Demantra Overview.ppt

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    For Oracle employees and authorized partners only. Do not distribute to third parties.

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    For Oracle employees and authorized partners only. Do not distribute to third parties.

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    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

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    Demantra in the context

    of APS (Broader Supply

    Chain PlanningApplication)

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    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

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    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

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    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

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    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

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    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

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    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.

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    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

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    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

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    A Demand Driven Supply

    Chain (Approach to

    Mitigating theChallenges)

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    Traditional Supply Chains

    DemandDemand SupplySupply

    Product

    Traditional

    Definition of

    Supply Chain

    Management

    CustomerSupplier

    Design

    Partner

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    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

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    Demand Shaping

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    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

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    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

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    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

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    Sample Business

    Processes Supported

    within Demantra

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    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

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    Workflow enabled Collaboration

    between Stakeholders

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    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

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    Disaggregating Higher Level Entries

    to Lower Level SKU/Location

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    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.

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    Expressions / Color Coding

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    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

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    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

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    Activity Based Shape Modeling

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    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.

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    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

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    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

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    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

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    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.

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    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

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    Summary

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    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

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    Glossary of Terms

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    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

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    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

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    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

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    WorksheetsUI Components

    Menu and

    Toolbar

    Table

    Graph

    Activity

    Details

    Embedded

    Worksheet

    Member

    Browser

    Notes and

    Attachments

    Status Bar

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    Workflow

    Web-based

    Not accessible to most end users

    Used to define and run workflows

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    Let us review on the system

    Login to the collaborator workbench using

    train##/train##

    Open worksheet Consensus Forecast

    Product Family