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Copyright Oracle Corporation, 2000. All rights reserved. ® Oracle Demand Planning Overview

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Page 1: demand planning

Copyright Oracle Corporation, 2000. All rights reserved.®

Oracle Demand Planning

Overview

Page 2: demand planning

Copyright Oracle Corporation, 2000. All rights reserved.®

Oracle Demand Planning Modular Courses

• Overview of Oracle Demand Planning (ODP)• Administering Oracle Demand Planning• Generating Forecasts• Analyzing and Managing Forecasts

Page 3: demand planning

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Objectives

After completing this module, you should be able to:• Explain features and benefits of Oracle Demand

Planning• Describe demand planning roles • Explain demand planning process steps

Page 4: demand planning

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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– Exception-based forecast tracking

and notifications

Page 5: demand planning

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Why is Demand Planning Difficult?

• Short product life cycles• Evolving market conditions• Global markets• Multiple sales channels• Multiple sources of information• Demand distortions

Page 6: demand planning

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Demand Distortions

• State of the economy• Promotions• Competitors’ responses to promotions• Product introduction and cannibalization• Lot-size discounts• Fiscal budget cycle• Allocations• Panic and perceptions• Hedging, commodity futures

Page 7: demand planning

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Why is Demand Planning Important? Demand Planning Benefits

• Improve forecast accuracy– Manage demand distortions– Plan collaboratively

• Improve operational plans– Inventory reduction– Higher fill rates– Higher revenue

Page 8: demand planning

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Improving Operational Plans

Forecasting

Planning Operations

Market1 2

34

Page 9: demand planning

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Impact of Forecast Accuracy on Safety Stock Requirements

Safety stock (SS) buffer inventory is proportional Safety stock (SS) buffer inventory is proportional to the average magnitude of forecast errors.to the average magnitude of forecast errors.

SSSSSSSS

Large deviationsLarge deviations Small deviationsSmall deviations

Page 10: demand planning

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Basing Demand Forecasts on Sales History

• Statistical extrapolation of history provides an objective baseline

• Issues:– Sales history usually underestimates the

actual level of demand.– The effect of unique future events are not

reflected in sales history data.– Products with short life cycles do not provide

enough historical sales data to identify trends and patterns.

• Solution: Supplement historical sales data with information about future events, promotions and customer plans.

Page 11: demand planning

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Key Features

• Internet collaboration• View and work with data that is

relevant to responsibilities• Integrate demand forecasts into

Advanced Supply Chain Planning• Unlimited forecast scenarios• Multidimensional analysis• Multiple statistical methods• Automatic selection of best-fit model• Exception reporting and feedback

Page 12: demand planning

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100% Internet-Based Solution

• Web browser access• Low cost to deploy• Global visibility

Page 13: demand planning

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Collaborative Forecasting

Actual SalesActual Sales Demand plansDemand plans

PeoplePeople

ForecastForecast

EventsEventsPromotionsPromotionsInternet

Page 14: demand planning

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Information Visibility

• Deploy information using the World-Wide Web• Information visibility across the supply chain• Internal and external collaboration with secured

access to detailed plans• Workflow gets the right information to the right

place quickly

Page 15: demand planning

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Continuous Improvement

SupplyChain

Planning

Establish ForecastAccuracy Targets

MeasureResults

Out ofTolerance

AlertNotifications

Adjust Forecast

• Integrated performance management• Exception notifications• Oracle Workflow process automation

Page 16: demand planning

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Integrated Modules

GlobalGlobalAvailable-to-PromiseAvailable-to-Promise

Demand Demand PlanningPlanning

Multi-Multi- Org.Org.PlanningPlanningServerServer

Supply ChainSupply ChainPlanning EnginePlanning Engine

Business Business Intelligence SystemIntelligence System

Transaction Transaction SystemsSystems

Page 17: demand planning

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Planning Server Information

• Historical sales• Marketing plans• Sales plans

Multi-Multi- Org.Org.PlanningPlanningServerServer

Page 18: demand planning

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Information Flow

ERPERP

DemandDemandPlanningPlanning

ASCPASCPBooking dataBooking dataShipment dataShipment dataManufacturing forecastManufacturing forecast

Sales forecastSales forecastSales opportunitiesSales opportunitiesMarketing eventsMarketing events

CRM CRM

ScenariosScenarios

Supply planSupply plan

Planned ordersPlanned orders

Page 19: demand planning

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Performance Feedback

Monitorperformance

Reportexceptions

Take correctiveactions

Compare actualto forecast

Page 20: demand planning

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General Features

• Activity log• Annotated forecast changes• Multiple allocation rules• Create new forecast • New product introductions• Event and promotion management• Ad hoc and predefined reports

Page 21: demand planning

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Statistical and Analytical Features

• Multiple forecasting techniques• Selection of best-fit model • Multidimensional analysis• Performance tracking

Page 22: demand planning

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Statistical Forecasting Methods

• Exponential smoothing– Single– Double– Holt-Winters

• Regression– Linear– 5 types of non linear

Page 23: demand planning

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Selection of Best-Fit Model

• Geneva forecast engine• Rapidly determines which forecasting models are

likely to produce the best statistical forecasts• Best-fit selection from nine models• Outlier detection and filtering• Seasonality and erratic demand filtering

Page 24: demand planning

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Scenarios, Reconciliation, and Consolidation Features

