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Supply Chain Dynamics, Value of Supply 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: [email protected], [email protected]
http://web.iitd.ac.in/~ravi1
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
Case 1: P&GCase 1: P&G--Dynamics of the Supply Chain Dynamics of the Supply Chain O
rder
Siz
e
Time
Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998
CustomerDemand
CustomerDemand
Retailer OrdersDistributor Orders
Production Plan
Case 1: P&G: What Management Gets... Case 1: P&G: What Management Gets... O
rder
Siz
e
Time
Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998
CustomerDemand
CustomerDemand
Production PlanProduction Plan
Case 1 P&G: What Management WantsCase 1 P&G: What Management Wants……
Vo
lum
es
Time
Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998
Production PlanCustomerDemand
CustomerDemand
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
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
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
Growth of demand variabilityGrowth of demand variability
Bullwhip Effect -- Retailer Demand
0
50
100
150
200
250
300
0 25 50 75 100
Time
De
ma
nd
Bullwhip Effect -- Distributor Demand
0
50
100
150
200
250
300
0 25 50 75 100
Time
De
ma
nd
� Retailer demand
Distributor demand �
Growth of demand variabilityGrowth of demand variability
Bullwhip Effect -- Distributor Demand
0
50
100
150
200
250
300
0 25 50 75 100
Time
De
ma
nd
Bullwhip Effect -- Manufacturer Demand
0
50
100
150
200
250
300
0 25 50 75 100
Time
De
ma
nd
� Distributor demand
Manufacturer demand �
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
•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 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.
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.
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.
Reorder Point with Variable DemandReorder Point with Variable Demand
stocksafety
yprobabilit level service toingcorrespond deviations standard ofnumber
demanddaily ofdeviation standard the
timelead
demanddaily average
pointreorder
where
=
=
=
=
=
=
+=
LZ
Z
L
d
R
LZLdR
d
d
d
σ
σ
σ
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
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
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
95
95
95
95
1
2
3
4
5
Week
At the end of week#1At the end of 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
Let us represent WeekLet us represent Week--beginning and Weekbeginning and Week--
ending inventory as followsending inventory as follows
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100 (start)
100 (end)
100
95
1
2
3
4
5
Week
Watch now, Watch now, very-very carefully, how Bullwhip , how Bullwhip
effect setseffect sets--inin
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100 (start)
100 (end)
100
?? 100 95
95
1
2
3
4
5
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100 (start)
100 (end)
100
90 100 95
95
1
2
3
4
5
Week
Watch now, veryWatch now, very--very carefully, how very carefully, how
Bullwhip effect setsBullwhip effect sets--inin
Watch how Bullwhip effect is entering at
Retailer level
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
??
95
95
1
2
3
4
5
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
(90+5)
95
95
1
2
3
4
5
(5)(90)
Week
Watch how Bullwhip effect is entering at Watch how Bullwhip effect is entering at
Retailer levelRetailer level
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
(90+5)
95
?? 95
95
95
1
2
3
4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
(90+5)
95
95 95
95
95
1
2
3
4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
(90+5)
95
95 95
95
95
95
1
2
3
4
5
(95)
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
95
95 95
95
95
?? 95
95
95
1
2
3
4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
95
95 95
95
95
95 95
95
95
1
2
3
4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
95
95 95
95
95
95 95
95
95
95
1
2
3
4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
95
95 95
95
95
95 95
95
95
95
95
1
2
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4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
95
95 95
95
95
95 95
95
95
? 95
95
95
1
2
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4
5
Week
Watch how Bullwhip effect sets in
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100 100 100
100
100
90 100
95
95
95 95
95
95
95 95
95
95
95 95
95
95
95
1
2
3
4
5
Week
Note how Bullwhip effect has found footNote how Bullwhip effect has found foot--hold at the hold at the
Retailer levelRetailer level
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100
100 100
100
100
90 100
95
95
95 95
95
95
95 95
95
95
95 95
95
95
95
1
2
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5
Week
Watch how Bullwhip effect is entering into Distributor Watch how Bullwhip effect is entering into Distributor
levellevel
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100
100
100 100
100
100
?? 100 90 100
95
95
95
1
2
3
4
5
Week
Watch how Bullwhip effect is entering into
Distributor level
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100 100 100
100
100 100
100
100
80 100 90 100
95
95
95
1
2
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4
5
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
95
1
2
3
4
5
(10)(80)
Watch how Bullwhip effect is entering into Watch how Bullwhip effect is entering into
Distributor levelDistributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
?? 90
95 95
95
95
95
1
2
3
4
5
Watch how Bullwhip effect is entering into Watch how Bullwhip effect is entering into
Distributor levelDistributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
?? 90
95 95
95
95
95
1
2
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5
Watch how Bullwhip effect is entering into Watch how Bullwhip effect is entering into
Distributor levelDistributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95 95
95
95
95
1
2
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4
5
Watch how Bullwhip effect has found a footWatch how Bullwhip effect has found a foot--
hold at Distributor levelhold at Distributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
95
95
95
1
2
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4
5
955
Watch how Bullwhip effect is expanding its Watch how Bullwhip effect is expanding its
wings at Distributor levelwings at Distributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
95
95
95
1
2
3
4
5
Watch how Bullwhip effect is expanding its Watch how Bullwhip effect is expanding its
wings at Distributor levelwings at Distributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
95
95
?? 95
95 95
95
95
95
1
2
3
4
5
Watch how Bullwhip effect is expanding its Watch how Bullwhip effect is expanding its
