SAS Demand-Driven Forecasting combines automation, analytics, and workflow to create accurate consensus forecasts on a large scale, enhancing supply chain efficiency. It utilizes a user-friendly interface to incorporate existing data and market signals, supporting organizations in improving forecast accuracy and decision-making. The solution is designed for various business roles, providing what-if analysis and scenario planning to align forecasts with dynamic market conditions.

1. FACT SHEET
SAS Demand-Driven Forecasting
®
Maximize profitability, market share and customer satisfaction
Today, most companies use legacy With SAS Demand-Driven forecasting,
What does SAS Demand-Driven
®
ERP/SCM solutions that are workflow- you can:
Forecasting do? based with little emphasis on analytics, • Harness your existing data with pow-
SAS Demand-Driven Forecasting drives resulting in inaccurate forecasts. This erful analytics through a user-friendly
the development of the consensus process is resource-intensive, time con-
forecast in conjunction with the S&OP interface.
suming and is driven solely by domain
process. Featuring not only scenario • Build a workflow designed around
modeling, but a new demand plan- knowledge and biased judgment.
your processes.
ning workbench to support advanced
consensus forecasting, it provides scal- Using inappropriate systems can put • Use business intelligence to drive
ability, automation, depth and a breadth your organization at a competitive what-if analysis and disseminate the
of advanced analytics to aid the demand results across your organization to
disadvantage and prohibit you from
forecasting and planning process.
driving top-line growth and fulfilling make better decisions.
Why is SAS Demand-Driven
®
customers’ needs. With appropriate • Shorten the time it takes to drive your
Forecasting important? technology, organizations can become supply chain and realize significant
SAS Demand-Driven Forecasting com- demand-driven by incorporating savings in time and money.
bines the power of automation, analytics customer demand signals and market • Support a formal S&OP process with
and workflow to generate an unbiased trends in the demand plan accurately, strong methodologies that incorpo-
accurate consensus forecast on a large- frequently and in real time – while
scale basis. Using what-if analysis capa- rate an understanding of organiza-
anticipating demand variability to tional dynamics.
bilities, you can adjust forecasts based
on a structured process that incorporates remove the threat to profit margins.
data and analysis – rather than pure Key Benefits
judgment – to enhance the accuracy of SAS combines the power of automa-
your forecasts. Improve statistical forecasting
tion, analytics and workflow to generate
accuracy across the product hierarchy
the most unbiased and accurate
For whom is SAS Demand-Driven
®
SAS’ patented statistical forecasting
forecast on a large-scale basis. SAS
Forecasting designed? engine has a complete array of
allows you to consolidate and reconcile
SAS Demand-Driven Forecasting is advanced forecasting methods,
large volumes of information in a
designed for forecast analysts, business
structured way to create accurate including Exponential Smoothing,
planners in sales, marketing and finance,
and senior level managers responsible for consensus forecasts and easily share Winter’s, ARIMA, ARIMAX, UCM and
creating sales forecasts that provide input them throughout the organization to dynamic regression to model and
into the consensus forecasting process. reduce excess inventory costs, forecast all products across an
eliminate out-of-stocks and improve organization’s product portfolio. SAS
downstream planning efficiencies. can integrate consumer demand (pull),
model it and forecast it automatically
The SAS solution automatically using award-winning data access tools.
creates a weighted consensus forecast
Reduce finished goods inventory
by tracking variation between forecasted
levels and stock-outs
and actuals to aid the consensus
forecasting process. SAS’ what-if SAS provides forecasts that reflect the
analysis and scenario modeling realities of the business, improving your
capabilities help you plan for future ability to forecast and plan future events
events, including new product launches, with confidence. As a result, safety
location and channel introduction, and stock levels can be tightened along with
simulate the impact of possible market- on-hand finished goods inventory,
ing investment strategies and product adding more efficiencies to the overall
mixes to find the optimal forecasting supply chain. Also stock-outs, or back
scenario for maximum profitability. orders, are reduced as the right

2. products are produced at the right time and share results through the SAS business. The open model repository
and stocked at the right locations. Supply Chain Intelligence Center using has all statistical methods, including:
SAS’ Web access engine across the time series, exponential smoothing,
SAS also provides a Multi-Echelon organizational business hierarchy. The Winter’s, ARIMA, ARIMAX, dynamic
Inventory Optimization component as solution features a new demand regression, UCM and custom methods.
