Weitere ähnliche Inhalte Ähnlich wie Intelligent Supply Chains af Charles Møller, CIP på AAU (20) Mehr von InfinIT - Innovationsnetværket for it (20) Kürzlich hochgeladen (20) Intelligent Supply Chains af Charles Møller, CIP på AAU2. Supply Chain Management?
Source: Lambert, 2008
"If you are in supply chain management today then complexity is a
cancer that you have to fight, and process management is the weapon.”
Tom Blackstock, Vice President, Supply Chain Operations, Coca-Cola North
America
© Charles Møller 2
3. Why do we need intelligent Supply Chains?
© Charles Møller 3
4. Two Supply Chain Paradigms…
• Traditional Supply Chain • Intelligent Supply Chain
Cost Value
Static Dynamic
Reactive Proactive
Flexibility Agility
Planning Execution
What is the optimal supply How do we use the existing
chain configuration? configuration in the most
effective way?
© Charles Møller 4
5. The Chief Supply Chain Officer Agenda (impact of challenge)
Source: IBM, 2009
Cost Containment • Rapid, constant change is rocking this traditional area of
strength and outstripping supply chain executives’ ability to
(55%) adapt.
Supply Chain Visibility • Flooded with more information than ever, supply chain
executives still struggle to “see” and act on the right
(70%) information.
Risk Management • CFOs are not the only senior executives urgently concerned
about risk; risk management ranks remarkably high on the
(60%) supply chain agenda as well.
Customer intimacy/ • Despite demand-driven mantras, companies are better
increased demand (56%) connected to their suppliers than their customers.
Globalization • Contrary to initial rationale, globalization has proven to be
(43%) more about revenue growth than cost savings.
© Charles Møller 5
6. Smarter Supply Chain of the Future?
Source: Lambert, 2008
“Volatile times demand pervasive visibility & flexibility”
The IBM Supply Chain Study, 2008
© Charles Møller 6
7. The Smarter Supply Chain of the Future Source: IBM, 2009
Instrumented Interconnected Intelligent
• Information that was • The entire supply chain • These supply chain
previously created by will be connected – not decisions will also be
people will increasingly just customers, much smarter
be machine-generated – suppliers and IT • Advanced analytics and
flowing out of sensors, systems in general, but modeling will help
RFID tags, meters, also parts, products decision makers
actuators, GPS and and other smart objects evaluate alternatives
more used to monitor the against an incredibly
• Inventory will count supply chain complex and dynamic
itself • Extensive connectivity set of risks and
• Containers will detect will enable worldwide constraints
their contents networks of supply • And smarter systems
• Pallets will report in if chains to plan and will even make some
they end up in the make decisions decisions automatically
wrong place together – increasing
responsiveness and
limiting the need for
human intervention
© Charles Møller 7
8. Examples of Smarter Cost Containment Source: IBM, 2009
Instrumented
• Sensor-based solutions to reduce inventory costs with increased visibility
• Production and distribution process detectors to monitor and control energy usage and waste
• Physical transportation, distribution and facility asset management, controlled and monitored with smart
devices for efficiency and utilization
Interconnected
• Agile, on demand network of suppliers, contract manufacturers, service providers and other (financial
and regulatory) constituents
• Outsourcing non-differentiating functions to share risks across the global network
• Variable cost structures that fluctuate with market demand
• Shared decision making with partners at source (local, regional, global strategies)
• Integrated, networked asset utilization and management
Intelligent
• Network and distribution strategy analysis and modeling with event simulations
• Scenario-based operational analysis
• Simulation models and analyzers to evaluate flexibility factors – service levels, costs, time, quality – with
inventory synchronization
• Sustainability models to analyze and monitor usage impact (carbon, energy, water, waste)
• Integrated demand and supply management with advanced decision support
© Charles Møller 8
9. Examples of Smarter Visibility Source: IBM, 2009
Instrumented
• Shelf-level replenishment
• Event-driven monitors and alert detection based upon thresholds and tolerances
• Smart devices and sensors (RFID) to capture real-time visibility: forecasts/orders, schedules/commitments,
pipeline inventory, shipment lifecycle status
• Sense-and-respond demand and supply signal notification
Interconnected
• ERP to ERP to ERP integration
• Multi-partner collaborative platform for suppliers, customers and service providers, with data synthesis and
decision support
• Integrated forecasting, orders and point-of-sale
• Dynamic supply-demand balancing with just-in-time and demand-driven replenishment
• Integrated performance management
Intelligent
• Pipeline inventory forecasting and analytics
• Service-level analysis with inventory optimization
• Optimized buy recommendations
• Price-protection analysis
• Advanced decision-support analytics and optimization to automate and self-actuate supply chain transactions
• Predictive buy-sell decision support
© Charles Møller 9
10. Examples of Smarter Risk Management Source: IBM, 2009
Instrumented
• Monitors and sensors for product traceability from ingredients to final customer consumption
• Sensor solutions for monitoring product condition through the supply chain to help ensure product
quality
• Weather intelligence and sensors for predictive analysis for supply planning, shipment routing and
allocations
Interconnected
• Resilient supply chain network design at strategic level
• Network integration with variable contingency plans and policies
