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Advancements in Demand Chain Management
정명진한국오라클
© 2008 Oracle Corporation – Proprietary and Confidential
Distributors &Channel Partners
OEMs
Configure& Package
Supplier
Component Mfg WebDirect
VAR /Retail
Supply Base OEMs
Distribution& Retail Channels
Customers
Contract Mfg (EMS) / Original Design Mfg (ODM)
SCM Value Chain
© 2008 Oracle Corporation – Proprietary and Confidential
Demand Driven Adaptive PlanningThe demand driven company runs on real-time information
Demand Driven leaders have:• 15% less inventory• 17% stronger order
fulfillment• 35% shorter cash-to-cash
cycle times
Which translates to:• 60% better profit margins • 65% better EPS • 2-3X the ROA
Source: AMR Benchmark
Demand Supply
Product
Sense Demand Respond to
Demand
ShapeDemand
© 2008 Oracle Corporation – Proprietary and Confidential
• Eliminate decision making latency by focusing on excellence in demand visibility
– Sense demand more frequently and closer to the point of consumption– Replace spreadsheets with one number demand management -
Collaborate with all constituents
• Improve your forecast accuracy– Use advanced analytics and statistics
• Shape demand– Promotion excellence and decomposition– Leverage granular demand signals (customer, channel, store, shelf)– Identify and simulate cross selling opportunities
• Evolve to real-time S&OP– Profitable demand response– Identify supply side opportunities– Define and monitor customer based metrics– Get real time visibility to sales tactics (price breaks, promotions, deals)
Oracle Demand Driven Adaptive PlanningReal-time demand sensing and collaborative consensus forecasting
© 2008 Oracle Corporation – Proprietary and Confidential
Sense demand real-timeDemand Management & Advanced ForecastingDemand Signal Repositories
Real Time Sales & Operations Planning
© 2008 Oracle Corporation – Proprietary and Confidential
Manufacturer OEM Retailer/Distributor Consumer
Sale
s
TimeSa
les
Time
Sale
s
TimeSales InventoriesForecasts
POS DataInventoriesForecasts
Reach Downstream to Cut The Noise
© 2008 Oracle Corporation – Proprietary and Confidential
Data Integration With Oracle DSR
TPM
TPO
APS
S&OP
DRP
SNO
PLM
• More timely data to better sense, shape and respond to demand
• Reduced manual effort and cost
• Consistent data more easily leveraged across teams and applications
–SO
A M
essa
ges
–A
ggre
gate
d D
eman
d Si
gnal
s• Data sources centrally cleansed,
harmonized and aggregated• Pre-built dashboards and reports• Powerful BI capabilities • “Sense & Respond” event management
Cap
ture
Man
age
Ana
lyze
Res
pond
Inte
grat
e
• POS sales• Price• Store inventory• Promotional plans• Store replen. rules• Store forecasts
Retail Store Data
• DC shipments• DC inventory• DC replen. rules
Retail DC/ Distributor Data
• Retail loyalty• IRI/AC Nielsen• 3rd party
demographic• Causal (weather,etc.)• RFID/EPC• IMS, NDC, EDI (867,
852), Scripts, Pedigree
• Unstructured text
Other External Data
Oracle Demand Signal
Repository
© 2008 Oracle Corporation – Proprietary and Confidential
REGION EAST FCST
REGION WEST FCST
REGION SOUTH FCST
US
Sense Demand Real-Time
• Demand changes get detected real-time and are instantly reflected to all constituents and exceptions are triggered automatically
STORE FORECAST
PRODUCT FORECAST
CHANNEL FORECAST
JAPAN
Region South SalesForecast QTY Change
Tokyo Store 1 Forecast Change (YEN)
MANUFACTURING FCST
MARKETING FCST
SALES FCST
HQ
TV add “camera +printer” promotionairs 12/21 8pm
Consensus Forecast
11/20 12pm:“New camerasales at 150%
of estimate”
11/18 5pm:“New photo printer sales at -25% of estimate, request TV add”
ALERT: “Problem in US Region East”
11/20 2pm:“Budget
approval for global TV add”
20th Century Fox processes real time updates from 15,000+ stores daily
Involve all constituents and forecast closer to the point of consumption
© 2008 Oracle Corporation – Proprietary and Confidential
Causal Analysis
Outlier Detection
Promotion Events
Seasonality
Cyclical Patterns
Trend
5-35% improvement
History
CausalFactors
BayesianEstimator
Model A CombinedModel
Forecast
Bayesian Optimizer
CausalsCausalsAnalysisAnalysis
OutlierOutlierDetectionDetection
PromotionalPromotionalEventsEvents
SeasonalitySeasonality
TrendTrend
CyclicalCyclicalPatternsPatterns
CausalsCausalsAnalysisAnalysis
OutlierOutlierDetectionDetection
PromotionalPromotionalEventsEvents
SeasonalitySeasonality
TrendTrend
CyclicalCyclicalPatternsPatterns
Improve Forecast AccuracyDesigned for planners, not programmers (“PhD in a box”)
© 2008 Oracle Corporation – Proprietary and Confidential
Sense Demand Real-TimeMonitor customer demand and respond to ensure high service levels
Disti, Product &Disti UPC #
Disti Inventory Levels
Customer & Company Forecasts