an optional feature to SAS Demand- planning workbench that provides
Driven Forecasting that includes workflow to generate a final consensus Flexible data modeling allows you to
distribution requirements planning forecast. The weighted consensus model large and complex forecasting
(DRP) reporting, sensitivity analysis and forecast, along with individual fore- structures and easily make changes to
scenario planning capabilities. casts, will populate a “gap” report, your forecast model to reflect changes in
providing information that can be your business and product structures.
Generate a more accurate consensus utilized during the S&OP process to For example, use forecast models for
forecast with gap analysis and strategies high-volume manufactured products,
finalize a consensus forecast that
reporting across all business units
helps drive all downstream planning highly seasonal products, promoted
The overall forecasting process and functions and/or systems. products and slow-moving items with
workflow are enhanced with SAS’ more intermittent demand.
structured approach provided with the Large-scale automated statistical
advanced consensus forecasting model selection and optimization Event modeling console
planner workbench supported by with hierarchical reconciliation
Model the effects of sales promotions,
advanced analytics. Statistically SAS’ patented expert-selection forecast marketing events, and other external
generated weighted consensus engine analyzes and combines various events (i.e., pricing policy actions,
forecasts are created automatically models to produce a forecast that best holidays, severe weather events, etc.)
using award-winning weighted com- depicts your organization at every level that affect the forecast. The console
bined forecasting methods. Gap of your corporate and product hierarchy statistically models events to determine
reports are generated electronically, for complex supply chain networks with sales lifts associated with promotions,
indicating the gap between the financial complex business rules. special marketing events and other
plan, all individual, departmental and irregular activities. Using patented
statistical baseline forecasts, with notes SAS provides hierarchical forecasting technology in the event model console,
indicating reasons. Those reports can for hundreds of thousands of data series you can choose among several event
be viewed through the SAS Supply and synchronizes and allocates forecasts types including pulse, level shift, ramp
Chain Intelligence Center using SAS’ from any level within the hierarchy. Other up/down and temporary events. And,
Web access engines. The reports can features include: pre-programmed holiday events are
be reviewed, changed and written back available (e.g., Christmas, Easter,
• Interactive point-and-click interface
to the SAS Demand-Driven Forecasting Thanksgiving and others).
(GUI).
data model during the consensus
forecasting process. • Project set-up wizards.
What-if analysis and scenario planning
• High performance hierarchical
With scenario analysis, evaluate
statistical engine.
Solution Overview exceptions to your sales history and plan
• Graphical engine. for future events – including new
SAS Demand-Driven Forecasting
• Statistical engine to provide various product, location and channel introduc-
automatically creates statistical forecasts
statistical calculations (e.g., MAPE, tion. Conduct what-if analyses using
on a large scale – based on a business
MAD, etc.). statistical models to find the optimal
hierarchy that utilizes the most current
• Filter generator. forecasting scenario based on available
statistical methods. It allows manual
marketing investment strategies. What-if
adjustments by domain experts and
A model repository analysis and scenario planning can be
automatically creates a weighted
used for any situation, including realistic,
consensus forecast based on variation SAS provides the appropriate forecast
optimistic and pessimistic projections.
