8/10/2019 Demantra Overview.ppt
1/45
For Oracle employees and authorized partners only. Do not distribute to third parties.
2008 Oracle Corporation Proprietary and Confidential
8/10/2019 Demantra Overview.ppt
2/45
For Oracle employees and authorized partners only. Do not distribute to third parties.
2008 Oracle Corporation Proprietary and Confidential
Safe Harbor Statement
The following is intended to outline our general
product direction. It is intended for information
purposes only, and may not be incorporated into any
contract. It is not a commitment to deliver any
material, code, or functionality, and should not berelied upon in making purchasing decisions.
The development, release, and timing of any
features or functionality described for Oracles
products remains at the sole discretion of Oracle.
8/10/2019 Demantra Overview.ppt
3/45
For Oracle employees and authorized partners only. Do not distribute to third parties.
2008 Oracle Corporation Proprietary and Confidential
Oracle Training MaterialsUsage
AgreementUse of this Site (Site) or Materials constitutes agreement with the following terms and conditions:
1. Oracle Corporation (Oracle) is pleased to allow its business partner (Partner) to download and
copy the information, documents, and the online training courses (collectively, Materials") found on this
Site. The use of the Materials is restricted to the non-commercial, internal training of the Partners
employees only. The Materials may not be used for training, promotion, or sales to customers or other
partners or third parties.
2. All the Materials are trademarks of Oracle and are proprietary information of Oracle. Partner or other
third party at no time has any right to resell, redistribute or create derivative works from the Materials.
3. Oracle disclaims any warranties or representations as to the accuracy or completeness of any
Materials. Materials are provided "as is" without warranty of any kind, either express or implied,
including without limitation warranties of merchantability, fitness for a particular purpose, and non-
infringement.
4. Under no circumstances shall Oracle or the Oracle Authorized Delivery Partner be liable for any loss,
damage, liability or expense incurred or suffered which is claimed to have resulted from use of this Siteof Materials. As a condition of use of the Materials, Partner agrees to indemnify Oracle from and against
any and all actions, claims, losses, damages, liabilities and expenses (including reasonable attorneys'
fees) arising out of Partners use of the Materials.
5. Reference materials including but not limited to those identified in the Boot Camp manifest can not be
redistributed in any format without Oracle written consent.
8/10/2019 Demantra Overview.ppt
4/45
For Oracle employees and authorized partners only. Do not distribute to third parties.
2008 Oracle Corporation Proprietary and Confidential
Title of Presentation
Presenters Name
Presenters Title
Oracle Demantra Overview
Presenters Name
Presenters Title
8/10/2019 Demantra Overview.ppt
5/45
Demantra in the context
of APS (Broader Supply
Chain PlanningApplication)
8/10/2019 Demantra Overview.ppt
6/45
Agenda
After completing this module, you should be able to:
Understand Demantra in the context of APS
Describe key capabilities of Oracle Demantra
Understand what business processes are supported within
Demantra
Understand Oracle Demantra Concepts and Jargon
8/10/2019 Demantra Overview.ppt
7/45
Oracle Advanced Planning Solution
Future *
Integrated
PlanningFunctions
Products
Platform
E1 EBS LegacyE
RP* *
WFL Common planning
data model
Connectors
Network
Design Demand Sensing
And ShapingPostponement
Optimization Holistic
Supply
PlanningPromise,
Distribute, and
ReplenishExecute to plan
Embedded
Analytics
Role-based Portals
PreconfiguredWorksheets and
Workbenches
Operational
ExcellenceReal-Time
S&OP
Demand driven
adaptive planning
Multi-Enterprise
Collaboration
Trading Partners
Best in class
Business
Processes
Supply Chain
Risk Management
Strategic
Network
Optimization
Inventory
Optimization
Real-Time
Sales &
Operations
Planning
Demand
Management
& Advanced
Forecasting
Predictive
Trade
Planning &
Optimization
Advanced
Supply Chain
Planning
Production
Scheduling
Global
Order
Promising
Collaborative
Planning
8/10/2019 Demantra Overview.ppt
8/45
Oracle Demantra Application Modules
Real-time Sales and
Operations Planning
Predictive Trade
Planning
Demand
Management
Advanced Forecasting
and Demand ModelingTrade Promotion
Optimization
Deduction and
Settlement Management
8/10/2019 Demantra Overview.ppt
9/45
Demantra IntegrationThe Big
Picture
Trade
Management
Execution
Siebel CRM
Supply Chain
Management
and Financials
Oracle EBS
Strategic Network Optimization
Inventory Optimization
Adv. Supply Chain Planning
Global Order Promising
Collaborative Planning
Supply Chain Planning
Demand Management
Demantra
Demand Management
Advanced Forecasting
Predictive Trade Planning
Promotion OptimizationDeduction and
Settlement Management
Trade Promotion Management
Real-TimeSalesand
OperationsPlanning
Production Scheduling
JDE E1
Supply Chain
Management
and Financials
Demand Management
8/10/2019 Demantra Overview.ppt
10/45
What is Demand Planning?
