Supply Chain Dynamics, Value ofSupply Chain Dynamics, Value of
Information & Bullwhip EffectInformation & Bullwhip Effect
...
Supply Chain StagesSupply Chain Stages
Supply Chain encompasses all activities associated with the flow
and transformation...
Case 1: P&GCase 1: P&G--Dynamics of the Supply ChainDynamics of the Supply Chain
OrderSize
Time
Source: Tom Mc Guffry, Ele...
Case 1: P&G: What Management Gets...Case 1: P&G: What Management Gets...
OrderSize
Time
Source: Tom Mc Guffry, Electronic ...
Case 1 P&G: What Management WantsCase 1 P&G: What Management Wants……
Volumes
Time
Source: Tom Mc Guffry, Electronic Commer...
Bullwhip EffectBullwhip Effect
Variability of demand amplified as we
move up the supply chain from the
retailer to the dis...
Impacts of the Bullwhip EffectImpacts of the Bullwhip Effect
Increased inventory
Overtime production and idle
production s...
The Bullwhip effect is a phenomenon illustrated in
distribution channels where variability of product orders
increase at e...
Growth of demand variabilityGrowth of demand variability
Bullwhip Effect -- Retailer Demand
0
50
100
150
200
250
300
0 25 ...
Growth of demand variabilityGrowth of demand variability
Bullwhip Effect -- Distributor Demand
0
50
100
150
200
250
300
0 ...
Five areas of supply chain management can contribute to
increased demand variability:
• Forecasting (Forecast Updates)
• L...
•Forecasting
(Forecast
Updates)
Contributors to Bullwhip Effect#1Contributors to Bullwhip Effect#1
Impact of Forecasting on the Bullwhip EffectImpact of Forecasting on the Bullwhip Effect
Let us understand this with perio...
Impact of Forecasting on the Bullwhip EffectImpact of Forecasting on the Bullwhip Effect
The base-stock level is typically...
Impact of Forecasting on the Bullwhip EffectImpact of Forecasting on the Bullwhip Effect
An important characteristic of al...
Reorder Point with Variable DemandReorder Point with Variable Demand
stocksafety
yprobabilitlevelservicetoingcorresponddev...
ExampleExample
Amplification of demand changes
that affect upstream operations
within the supply chain
Assumes stocks of o...
At the start of the week#1At the start of the week#1
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order...
Manufacturer Distributor Retailer Demand
Prod Stock Prod Stock Prod Stock
100 100
100
100 100
100
100 100
100
100
60 100
8...
•LEAD
TIME
Contributors to Bullwhip Effect#2Contributors to Bullwhip Effect#2
Impact of Lead Times on the Bullwhip EffectImpact of Lead Times on the Bullwhip Effect
To calculate safety stock levels an...
Measuring the Bullwhip EffectMeasuring the Bullwhip Effect
Between Retailer and ManufacturerBetween Retailer and Manufactu...
2
2
5
)1(2
5
)1(2
1
)(
)(
++≥
DVar
QVar
…if the retailer estimates the mean demand based on a five period
moving average (...
Lower Bound of Increase VariabilityLower Bound of Increase Variability
0
2
4
6
8
10
12
3 5 10 15 20 25 30
p (number of per...
ConsequencesConsequences……..
Increased safety stock
Reduced service level
Inefficient allocation of resources
Increased tr...
MultiMulti--Stage Supply ChainsStage Supply Chains
Consider a multi-stage supply chain:
– Stage i places order qi to stage...
∏
∑∑
−
=
==


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++≥
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k
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MultiMulti--Stage Systems: Var(qStage Systems: Var(qkk
)/Var(D))/Var(D)
0
5
10
15
20
25
30
0 10 20 30
Dec, k=5
Cen, k=5
De...
The Bullwhip Effect:The Bullwhip Effect:
Managerial InsightsManagerial Insights
Exists, in part, due to the retailer’s nee...
ORDER
BATCHING
Contributors to Bullwhip Effect#3Contributors to Bullwhip Effect#3
Order batchingOrder batching
Driven by
– Economies of scale in order costs
– Economies of scale in transportation
(TL vs. ...
