VALUE OF INFORMATIONVALUE OF INFORMATION-BULLWHIP EFFECT--BULLWHIP EFFECT-

Value of InformationValue of Information

“In modern supply chains, information replaces inventory” (True or False Why?)

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.

The Bullwhip EffectThe Bullwhip Effect and its Impact on the Supply Chain and its Impact on the Supply Chain

Consider the order pattern of a color television model sold by a large electronics manufacturer to one of its accounts, a national retailer.

Fig 1. Order Stream

Fig 2. Point-of-sales Data-Original

Figure 3. POS Data After Removing

Promotions

The Bullwhip EffectThe Bullwhip Effect and its Impact on the Supply Chain and its Impact on the Supply Chain

Figure 4. POS Data After Removing Promotion & Trend

The Bullwhip EffectThe Bullwhip Effectand its Impact on the Supply Chainand its Impact on the Supply Chain

Higher Variability in Orders Placed by Higher Variability in Orders Placed by Computer Retailer to Manufacturer Than Computer Retailer to Manufacturer Than Actual SalesActual Sales

Increasing Variability of Orders Up the Supply ChainIncreasing Variability of Orders Up the Supply Chain

We Conclude ….We Conclude ….

Order variability is amplified up the supply chain; upstream echelons face higher variability.

Consequences….Consequences….

Increased safety stock Reduced service level Inefficient allocation of resources Increased transportation costs Excess inventories Problems with quality Increased raw material costs Overtime expenses Lengthened leadtime Lost sales

Cause of BW:Cause of BW:1.Demand Forecasting1.Demand Forecasting

One day, the manager of a retailer observed a larger demand (sales) than expected.

He increased the inventory level because he expected more demand in the future (forecasting).

The manager of his wholesaler observed more demand

(some of which are not actual demand) than usual and increased his inventory.

This caused more (non-real) demand to his maker; the manager of the maker increased his inventory, and so on. This is the basic reason of the bull whip effect.

Cause of BW:Cause of BW:２．２． Lead timeLead time

With longer lead times, a small change in

the estimate of demand variability implies

a significant change in safety stock,

reorder level, and thus in order quantities.

Thus a longer lead time leads to an

increase in variability and the bull whip

effect.

Cause of BW:Cause of BW:３．３． Order BatchingOrder Batching

When using a min-max inventory policy, then the wholesaler will observe a large order, followed by several periods of no orders, followed by another large order, and so on.

The wholesaler sees a distorted and highly variable pattern of orders.

Thus, batch ordering increases the bull whip effect.

Takes care of promotional aspects also.

Cause of BW:Cause of BW:Variability of Price/Forward BuyingVariability of Price/Forward Buying

Retailers (or wholesalers or makers) offer promotions and discounts at certain times or for certain quantities.

Retailers (or customers) often attempt to stock up when prices are lower.

It increases the variability of demands and the bull whip effect.

Cause of BW:Cause of BW: ５． ５． Rationing & Shortage GamingRationing & Shortage Gaming

When retailers suspect that a product will be in short supply, and therefore anticipate receiving supply proportional to the amount ordered (supply allocation).

When the period of shortage is over, the retailer goes back to its standard orders, leading to all kinds of distortions and variations

Supply Chain in EquilibriumSupply Chain in Equilibrium

Customer demand forecast = 10 units

Suppliers Producers Distributors Retailers

Products & Services

Products & Services

Products & Services

Information

Cash

Key: = Inventory Levels

10 Units 10 Units 10 Units

10 Units 10 Units 10 Units

Retailers are selling product at a constant rate and price. Firms along the supply chain are able to set their inventory to meet demand.