wings at Distributor levelwings at Distributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
95
95
95 95
95 95
95
95
95
1
2
3
4
5
Watch how Bullwhip effect is expanding its Watch how Bullwhip effect is expanding its
wings at Distributor levelwings at Distributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
95
95
95 95
95
95 95
95
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95 95
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95 95
95
95
95
1
2
3
4
5
Watch how Bullwhip effect is expanding its Watch how Bullwhip effect is expanding its
wings at Distributor levelwings at Distributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
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95 95
95
95 95
95
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95 95
95
95 95
95
95
95
1
2
3
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5
Watch how Bullwhip effect has settled badly at Watch how Bullwhip effect has settled badly at
Distributor levelDistributor level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order Stock 100 100
100
100 100
100
100
80 100
90
90 100
95
95
100 90
95
95 95
95
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95 95
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95 95
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95 95
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95 95
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95
1
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5
Similarly try at Manufacturer level pleaseSimilarly try at Manufacturer level please
Week
Manufacturer Distributor Retailer Demand
Prod Stock Prod Stock Prod Stock 100 100
100
100 100
100
100 100
100
100
95
1
2
3
4
5
Similarly try at Manufacturer level pleaseSimilarly try at Manufacturer level please
Week
Manufacturer Distributor Retailer Demand
Prod Stock Prod Stock Prod Stock 100 100
100
100 100
100
100 100
100
100
?? 100
80 100
90
90 100
95
95
95
1
2
3
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5
Watch how Bullwhip effect is entering into Watch how Bullwhip effect is entering into
Manufacturer levelManufacturer level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Prod Stock Prod Stock 100 100
100
100 100
100
100 100
100
100
60 100
80 100
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90 100
95
95
95
1
2
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Watch how Bullwhip effect has entered into Watch how Bullwhip effect has entered into
Manufacturer levelManufacturer level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Prod Stock Prod Stock 100 100
100
100 100
100
100 100
100
100
60 100
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80 100
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90 100
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95
?? 80
100 90
95
95 95
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95
95
1
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5
Watch how Bullwhip effect is expanding its Watch how Bullwhip effect is expanding its
wings at Manufacturer levelwings at Manufacturer level
Week
Manufacturer Distributor Retailer Demand
Prod Stock Prod Stock Prod Stock 100 100
100
100 100
100
100 100
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60 100
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80 100
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90 100
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120 80
100 90
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95 95
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95
1
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5
Watch how Bullwhip effect has expanded its Watch how Bullwhip effect has expanded its
wings at Manufacturer levelwings at Manufacturer level
Week
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
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90 100
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120 80
100
100 90
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95 95
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?? 100
95 95
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95 95
95
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95
1
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Watch how Bullwhip effect is aggravatingWatch how Bullwhip effect is aggravating
Week
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
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90 100
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95
120 80
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100 90
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90 100
95 95
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95 95
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95
1
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Watch how Bullwhip effect is aggravatingWatch how Bullwhip effect is aggravating
Week
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
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90 100
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95 95
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95 95
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?? 95
95 95
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95 95
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95
1
2
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Watch how Bullwhip effect is aggravatingWatch how Bullwhip effect is aggravating
Week
Manufacturer Distributor Retailer Demand
Prod Stock Order Stock Order 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
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90 100
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95 95
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95 95
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95 95
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95
1
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Watch how Bullwhip effect has aggravatedWatch how Bullwhip effect has aggravated
Week
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
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
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90 100
95
95
120 80
100
100 90
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95 95
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90 100
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95 95
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95 95
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1
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Watch how Bullwhip effect has aggravatedWatch how Bullwhip effect has aggravated
Week
•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 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.