Order batchingOrder batching
Increases the variability of demand
as seen by the upstream member of
the supply chain
– No d...
PRICE
FLUCTUATION
Contributors to Bullwhip Effect#4Contributors to Bullwhip Effect#4
Price fluctuationsPrice fluctuations
Driven by
– Price discounts
– Quantity or volume discounts
– Coupons
– Rebates
Price fluctuationsPrice fluctuations
Create
– Swings in demand (high during low
price periods; low during normal price
per...
•RATIONING
&
SHORTAGE
GAMING
Contributors to Bullwhip Effect#5Contributors to Bullwhip Effect#5
Rationing and Shortage GamingRationing and Shortage Gaming
During shortages rationing is often
based on a fraction of the ...
Impact ofImpact of Inflated ordersInflated orders on the Bullwhipon the Bullwhip
Shortage gaming occurs in an environment ...
Bullwhip EffectBullwhip Effect
In summary, the bullwhip effect will occur to some degree in
most all supply chains. The ex...
•HOW TO
TAME?
Bullwhip Effect: ITS YOUR TURNBullwhip Effect: ITS YOUR TURN
Managing the Bullwhip EffectManaging the Bullwhip Effect
We can…
…reduce uncertainty
…reduce demand variability
…reduce le...
Avoid multiple demand forecastAvoid multiple demand forecast
updatesupdates
Share consumption data with upstream
members
–...
Reducing Demand UncertaintyReducing Demand Uncertainty
Centralized vs. Decentralized InformationCentralized vs. Decentrali...
Reducing UncertaintyReducing Uncertainty
Practices that support effort to reduce uncertainty involve the
implementation of...
Reducing Demand VariabilityReducing Demand Variability
In addition to sharing information through EDI and XML
technologies...
Reducing Lead Times (Cycle Time)Reducing Lead Times (Cycle Time)
Two strategies that help to reduce lead times include cro...
Reduce Order batchingReduce Order batching
Reduce order costs
– Use EDI and standardize ordering
processes
– Innovative tr...
Stabilize pricesStabilize prices
Avoid price discounting and volume
discounting
Same day low prices (Wal-Mart)
Eliminate gaming in shortage situationsEliminate gaming in shortage situations
Allocate product based on past sales
not on...
Establishing PartnershipsEstablishing Partnerships
Each of the methods outlined earlier rely on closer relationships
betwe...
Supply Chain Coordination InitiativesSupply Chain Coordination Initiatives
FrameworkFramework
Causes of
the Bullwhip
Effec...
Coping with the Bullwhip EffectCoping with the Bullwhip Effect
Reduce Variability and Uncertainty
- POS
- Sharing Informat...
Example:Example:
Quick Response at BenettonQuick Response at Benetton
Benetton, the Italian sportswear manufacturer,
was f...
Example:Example:
Quick Response at BenettonQuick Response at Benetton
Benetton uses an effective strategy, referred
to as ...
How Does BenettonHow Does Benetton
Cope with the Bullwhip Effect?Cope with the Bullwhip Effect?
1. Integrated Information ...
You May Try This:You May Try This:
--Use Beer Distribution Game to Demonstrate and AnalyzeUse Beer Distribution Game to De...
Supply Chain StructureSupply Chain Structure
Supply chains typically consist of the
following “players”:
– Retailers
– Who...
Demands in Supply ChainsDemands in Supply Chains
Retailers respond to customer demands.
Orders placed by retailers become
...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
Example: 2 retailers with the same wholesaler
– Periodic ...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
Example: 3 retailers with the same wholesaler
– Periodic ...
62
Example Supply Chain StagesExample Supply Chain Stages
Supplier Manufacturer One
Distributor
Three
Retailers
Many
Custo...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
(Constant customer demands = 10+25+15=50 units/day)(Const...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
(Constant customer demands = 10+25+15=50 units/day)(Const...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
(Constant customer demands = 10+25+15=50 units/day)(Const...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
(Constant demands)(Constant demands)
R e t a ile r 1 De m...
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains
(Random demands)(Random demands)
R e t a i l e r 1 D e m ...
ObservationObservation……
Different chain phases have different
calculations of demand quantity, thus
the longer the chain ...
