oracle demand planning overview

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Oracle Demand PlanningOracle Demand Planning

OverviewOverview


Oracle Demand Planning Modular Courses

Oracle Demand Planning Modular Courses

• Overview of Oracle Demand Planning (ODP)

• Administering Oracle Demand Planning

• Generating Forecasts

• Analyzing and Managing Forecasts

• Overview of Oracle Demand Planning (ODP)

• Administering Oracle Demand Planning

• Generating Forecasts

• Analyzing and Managing Forecasts


ObjectivesObjectives

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

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


What is Demand Planning?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

• 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


Why is Demand Planning Difficult?Why is Demand Planning Difficult?

• Short product life cycles

• Evolving market conditions

• Global markets

• Multiple sales channels

• Multiple sources of information

• Demand distortions

• Short product life cycles

• Evolving market conditions

• Global markets

• Multiple sales channels

• Multiple sources of information

• Demand distortions


Demand DistortionsDemand 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

• 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


Why is Demand Planning Important? Demand Planning Benefits

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

• Improve forecast accuracy

– Manage demand distortions

– Plan collaboratively

• Improve operational plans

– Inventory reduction

– Higher fill rates

– Higher revenue


Improving Operational PlansImproving Operational Plans

Forecasting

Planning Operations

Market1 2

34


Impact of Forecast Accuracy on Safety Stock Requirements

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


Basing Demand Forecasts on Sales HistoryBasing 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.

• 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.


Key FeaturesKey Features

• Internet collaboration

• View and work with data that isrelevant 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

• Internet collaboration

• View and work with data that isrelevant to responsibilities

• Integrate demand forecasts into Advanced Supply Chain Planning

• Unlimited forecast scenarios


• Multiple statistical methods

• Automatic selection of best-fit model

• Exception reporting and feedback


100% Internet-Based Solution100% Internet-Based Solution

• Web browser access

• Low cost to deploy

• Global visibility

• Web browser access

• Low cost to deploy

• Global visibility


Collaborative ForecastingCollaborative Forecasting

Actual SalesActual Sales Demand plansDemand plans

PeoplePeople

ForecastForecast

EventsEventsPromotionsPromotions

Internet


Information VisibilityInformation 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

• 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


Continuous ImprovementContinuous Improvement

SupplyChain

Planning

Establish ForecastAccuracy Targets

MeasureResults

Out ofTolerance

AlertNotifications

Adjust Forecast

• Integrated performance management

• Exception notifications

• Oracle Workflow process automation

• Integrated performance management

• Exception notifications

• Oracle Workflow process automation


Integrated ModulesIntegrated Modules

GlobalGlobalAvailable-to-PromiseAvailable-to-Promise

Demand Demand PlanningPlanning

Multi-Multi- Org.Org.Planning

PlanningServerServer



Supply ChainSupply ChainPlanning EnginePlanning Engine

Business Business Intelligence SystemIntelligence System

Transaction Transaction SystemsSystems


Planning Server InformationPlanning Server Information

• Historical sales

• Marketing plans

• Sales plans

• Historical sales

• Marketing plans

• Sales plansMulti-Multi- Org.Org.Planning





Information FlowInformation 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


Performance FeedbackPerformance Feedback

Monitorperformance

Reportexceptions

Take correctiveactions

Compare actualto forecast


General FeaturesGeneral Features

• Activity log

• Annotated forecast changes

• Multiple allocation rules

• Create new forecast

• New product introductions

• Event and promotion management

• Ad hoc and predefined reports

• Activity log

• Annotated forecast changes

• Multiple allocation rules

• Create new forecast

• New product introductions

• Event and promotion management

• Ad hoc and predefined reports


Statistical and Analytical FeaturesStatistical and Analytical Features

• Multiple forecasting techniques

• Selection of best-fit model


• Performance tracking

• Multiple forecasting techniques

• Selection of best-fit model


• Performance tracking


Statistical Forecasting MethodsStatistical Forecasting Methods

• Exponential smoothing

– Single

– Double

– Holt-Winters

• Regression

– Linear

– 5 types of non linear

• Exponential smoothing

– Single

– Double

– Holt-Winters

• Regression

– Linear

– 5 types of non linear


Selection of Best-Fit ModelSelection 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

