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Disclaimer: Opinions expressed in this presentation are that of the author. It does notrepresent the consensus opinion of MIT as an institution or other faculty that may bedirectly or indirectly associated with MIT School of Engineering or MIT Sloan School. u UNCERTAINTY URL for powerpoint presentation http:/supplychain.mit.edu/innovationEducation Course 1.270 / ESD.273 Nobel Prize in Economics 2002 (announced today, 09 Oct 2002)for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty for having established laboratory experiments as a tool in empirical economic analysis, especially in the study of alternative market mechanisms Daniel Kahneman Vernon L. Smith 1/2 of the prize 1/2 of the prize USA and Israel USA Princeton University Princeton, NJ, USA George Mason University Fairfax, VA, USA b. 1934 b. 1927 BODY SCANNER BY TC2 Invasion of the Body Scanners Digitally speaking Part of the Process PERSONALDIGITALPROFILE Customer: How will I look in this dress? Retailer: What should we order for Fall ?Manufacturer: Whats the next demand? Data miningData MartRetailers AccessoriesJewelry, ShoesShiseido, CoachHarrods, M&SGucci, BallysGuerlain, PoloUSD, DEMEURO, INRYEN, YUANTRAVELHEALTHEDUCATIONARTS & MUSICCelebrityGalleryWorld History ofFashionThe Way We Wore Data Warehouse BODY SCAN eFASHIONEBCB2BAnne KleinLevis, BebeTalbots, AX China, India, SiamFABRICSUPPLIERSDataWarehouse FABRICBROKERINDEPENDENTDESIGNBROKER Global DesignWAREHOUSEMEDIA / POPTailors-Contract Shops AmateursDesign ForumManufacturingTailor BrokerOrder Individual Tailors On-callPreference Survey SHIPPING MALLam FinancialRETURNCRM DONATESalvation ArmyCAREGoodwill eBAYBoutiquesJ C PenneyOutlet Stores AmateurModelsSHIPPING ERP RETAILERSMACYS, NORDSTROM, BLOOMINGDALES PERSONALPROFILESOFTWARE PERSONALPROFILEANALYSISPortal CRM $ billion 1.2 2.3 3.7 5.4 7.9 11.5 16.81997 1998 1999 2000 2001 2002 2003 024681012 141618Customer Relationship Management Source: AMR Research 1999 October Lack of rule-based resolution: expectation vs resultu Financial Impactu Cost of Correctionu Side Effects Financial Impactu Opportunity lost: unable to ramp upu Economic loss: unable to ramp down Cost of Correctionu Resourcesu Inventory Side Effects (undesirable)u Tackle only symptomsu Negative fall out Insulation of Planning from Execution Individual optimisation not SC optimisation Smart-Hub and Dumb-Spoke Configuration Isolation of Environment of Operation What to do ? Understand customer need Monitor supply availability Manage supply chain partner performance Decentralize problem solving Monitor corrective actions and feedback Include macro-economic indicators Financial Impactu Opportunity lost: unable to ramp upu Economic loss: unable to ramp down Push-Pull Supply ChainsThe Supply Chain Time LineLow Uncertainty High Uncertainty CustomersSuppliers PUSH STRATEGY PULL STRATEGY From Make-to-Stock Model.ConfigurationAssemblySuppliers to Assemble-to-Order ModelConfigurationAssemblySuppliers Imagination is out of focus ! I nventory Management Order Processing E-BusinessVendor ManagementTaxElectronic CommerceFinancialsMarketingExecutive I nformationI nventory ProgramsAccounts PayableStock TransfersWarehouseI nbound QA1ReceivingRepair OrdersPurchasing Accounts ReceivableOutbound QAShippingOrder ServicesQuotingCreditCustomer Management www.w3c.org Observation 199883 million accessthe Internet inlanguages otherthan English Projection 200570% of 1 billionusers may notspeak EnglishFACT46% US businessrefuse intl orderbecause they lack means toprocess them. Japanese Spanish GermanFrench Chinese DutchKorean Swedish Italian Conceptual advances occur about twice a century and lead to wealth of nations DistributedIntelligence Nanotech PLANEXECUTESENSERESPONDDEMAND EXCEPTION Customer Customers DCMANUFACTURERRaw material SUPPLIERS StoreStoreStoreStoreStoreStoreStoreStoreDCDCDCPaperMedicalCotton StorePlant DCPlant DC REAL TIME ePCePC data from RFID TagReplenishmentneeds ConfirmationLoads Store Orders