Bullwhip EffectBullwhip Effect
In 2001, Cisco
was forced to
write down $2.2
billion worth of
obsolete
inventory, due to
un...
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7a session 7_bulwhip effect cfvg 2012

  1. 1. Supply Chain Dynamics, Value ofSupply Chain Dynamics, Value of Information & Bullwhip EffectInformation & Bullwhip Effect Dr. Ravi Shankar Dr. RAVI SHANKAR Professor Department of Management Studies Indian Institute of Technology Delhi Hauz Khas, New Delhi 110 016 India Phone: +91-(11) 2659-6421 (O) Fax: (+91)-(11) 26862620 Email: ravi1@dms.iitd.ac.in, r.s@rediffmail.com http://web.iitd.ac.in/~ravi1
  2. 2. Supply Chain StagesSupply Chain Stages Supply Chain encompasses all activities associated with the flow and transformation of materials and information from the raw material stage through to the end user. Supplier Manufacturer Distributor Retailer Customer
  3. 3. Case 1: P&GCase 1: P&G--Dynamics of the Supply ChainDynamics of the Supply Chain OrderSize Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998 Customer Demand Customer Demand Retailer Orders Distributor Orders Production Plan
  4. 4. Case 1: P&G: What Management Gets...Case 1: P&G: What Management Gets... OrderSize Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998 Customer Demand Customer Demand Production PlanProduction Plan
  5. 5. Case 1 P&G: What Management WantsCase 1 P&G: What Management Wants…… Volumes Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998 Production Plan Customer Demand Customer Demand
  6. 6. Bullwhip EffectBullwhip Effect Variability of demand amplified as we move up the supply chain from the retailer to the distributor to the manufacturer to the suppliers
  7. 7. Impacts of the Bullwhip EffectImpacts of the Bullwhip Effect Increased inventory Overtime production and idle production scheduling Excessive or insufficient capacity Poor customer service due to unavailable products Expedited shipments
  8. 8. The Bullwhip effect is a phenomenon illustrated in distribution channels where variability of product orders increase at each subsequent echelon (stage) in the channel. Even though retail sales may fluctuate little, orders from retailer to distributor fluctuate more and orders from the distributor to the manufacturer fluctuate more yet. Consider the following graph ….. The Bullwhip EffectThe Bullwhip Effect
  9. 9. Growth of demand variabilityGrowth of demand variability Bullwhip Effect -- Retailer Demand 0 50 100 150 200 250 300 0 25 50 75 100 Time Demand Bullwhip Effect -- Distributor Demand 0 50 100 150 200 250 300 0 25 50 75 100 Time Demand Retailer demand Distributor demand
  10. 10. Growth of demand variabilityGrowth of demand variability Bullwhip Effect -- Distributor Demand 0 50 100 150 200 250 300 0 25 50 75 100 Time Demand Bullwhip Effect -- Manufacturer Demand 0 50 100 150 200 250 300 0 25 50 75 100 Time Demand Distributor demand Manufacturer demand
  11. 11. Five areas of supply chain management can contribute to increased demand variability: • Forecasting (Forecast Updates) • Lead Times • Order Batching • Price Fluctuations • Shortage Gaming Let’s consider each. Contributors to VariabilityContributors to Variability
  12. 12. •Forecasting (Forecast Updates) Contributors to Bullwhip Effect#1Contributors to Bullwhip Effect#1
  13. 13. Impact of Forecasting on the Bullwhip EffectImpact of Forecasting on the Bullwhip Effect Let us understand this with periodic review policy where the inventory policy is characterized by a single parameter, the base- stock level. That is, the warehouse determines a target inventory level, the base-stock level, and each review period, the inventory position is reviewed, and the warehouse orders enough to raise the inventory position to the base- stock level.
  14. 14. Impact of Forecasting on the Bullwhip EffectImpact of Forecasting on the Bullwhip Effect The base-stock level is typically set equal to the average demand during lead time and review period plus a multiple of the standard deviation of demand during lead time and review period. The latter quantity is referred to as safety stock. Typically, managers use standard forecast smoothing techniques to estimate average demand and demand variability.