Measuring the Bullwhip EffectMeasuring the Bullwhip EffectBetween 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
2221
)(
)(
p
L
p
L
DVar
QVar++≥
2
2
5
)1(2
5
)1(21
)(
)(++≥
DVar
QVar
…if the retailer estimates the mean demand based on a five periodmoving 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 ofperiods included in the moving average forecast and the ratio between consumer demand and retail orders.
=
Measuring the Bullwhip EffectMeasuring the Bullwhip EffectBetween Retailer and ManufacturerBetween Retailer and Manufacturer
Lower Bound of Increase VariabilityLower Bound of Increase Variability
0
2
4
6
8
10
12
3 5 10 15 20 25 30p (number of periods in moving average)
Var (Q)/Var (D)
L = 5 L = 3 L = 1
2
2221
)(
)(
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.
ConsequencesConsequences……..
� Increased safety stock
� Reduced service level
� Inefficient allocation of resources
� Increased transportation costs
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.
RetailerStage 1
ManufacturerStage 2
SupplierStage 3
qo=D q1q2
L1 L2
∏
∑∑
−
=
==
++≥
++≥
1
12
2
2
2
11
221
)(
)(
)(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 Chains Stage Supply Chains
(Formula)(Formula)
MultiMulti--Stage Systems: Var(qStage Systems: Var(qkk)/Var(D))/Var(D)
05
1015202530
0 10 20 30
Dec, k=5
Cen, k=5
Dec, k=3
Cen, k=3
k=1
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.
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. LTL)
– MRP systems (updated monthly or periodically)
– Push ordering (e.g., to meet a quarterly sales quota) drive order batching
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
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 periods)
� Problems include
– Overtime and idle production time
– Premium freight charges
– Inventory accumulations
•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 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
Impact of Impact 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 andproducts are returned.
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?
•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 lead-times
� …establish strategic partnerships
� Information sharing
� Channel alignment
� Operational efficiencies.
Avoid multiple demand forecast Avoid 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
Reducing Demand UncertaintyReducing Demand UncertaintyCentralized 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).
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 thatsupports information sharing over the internet.
Reducing Demand VariabilityReducing Demand Variability
In addition to sharing information through EDI and XML technologies, companies are closing the supply chain gap throughinitiatives 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.
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.
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
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 salesnot on current orders
� Share information about capacity
� Long term contracting to allow vendors to adjust capacity
� Eliminate generous return and order cancellation policies
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.
Supply Chain Coordination InitiativesSupply Chain Coordination Initiatives
FrameworkFrameworkCauses 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)
Coping with the Bullwhip Effect Coping 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
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.
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.
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
You May Try This:You May Try This:
--Use Beer Distribution Game to Demonstrate and Analyze Use Beer Distribution Game to Demonstrate and Analyze
Bullwhip EffectBullwhip Effect
--Use CD given with the Text bookUse CD given with the Text book
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.
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.
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
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
102
Example Supply Chain StagesExample Supply Chain Stages
Supplier Manufacturer One
Distributor
Three
RetailersMany
Customers
Bullwhip Effect in Supply Chains Bullwhip 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
Bullwhip Effect in Supply Chains Bullwhip 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
Bullwhip Effect in Supply Chains Bullwhip 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
Bullwhip Effect in Supply ChainsBullwhip Effect in Supply Chains(Constant demands)(Constant demands)
R e t a i l e r 1 D e 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 50R e t a i l e r 3 D e m a n d
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
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
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0
Demands O bserved by Wholesaler
0
50
100
150
200
250
300
0 5 10 15 20 25 30 35 40 45 50
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.
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.