Planning for future demand scenarios
Estimate future demand based on market conditions Collaborative planning process involving internal and external participants
A crucial function for improving operational plans
Optimal resource allocation
Reduced inventory levels
Improved customer satisfaction
Compare and consolidate disparate forecasts
Sales, Marketing, Manufacturing
In units or amount
Improve forecast accuracy
Better statistical forecasts
Manage by exception
Multi-dimensional OLAP for analysis (product, channel, geography, )
User-defined exceptions
Proactive notifications
8/10/2019 Demantra Overview.ppt
11/45
Stock outs & non-
availability
Customer Switching
Excessive inventory
Promotions negativeROI
Loss of revenue
NPI failure
Long
manufacturing
lead times
Promotions/Deals
fluctuate demand
Poor collaboration between
sales, marketing, demand
mgmt., operations, and with
customers
Product variations to
meet different
geographical and legal
requirements
Extreme
product
segmentation
Shorter product
lifecycles
High inventory
costs
Frequent new
product
introductions
Proper Demand Management and
Sales and Operations Planning helps
companies solve these challenges
and increase profitable revenue
growth.
8/10/2019 Demantra Overview.ppt
12/45
Typical Challenges
Shorter Product Lifecycles Frequent new product introductions putting increased burden on operations
Shorter life span of the product making it difficult to forecast
Extreme Product Segmentation Extreme segmentation of the product by color and aesthetic attributes to meet
various demographic needs causing stock-outs or excess inventory of certain
products. Product variations to meet different geographical and legal requirements. For
example, manuals, labeling and software to meet various language needs.
Disconnected sales and operations Lack of integration between sales/marketing and operations
Planning and review process is extremely manual and time consuming
Inferior systems Manual processes, low visibility in a globalized business climate
Multiple non integrated local systems
8/10/2019 Demantra Overview.ppt
13/45
What are the Implications?
Impact to customer service levels
Stock outs due to insufficient forecast can cause customers to switch
suppliers or be dissatisfied
Reduced pricing power; affecting the margins
Improper capital allocation
Forecast created for the wrong product could cause your supply chain to
be over-driven resulting in excess inventory Impact to resources such as capital, space, production resources, etc.
Lost opportunity to sell your products and increase revenue and profits
Inability to react to changing market conditions
If changing market conditions are not turned into advantage, profitability
may suffer
Competitors may gain
Unmet expectations
All of the above could result in unmet corporate expectations and decline
in shareholder value
8/10/2019 Demantra Overview.ppt
14/45
A Demand Driven Supply
Chain (Approach to
Mitigating theChallenges)
8/10/2019 Demantra Overview.ppt
15/45
Traditional Supply Chains
DemandDemand SupplySupply
Product
Traditional
Definition of
Supply Chain
Management
CustomerSupplier
Design
Partner
8/10/2019 Demantra Overview.ppt
16/45
Technology
Opportunities
Supply
Risk
Management
Demand
Insights
Product
DemandSupply
Demand-driven Processes
Drive a
Profitable
Demand
Response
Sense
Demand
Proactive approach to demand
management
Makes your supply chain
demand driven
Improved profitability due
proper prioritization of
demands,
Promotes collaboration
amongst all stakeholders
Supports replenishment system
with immediate visibility to
changing needs
Shape
Demand
Source: AMR Research
8/10/2019 Demantra Overview.ppt
17/45
Demand Shaping
8/10/2019 Demantra Overview.ppt
18/45
Shaping demands at the Heart of a
Demand Driven Supply Network
(DDSN) What is Shaping Demands?