  15. 15. Impact of Forecasting on the Bullwhip EffectImpact of Forecasting on the Bullwhip Effect An important characteristic of all forecasting techniques is that as more data are observed, the estimates of the mean and the standard deviation (or variability) of customer demands are regularly modified. Since safety stock, as well as the base-stock level, strongly depends on these estimates, the user is forced to change order quantities, thus increasing variability.
  16. 16. Reorder Point with Variable DemandReorder Point with Variable Demand stocksafety yprobabilitlevelservicetoingcorresponddeviationsstandardofnumber demanddailyofdeviationstandardthe timelead demanddailyaverage pointreorder where = = = = = = += LZ Z L d R LZLdR d d d σ σ σ
  17. 17. ExampleExample Amplification of demand changes that affect upstream operations within the supply chain Assumes stocks of one week demand Lead time= 1 week Backorder allowed
  18. 18. At the start of the week#1At the start of the week#1 Manufacturer Distributor Retailer Demand Prod Stock Order Stock Order Stock 100 100 100 100 100 100 100 95 1 2 3 4 5 Week
  19. 19. Manufacturer Distributor Retailer Demand Prod Stock Prod Stock Prod Stock 100 100 100 100 100 100 100 100 100 100 60 100 80 80 100 90 90 100 95 95 120 80 100 100 90 95 95 95 95 95 90 100 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 1 2 3 4 5 Watch how Bullwhip effect has aggravatedWatch how Bullwhip effect has aggravated Week
  20. 20. •LEAD TIME Contributors to Bullwhip Effect#2Contributors to Bullwhip Effect#2
  21. 21. Impact of Lead Times on the Bullwhip EffectImpact of Lead Times on the Bullwhip Effect To calculate safety stock levels and base-stock levels, we in effect multiply estimates of the average and standard deviation of the daily customer demands by the sum of the lead time and the review period. Thus, with longer lead times, a small change in the estimate of demand variability implies a significant change in safety stock and base-stock level, leading to a significant change in order quantities. This, of course, leads to an increase in variability.
  22. 22. Measuring the Bullwhip EffectMeasuring the Bullwhip Effect Between Retailer and ManufacturerBetween Retailer and Manufacturer Assuming a moving average forecasting technique based on “p” observations, every period the retailer calculates a new mean and standard deviation based on the “p” most recent observations of demand, the target inventory also changes. The ratio between orders to the manufacturer (Q) and retailer demand (D) is: Therefore….. 2 2 22 1 )( )( p L p L DVar QVar ++≥
  23. 23. 2 2 5 )1(2 5 )1(2 1 )( )( ++≥ DVar QVar …if the retailer estimates the mean demand based on a five period moving average (p = 5), and that an order placed by the retailer at the end of period t is received at the start of period t + 1 (L = 1) then the variance of the orders placed by the retailer will be…. 4.1 )( )( ≥ DVar QVar …or at least 40% larger than the variance of customer demand. The following slide plots the relationship between the number of periods included in the moving average forecast and the ratio between consumer demand and retail orders. = Measuring the Bullwhip EffectMeasuring the Bullwhip Effect Between Retailer and ManufacturerBetween Retailer and Manufacturer
  24. 24. Lower Bound of Increase VariabilityLower Bound of Increase Variability 0 2 4 6 8 10 12 3 5 10 15 20 25 30 p (number of periods in moving average) Var (Q)/Var (D) L = 5 L = 3 L = 1 2 2 22 1 )( )( p L p L DVar QVar ++≥ LSTDzAVGL ××+×=minBased on an order-up-to inventory policy where, L = Lead time (number of periods) p = Periods in moving average forecast Q = Retail order quantity D = Consumer demand Extending the logic presented in the previous algorithm, this graph suggests that forecasting techniques that incorporate more history in the forecasts, (“p” periods), and hence a smoother forecast, can help to reduce the ratio of variability in orders. It also indicates (colored lines) that the lead time used in the inventory algorithm can have a significant impact on order variability.