Supply Chain DisruptedSupply Chain Disrupted

Customer Demand forecast = 20 units

SuppliersProducers

Distributors

Retailers

Products & Services

Products & Services

Products & Services

Information Flow

Cash Flow

Key: =Inventory Levels

160 Units 80 Units 40 Units

80 Units 40 Units 20 Units

As demand increases, the distributor decides to accommodate the forecasted demand and increase inventory to buffer against unforeseen problems in demand. Each step along the supply chain increases their inventory (double in this example) to accommodate demand fluctuations. The top of the supply chain receives the harshest impact of the whip effect.

Consider a simple supply chain…Consider a simple supply chain…

Single retailer, single manufacturer. Retailer observes customer demand, Dt. Retailer orders qt from manufacturer.

Retailer ManufacturerDt

qt

L

Quantifying the Bullwhip EffectQuantifying the Bullwhip Effect

Suppose a P period moving average is used.

If the variance of the customer demand seen by the retailer i

s Var(D), then the variance of the orders placed by that retail

er to the manufacturer, Var(Q), relative to the variance of cu

stomer demand satisfies:

2

2221

)(

)(

P

L

P

L

DVar

qVar

Var(q)/Var(D): For Various Lead TimesVar(q)/Var(D): For Various Lead Times

L=5

L=3

L=1

0

2

4

6

8

10

12

14

0 5 10 15 20 25 30

L=5

L=3

L=1

P

A lower bound on the increase in variability given as a function of p

Figure shows the lower bound on the increase in variability as a function of p for various values of the lead time,L. When p is large, and L is small, the bullwhip effect due to forecasting error is negligible.

The bullwhip effect is magnified as we increase the lead time and decrease p.

Assume p=5, L=1

The variance of the orders placed by the retailer to the manufacturer will be at least 40 percent larger than the variance of the customer demand.

2

2

( ) 2 21 1.4

( )

Var q L L

Var D P P

Multi stage SC systemsMulti stage SC systems

External Demand

Order lead time Delivery lead time

Order lead time Delivery lead time

Order lead time Delivery lead time Production lead time

Retailer

Wholesaler

Distributor

Factory

Multi-Stage Supply ChainsMulti-Stage 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

Manufacturer Stage 2

Supplier Stage 3

qo=D q1q2

L1 L2

SC with centralized Demand Information Centralized: each stage bases orders on retailer’s forecast

demand.

The retailer observes customer demand, forecasts the mean demand using a moving average with p demand observations, finds his target inventory level based on the forecast mean demand, and places an order to the wholesaler.

The wholesaler receives order along with the retailer’s forecast mean demand, uses this forecast to determine his target inventory level, and place an order to the distributor.

Similarly, the distributor

places order to the factory.

SC with centralized Demand Information (cont’)

In this centralized SC, each stage of the SC receives the retailer’s forecast mean demand and follows and order-up-to inventory policy based on this mean demand.

2

2

11

221

)(

)(

P

L

P

L

DVar

qVar

k

ii

k

iik

The variance of the orders placed by the kth stage of the SC, Var(Qk), relative to the variance of the customer demand, Var(D), is just:

SC with centralized Demand Information (cont’)

For example, if the lead time from the retailer to the wholesaler is two periods, then L1=2. Similarly, if the lead time from the wholesaler to the distributor is two periods, then L2=2, and if the lead time from the distributor to the factory is also two periods, then L3=2.

The total lead time from the retailer to the factory is L1+L2+L3=6

This expression for the variance of the orders placed by the kth stage is very similar to the expression in the previous section, with the single stage lead time.

Decentralized Demand informationDecentralized Demand information

Decentralized: each stage bases orders on previous stage’s demand. The retailer does not make its forecast mean demand available to the remainder of

the SC. Instead, the wholesaler must estimate the mean demand based on the orders received from the retailer.

The variance of the orders placed by the kth stage of the SC, Var(Qk),relative to the variance of the customer demand, Var(D) satisfies:

k

i

iik

P

L

P

L

DVar

qVar

12

2221

)(

)(

The variance increases multiplicatively at each stage of the SC.