Week of Inventory Cover
Replenishment Status
ConsensusForecast
On Hand Inventory
Resolution
Actual POS
Demand VariabilityOrange: Potential OOS
Red: Current OOS
Forecast based on POS data from DistisMeasure the weeks of Inventory cover at the distis
Compare POS data with Consensus PlanIdentify potential stock outs and resolve
© 2008 Oracle Corporation – Proprietary and Confidential
Sense Demand Real-Time
Partner Inputs:
XML,EDI or Manual
Partner Forecast Metrics
• Improve demand visibility with customer collaboration
• Tailor worksheets to specific customer needs
• Worksheet can be attached to a task• Direct alerts via application or email• Automate internal notification on customer
input• Field-level security tied to customer
access privileges
Collaborate with customers and measure impacts
© 2008 Oracle Corporation – Proprietary and Confidential
Shape Demand for ProfitabilityPredictive Trade Planning & Optimization
Real Time Sales & Operations Planning
© 2008 Oracle Corporation – Proprietary and Confidential
New Products Introduction
• New products present forecasting challenges– Limited or no demand history for a given item– May combine characteristics of several previous products – Price points, changing market conditions may be different – Product demand changes over product life cycle
Chaining
New Product C = 30% Product A + 75% Product B
Shape Modeling
•Apply shapes, scaled for volume and time
•Re-scale base on initial demand data
Attribute-Based Forecasting
Model new item based on past behavior of other items with similar attributes
Accurately forecast demand for new products based on existing data
© 2008 Oracle Corporation – Proprietary and Confidential
New Products Introduction
Derive forecast for new product and adjust forecast based on actual demand
Automatically detect outliers
View demand of comparable products based on characteristics
Accurately forecast demand for new products based on existing data
© 2008 Oracle Corporation – Proprietary and Confidential
0
500
1000
1500
2000
2500
3000
Week 1 Week 6 Week 11
Cas
es
CannibalizationPre- and post-effectsCompetitive switchingCategory growthBaselineActual
Netlift
Baseline
TPR Display
0
500
1000
1500
2000
2500
3000
Week 1 Week 6 Week 11
Week
Cas
es
Actual
TPR Display
TPR Display
Product Margin $450,000 $450,000
Promotion cost $250,000 $250,000
Net profit $200,000 $200,000Promotion ROI 80% 80%
TPR Display
$150,000 $300,000
$250,000 $250,000
-$100,000 $50,000
-40% 20%
Analytics Required to Measure Real ROI
Promoted Volume Does Not Provide Complete Picture
True Promotional ROI Is Not Obvious
*. TPR : Temporary price reduction
© 2008 Oracle Corporation – Proprietary and Confidential
Decomposition of the Promotional Lift
Data
Incremental
Baseline
Intelligence-Knowledge-Collaboration-Value
Baseline
Trade
Consumer
Advertising
vs.
Traditional ItemEvaluation Demantra’s Promotion Evaluation
Competitive Account
Switching
Baseline
Category Growth
Category Cannibalization
Pantry Load
Competitive Brand Switching
Baseline
Brand Growth
Brand Cannibalization
Pantry Load
Account Switching
Forward Buy
RetailerManufacturer
True Net Lift
© 2008 Oracle Corporation – Proprietary and Confidential
• Compare planned versus actual results • Color coding highlights better than
expected or under performing results• Lift decomposition to identifies
components of lift including cannibalization
• Drill down to speed analysis• Exception process can route analysis
based on user defined rules
Manufacturer and Retailer Analysis
© 2008 Oracle Corporation – Proprietary and Confidential
Consumer Driven TPM Process Architecture“Its All About Sell Through, Not Sell In…”
RETAILER
POSData
ReplenishmentPlan
Promotional Plan – Retailer
Driven
Corporate Demand Management Application (Oracle/Demantra RT
S&OP)
TPM Application(Oracle/Demantra)
Manufacturer Funded Trade Promotions
National Promotions Customer Specific Promotions
Profitability Review and
Approval with Senior
Management
Internal S&OP Process, Inventory Optimization to Maximize ROI on Trade Spend
TPM Case Study - Vtech
© 2008 Oracle Corporation – Proprietary and Confidential
Demand Planning and TPM Analytical LinkageTPM Case Study - Vtech
© 2008 Oracle Corporation – Proprietary and Confidential
TPM Case Study - Vtech
P&LP&L Item DESCRIPTION Benefit Reference
& savingSales Gross Domestic Sales Improved Service leads to instock improvement 3% Of revenue
Increased Opportunity sales as a reliable vendor 3% Of revenueSales Allowances & Adjustments Price Protection Reducing Retail inventory proportionately reduces PP -3% Of revenue Rebate Expenses Less requirement to "blow out" excess -2% Of revenue
