your needs or your IT environment change and they will SAP APO Demand Planning can

adapt to these changes.

n A robust, business-driven solution

Based on SAPs proven exper tise in SAP R/3 client/

server technology and in real-world business

processes, Demand Planning is built to answer the

specific demand planning and information

requirements of planners and forecasters in all

industr ies, reliably and effectively.


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For your note:


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