Shaping demands can be defined as aligning your forecast toreality by taking all possible variables into consideration OR
Fully exploit market to maximize objectives
Strategic predictive forecasting Collaborate with stakeholders
Historical demand patterns
Managing new product introductions
Discounts and promotions
Trade promotion and promotion optimization Operational planning to satisfy demands
Sales and operations planning
Supply planning based on global forecasts
Supply positioning
8/10/2019 Demantra Overview.ppt
19/45
Strategic Predictive Forecasting
Collaboration Collaborate to incorporate inputs from different stake-holders in
the organizationsuch as marketing/sales/Operations
Forecast at the appropriate level of aggregation. For example,there may not be enough information for forecast at an individualitem/location combination
Historical demand patterns Seasonality and Trends Shape Modeling
Causal Factors
Manage new product introductions New item / store introductions
Lifecycle / supersession / Product phase-in and phase-outs Discounts and promotion optimization
Effect of discounts and promotions
Promotion optimization
8/10/2019 Demantra Overview.ppt
20/45
Operational Planning
Tolerance along time and organization dimensionsfor fulfilling demands Global forecasting and consumption
Automatically sourcing forecasts to appropriateorganizations that fulfill demands
Sales and Operations Planning Review current demand fulfillment Consider constrained supply
Re-prioritize demands
Supply Positioning
Consider forecast accuracy measures to determineinventory levels
Postponement optimization
8/10/2019 Demantra Overview.ppt
21/45
Sample Business
Processes Supported
within Demantra
8/10/2019 Demantra Overview.ppt
22/45
Workflow enabled Collaboration
Why collaboration capabilities are important?
It is extremely critical to bring sales, operations, finance and marketing toagreement on a single forecast number.
A platform that enables collaboration between these stakeholders will
result in a better aligned corporation marching towards a common goal.
Ability to easily tailor process flows that is custom to each business
Web based workflow development tool allows creating new workflows
and modifying canned workflows easy.
For example, you can have a workflow that enables collaboration
between account manager, regional manager and country manager
before finalizing the forecast.
Process to define and handle exceptions
Create workflows to handle exception events such as over/underforecasting and remediation plans
Workflows to integrate external systems
Facilitate integrating external systems data through workflows
For example, allocate around intersections that have sales orders
8/10/2019 Demantra Overview.ppt
23/45
Workflow enabled Collaboration
between Stakeholders
8/10/2019 Demantra Overview.ppt
24/45
Disaggregating Higher Level Entries
to Lower Level SKU/Location
Why is this important?
If the forecast quantities end up entered for the wrong products/locations, itcould result in overconsumption and hence result in excess inventory
Can be mitigated with robust disaggregation mechanisms
Demantra supports multiple disaggregation schemes
Proportionalwhere the allocation logic is based on another series
Proport Mechanism to control disaggregation during analytical engine runs
Proportional
When a series is defined, modelers have the ability to define theallocation to be based on another series.
The basis series could be computed based on a business specific logic orcould be collected data series such as order history and backlog.
Custom Methods Define custom methods that can be invoked for any special allocation logic.
For example, allocate around intersections that have sales orders
8/10/2019 Demantra Overview.ppt
25/45
Disaggregating Higher Level Entries
to Lower Level SKU/Location
8/10/2019 Demantra Overview.ppt
26/45
Expressions to Facilitate Numerical
Calculations / Quick Review
Server Expressions
These are expressions that uses database grouping functions such as
average, sum, etc.