StatusImmediateReplenishmentneedsFutureshipping needsReplenishmentneeds determinedfrom RFID Tag info“Intelligent Signal” PORTALS / ExchangeTransport Customer Info CenterManufacturerHQ real timeRFID data Personal CareConsumer TissueHealth Care InformationAgentInventory Early Warning AgentTLB AgentCross-Docking Agent ConsumptionInventoryDataDC to Mfr DCDCDCPaperMedicalCotton Plant DCPlant DC CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore Industry best now versus what can be achieved:Day 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 =Product =Info Day 7Received, unloaded & stocked on store shelvesDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 =Non-value-added time=Product =Info PortalTransport CustomerCenterManufacturer DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStoreConsumerBuys SCOTT 2pm Day 0 =Product =Info DCDCDCPaperMedicalCotton Plant DCPlant DC PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =InfoRFI D Smart Tag atPOS read 2pm Day 0Day 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info0101100110111010001112pm Day 0RFID Smart tag datatransmitted instantly 010110011011101000111 DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info010110011011101000111010110011011101000111 2:10pm Day 0Replenishment needs receivedby scheduling (TLB) systems DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info010110011011101000111 2:35 pm, Day 0System detects OOS danger at customer & co-ordinates rapid-response shipment (reallocation of en route load evaluated)010110011011101000111010110011011101000111 010110011011101000111 DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =InfoSmart Plannerinterrogates demand filter DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =InfoSmart Planner integrates info:current inventory, shipment, planning DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =InfoSmart Planner executes changes, broadcasts plan, exceptions, options DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info10pm Day 0Customer DC receives SCOTT DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info11pm Day 0Customer DC ships SCOTT DCDCDCPaperMedicalCotton Plant DCPlant DCDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 PortalTransport CustomerCenterManufacturer CustomerStoreStoreStoreStoreStoreStoreStoreStoreStore=Product =Info3am Day 1Received, unloaded & stocked on store shelves DCDCDCPaperMedicalCotton Plant DCPlant DC CustomerStoreStoreStoreStoreStoreStoreStoreStoreStoreDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 =Product =Info3am Day 1Received, unloaded & stocked on store shelvesDay 1 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8Day 2Day 0 =Non-value-added time=Product =InfoPortalTransport CustomerCenterManufacturer 2008: P&G shortens replenishment cycle from 120 days to 1 day 1 2008: P&G shortens replenishment cycle from 120 days to 1 day 2 2008: P&G shortens replenishment cycle from 120 days to 1 day 3 2008: P&G shortens replenishment cycle from 120 days to 1 day 4 2008: P&G shortens replenishment cycle from 120 days to 1 day 5 2008: P&G shortens replenishment cycle from 120 days to 1 day 6 2008: P&G shortens replenishment cycle from 120 days to 1 day 7 2008: P&G shortens replenishment cycle from 120 days to 1 day 8 MIT Forum for Supply Chain Innovation A Intelligent Agents (software program that): Perceives its environment Acts autonomously Interacts to share objectives, constraints, etc Anticipates and reacts flexibly to its environment Learns from its experience and environmentIntelligent Agents InformMonitorCoordinateControlManageExecute The White House said the increased technology spending mentioned by President Clintonduring last weeks State of the Unionaddress could be used, for example, to create intelligent agents that roam the Internet collecting information.AP News Service, 24 January 1999 Advances in data routing emerging from study of ANTS Antbased algorithms developed from the concept of Swarm IntelligenceXA XA XA AA X X
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