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“ Bullwhip” Effect   Reducing the risk of customers’ stock- outs and other disruption in the supply process Anand Subramaniam
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“ Bullwhip” Effect - Causes
“Bullwhip” Effect Each organisation in the supply chain seeks to solve the problem from its own perspective Wholesaler’s Orders to Manufacture Time 0 5 10 15 20 Consumer Sales Order Quantity 0 5 10 15 20 Time Retailer’s Order to Manufacture Order Quantity 0 5 10 15 20 Time Order Quantity 0 5 10 15 20 Time Manufacturer’s Orders to Supplier Order Quantity
“Bullwhip” Effect – Main Causes “ Bullwhip” Causes Long lead times / to many intermediaries Inflated orders due to lack of information sharing Price fluctuation (Promotional sales) Order batching / large lot size Updating Demand Forecast
Demand Fluctuation.. Causes Demand Forecast Long order lead times Volume / transport discounts Poor customer service rates Promotional activity No minimum or maximum order quantities Product proliferation Poor communication Safety stocks that depend on erratic demand variance /  long lead times
Order Batching.. Causes Order Batching Economies of scale in transportation - full truckload rates Periodic planning and ordering as part of MRP and periodic review systems Push” ordering motivated by short term financial performance measures Economies of scale in ordering cost &  manufacturing setups - leads to batching
Price Fluctuation.. Causes Price Fluctuation Trade promotions and supply chain management Variance from buying big quantities to the consumption rate Quantity discounts and advance purchases Wide swings resulting in capacity adjustment costs, high inventory costs, transport diseconomies
Inflated / Deflated Needs.. Causes Inflated / Deflated Customers exaggerate their real needs When capacity constraints are removed, orders suddenly drop Where demand exceeds manufacturing capacity leads to rationing of  order fulfillment
These causes leads to… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Managing the “Bullwhip” Effect Manage ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Bullwhip” Effect - On Supply Chain
On Supply Chain – Pitfalls / Opportunities Manufacture Customer Warehouse Purchase Operations Design Information Systems ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
SC Integration – Dealing with Conflicts ,[object Object],[object Object],[object Object],[object Object],[object Object]
“ Bullwhip” Effect - Example
Example – “Bullwhip” Effect ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Assume that pick up a new customer and their orders are now $1.5B / week (every week) $0 $1B $1B $1B Week 0 Unmet Need Inventory Inbound On Order
Example – “Bullwhip” Effect (Contd.) Impact of a new customer and their orders of $1.5B / week (every week).  Impact Before & After If you had all the information, this would result in 3 weeks of disruption (finance, transport, inventory, sales, marketing etc.) and would lead to incorrect demand signals
Example – “Bullwhip” Effect (Contd.) After Before $1.5B $1.5B $1.5B $1.5B Future $.5B $1B $1B $1.5B Week 1 $1.0B $1B $1.5B $1.5B Week 2 $1.5B $1.5B $1.5B $1.5B Week 3 Unmet Need Inventory Inbound On Order $0 $1.5B $1.5B $1.5B Week 4 $.5B $1B $1B $3.0B Week 1 $1.0B $1B $3.0B $1.5B Week 2 $1.5B $3.0B $1.5B $1.5B Week 3 Unmet Need Inventory Inbound On Order
Information Sharing
No Information Sharing Lack of information sharing Product Flow Customer Retailer Wholesaler Manufacturer Tier 1 Supplier Tier 2 Supplier
Buyer / Seller - Information Sharing  Sellers Buyers Application providers (point-to-point - EDI) App. Service Providers (ASPs) eHub Market place provider
Sharing Information - Types VMI / Continuous Replinsh-ment / 3 PL Production / Delivery Schedule Order Status (track & trace) Channel Alignment / Consolidate Sales / POS / EDI Data Sales Forecast Information Types Capacity / utilisation or Mixed SKUs Performance Metrics
EDI Challenges Rigid text formats / rigid design for transaction processing EDI Challenges Installation costs Multiple industry specific standards Batch Oriented