• Integration of financial and operational analysis
• Compliance strategies and policies with suppliers, service providers, contract manufacturers
• Networked sustainability policies for entire product lifecycle from design through consumption to afterlife
Intelligent
• Probability-based risk assessment and predictive analysis: likelihood, severity, ease of detection for key
risk factors with mitigation policies and procedures
• Risk-based financial impact analysis: decision tree, sensitivity analysis
• Risk-adjusted inventory optimization
• Disaster response simulation models
• Bayesian supply chain risk analysis and mitigation models
© Charles Møller 10
11. Examples of Smarter Customer Interaction Source: IBM, 2009
Instrumented
• Sensor solutions to signal retail shelf requirements
• On-site services such as automated sensor-based checkout
• Product authentication and consumer loyalty program access with customer cell phones
• Embedded software and analytics for automated product defect and service alerts
Interconnected
• Global versus regional versus local strategies and tactics
• Networked S&OP with optimized forecast, buy/sell decision support
• Sustainable, “green” considerations and co-branding: Product design and packaging, Co-
branding with customer initiatives, Compliance programs
• Customer collaboration throughout all supply chain processes
Intelligent
• Customer segmentation of product/service portfolio: profitability; geography/market;
product/service mix
• Simulation models of customer behavior, buying patterns and market penetration applied to
planning and operations volumes
• Optimized inventory pipeline planning and execution by customer segment
• Cost-to-serve models and analysis
© Charles Møller 11
12. Examples of Smarter Global Integration Source: IBM, 2009
Instrumented
• Sense-and-respond event management for end-to-end supply chain activities
• Sensors and actuators: manufacturing, logistics, and process control
• Real-time interconnection with sensors to detect product and shipment locations worldwide
• Sensor solutions connecting the expanding global trading partner infrastructure for increased supply chain
visibility
Interconnected
• Global “centers of excellence” to optimize capability and delivery
• Right-sourced global logistics network
• SOA-based integration of heterogeneous systems
• Collaboration tools embedded into performance management system
• End-to-end supply chain collaboration tools and methods
Intelligent
• Integrated dashboards for KPIs and event alerts, driven by business rules
• Demand, supply and distribution network planning and execution
• Simulation models and scenario-based strategies for planning
• Optimization of inventory throughout all phases of pipeline activity
• Integration of risk management and mitigation approaches
• Integrated production planning and execution
© Charles Møller 12
13. Designing Intelligent Supply Chains…
Source: Adapted from Siurdyban & Møller, 2009
• Development • Operational
Perspective perspective
• Structure • Process
Build Run
Problems
Guidelines
Evaluate
Transform Grow
• Innovation • Learning
perspective perspective
• Evolution • Refinement
© Charles Møller 13
14. Værdikæder i netværk – plug’n play supply chain (1)
• Problemstilling/rationale
Fremstilling foregår i dag i åbne globale værdikæder
Det gælder også for danske fremstillingsvirksomheder, hvor specielt de
større virksomheder organiserer deres fremstillingsaktiviteter i globale
værdikæder
Det giver ikke alene virksomhederne optimal adgang til nye markeder, men
også til teknologi, forskning samt højtuddannet og kvalificeret arbejdskraft
Dansk industri består imidlertid overvejende af små og mellemstore
virksomheder, hvor en meget stor andel fungerer som fleksible
underleverandørvirksomheder, der pga. størrelse og ressourcer primært
fokuserer på nærmarkeder
Problemet for mange af disse virksomheder er, at selv om de besidder en høj
kompetence inden for hvert deres felt, så kan de ikke alene matche de store
internationale kunders krav
De har ikke adgang til et netværk af samarbejdspartnere, der
komplementerer deres specialer og de har ikke kapitalstyrke eller opgaver
nok til at kunne opretholde specialistkompetencer
Der ligger derfor store muligheder for Danske underleverandører, hvis
mulighederne for samarbejde i netværk forbedres
© Charles Møller 14
15. Værdikæder i netværk – plug’n play supply chain (2)
• Mulige forsknings og udviklingsopgaver
Udvikle metoder og teorier for, hvordan man optimerer/opdeler og skaber øget værdi i
komplekse værdikæder
Integration mellem OEM’s og mindre leverandørers ”produktionssystemer”
Udvikling af et fleksibelt IT system, der kan samle værdikæder i et netværk med
ukendte partnere
Udvikling af en virtuel markedsplads til hurtig udbygning af netværk
Udvikling af metoder, der sikrer, at vi som minimum får den sammen produktivitet i
netværk som i forhold til single location produktion
Udvikling af metoder og teknologier der understøtter distribueret R&D
Innovativ udvikling i netværk, eg. i sammen med kunden, leverandører og videncentre
Integration af teknologileverandører i udvikling
Udforskning af netværkssamarbejde og konceptet ”Intelligente” forsyningskæder
Centrale faktorer og egenskaber der karakteriserer netværk, som bringer dem op på et
langsigtet vedvarende kompetitivt niveau
Identifikation af hvilke teknologier, der kan blive danske spydspidser inden for design af
nye produktionssystemer
Udvikling af konceptuelle modeller for netværk og tilsvarende produktionssystemer
© Charles Møller 15
16. Key Ideas for researching the Intelligent Supply Chain
Network-Centric
Approach
Real-time
Enterprise
Business Process
Management
Enabling
Technologies
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