For example, you could have an expression that computes the average
selling price at the category level and determine profitability.
Client Expressions These are expressions that enable using mathematical formulas and if-then-
else statements using different series data.
For example, you could have an expressions that makes the forecast equal
to or above the sales order quantity for any given combination.
Color expressions
These are expressions that color code the cell based on conditionality. For example, you could color all cells red when the forecast variance is
above a certain percentage.
8/10/2019 Demantra Overview.ppt
27/45
Expressions / Color Coding
8/10/2019 Demantra Overview.ppt
28/45
Demantras Statistical Forecasting
Capabilities
Bayesian-Markov algorithm uses amixed model that is better than
best-fit approaches.
Unlimited dimensions and
hierarchies
Forecast tree uses hierarchy to
determine the best levels toforecast
For example, start at the lowest
levels in the hierarchy and then
move up one step at a time.
Attribute based forecasting
capabilities
Nodal tuning capabilities
Advanced reporting capabilities
such as graphs, charts, various
summarization capabilities.
CausalAnalysis
OutlierDetection
PromotionEvents
Seasonality
Cyclical Patterns
Trend
HistoricaldataBayesian
Estimator
Forecast
Multiple
causal
factors
Combined
model
Bayesian
Optimizer
8/10/2019 Demantra Overview.ppt
29/45
Shape Modeling
Activity based shape modeling
Demantra captures the profile of historical demand over aperiod of time
Apply shapes scaled for volume and time to future forecasts
Alignment of future forecasts shape dictated by QuantityAlignment Duration specified in another series
Supported in Demand Planning mode and Promotion
Effectiveness mode Promotion Shape Modeling
Similar to Activity based shape modeling but in additionconsiders promotion attributes
Available only in PE mode
Shape modeling applicable only when there iscontinuous stream of demand data
8/10/2019 Demantra Overview.ppt
30/45
Activity Based Shape Modeling
8/10/2019 Demantra Overview.ppt
31/45
Causal Factors Global Factors
Model global causal factors that
apply to all products andlocations
For example, holidays such as
Thanksgiving and Christmas,
seasons, etc
Local Factors Local causal factors apply to a
specific product and location
For example, a snow plough is
more likely to sell more during
snowy season in the North-East
than in Arizona.
Improved forecast accuracy as a
result of better incorporation of
the causals.
8/10/2019 Demantra Overview.ppt
32/45
Member Management New Products Introduction
All combinations are stored at
lowest levels Most members have combinations
with sales data and hence enabled
for forecasting
For introducing new, use tools such
as Member Management to enable
them for forecasting
Create a new member at anyaggregation level in the product
hierarchybut typically lowest level
members
Link new products to Locations Link a new product to a location or an
existing product to a new location
Create combinations ofproduct/locations
Dummy history creation
Insert dummy historical records
Enables viewing combinations in
worksheets
8/10/2019 Demantra Overview.ppt
33/45
Chaining
Forecasting new product / stores
Chaining is the process of copying series data from one set ofcombinations to new set of combinations.
If you have new product/location combinations, use chaining tocreate history so Demantra can generate forecast.
Item Similarity
For example, you created new store X which sells same items as
existing store Y Chaining creates all the relevant item combinations for new store X
based on Y
Location Similarity
For example, you created a new item B which is similar to item A andsold in all locations
Chaining creates all relevant location combinations for B based on A
Proport Mechanisms
Multiple proportionality options exist for disaggregating to newcombinationssuch as Target, Source, Equal and Similar
8/10/2019 Demantra Overview.ppt
34/45
Global ForecastingPublish from
Demantra, Consume and Distribute
within ASCP Publish forecast from Demantra to
ASCP without the context of an
Organization Define sourcing rules to distribute the
forecast to appropriate fulfillment centers
based on regions/category/Item and
Instance.
ASCP utilizes the sourcing rules to
distribute the remaining forecast after
consumption.