• Multiple forecasting scenarios• Top-down, middle-out, and bottom-up

allocation strategies• Forecast adjustments• Multiple units of measure• Convert units to currency and

vice versa• Consolidation of individual forecasts

Page 25: demand planning

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Scenarios

Salesforecasts

Customerforecasts

Unconstrainedforecasts

Statisticalforecasts

Manufacturingforecasts

Marketingevents

Page 26: demand planning

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Demand Analysis

• Unconstrained demand forecasts• Constrained supply plans• Resource cost versus lost sales

Page 27: demand planning

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Oracle8Oracle8ii

TutorTutor

DesignerDesigner

DiscovererDiscoverer

GeneralGeneralLedgerLedger

Product

GeographyGeography

Multidimensional ModelSales

TimeTime

AsiaAsiaEuropeEurope

AmericasAmericas

MayMay JuneJune JulyJuly AugustAugust

Page 28: demand planning

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Three Typical Dimensions

ProductProduct

TimeTimeGeographicGeographicRegionRegion

Page 29: demand planning

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Multidimensional Flexibility

Analyze how sales for a product and location change over time

Compare demand for different products bytime and location

Compare regional demand by time and product

Perform Ad Hocqueries

Page 30: demand planning

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FiscalCalendarhierarchy

GregorianCalendarhierarchy

ManufacturingCalendarhierarchy

Time DimensionHierarchies

ManufacturingManufacturingperiodperiod

YearYear Fiscal yearFiscal year

Fiscal quarterFiscal quarter

Fiscal monthFiscal monthManufacturingManufacturing

weekweek

QuarterQuarter

MonthMonth

AllAll

DayDay

Page 31: demand planning

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ProductCategoryhierarchy

ProductFamily

hierarchy

Product Dimension Hierarchies

AllAll

Product familyProduct family Product categoryProduct category

ProductProduct

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CustomerClass

hierarchy

CustomerGroup

hierarchyGeographyhierarchy

Geography Dimension Hierarchies

AreaAreaCustomerCustomer

classclass

CustomerCustomerRegionRegion

CustomerCustomergroupgroup

AllAll

Ship-to locationShip-to location

CountryCountry

Page 33: demand planning

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Demand Planning Roles

• Demand Planning System Administrator– Demand Planning Integration Administrator – Demand Planning Administrator

Demand Planning Demand Planning Integration Administrator:Integration Administrator:

Demand planningDemand planningserver, RDBMSserver, RDBMS

Demand Planning Demand Planning Administrator:Administrator:

ExpressExpress

Page 34: demand planning

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Demand Planning Roles

• Demand Planner– Analyzing and forecasting demand – Submitting scenarios

• Demand Planning Manager– Review and adjust forecasts– Submit final scenarios

Page 35: demand planning

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Demand Planning Setup Steps

System Administrator:1. Set up instances.2. Create database links.Demand Planning Integration Administrator:3. Create dimension definitions.4. Create demand plan definitions.5. Define scenarios.6. Run collection programs to load interface tables.

Page 36: demand planning

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Demand Planning Process Steps

Demand Planning Administrator:7. Load data into Oracle Express database.8. Generate baseline forecasts.9. Assign data to users, generate reports, and notify

users.

Page 37: demand planning

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Demand Planning Process Steps

Demand Planners:10. Analyze and adjust forecasts.11. Submit saved forecast scenarios to the shared

server.

Page 38: demand planning

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Demand Planning Process Steps

Demand Planning Administrator:12. Consolidate forecasts.Demand Planning Manager:13. Perform managerial review of forecasts.Demand Planning Administrator:14. Submit final forecasts to the planning server.

Page 39: demand planning

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Demand Planning Process Steps

Demand Planning Administrator:15. Clean up the database and prepare for the next

round of planning.

$10$10

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$91 $91

Database

Page 40: demand planning

Copyright Oracle Corporation, 2000. All rights reserved.®

Summary

In this lesson, you should have learned how to:• Explain features and benefits of Oracle Demand

Planning (ODP)• Describe demand planning roles and processes

Page 41: demand planning

Copyright Oracle Corporation, 2000. All rights reserved.®

4141

Review Question

Regarding statistical demand forecasts based onsales history data —1. A strength is their ability to account for the effects

of future events, promotions and customer plans.2. They are useful for providing an objective

baseline.3. They become more useful when products have

shorter life cycles.4. They tend to overestimate the actual level of

demand.

Page 42: demand planning

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4242

Review Question

Regarding statistical demand forecasts based onsales history data —1. A strength is their ability to account for the effects

of future events, promotions and customer plans.2. They are useful for providing an objective

baseline.3. They become more useful when products have

shorter life cycles.4. They tend to overestimate the actual level of

demand.

Page 43: demand planning

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4343

Review Question

A large customer uses the internet to communicate aforecast of their demand for your products to yourdemand planning system. This collaborative customer is acting in the role of:1. Demand plan manager2. Demand planner3. Demand planning administrator4. Demand planning integration administrator5. System administrator

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4444

Review Question Solution

A large customer uses the internet to communicate aforecast of their demand for your products to yourdemand planning system. This collaborative customer is acting in the role of:1. Demand plan manager2. Demand planner3. Demand planning administrator4. Demand planning integration administrator5. System administrator

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4545

Review Question

The demand plan manager is responsible for:1. Setting up instances2. Defining scenarios 3. Generating baseline forecasts4. Assigning data slice to demand planners 5. Reviewing and approving final forecasts

Page 46: demand planning

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4646

Review Question Solution

The demand plan manager is responsible for:1. Setting up instances2. Defining scenarios 3. Generating baseline forecasts4. Assigning data slice to demand planners 5. Reviewing and approving final forecasts