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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.
IBM, DB2, OS/2, DB2/6000, Parallel Sysplex, MVS/ESA, RS/6000, AIX, S/390, AS/400, OS/390, and OS/400 areregistered trademarks of IBM Corporation.
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ORACLE is a registered trademark of ORACLE Corporation, California, USA.
INFORMIX-OnLine for SAP is a registered trademark of Informix Software Incorporated.
UNIX,X/Open,OSF/1, and Motif are registered trademarks of SCO Santa Cruz Operation.
ADABAS is a registered trademark of Software AG.
SAP and SAP-Logo, R/2, R/3, RIVA, ABAP, SAP-EDI, SAP Business Workflow, SAP EarlyWatch, SAP ArchiveLink, ALE/WEB,BAPI, SAPPHIRE, Management Cockpit, SEM, are trademarks or registered trademarks of SAP AG in Germany and in several othercountries all over the world.
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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