between forecasted and actuals. methods to address your product
portfolio requirements regarding harvest, Demand planning workbench
Monitoring, tracking and reporting with growth, niche and new product
The demand planning workbench allows
alerts allow you to compare the demand, based on the unique market-
you to import and consolidate internal
forecasts to KPIs, track performance place dynamics associated with your

3. and external customer forecasts (sales,
Key Features
marketing, finance and others). Using
what-if analysis capabilities, easily adjust Model repository with pre-defined models:
• Time series methods
the statistical baseline forecasts based
• Single Exponential Smoothing
on a structured process that incorpo-
• Holt’s/Brown’s Two Parameter Exponential Smoothing
rates data and analysis – rather than
• Winter’s Three Parameter Exponential Smoothing
pure judgment – to enhance the • Additive/Multiplicative
accuracy of your forecasts. You can • ARIMA
automatically create a weighted • Causal methods
consensus forecast using SAS’ • ARIMAX (ARIMA with intervention and causal variables)
weighted statistical method embedded • Lagged variables/transfer functions
in the demand planning workbench. • Dynamic Multiple Regression
• UCM (Unobserved Components Model)
The automatically generated statistical • Open model repository
weighted consensus forecast is • Add your own custom models
surfaced through the SAS Supply Chain Event modeling console:
Intelligence Center, or can be exported • Interactive JAVA GUI
to Excel as part of a consensus • Pre-defined holiday events (Christmas, Easter, etc.)
forecasting process in support of the • Automatic date realignment for Easter and other moving holidays
S&OP planning process. The reports • Customer event creator
• Four event types
can be shared across the enterprise us-
• Pulse
ing the SAS Supply Chain Intelligence
• Ramp up/down
dashboard Web access engine.
• Level shift
Centralized, collaborative templates are • Temporary
used to simplify the enterprisewide con-
What-if analysis and scenario planning:
sensus forecasting process using the
• Plug-in into the DDF applications dashboard
Demand Planning Workbench workflow • What-if planning capabilities using model parameter estimates
to finalize the consensus forecast and • Ability to change model parameter estimates to determine effects on forecasts
drive S&OP requirements planning.
Demand planning workbench:
• Interactive Consensus Planner workbench (workflow) with GUI
An automated interactive application and
• Automatic weighted consensus forecast generator
set of screens and reports help you • Override templates with drill down/up capabilities
collect and consolidate internal and • Web Access for sharing, viewing and authorized changes
external forecasts to create a consensus
Monitor, track and report:
forecast to drive the S&OP process. • Supply Chain Intelligence Center Dashboard with KPIs/Metrics
Forecasts can be averaged or weighted • Series of interactive forecasting monitoring and tracking reports
based on past performance for recon- • Series of alerts (graphical/tabulator) monitor excepts
ciliation. Assessment routines can be • Drill down/up capabilities
performed against financial KPIs to
determine the financial impact from a
revenue management perspective. The SAS application provides Web- Technical Requirements
enabled reports to monitor and track
Monitoring, tracking and reporting forecast performance and interaction Client environment
with the demand planning workbench, • Windows (x86-32): Windows 2000
Monitor, track and report with drillable
allowing access on an enterprisewide Professional, Windows XP Professional
alerts surfaced through a balanced
scorecard, or dashboard. Surface basis. Included in the dashboard are • Internet Explorer 6 and later
forecasting results with KPIs and alerts to identify key issues related to • Microsoft Office 2000 or later
performance metrics through a series of forecast performance – such as (for Microsoft Office add-in)
monitoring, tracking and reporting exception reports and iterative reviews of
• Microsoft .NET framework 1.1
capabilities using the SAS Supply Chain the consensus forecast.
(for Microsoft Office add-in)
Intelligence Center.

4. Additional software
• JRE: 1.4.2_09 (Sun)
• MySQL Pro 5.0.22
• MySQL Connector/J 5.0.3,
commercial version
Server environment
SAS Servers, including Base SAS and
SAS Metadata Server, can be installed
on one or more hardware systems in a
multitier configuration.
Operating Systems
• AIX: Release 5.2 / 5.3
• Windows (x86-32): Windows NT
4 Server, Windows 2000 Server,
Windows Server 2003
Figure 1. Supply Chain Intelligence Center featuring the Interactive Business
• Solaris SPARC Version 10
Intelligence Dashboard.
Additional software
• BEA WebLogic 8.1 service pack 3
• MySQL 5.0.22
Mid-tier environment
Additional required/optional software:
• SAS client and mid-tier require JRE
1.4.2_09
• BEA WebLogic 8.1 service pack 3
• WebSphere Application Server
Network Deployment Version 5.1.1.5
Figure 2. What-if analysis and simulation application helps planners make overrides in a
more structured environment using data and analytics versus pure judgment.
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