Speculation, Postponement and Bullwhip Effect

Outbound Logistics Flows

• The lead times are shorter in outbound than inbound logistics

• Companies having short lead times in outbound logistics tend to have short lead times in inbound logistics and vice-versa

• Companies that have a high level of outbound inventory turnover tend to have a high level of inbound inventory turnover and vice-versa

• There is a higher inventory turnover in outbound logistics than in inbound logistics

• There is thus an association between the inventory trends in outbound and outbound logistics flows overall inventories are higher in inbound logistics than in outbound logistics

Implications

• There is a potential Bull Whip Effect between inbound and outbound logistics flows.

• This has a managerial implication that managers have to consider upstream activities in the supply chain when they are striving to improve their performance in the interface towards their present and potential customers and vice-versa.

• It is also reasoned that the Bullwhip Effect between inbound and outbound logistics is because principle of postponement in outbound and principle speculation in inbound.

Principles of Postponement

• Postponement of companies’ business operations reduces the risk by moving the differentiation nearer to the time of exchange.

• It provides a point of departure for a critical examination to enhance the performance of companies’ business operations.

Postponement and Value Chain

• Porter’s concept of value chain indicates that there is an adding of value in a company’s successive business activities.

• Therefore, the finished goods have generated costs that represent a higher value.

• The financial costs of inventories is higher in outbound logistics.

• It forces companies to be more restricted in maintaining these inventories.

Principles of Speculation

• The principle of speculation facilitates a counter view in relation to the principle of postponement.

• The Bullwhip effect therefore, exists because of the gap between speculation and postponement of business activities.

• In a managerial context, Bullwhip effect is eliminated if there is no gap between the degree of speculation and postponement of business activities.

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The See-Saw Model of Bullwhip Effect

• In this model, the gap between the degree of speculation and postponement of business activities is assumed to influence the Bullwhip Effect.

• If there is a high degree of speculation (i.e. a low degree of postponement) in inbound logistics and a high degree of postponement (i.e. a low degree of speculation) in outbound logistics, then the Bullwhip Effect is high (i.e. an upstream unbalanced see-saw scenario)

• If there is low degree of speculation (i.e. a high degree of postponement) in inbound logistics and a low degree of postponement (i.e. a high degree of speculation) in outbound logistics, then the Bullwhip Effect might be interpreted as high (i.e. downstream unbalanced see-saw scenario)

Multiple Facets of the Bullwhip Effect Construct

1.Dynamics model of the bullwhip effect construct

2.Rubber-band principle3.A typology of stocking level variability4.Different levels of analysis of the Bullwhip

Effect.5.Size of the company6.Redefinition of the Bullwhip Effect

Construct

Dynamics Model of the Bullwhip Effect Construct

• Bullwhip Effect is caused by a sequence of happenings in and between value change and value systems.

• It may be estimated by measuring the construct in one or several occasions.

• Therefore, Bullwhip Effect can be dynamic (i.e. continuous - several occasions) or static (i.e. discontinuous – one occasion)

Parameters that influence the dynamics of Bullwhip Effect

1. Time2. Context • As time moves on, the context evolves and therefore,

stocking level variability increases. • These two parameters in conjunction create a generic

conceptual model and contribute to describe the dynamics of the Bullwhip Effect construct.

• When Bullwhip Effect between stocking levels is explored on one occasion, the research reflects on the spot account construct (static).

• When it is explored on several occasions, the research reflects a periodic construct (dynamic).

Rubber-band Principle

• Stocking level variability is affected by up-downstream or down-upstream business operation between value change.

• This should be explored based upon the outcome of a set of interactive and iterative processes.

• The dynamics of stock level variability can be illustrated by rubber-band principle.

• Rubber has two components:-1. Rubber: refers to elasticity, flexibility and changeability

of business operations.2. Band: refers to that stocking level variability is derived

from the lack of synchronization in sequential and continuous processes of business operations

Comparison with congested traffic

• There is desynchronized reaction pattern among drivers in queues of vehicles (demand cycles in upstream or downstream value systems affect the stock level.

• Lack of synchronization is reflected in spasmodic movements (some inventories are kept in stock , others are delivered to another stock level.

• Some vehicles move fast or slow than others (some stock levels are more or less inventories in stock and are kept longer or shorter periods of time).

• Lack of synchronization disappears when the drivers leave the traffic (stocking level variability continues until inventories reach point of consumption.

Rubber-band comparison

• Movement of vehicles and movement of inventories resemble the characteristics of the rubber-band as it is tensioned and slackened.