Multi-Stage Multi-Stage Systems:Var(qSystems:Var(qkk)/Var(D))/Var(D)

0

5

10

15

20

25

30

0 5 10 15 20 25

Dec, k=5

Cen, k=5

Dec, k=3

Cen, k=3

k=1

Increase in variability for centralized and decentralized system

Effect of Information SharingEffect of Information Sharing It is now clear that by sharing demand information with

each stage of the SC, we can significantly reduce the

bullwhip effect.

When demand information is centralized, each stage of

the SC can use the actual customer demand data to

estimate the average demand.

When demand information is not shared, each stage

must use the orders placed by the previous stage to

estimate the average demand. These orders are more

variable than the actual customer demand data, thus, the

forecasts created using these orders are more variable,

leading to more variable orders.

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.

Centralized demand information can

significantly reduce the bullwhip effect, but will

not eliminate it.

Coping with the BW EffectCoping with the BW Effect１．１． Demand uncertaintyDemand uncertainty

Adjust the forecasting parameters, e.g., larger p for the

moving average method.

Centralizing demand information; by providing each

stage of the supply chain with complete

information on actual customer demand (POS: Point-

Of-Sales data ）

Continuous replenishment

VMI （ Vender Managed Inventory: VMI ）

Coping with the BW EffectCoping with the BW Effect２．２． Lead time Lead time

Lead time reduction

Information lead time can be reduced using EDI

（ Electric Data Interchange ） or

CAO （ Computer Assisted Ordering ）

Cross docking

Coping with the BWCoping with the BW３．３． Order BatchingOrder Batching

Reduction of fixed ordering cost using EDI and

CAO

3PL （ Third Party Logistics ）

VMI

Shipping in LTL sizes by combining shipments

The supplier—usually the manufacturer but sometimes a

reseller or distributor—makes the main inventory

replenishment decisions for the consuming organization. The supplier monitors the buyer’s inventory levels (physically

or via electronic messaging) and makes periodic resupply deci

sions regarding order quantities, shipping, and timing.

Transactions customarily initiated by the buyer (like purchase

orders) are initiated by the supplier instead.

The purchase order acknowledgment from the supplier may b

e the first indication that a transaction is taking place; an adva

nce shipping notice informs the buyer of materials in transit.

The VMI PartnershipThe VMI Partnership

The manufacturer is responsible for both its own inventory and the inventory stored at is customers’ distribution centers.

Coping with the BW EffectCoping with the BW Effect４． ４． Variability of PriceVariability of Price

Stabilize pricing Eliminate promotions & variation in prices Limit quantity purchased during a promotion

Coping with the BW EffectCoping with the BW Effect５． ５． Rationing & Shortage GamingRationing & Shortage Gaming

Allocate the lacking demand due to sales volume

and/or market share instead of order volume.

（ General Motors ， Saturn, Hewlett-Packard ）

Share the inventory and production information

of makers with retailers and wholesalers.

（ Hewlett-Packard ， Motorola ）

Reducing BW effect in your firmReducing BW effect in your firm

Are prices in your supply chain stable? Is information between firms along the

supply chain accurate and timely? Is sales being forecasted on projected data? Are you forecasting sales using data from

EDI or Point of Sale computer systems. Are incentives for sales representatives along

the supply chain at minimum? Are orders being placed in small increments? Are batch orders reduced to minimum levels?

Reducing BW effect in your firmReducing BW effect in your firm

If you answered no to any of the previous questions regarding your firm and the bullwhip effect, then you may have an opportunity to reduce costs to your individual firm.

Information for Effective ForecastsInformation 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.

Information for Coordination of Information for Coordination of SystemsSystems

Information is required to move from local to global optimization

Questions: Who will optimize? How will savings be split?

Information is needed : Production status and costs Transportation availability and costs Inventory information Capacity information Demand information

Locating Desired ProductsLocating 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 ReductionLead-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 ConflictsInformation 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

THANK YOUTHANK YOU