• 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


Scenarios, Reconciliation, and Consolidation Features

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

• 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


ScenariosScenarios

Salesforecasts

Customerforecasts

Unconstrainedforecasts

Statisticalforecasts

Manufacturingforecasts

Marketingevents


Demand AnalysisDemand Analysis

• Unconstrained demand forecasts

• Constrained supply plans

• Resource cost versus lost sales

• Unconstrained demand forecasts

• Constrained supply plans

• Resource cost versus lost sales


Oracle8Oracle8ii

TutorTutor

DesignerDesigner

DiscovererDiscoverer

GeneralGeneralLedgerLedger

Product

GeographyGeography

Multidimensional ModelMultidimensional Model

SalesSales

TimeTime

AsiaAsia

EuropeEurope

AmericasAmericas

MayMayJuneJune JulyJuly AugustAugust


Three Typical DimensionsThree Typical Dimensions

Pro

du

ctP

rod

uct

TimeTimeGeographicGeographicRegionRegion


Multidimensional FlexibilityMultidimensional 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


FiscalCalendarhierarchy

GregorianCalendarhierarchy

ManufacturingCalendarhierarchy

Time DimensionHierarchiesTime DimensionHierarchies

ManufacturingManufacturingperiodperiod

YearYear Fiscal yearFiscal year

Fiscal quarterFiscal quarter

Fiscal monthFiscal month

ManufacturingManufacturingweekweek

QuarterQuarter

MonthMonth

AllAll

DayDay


ProductCategoryhierarchy

ProductFamily

hierarchy

Product Dimension HierarchiesProduct Dimension Hierarchies

AllAll

Product familyProduct family Product categoryProduct category

ProductProduct


CustomerClass

hierarchy

CustomerGroup

hierarchyGeographyhierarchy

Geography Dimension HierarchiesGeography Dimension Hierarchies

AreaAreaCustomerCustomer

classclass

CustomerCustomerRegionRegion

CustomerCustomergroupgroup

AllAll

Ship-to locationShip-to location

CountryCountry


Demand Planning RolesDemand Planning Roles

• Demand Planning System Administrator

– Demand Planning Integration Administrator

– Demand Planning Administrator

• 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


Demand Planning RolesDemand Planning Roles

• Demand Planner

– Analyzing and forecasting demand

– Submitting scenarios

• Demand Planning Manager

– Review and adjust forecasts

– Submit final scenarios

• Demand Planner

– Analyzing and forecasting demand

– Submitting scenarios

• Demand Planning Manager

– Review and adjust forecasts

– Submit final scenarios


Demand Planning Setup StepsDemand 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.

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.


Demand Planning Process StepsDemand 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.


7. Load data into Oracle Express database.

8. Generate baseline forecasts.

9. Assign data to users, generate reports, and notify users.



Demand Planners:

10. Analyze and adjust forecasts.

11. Submit saved forecast scenarios to the shared server.

Demand Planners:

10. Analyze and adjust forecasts.

11. Submit saved forecast scenarios to the shared server.




12. Consolidate forecasts.

Demand Planning Manager:

13. Perform managerial review of forecasts.


14. Submit final forecasts to the planning server.


12. Consolidate forecasts.

Demand Planning Manager:

13. Perform managerial review of forecasts.


14. Submit final forecasts to the planning server.




15. Clean up the database and prepare for the next round of planning.


15. Clean up the database and prepare for the next round of planning.

$10$10

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X49X49

1267612676

14141212Q85Q85

$91 $91

Database


SummarySummary

In this lesson, you should have learned how to:

• Explain features and benefits of Oracle Demand Planning (ODP)

• Describe demand planning roles and processes

In this lesson, you should have learned how to:

• Explain features and benefits of Oracle Demand Planning (ODP)

• Describe demand planning roles and processes


4141

Review QuestionReview 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.







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4343


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 manager

2. Demand planner

3. Demand planning administrator

4. Demand planning integration administrator

5. System administrator



2. Demand planner





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Review Question SolutionReview Question Solution



2. Demand planner






2. Demand planner





4545


The demand plan manager is responsible for:

1. Setting up instances

2. Defining scenarios

3. Generating baseline forecasts

4. Assigning data slice to demand planners

5. Reviewing and approving final forecasts








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Review Question SolutionReview Question Solution













oracle demand planning overview

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