supply chain integration and e-business strategies - rg

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    Supply Chain Integration

    and e-Business Strategies

    Ranjan Ghosh

    Indian Institute of ManagementCalcutta

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    Outline

    Review

    Supply Chain Dynamics

    A new Supply Chain Paradigm Matching Products with Strategies

    e-Business Opportunities

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    The Dynamics of the Supply

    Chain

    OrderS

    ize

    Time

    Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998

    CustomerDemand

    Retailer Orders

    Distributor Orders

    Production Plan

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    The Dynamics of the Supply

    Chain

    OrderS

    ize

    Time

    Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998

    CustomerDemand

    Production Plan

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    What are the Causes

    Promotional sales

    Volume and Transportation discounts

    Batching Inflated orders

    Demand Forecast

    Long cycle times Lack of Visibility to demand information

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    Consequences

    Increased safety stock

    Reduced service level

    Inefficient allocation of resources

    Increased transportation costs

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    The Bullwhip Effect:Causes thereof

    Variability in customer orders

    Delivery lags, particularly long cycle times

    Information lags

    Promotional Campaigns/Variation in Prices

    Over and Under Ordering

    Lumpiness in ordering Misperceptions of feedback

    Chain accumulations

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    The Bullwhip Effect:Managerial Insights

    Exists, in part, due to the retailers need toestimate the mean and variance of demand.

    The increase in variability is an increasing

    function of the lead time. The more complicated the demand models

    and the forecasting techniques, the greaterthe increase.

    Centralized demand information can reducethe bullwhip effect, but will not eliminate it.

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    Coping with the Bullwhip Effectin Leading Companies

    Reduce Variability and Uncertainty

    - POS

    - Sharing Information

    - Year-round low pricing

    Reduce Lead Times

    - EDI

    - Cross Docking

    Collaborative Channel Management & Alliances

    Vendor managed inventory

    On-site vendor representatives

    Th F i N

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    The Future is Not

    What

    it Used to be

    Reduce cost

    Increase Profit

    Increase service level

    Increase flexibility

    A new Business Modele-

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    Reality is Different..

    Peapod Example Founded 1989

    140,000 members, largest on-line grocer

    Revenue tripled to $73 million in 1999

    1st Quarter of 2000: $25M Sales, Loss: $8M

    Amazon.com Example Founded in 1995; 1st Internet purchase for most people

    1996: $16M Sales, $6M Loss

    1999: $1.6B Sales, $720M Loss 2000: $2.7B Sales, $1.4B Loss

    Last quarter of 2001: $50M Profit

    Total debt: $2.2B

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    Reality is Different.

    Dell Example: Dell Computer has outperformed the competition in

    terms of shareholder value growth over the eight

    years period, 1988-1996, by over 3,000% (seeAnderson and Lee, 1999)

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    Reality is Different.

    Cisco Example:

    Ciscos Internet based business model has beeninstrumental in our ability to quadruple in size from

    fiscal 1994 to fiscal 1998 ($1.3B to over $8B), hireapproximately 1000 new employees per quarter andsaving $560M annually in business expenses (PeterSolvik, CIO Cisco)

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    e-Business is a collection of business modelsand processes motivated by Internet

    technology, and focusing on improving theextended enterprise performance e-commerce is part of e-Business

    Internet technology is the driver of the businesschange

    The focus is on the extended enterprise: Intra-organizational

    Business to Consumer (B2C)

    Business to Business (B2B)

    The e-BusinessModel

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    A new Supply Chain Paradigm

    A shift from a Push System...

    Production decisions are based onforecast

    to a Push-Pull System

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    From Make-to-Stock Model.

    ConfigurationAssemblySuppliers

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    Demand Forecast

    The three principles of all forecastingtechniques:

    Forecasts are usually wrong

    The longer the forecast horizon the worst

    is the forecast

    Aggregate forecasts are more accurate The Risk Pooling Concept

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    A new Supply Chain Paradigm

    A shift from a Push System...

