Bullwhip Effect – Definition

Cite this article as:"Bullwhip Effect – Definition," in The Business Professor, updated March 5, 2019, last accessed July 14, 2020, https://thebusinessprofessor.com/lesson/bullwhip-effect-definition/.

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Bullwhip Effect (Supply Chain) Definition

Bullwhip effect is a conception in which the orders at the start of the supply chain have a greater impact further down the chain.

The bullwhip effect explanation can be as the occurrence noticed by supply chain involving orders sent to producers and suppliers create greater variations than sales to the end customer. The uneven orders in the supply chain in the lower level of the supply chain grows becoming unique up to the supply chain. The variation has the possibility of smoothness interruption of the supply chain process at every level in the series will exaggerate the fluctuations by over or underestimate the demand of a product.

A Little More on What is the Bullwhip Effect?

Many factors have been said to co-contribute to Bullwhip effect in the supply chain; the following are just a few of such factors:

Supply chain disorganisation where larger or smaller amounts of the product needed are ordered as a result of the pre-supply chain under or overreaction.

Insufficient or absence communication between each supply chain level affects the smooth of the processes. There might be varied product perception by managers in different levels of the supply chain resulting in different quantities ordered.

Batching of orders where clients do not place the order immediately but accumulates them and make weekly or monthly order. The ordering method creates the demand variation; for example, they may create demand inrush at one point and followed a period of no demand.

Price fluctuation, Regular payment patterns can be affected by discount and other cost charges as buyers long for the discount advantages available in short term period, the availability of discount in the short term increases the demand causing uneven production and sales

Demand information, Reliance on the historical demand information in the estimation of current demand for a product is not accurate as fail to consider the overtime price variation.

Example of the bullwhip effect

The products actual demand and that of its materials begin with the customer even though the products demand is affected the supply chain for instance downwards when the actual customer’s demand is eight, and the retailer might order ten from the distributor having extra two units are for stock safety. This followed by a supplier ordering for twenty units from a manufacturer to enable them to take advantage of bulk purchase discount in addition to stock guarantee for timely shipment to retailers. Subsequently, the manufacturer receives the order and makes an order of forty units utilising economies of scale. The entire series of order results in the production of forty units of a product as a result of eight units’ demand

Even though the bullwhip effect is a frequent problem to supply chain management, understanding the contributory factors to bullwhip is very important to managers in devising their mitigating methods.

References for Bullwhip Effect

http://www.businessdictionary.com/definition/bullwhip-effect.html

https://en.wikipedia.org/wiki/Bullwhip_effect

https://www.aalhysterforklifts.com.au/index.php/about/blog-post/what_is_the_bullwhip_effect_understanding_the_concept_definition