  25. 25. ConsequencesConsequences…….. Increased safety stock Reduced service level Inefficient allocation of resources Increased transportation costs
  26. 26. MultiMulti--Stage Supply ChainsStage Supply Chains Consider a multi-stage supply chain: – Stage i places order qi to stage i+1. – Li is lead time between stage i and i+1. Retailer Stage 1 Manufacturer Stage 2 Supplier Stage 3 qo=D q1 q2 L1 L2
  27. 27. ∏ ∑∑ − = ==       ++≥ ++≥ 1 1 2 2 2 2 11 22 1 )( )( )(2)(2 1 )( )( k i ii K k i i k i iK p L p L DVar QVar p L p L DVar QVar MultiMulti--Stage Supply ChainsStage Supply Chains (Formula)(Formula)
  28. 28. MultiMulti--Stage Systems: Var(qStage Systems: Var(qkk )/Var(D))/Var(D) 0 5 10 15 20 25 30 0 10 20 30 Dec, k=5 Cen, k=5 Dec, k=3 Cen, k=3 k=1
  29. 29. The Bullwhip Effect:The Bullwhip Effect: Managerial InsightsManagerial 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 reduce the bullwhip effect, but will not eliminate it.
  30. 30. ORDER BATCHING Contributors to Bullwhip Effect#3Contributors to Bullwhip Effect#3
  31. 31. Order batchingOrder batching Driven by – Economies of scale in order costs – Economies of scale in transportation (TL vs. LTL) – MRP systems (updated monthly or periodically) – Push ordering (e.g., to meet a quarterly sales quota) drive order batching
  32. 32. Order batchingOrder batching Increases the variability of demand as seen by the upstream member of the supply chain – No demand in some periods, large demands in others – Mitigated if customer cycles do not overlap, but they often do
  33. 33. PRICE FLUCTUATION Contributors to Bullwhip Effect#4Contributors to Bullwhip Effect#4
  34. 34. Price fluctuationsPrice fluctuations Driven by – Price discounts – Quantity or volume discounts – Coupons – Rebates
  35. 35. Price fluctuationsPrice fluctuations Create – Swings in demand (high during low price periods; low during normal price periods) Problems include – Overtime and idle production time – Premium freight charges – Inventory accumulations
  36. 36. •RATIONING & SHORTAGE GAMING Contributors to Bullwhip Effect#5Contributors to Bullwhip Effect#5
  37. 37. Rationing and Shortage GamingRationing and Shortage Gaming During shortages rationing is often based on a fraction of the orders placed by a firm – Incentive to increase orders during shortages, place orders with multiple firms, and cancel orders once inventory arrives – Large swings in perceived demand at upstream components of supply chain
  38. 38. Impact ofImpact of Inflated ordersInflated orders on the Bullwhipon the Bullwhip Shortage gaming occurs in an environment of tight supply. Supply chain customers may order larger quantities with the expectation that they will receive a greater allocation quantity of product(s) in short supply. The impact on the supply chain is a significant increase in forecasted demand as the inflated orders are received. When products become available an oversupply can occur as orders placed earlier (created to enhance allocation) are cancelled and products are returned.
  39. 39. Bullwhip EffectBullwhip Effect In summary, the bullwhip effect will occur to some degree in most all supply chains. The extent of the effect will vary and will impact inventory requirements, production scheduling and operations, manufacturing and distribution capacity requirements among other areas. What action can we take to counteract the Bullwhip effect?
  40. 40. •HOW TO TAME? Bullwhip Effect: ITS YOUR TURNBullwhip Effect: ITS YOUR TURN
  41. 41. Managing the Bullwhip EffectManaging the Bullwhip Effect We can… …reduce uncertainty …reduce demand variability …reduce lead-times …establish strategic partnerships Information sharing Channel alignment Operational efficiencies.
  42. 42. Avoid multiple demand forecastAvoid multiple demand forecast updatesupdates Share consumption data with upstream members – Point of sale data given to distributors and manufacturers – Use EDI and internet to share data – Vendor managed inventory or continuous replenishment programs – Direct sale techniques to get downstream demand info. – Share sales, capacity and inventory data to reduce gaming
  43. 43. Reducing Demand UncertaintyReducing Demand Uncertainty Centralized vs. Decentralized InformationCentralized vs. Decentralized Information Dec K = 5 Cen K = 5 Dec K = 3 Cen K = 3 K = 1 p, number of periods in moving average Var (Qk) / Var (D) (K = stage in chain) This graph compares the lower bound of variability in a multi- echelon supply chain when demand is not shared between customers (dashed line) and suppliers, and when demand is shared (solid line).
