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Information as an Enabler to Supply Chain
Value of Information
“In modern supply chains, information replaces inventory” Why is this true? Why is this false?
Information is always better than no information. Why?
Information is the supply chain driver that serves as a glue allowing the other drivers to work together to create an integrated, coordinated supply chain
Types of Information
Supplier information Manufacturing information Distribution and retailing information Demand information
Characteristics of good information
Information must be accurate Information must be accessible in a timely
fashion Information must be of the right kind
Value of Information
Information Helps reduce variability Helps improve forecasts Enables coordination of systems and
strategies Improves customer service Facilitates lead time reductions Enables firms to react more quickly to
changing market conditions
Information for Coordination of Systems
Information is required to move from local to global optimization
Information is needed : Production status and costs Transportation availability and costs Inventory information Capacity information Demand information
Increasing Variability Upstream the Supply Chain –Bullwhip Effect
Bullwhip Effect
Increasing propagation of variability upstream through the supply chain
We Conclude ….
Order variability is amplified up the supply chain; upstream echelons face higher variability.
What you see is not what they face.
What are the Causes….
Demand forecasting Min-max inventory level Order-up-to level orders increase more than forecasts
Long cycle times Long lead times magnify this effect Impact on safety stock Product life cycle
Batch ordering Volume & transportation discount
What are the Causes….
Price fluctuation Promotional sales Forward buying
Inflated orders Orders placed increase during shortage
periods IBM Aptiva orders increased by 2-3 times
when retailers thought that IBM would be out of stock over Christmas
What are the Causes…. Single retailer, single manufacturer.
Retailer observes customer demand, Dt. Retailer orders qt from manufacturer.
Retailer ManufacturerDt qt
L
Consequences….
Increased safety stockReduced service levelInefficient allocation of
resourcesIncreased transportation costs
Ways to Cope with the Bullwhip Effect
Reducing uncertainty Centralizing demand information Bullwhip inherent in use of various forecasting techniques
Reducing variability Use of EDLP strategy (Payless)
Lead time reduction Order lead time (time to produce and ship) Information lead time (time to process order) Efficient network distribution design
Strategic partnership Vendor managed inventory (VMI) Sharing of customer information Collaborative forecasting
Coping with the Bullwhip Effect in Leading Companies
Reduce uncertainty POS Sharing information Sharing forecasts and policies
Reduce variability Eliminate promotions Year-round low pricing
Reduce lead times EDI Cross docking Transmitting POS data upstream
Strategic partnerships Vendor managed inventory Data sharing
Information for Effective Forecasts
Pricing, promotion, new products Different parties have this information Retailers may set pricing or promotion without
telling distributor Distributor/Manufacturer might have new
product or availability information Collaborative Forecasting addresses these
issues.
Locating Desired Products
How can demand be met if products are not in inventory? Locating products at other stores What about at other dealers?
What level of customer service will be perceived?
Lead-Time Reduction
Why? Customer orders are filled quickly Bullwhip effect is reduced Forecasts are more accurate Inventory levels are reduced
How? EDI POS data leading to anticipating incoming
orders.
Information to Address Conflicts Lot Size – Inventory:
Advanced manufacturing systems POS data for advance warnings
Inventory -- Transportation: Lead time reduction for batching Information systems for combining shipments Cross docking Advanced DSS
Lead Time – Transportation: Lower transportation costs Improved forecasting Lower order lead times
Product Variety – Inventory: Delayed differentiation
Cost – Customer Service: Transshipment
Impact of the Bullwhip Effect
Performance Measure Impact on Performance
Manufacturing Cost
Inventories
Lead Time
Transport Cost
Shipping & Receiving Cost
Customer Service Level
Profitability
Bull Whip Effect - Operational Obstacles (Batching)
Contributing factors High Order Cost Full TL economies Random or correlated ordering
Counter Measures EDI & Computer Assisted Ordering (CAO) Discounted on Assorted Truckload, consolidated by 3rd
party logistics Regular delivery appointment Volume and not lot size discounts
State of Practice McKesson, Nabisco, ... 3rd party logistics in Europe, emerging in the U.S. P & G
Bull Whip Effect - Pricing Obstacles
Contributing factors High-Low Pricing leading to forward buy Delivery and Purchase not synchronized
Counter Measures EDLP Limited purchase quantities Scan based promotions
State of Practice P&G (resisted by some retailers) Scan based promotion
The Bullwhip Effect: Information Processing Obstacles
Contributing factors No visibility of end demand Multiple forecasts Long lead-time
Counter Measures Access sell-thru or POS data Direct sales (natural on web) Single control of replenishment Lead time reduction
State of Practice Sell-thru data in contracts (e.g., HP, Apple, IBM) CFAR, CPFR, CRP, VMI (P&G and Wal-Mart) Quick Response Mfg. Strategy
Bull Whip Effect - Operational Obstacles
Contributing factors Proportional rationing scheme Ignorance of supply conditions Unrestricted orders & free return policy
Counter Measures Allocation based on past sales. Shared Capacity and Supply Information Flexibility Limited over time, capacity reservation
State of Practice Saturn, HP Schedule Sharing (HP with TI and Motorola) HP, Sun, Seagate
Managerial Implications of the Bull Whip Effect - Behavioral Factors
Contributing factors Lack of trust Local reaction
Counter Measures Building trust and partnership
State of Practice Wal-Mart and P&G with CFAR
The Bullwhip Effect:Managerial Insights Exists, in part, due to the retailer’s need to estimate
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 greater the increase. Centralized demand information can significantly
reduce the bullwhip effect, but will not eliminate it.
Steps in Cycle Time Reduction
Establish a cycle-time reduction team Develop an understanding of given SC
processes and current cycle time performance
Identify opportunities for cycle time reduction Develop and implement recommendations for
cycle time reduction Measure process cycle time reduction Conduct CI efforts for process cycle time
reduction
CSF of Cycle Time Reduction
Top management support Commitment to significant cycle time
reduction Use of cross function teams Application of TQM tools Training in cycle time reduction approaches Establish, monitor, and report cycle time
performance measures Collaboration with supply chain member
Locating Desired Products
How can demand be met if products are not in inventory? Locating products at other stores What about at other dealers?
What level of customer service will be perceived?