Other Challenges Challenges Confidentiality of shared information Timeliness and accuracy of information Anti-trust implications, such as possible price fixing behavior Technological constraints Aligning incentives of different partners Trust and cooperation Upstream variability are always greater than those of the downstream
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The "Bullwhip" Effect

  • 1. “ Bullwhip” Effect Reducing the risk of customers’ stock- outs and other disruption in the supply process Anand Subramaniam
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  • 5. “Bullwhip” Effect Each organisation in the supply chain seeks to solve the problem from its own perspective Wholesaler’s Orders to Manufacture Time 0 5 10 15 20 Consumer Sales Order Quantity 0 5 10 15 20 Time Retailer’s Order to Manufacture Order Quantity 0 5 10 15 20 Time Order Quantity 0 5 10 15 20 Time Manufacturer’s Orders to Supplier Order Quantity
  • 6. “Bullwhip” Effect – Main Causes “ Bullwhip” Causes Long lead times / to many intermediaries Inflated orders due to lack of information sharing Price fluctuation (Promotional sales) Order batching / large lot size Updating Demand Forecast
  • 7. Demand Fluctuation.. Causes Demand Forecast Long order lead times Volume / transport discounts Poor customer service rates Promotional activity No minimum or maximum order quantities Product proliferation Poor communication Safety stocks that depend on erratic demand variance / long lead times
  • 8. Order Batching.. Causes Order Batching Economies of scale in transportation - full truckload rates Periodic planning and ordering as part of MRP and periodic review systems Push” ordering motivated by short term financial performance measures Economies of scale in ordering cost & manufacturing setups - leads to batching
  • 9. Price Fluctuation.. Causes Price Fluctuation Trade promotions and supply chain management Variance from buying big quantities to the consumption rate Quantity discounts and advance purchases Wide swings resulting in capacity adjustment costs, high inventory costs, transport diseconomies
  • 10. Inflated / Deflated Needs.. Causes Inflated / Deflated Customers exaggerate their real needs When capacity constraints are removed, orders suddenly drop Where demand exceeds manufacturing capacity leads to rationing of order fulfillment
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  • 13. “ Bullwhip” Effect - On Supply Chain
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  • 18. Example – “Bullwhip” Effect (Contd.) Impact of a new customer and their orders of $1.5B / week (every week). Impact Before & After If you had all the information, this would result in 3 weeks of disruption (finance, transport, inventory, sales, marketing etc.) and would lead to incorrect demand signals
  • 19. Example – “Bullwhip” Effect (Contd.) After Before $1.5B $1.5B $1.5B $1.5B Future $.5B $1B $1B $1.5B Week 1 $1.0B $1B $1.5B $1.5B Week 2 $1.5B $1.5B $1.5B $1.5B Week 3 Unmet Need Inventory Inbound On Order $0 $1.5B $1.5B $1.5B Week 4 $.5B $1B $1B $3.0B Week 1 $1.0B $1B $3.0B $1.5B Week 2 $1.5B $3.0B $1.5B $1.5B Week 3 Unmet Need Inventory Inbound On Order
  • 21. No Information Sharing Lack of information sharing Product Flow Customer Retailer Wholesaler Manufacturer Tier 1 Supplier Tier 2 Supplier
  • 22. Buyer / Seller - Information Sharing Sellers Buyers Application providers (point-to-point - EDI) App. Service Providers (ASPs) eHub Market place provider
  • 23. Sharing Information - Types VMI / Continuous Replinsh-ment / 3 PL Production / Delivery Schedule Order Status (track & trace) Channel Alignment / Consolidate Sales / POS / EDI Data Sales Forecast Information Types Capacity / utilisation or Mixed SKUs Performance Metrics
  • 24. EDI Challenges Rigid text formats / rigid design for transaction processing EDI Challenges Installation costs Multiple industry specific standards Batch Oriented
  • 25. Other Challenges Challenges Confidentiality of shared information Timeliness and accuracy of information Anti-trust implications, such as possible price fixing behavior Technological constraints Aligning incentives of different partners Trust and cooperation Upstream variability are always greater than those of the downstream
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