• Repeated pulling of rubber-band at one end and having a small weight at the other end illustrates congestion Vs. decongestion and also dilemma of stocking level variability (Bullwhip Effect).

Pulling of Rubber-band

• As the rubber-band is pulled, it will be tensioned, thinner in the middle, both ends relatively thicker.

• When inventories are demanded downstream, stocking level variability occurs as real time transfer of demand cycles between levels does not usually take place in the system.

Slackening of the Rubber-band

• When the rubber-band is slackened, the middle becomes thicker, the ends will become relatively thinner.

• It means that as the demand in the marketplace changes, it effects the stocking level variability in value systems.

• The width of the rubber band illustrates the stock level variability; thinner band represents decreased variability and a thicker band represents increased variability.

• By repeated repulling the rubber impact of the seasonality of demand cycles may be used to illustrate stock level variability.

Rubber-band and dynamics of Bullwhip Effect

• Bullwhip Effect has neither a beginning nor an end in value system. It is dependent upon the continuous dynamics in the marketplace (i.e. seasonality of demand cycles)

• It also reflects consequences of continuous spasmodic stock level variability.

• Therefore, the construct is both dynamic and continuous.• Bullwhip Effect is usually seen as a unidirectional construct that is

down-upstream variability approach.• If we push the rubber-band from an upstream location, it will

slacken, bend and jam (i.e. causing the build-up of inventories further downstream)

• The rubber-band has to be pulled as well as inventories should be pulled based upon market place demand cycle.

Typology of Stocking Level Variability

• Bullwhip Effect is explored in terms of increased upstream variability as well as increased downstream variability.

• Equilibrium between the degree of speculation and postponement in different stock levels smoothens both Bullwhip Effect and Reversed Bullwhip Effect.

• A typology of stock level variability consists of two stock levels:-

1. Upstream unit of analysis2. Downstream unit of analysis

Each unit of analysis (stock level) is divided into principles of speculation and postponement.

This creates four stock level variability situation each with its own unique characteristics that separate them from each other.

4 Cells of TypologyCell: Top right hand cornerPrinciple of speculation dominates in inbound

logistics, (inventories are higher) than in the outbound logistics (inventories are lower). This is the traditional approach of the Bullwhip Effect.

Bullwhip Effect occurs when degree of speculation in inbound flows is stronger in relation to postponement in outbound flows.

Cell: Bottom left hand cornerPrinciple of speculation dominates in outbound

logistics (inventories are higher) than in the inbound logistics (inventories are lower).

This is Reversed Bullwhip Effect and occurs when degree of speculation in inbound flows is weaker than postponement in outbound flows.

Reversed Bullwhip Effect

It occurs when there are:-• Uncertainties upstream in the supply (limited

production capacity, product quality deficiencies, unreliable deliveries, unreliable transport, inaccurate information sharing)

1. Reverse Bullwhip effect scenario occurs when the degree of speculation in the inbound logistics in relation to the degree of postponement in the outbound flows is weaker.

Cells: Top left and bottom right corners

No Bullwhip Effect signifies that there is a balance between inventory management of business activities in inbound and outbound logistics.

That means the principle of speculation (or postponement) dominates equally in a company’s inventory management of business activities in inbound and outbound logistics.

Network Model

• The network model consists of three components.

1. Actors:- this can be a company, a group of companies, an individual or a group of individuals. Actors consume resources when activities are performed.

2. Activities:- these are business functions performed in the business environment.

3. Resources:- these are tangible and intangible assets for actors to perform business activities.

Dependencies

There are three generic categories of dependencies between buyers and sellers for the typology of Bullwhip Effect

1. Time dependence• Time compression, order response• Agility and ability to change direction2. Functional dependence:-businesses are specialized

and complement each other3. Relationship dependence:-business activities are

dependent upon the interaction process between companies in marketing channels.

These dependencies create a dynamic business environment.

Bullwhip Effect Dynamic Model

• The network and the typology can be incorporated in a dynamic business environment to create a dynamic model.

• The model considers generic dependencies between the business activities, the type of logic flows and the components of the network so that a change in one of the components has an impact on others and vice-versa.

Implications of Dependencies

• The model also suggests that impact of generic dependencies on actors’ activities and resources is stronger in inbound logistics than outbound logistics as there is high level of dependencies between them.

• The impact of generic dependencies on actors, activities and resources is weaker in the inbound logistics flows than in the outbound logistics as there is low levels of dependencies between them.