    Production decisions are based onforecast

    to a Push-Pull System

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    Push-Pull Supply Chains

    Push-Pull Boundary

    PUSH STRATEGY PULL STRATEGY

    Low Uncertainty High Uncertainty

    The Supply Chain Time Line

    CustomersSuppliers

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    A new Supply Chain Paradigm

    A shift from a Push System...

    Production decisions are based onforecast

    to a Push-Pull System

    Parts inventory is replenished based onforecasts

    Assembly is based on accurate customerdemand

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    .to Assemble-to-Order Model

    ConfigurationAssemblySuppliers

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    Business models in the BookIndustry

    From Push Systems...

    Barnes and Noble

    ...To Pull Systems

    Amazon.com, 1996-1999

    And, finally to Push-Pull Systems

    Amazon.com, 1999-present 7 warehouses, 3M sq. ft.,

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    Direct-to-Consumer:Cost Trade-Off

    Cost Trade-Off for BuyPC.com

    $0$2$4

    $6$8

    $10$12$14$16

    $18$20

    0 5 10 15

    Number of DC's

    Cost($million)

    Total Cost

    Inventory

    Transportation

    Fixed Cost

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    Industry Benchmarks:Number of Distribution Centers

    Sources: CLM 1999, Herbert W. Davis & Co; LogicTools

    Avg.# ofWH 3 14 25

    Pharmaceuticals Food Companies Chemicals

    - High margin product- Service not important (oreasy to ship express)- Inventory expensiverelative to transportation

    - Low margin product- Service very important- Outbound transportationexpensive relative to inbound

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    e-Business in the Retail Industry

    Brick-&-Mortar companies establish Virtual retailstores

    Wal-Mart, K-Mart, Barnes and Noble

    Use a hybrid approach in stocking High volume/fast moving products for local storage

    Low volume/slow moving products for browsing andpurchase on line

    Channel Conflict Issues

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    E-Fulfillment Requires aNew Logistics Infrastructure

    Traditional Supply Chain e-Supply Chain

    Supply Chain Strategy Push Push-Pull

    Shipment Type Bulk Parcel

    Inventory Flow Unidirectional Bi-directional

    Reverse Logistics Simple Highly Complex

    Destination Small Number of Stores Highly Dispersed Customers

    Lead Times Depends Short

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    Wal-Marts e-fulfillmentStrategy

    Wal-Mart has always prided itself in its in-housedistribution operations.

    Thus, it was a huge surprise when the companyannounced that it plans to hire an outside firm to handle

    order fulfillment and warehousing for its on-line storeWal-Mart.com, which the retailer launched in the fall of1999.

    Filling orders behind the scenes of Wal-Marts cyberstoreis Fingerhut Business Services. Fingerhut will provide

    Internet order fulfillment, warehousing, shipment,payment processing, customer service and merchandisereturns.

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    Matching Supply ChainStrategies with Products

    Pull Push

    Pull

    Push

    I

    Computer

    II

    IV III

    Demanduncertainty

    (C.V.)

    Delivery cost

    Unit price

    L H

    H

    L

    Economies of

    Scale

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    Locating the Push-PullBoundary

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    Organizational Skills Needed

    RawMaterial Customers

    PullPush

    Low Uncertainty

    Long Lead Times

    Cost Minimization

    Resource Allocation

    High Uncertainty

    Short Cycle Times

    Service Level

    Responsiveness

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    e-Business Opportunities:

    Reduce Facility Costs

    Eliminate retail/distributor sites

    Reduce Inventory Costs

    Apply the risk-pooling concept

    Centralized stocking

    Postponement of product differentiation

    Use Dynamic Pricing Strategies toImprove Supply Chain Performance

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    e-Business Opportunities:

    Supply Chain Visibility

    Reduction in the Bullwhip Effect Reduction in Inventory

    Improved service level

    Better utilization of Resources

    Improve supply chain performance Provide key performance measures

    Identify and alert when violations occur

    Allow planning based on global supply chain data