Consumption at multiple levels in
location hierarchy Zone / Region
Ship to Location
Consumption by multiple levels in
Item hierarchy Item
Demand Class
8/10/2019 Demantra Overview.ppt
35/45
Consumption tolerance along time
dimensions Backward Days
First look for the forecast on the day of thesales order.
Then days backwards from sales order date
the forecast should be consumed.
Forward Days
After scanning backwards, scan forward to
look for forecast to consume.
Consume within time bucket For non-daily buckets, force the
consumption of the forecast only within that
bucket and not allow spanning backwards
and forwards.
Criticality of consumption
If the forecasts are not consumed properly,
supply chain will be overdriven causing
excess inventory
All these different options can be taken
advantage to shape forecast demands to
align with reality.
8/10/2019 Demantra Overview.ppt
36/45
RespondProfitably Balance Supply
and Demand Visibility to logistics and production constraints
in one number planning process Integrated with Strategic Network Optimization
and Advanced Supply Chain Planning to
evaluate supply constraints
Quickly and interactively simulate impact of
demand changes on the supply picture with
a common presentation layer Integrated with Inventory Optimization for safety
stock targets and postponement strategies
Quickly simulate impact of demand
scenarios and varying budgets on service
levels and hedging strategies
8/10/2019 Demantra Overview.ppt
37/45
Summary
8/10/2019 Demantra Overview.ppt
38/45
Path to implement
Start with the corporate objectives
Identify and prioritize corporate objectives For example, improve forecast accuracy by 10% or reduce stock-
outs of certain product line, etc.
Drill down to specifics Determine what is needed to accomplish the objectives
For example, better collaboration among stakeholders or improved
statistical forecasting capability, etc. Map the software functionality to meet specific requirements Demantra is a suite of products within larger APS umbrella with
many components and overlapping features
Identify the specific features that meet your needs
Then choose the components that provide those features
Layout an incremental rollout plan Start with the quick wins Expand the footprint with minimal change management impact
8/10/2019 Demantra Overview.ppt
39/45
Glossary of Terms
8/10/2019 Demantra Overview.ppt
40/45
Levels control how data is aggregated andorganized
Used in worksheets, filters, import or export, andforecasting
Types of levels: Items - group data according to characteristics of
items
Locations - group data according to characteristics oflocations
Combinations - group data according to time-independent characteristics of item-locationcombinations (i.e. Sales Rep)
Time-group data by sales date
Promotions - group data according to characteristicsof Promotions including Item, Location and Time
Settlements - group data according to characteristicsof Settlements including Item, Location and Time
Levels
8/10/2019 Demantra Overview.ppt
41/45
Series
A set of data that can be displayed in a worksheet table or
graph, at any aggregation level 3 datatypes of Series: Numeric, String or Date
Types of Series: Sales Series - Consists of time-dependent data for each item-location
combination
Matrix Series - Consists of time-independent data for each item-locationcombination (i.e. Store Minimum)
Promotion Series - Consists of data for each promotion at each item-location combination, at each time bucket
Level Series - Stores data associated with a specific member in a level
8/10/2019 Demantra Overview.ppt
42/45
Worksheets
Within Demantra, users work almost entirely withinworksheets
A worksheet is a customized working environment where
users can view and edit data
When users save changes back to the database, theybecome available to other users and to downstream
operations
A worksheet consists of one or more views, usually
displayed as tabs or MDI within the worksheet
Each view retrieves a set of data that is aggregated in a
specific way and that may also be filtered
8/10/2019 Demantra Overview.ppt
43/45
WorksheetsUI Components
Menu and
Toolbar
Table
Graph
Activity
Details
Embedded
Worksheet
Member
Browser
Notes and
Attachments
Status Bar
8/10/2019 Demantra Overview.ppt
44/45
Workflow
Web-based
Not accessible to most end users
Used to define and run workflows
8/10/2019 Demantra Overview.ppt
45/45
Let us review on the system
Login to the collaborator workbench using
train##/train##
Open worksheet Consensus Forecast
Product Family