The impact of generic dependencies on actors, activities and resources is equal in the inbound and outbound logistics on account of levels of dependencies between them.

Different levels of analysis of the Bullwhip Effect

Bullwhip effect applies to four levels:-1. Within a value chain2. Between value chains3. Within a value system4. Between value systemsThe pair perspectives of stocking level variability are 1.Inbound vs outbound2.Internal vs. external3.Direct vs indirect4.Upstream vs downstream 5.Intra vs inter

• Level 1, 2 , 3 have a channel orientation of stock level variability. This is intra-channel perspective.

• Level 4 has a market orientation which is an inter-channel perspective.

Size of the company, inbound and outbound inventories

Larger companies in inbound logistics flows as compared to small companies

• Higher inventory turnover,• more upward lead time trends• More upward inventory level trends Larger companies in outbound logistics flows as

compared to small companies• Higher inventory turnover• Shorter lead time• More upward lead time trends• More upward inventory level trends

Bullwhip Effect redefined

1. The Bullwhip Effect construct can be now defined as:- the relative variability between stocking levels in and between value change and value systems.

2. Specifically it is defined as:-the relative variability between stocking levels caused by the degrees of postponement and speculation. The relativity between stocking level variability refers to either internal or external, inbound or outbound, direct or indirect, upstream or downstream, and intra- or inter-channel.

The proposed redefinition does not state that variability has to be upstream, it can also be downstream.

Mitigation of Bullwhip Effect

1. Reduction of lead time2. Revision of reordering procedures3. Limitation of price fluctuations4. Integration of planning and performance measurement5. Shared knowledge with suppliers and customers to

better gauge demand6. Cooperation with supply chain partners to determine

what information is causing an overreaction7. Use of internet –enabled technology and the

application of the web to speed communications and improve response time

How to cope with Bullwhip Effect

1. Reduce uncertainty: Provide complete information on actual demand. POS

2. Strategic partnership: VMI, alliances

3. Reduce variability: EDLP, elimination of price promotions, stable prices.

How to reduce and control variability?

1. Avoid multiple demand forecast updates

2. Break order batches

3. Stabilize prices

4. Eliminate gaming in shortage situations

5. Control Lead time

Avoid multiple demand forecast updates

• Order on ultimate customer demand: and not on the ordering behaviour of immediate downstream partner, as ordering behaviour shows amplification to account for order batches and overreactions. Use POS, EDI, VMI, Supply chain responsibility through strategic partnership

• Centralized procurement: plan central purchase to avoid uncertainties of multiple forecasts.

• Direct sales to customers, avoiding intermediate channels

Break Order Batches

• Control on Batch ordering: Batches carry no relationship with needs. A distorted picture of patterns of orders emerges to the factory.

• Reduced batch: brings down lead time and hence safety stock

Advantages of full truck loads are achieved through assorted loads

Stabilize Prices

1. Control on Price fluctuations: Promotional discounts and price variations lead to influencing demand but not the actual needs

2. Stabilize prices: EDLP,

3. Reduce variability: of volumes, of prices

4. Penalties on returns: Often the channels return the products if these are not sold. Introduce strictness, penalties

Eliminate gaming in shortage conditions

Gaming means customers order additional, non-required amounts, since they expect to receive only a portion of outstanding orders from factory due to shortage situation

• Control on Inflated orders: Shortages tend to magnify the bull whip effect and results become obvious when period of shortages is over

• Penalties on cancellations: Strict conditions on cancellation of orders

• Control process time: Eliminate or reduce delays which lead to shortages

• Centralized Information : One of the most important factors to control bullwhip effect.

Lead time control

• Lead time includes:Time to processTime to ship or transportInformation lead time To calculate safety stocks, we in fact multiply estimates of average demand and standard deviation of demand by lead time.

•Longer the lead time, more significant is the change in safety stock and reorder level.•Longer lead time increases variability.•Use EDI for information systems

McCullen and Towill approach

Four material flow principles to reduce bullwhip effect

1. Control system

2. Time compression

3. Information transparency

4. Echelon elimination

Kelle and Mine Approach

Bullwhip effect is reduced through controls of:• Purchase order of individual retailers• Aggregate orders of the retailers• Suppliers ordering and producing policy Demand correlation can reduce the variability of

aggregate ordersAutocorrelation in buyers orders can smooth the

suppliers ordering policySmall frequent orders decreases both

variability and uncertainty

Yu et al Approach

• Partnership reduces inventory as well as costs

• Reduces bullwhip associated wit decentralized controls

• Collaboration can control forecast fluctuations