Academic Research on Bullwhip Effect

  • Information distortion in a supply chain: The bullwhip effect, Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Management Science, 43(4), 546-558. The paper puts consideration to links of supply chain companies beginning with the immediate initial member. The incoming orders from downstream members serve as significant input data to upstream production and inventory decisions. The author outlines the distortion of information resulting from the misguiding of upstream members in inventory and production decisions. The paper performs analysis of the bullwhip effect sources, and they are processing of demand signs, game rotation, order batching and variation in price. Also, the paper discusses the harmful impacts of distortion reduction.
  • The bullwhip effect in supply chains, Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Sloan management review, 38, 93-102.  The author outlines the effects of information distortion from one end to another in the supply chain can lead to major wastages that include; investments in excess inventory, poor customer service, lost revenues, wrong capacity decisions, ineffective transportation and erred schedules in production. The paper also states the resultant effect of bullwhip effect that affects the demand in transition and the common symptoms of the distortion that include excessive inventory, poor product forecast, production capacities that are either insufficient or excess, unavailable products or long backlogs resulting to poor customer service, undetermined production and high correction costs.
  • Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information, Chen, F., Drezner, Z., Ryan, J. K., & Simchi-Levi, D. (2000). Management Science, 46(3), 436-443. Bullwhip effect, a significant examination in the supply chain, suggest that demand variation is directly proportional to the up movement in the supply chain. The paper deals with the quantification of the bullwhip effects for two staged supply comprising retailer and a single manufacturer. The model we used entails demand forecasting and order lead time that is believed to be affecting the bullwhip effect. The results found was extended to multiple stage supply chains with and without centralised customer demand information. The author demonstrated that the bullwhip effects could be mitigated but not done away with by demand information centralisation.
  • Quantifying the bullwhip effect in supply chains, Metters, R. (1997). Journal of operations management, 15(2), 89-100. The author puts many companies functioning as a serial supply chain with the end user providing demand information to the last company in the supply chain while the demand information in the upstream is formed by next preceding company in the chain. The other states that demand distortion also known as the bullwhip effect causes wastage for the upstream companies. The paper aims at the bullwhip magnitude identification by the establishment of verifiable lower bound on the profitability impact of the bullwhip effect.
  • Information distortion in a supply chain: the bullwhip effect, Lee, H. L., Padmanabhan, V., & Whang, S. (2004). Management Science, 50(12_supplement), 1875-1886. The author put a series of companies with every order from its immediate upstream member under the supply chain into an evaluation. The order from the downstream company member acts like input for the immediate upstream company production and inventory decisions making. The paper outlines that information received from downstream are always inaccurate as a result of the distortion they have undergone. The paper ascertains the four causes of the bullwhip effects to be: processing of demand signals, rationing game, order batching and price variation. The discussion also involved the mitigating actions for detrimental impacts of distortion.
  • The effect of vendor managed inventory (VMI) dynamics on the Bullwhip Effect in supply chains, Disney, S. M., & Towill, D. R. (2003). International journal of production economics, 85(2), 199-215. The paper is about the comparison between the budgeted performance of vendor managed inventory (VMI) supply chain with the serially linked supply chain. The comparison aimed to identify the impacts of the two alternative structures on the bullwhip effect generated in the supply chain. The findings showed the VMI importance in responding to abrupt and fast changing in demand, for instance, the change in demand as a result of discount ordering and price variations. The paper finalizes by stimulating the VMI and series chain response to a pattern of a representative sale, and the result is similar to rich picture forecast performance based on deterministic inputs.
  • Measuring and avoiding the bullwhip effect: A control theoretic approach, Dejonckheere, J., Disney, S. M., Lambrecht, M. R., & Towill, D. R. (2003). European Journal of Operational Research, 147(3), 567-590.  The supply chain members use the replacement rule which is a significant contributing factor to bullwhip effect. A bullwhip effect caused by different forecasting methods in order-up-to replacement policies is analysed.  Variance facilitation is quantified and the proving of the guarantee to the bullwhip effects in the order-up-to model regardless of the used forecasting method. When there is inflexibility in production, and much cost is incurred in switching up and down production quantities, there are a possibility undesirability and achievement of order-up-to policies. Control system engineering is the basis of a methodology allowing essential perception to be acquired regarding different behaviour of replenishment rules.
  • Behavioural causes of the bullwhip effect and the observed value of inventory information, Croson, R., & Donohue, K. (2006). Management Science, 52(3), 323-336. The paper defines the bullwhip effect as the order’s tendency of increasing variability as one climbs up the supply chain. The Bullwhip effects’ study from a behavioural viewpoint of simple, serial, and supply chain in consideration of information lags and stochastic demand. From the two examinations conducted, Bullwhip and the underlying nature of underweighting are left with the sharing inventory level’s information. On the other hand, inventory information is important in mitigating the bullwhip effects by enabling better forecasting and preparation from upstream members in the downstream variation of inventory needs. The study outcome supports a theoretical suggested conception of gain made to buy upstream chain members from information sharing initiatives.
  • Measuring the bullwhip effect in the supply chain, Fransoo, J. C., & Wouters, M. J. (2000). Supply Chain Management: An International Journal, 5(2), 78-89. The author states that even though, there has been a discussion on the increase of demand variability in the supply chain, the physical measurement of the bullwhip effect involves some problems that have never been attended. The problems deal with aggregation of data, data incompleteness, and demand data isolation for the supply chain that is defined and are part of the larger supply cycle. This paper deals with conceptual measurement problems discussion in addition to discussing experiences involved in handling these problems in industrial activity. The outcome of the measurement bullwhip effect of two supply chains are also presented
  • The bullwhip effect—the impact of stochastic lead time, information quality, and information sharing: a simulation study, Chatfield, D. C., Kim, J. G., Harrison, T. P., & Hayya, J. C. (2004). Production and Operations Management, 13(4), 340-353.  SISCO simulation method is used in the examination of the effects of stochastic lead time and sharing of information and the information quality in the order-u-to level inventory system. From the simulation, lead time variability worsens the variance facilitation in the supply chain, information sharing and quality are essential. Other assumptions made are by the dialogue with large supply chain managers.
  • In search of the bullwhip effect, Cachon, G. P., Randall, T., & Schmidt, G. M. (2007). Manufacturing & Service Operations Management, 9(4), 457-479. The author states that the bullwhip effect is the increase in demand’s variability in the supply chain retailers to manufacturing firms. The aim of this study is documenting the strength of bullwhip effects in the US. A wholesale industry was found to show bullwhip effects when the inflow material variance to the industry was greater than the industry sales variance. While the retail sector does not show the bullwhip effects, by the theoretical explanation for either not observation of demand facilitation, a significant proportion of differences are explained in the extent bullwhip showed by industries. In conclusion, the paper states that the seasonal industry demand is inversely related to industries amplifies volatility

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