  44. 44. Reducing UncertaintyReducing Uncertainty Practices that support effort to reduce uncertainty involve the implementation of systems such as Electronic Data Interchange (EDI), Extensible Markup Language (XML). Both these technologies allow companies to share information (such as consumer sales) with partner companies in the supply chain. EDI uses specific network services, XML is a new technology that supports information sharing over the internet.
  45. 45. Reducing Demand VariabilityReducing Demand Variability In addition to sharing information through EDI and XML technologies, companies are closing the supply chain gap through initiatives such as Vendor Managed Inventories (VMI), Quick Response (QR), and Efficient Consumer Response (ECR). Each of these initiatives offers a means to more closely coordinate supply chain inventories, in some cases making the supplier responsible for inventory levels at customer locations. This provides organizations up the chain with even greater visibility of demand patterns and product availability.
  46. 46. Reducing Lead Times (Cycle Time)Reducing Lead Times (Cycle Time) Two strategies that help to reduce lead times include cross- docking and postponement. Cross-docking establishes order requirements at the store level for placement to the supplier. As the orders are delivered to the retail distribution center, they are immediately staged for store delivery, thus eliminating DC inventories. Postponement delays the differentiation of products until the time of order. A basic system may be manufactured (say a base PC unit). Key components are then added at the time of order. Manufacturers are able to combine demand for the base product, hold less expensive inventories of components, and reduce cycle times.
  47. 47. Reduce Order batchingReduce Order batching Reduce order costs – Use EDI and standardize ordering processes – Innovative transportation (3PL) • TL with products from multiple suppliers • TL with same product to multiple customers
  48. 48. Stabilize pricesStabilize prices Avoid price discounting and volume discounting Same day low prices (Wal-Mart)
  49. 49. Eliminate gaming in shortage situationsEliminate gaming in shortage situations Allocate product based on past sales not on current orders Share information about capacity Long term contracting to allow vendors to adjust capacity Eliminate generous return and order cancellation policies
  50. 50. Establishing PartnershipsEstablishing Partnerships Each of the methods outlined earlier rely on closer relationships between customers and suppliers in order to support greater information sharing and the development of trust between the organizations. An additional strategy involving partnerships is the concept of Every Day Low Pricing (EDLP). EDLP eliminates the pattern of promotion offered by suppliers. By trading off the promotional efforts with a consistent and lower price the incentive for customers to place forward buys is eliminated and reduced variability in demand helps the supplier lower costs and maintain profitable margins.
  51. 51. Supply Chain Coordination InitiativesSupply Chain Coordination Initiatives FrameworkFramework Causes of the Bullwhip Effect Information Sharing Channel Alignment Operational Efficiency Demand Forecasting Update Understanding system dynamics Using point of sale (POS) data EDI, XML (internet) Computer Assisted Ordering Vendor Managed Inventory (VMI) Information sharing Consumer direct Lead-time reduction Echelon-based inventory control Order Batching EDI Extensible Markup Language (XML). Internet ordering Discounts for assortment planning Delivery appointments Consolidation Logistics outsourcing Reducing order costs Computer Assisted Ordering Price Fluctuations Continuous Replenishment Programs (CRP) Every Day Low Pricing (EDLP) Every Day Low Pricing (EDLP) Activity Based Costing (ABC) Shortage Gaming Sharing sales, capacity, and inventory data Allocation based on passed salesSource: Lee et al. (1997)
  52. 52. Coping with the Bullwhip EffectCoping with the Bullwhip Effect Reduce Variability and Uncertainty - POS - Sharing Information - Year-round low pricing Reduce Lead Times - EDI - Cross Docking Alliance Arrangements – Vendor managed inventory – On-site vendor representatives
  53. 53. Example:Example: Quick Response at BenettonQuick Response at Benetton Benetton, the Italian sportswear manufacturer, was founded in 1964. In 1975 Benetton had 200 stores across Italy. Ten years later, the company expanded to the U.S., Japan and Eastern Europe. Sales in 1991 reached 2 trillion. Many attribute Benetton’s success to successful use of communication and information technologies.