Cost of Sales Obsolete Inventory - NRV Reduces reserves required for obsolete inventory -30% Of existing reserves Ocean Freight Amortization Optimize inbound freight to reduce costs -35% Of existing costs Air Freight Eliminate all but exceptions & emergencies -75% reference existing costs Freight on Sales Optimize outbound freight & eliminate expedites -25% reference existing costs
Net Profit (Loss) 3% to 5% improvement is achievable 3% plus
An extraordinary opportunity
Justifying the Investment & returns
© 2008 Oracle Corporation – Proprietary and Confidential
Evolve to Real-Time S&OPReal-Time Sales & Operations PlanningHyperion
Real Time Sales & Operations Planning
© 2008 Oracle Corporation – Proprietary and Confidential
Evolve to Real-Time S&OP
• Identify financial and revenue goals• Analyze demand and develop sales
forecast• Synchronize plan across Finance, Sales,
Marketing, and Supply Chain • Determine potential market variables
• Review supply and demand plans• Develop constrained plan• Monitor results and respond to
deviations• Create promotions and incentives to
shape demand and close gaps
Marketing
Manufacturing
Finance
Executives
ProductDevelopment
Strategic plans Profitability
Promotional andvolume plans Service levels
Demand plans Inventory levels
Capacity plans Promotion effectiveness
Phase in and phase out products Plan accuracy
Strategic
Tactical Decisions
Sales
Make demand and supply decisions simultaneously
© 2008 Oracle Corporation – Proprietary and Confidential
Zebra Synchronizes Demantra Demand Management and Oracle CRM Opportunities with Hyperion Financial Plans/Budgets as part of S&OP
Rough-CutCapacity Planning
Business Planning and Budgeting
(Hyperion)
MasterScheduling
Detailed Material/Capacity Planning
Plant & SupplierScheduling
Execution
MarketingForecast
Sales Forecast
Sales Execution
CRMOpportunities
DevelopmentPlan
MARKETING andSALES
OPERATIONS andCONTRACT MFG
FinancialPlans (Hyperion)
Production Plans (SNO)
Detailed Sales Plans
Demand Management Aggregate
Sales Plan
Sales & OperationsPlanning
(Demantra)
ASCPOracle CRM
Demantra
Real-Time S&OP Case Study
© 2008 Oracle Corporation – Proprietary and Confidential
Demand DataAdjust &
Clean historical data(Demantra)
Base Line Forecast(Demantra)
Statistical, Rule-based, adaptative
Forecast)
Plan Performance Measurement
(Hyperion)And identification of areas of
improvements
Financial Plans/Budgets
(Hyperion)review, consolidation
Marketing Input(Demantra)
Pricing, Market Analysis, Seasonality, etc.
Collaboration with customer (Demantra)
Includes customer input, tracks accuracy,
adjusts if necessary
Sales Input (Demantra)New/Lost Customers
input,Regional Market changes, key customer
forecasts
Consensus Forecast(Demantra)used as an
input to supply planning
Plan Tune-Up (Demantra)Exception-based monitoring of key
demand indicators
Supply Planning, Demand Shaping
(Demantra and SNO)
Demantra
Real-Time S&OP Case Study
© 2008 Oracle Corporation – Proprietary and Confidential
Hyperion generate business planning & budgetingBusiness Planning & Budgeting
© 2008 Oracle Corporation – Proprietary and Confidential
Hyperion Worksheets are Generated during S&OP Process for P&L Impact View of S&OP Plans sent from Demantra
Profit & Loss Analysis
© 2008 Oracle Corporation – Proprietary and Confidential
• Seeded worksheet templates for the consensus process
• Stakeholders review and adjust forecast
• Data tailored for role• Compare with
Consensus Forecast• Track accuracy of
input to the consensus process
Automate Consensus Planning Tailored worksheets for management participation
Sales Manager at customer and
product family by month
Marketing Manager at category by
quarter
© 2008 Oracle Corporation – Proprietary and Confidential
Highly Interactive Simulation and Analysis
Compare scenarios for decision making
Optimize supply network and constrain
Publish working consensus forecast
© 2008 Oracle Corporation – Proprietary and Confidential
Management Review - Demand Review
How has the plan changed?
Order backlog increasing?
How are we tracking to forecast?
© 2008 Oracle Corporation – Proprietary and Confidential
Management Review - Supply Review
Where are we resource
constrained?
Are we supply constrained?
How are product categories
performing?
Are we producing to
plan?Supplier
overloading?
© 2008 Oracle Corporation – Proprietary and Confidential
Management Review - Executive Review
How are we performing to performance
metrics?Are we on
plan financially?
Where are we behind budget?
© 2008 Oracle Corporation – Proprietary and Confidential
Consumer Durables
Industrial Manufacturing
Medical Devices
We predict the impact of today’s business decisions on tomorrow’s business performanceConsumer Goods
Retail / Wholesale
Media and Entertainment
High Technology
References
© 2008 Oracle Corporation – Proprietary and Confidential
Q U E S T I O N SA N S W E R S