  54. 54. Example:Example: Quick Response at BenettonQuick Response at Benetton Benetton uses an effective strategy, referred to as Quick Response, in which manufacturing, warehousing, sales and retailers are linked together. In this strategy a Benetton retailer reorders a product through a direct link with Benetton’s mainframe computer in Italy. Using this strategy, Benetton is capable of shipping a new order in only four weeks, several week earlier than most of its competitors.
  55. 55. How Does BenettonHow Does Benetton Cope with the Bullwhip Effect?Cope with the Bullwhip Effect? 1. Integrated Information Systems • Global EDI network that links agents with production and inventory information • EDI order transmission to Head Quarter • EDI linkage with air carriers • Data linked to manufacturing 2. Coordinated Planning • Frequent review allows fast reaction • Integrated distribution strategy
  56. 56. You May Try This:You May Try This: --Use Beer Distribution Game to Demonstrate and AnalyzeUse Beer Distribution Game to Demonstrate and Analyze Bullwhip EffectBullwhip Effect --Use CD given with the Text bookUse CD given with the Text book
  57. 57. Supply Chain StructureSupply Chain Structure Supply chains typically consist of the following “players”: – Retailers – Wholesalers – Distributors – Manufacturers Each player typically makes decision independently or in a decentralized manner.
  58. 58. Demands in Supply ChainsDemands in Supply Chains Retailers respond to customer demands. Orders placed by retailers become demands for wholesalers. Order placed by wholesalers become demands for distributors Order placed by distributors become demands for manufacturers. – Manufacturers must produce items to meet these demands.
  59. 59. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains Example: 2 retailers with the same wholesaler – Periodic (s, Q) policy. – Review Period = 1 day Retailer-1 – Demand at Retailer 1 = 10/day (constant) – Policy of Retailer 1 = (20,50) – Beginning Inventory= 20 Items
  60. 60. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains Example: 3 retailers with the same wholesaler – Periodic (s, Q) policy. – Review Period = 1 day Retailer-2 – Demand at Retailer 2 = 25/day (constant) – Policy of Retailer 2 = (50,125) – Beginning Inventory= 100 Items Retailer-3 – Demand at Retailer 3 = 15/day (constant) – Policy of Retailer 1 = (30,120) – Beginning Inventory= 120 Items
  61. 61. 62 Example Supply Chain StagesExample Supply Chain Stages Supplier Manufacturer One Distributor Three Retailers Many Customers
  62. 62. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains (Constant customer demands = 10+25+15=50 units/day)(Constant customer demands = 10+25+15=50 units/day) Day Beg. Inv. Dem. Ord. Beg. Inv. Dem. Ord. Beg. Inv. Dem. Ord. Observed Cust. Dem. 1 20 10 ?? 100 25 150 15 ?? ?? 2 10 10 75 25 135 15 0 50 3 50 10 50 25 ?? 120 15 125 50 4 40 10 25 25 105 15 0 50 5 30 10 125 25 90 15 0 50 6 20 10 ?? 100 25 75 15 50 50 7 10 10 75 25 60 15 0 50 8 50 10 50 25 ?? 45 15 125 50 9 40 10 25 25 30 15 ?? 120 50 10 30 10 125 25 15 15 0 50 11 20 10 ?? 100 25 120 15 50 50 12 10 10 75 25 105 15 0 50 13 50 10 50 25 ?? 90 15 125 50 14 40 10 25 25 75 15 0 50 15 30 10 125 25 60 15 0 50 16 20 10 ?? 100 25 45 15 50 50 17 10 10 75 25 30 15 ?? 120 50 18 50 10 50 25 ?? 15 15 125 50 19 40 10 25 25 120 15 0 50 20 30 10 125 25 105 15 0 50 Retailer 1 Retailer 2 Retailer 3 Demands to Wholesaler
  63. 63. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains (Constant customer demands = 10+25+15=50 units/day)(Constant customer demands = 10+25+15=50 units/day) Day Beg. Inv. Dem. Ord. Beg. Inv. Dem. Ord. Beg. Inv. Dem. Ord. Observed Cust. Dem. 1 20 10 50 100 25 150 15 50 50 2 10 10 75 25 135 15 0 50 3 50 10 50 25 125 120 15 125 50 4 40 10 25 25 105 15 0 50 5 30 10 125 25 90 15 0 50 6 20 10 50 100 25 75 15 50 50 7 10 10 75 25 60 15 0 50 8 50 10 50 25 125 45 15 125 50 9 40 10 25 25 30 15 120 120 50 10 30 10 125 25 15 15 0 50 11 20 10 50 100 25 120 15 50 50 12 10 10 75 25 105 15 0 50 13 50 10 50 25 125 90 15 125 50 14 40 10 25 25 75 15 0 50 15 30 10 125 25 60 15 0 50 16 20 10 50 100 25 45 15 50 50 17 10 10 75 25 30 15 120 120 50 18 50 10 50 25 125 15 15 125 50 19 40 10 25 25 120 15 0 50 20 30 10 125 25 105 15 0 50 Retailer 1 Retailer 2 Retailer 3 Demands to Wholesaler
  64. 64. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains (Constant customer demands = 10+25+15=50 units/day)(Constant customer demands = 10+25+15=50 units/day) Day Beg. Inv. Dem. Ord. Beg. Inv. Dem. Ord. Beg. Inv. Dem. Ord. Observed Cust. Dem. 1 20 10 50 100 25 150 15 50 50 2 10 10 75 25 135 15 0 50 3 50 10 50 25 125 120 15 125 50 4 40 10 25 25 105 15 0 50 5 30 10 125 25 90 15 0 50 6 20 10 50 100 25 75 15 50 50 7 10 10 75 25 60 15 0 50 8 50 10 50 25 125 45 15 125 50 9 40 10 25 25 30 15 120 120 50 10 30 10 125 25 15 15 0 50 11 20 10 50 100 25 120 15 50 50 12 10 10 75 25 105 15 0 50 13 50 10 50 25 125 90 15 125 50 14 40 10 25 25 75 15 0 50 15 30 10 125 25 60 15 0 50 16 20 10 50 100 25 45 15 50 50 17 10 10 75 25 30 15 120 120 50 18 50 10 50 25 125 15 15 125 50 19 40 10 25 25 120 15 0 50 20 30 10 125 25 105 15 0 50 Retailer 1 Retailer 2 Retailer 3 Demands to Wholesaler
  65. 65. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains (Constant demands)(Constant demands) R e t a ile r 1 De m a n d 0 5 10 15 20 25 30 0 5 10 15 20 25 30 35 40 45 50 R e t a i l e r 2 D e m a n d 0 5 10 15 20 25 30 0 5 10 15 20 25 30 35 40 45 50Re t a i l e r 3 De ma nd 0 5 10 15 20 25 30 0 5 10 15 20 25 30 35 40 45 50 Demands Observed by Wholesaler 0 50 100 150 200 250 300 0 5 10 15 20 25 30 35 40 45 50
  66. 66. Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains (Random demands)(Random demands) R e t a i l e r 1 D e m a n d 0 10 20 30 40 50 60 70 80 90 100 0 5 10 15 20 25 30 35 40 45 50 R e t a i l e r 2 D e m a n d 0 10 20 30 40 50 60 70 80 90 100 0 5 10 15 20 25 30 35 40 45 50 R e t a i l e r 3 D e m a n d 0 10 20 30 40 50 60 70 80 90 100 0 5 10 15 20 25 30 35 4 0 45 50 Demands Observed by Wholesaler 0 50 100 150 200 250 300 0 5 10 15 20 25 30 35 40 45 50
  67. 67. ObservationObservation…… Different chain phases have different calculations of demand quantity, thus the longer the chain between the customer and manufacturer the bigger the demand variation. – Increases the level of inventory – Prolongs the lead time – Demands more efficient transportation – Increases labor costs – Decreases the level of product availability – Leads to distrust among participants.
  68. 68. Bullwhip EffectBullwhip Effect In 2001, Cisco was forced to write down $2.2 billion worth of obsolete inventory, due to uncertain variations in its demand in its supply chain.
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