Layers and Mechanisms: A New Taxonomy for the Bullwhip Effect
Layers and mechanisms: A new taxonomy
for the Bullwhip Effect
Giovanni Miragliotta
In this article, Giovanni Miragliotta has two main purposes. The first one is to strengthen the knowledge on the dynamics of a supply chain via a deep review of the Bullwhip Effect. The second one is to build a new framework abled to classify the causes of the Bullwhip effect. Furthermore, this framework can distinguish layers and mechanisms that lead to Bullwhip Effect and so help managers to better understand the causes of this effect and to implement the better solution to reduce the Bullwhip Effect.
The concept of Bullwhip effect has been introduced by Simon (1952) and Forrester (1961) but it was the role-playing simulation game developed by the MIT, the beer Game, which revealed this effect to the world.
Review of the literature about the BE (stat-of-the art knowledge about this subject)
In 1961 Burbidge introduced the first accurate definition of the Bullwhip Effect which was completed by Towill (1997) who identified two different factors for the demand variations; the demand variations amplification effect and the rogue seasonality. All those improvements can lead to a general definition of the Bullwhip Effect: “a supply chain phenomenon revealed by a distortion (variability amplification and/or rogue seasonality) of the demand signal as it is transmitted upstream, from retailers to suppliers.”
The purpose of the literature review is to list the available knowledge on the Bullwhip Effect and to prove that a new framework is mandatory.
The Bullwhip Effect is most commonly measured and detected by the variance ratio - the ratio between the demand variance at the downstream and at the upstream stages.
Nevertheless other measurement procedures exist and they concentrate more or less on some factors as for instance the final demand data set, the seasonality coefficient and the coefficient of variation. In 2004, to avoid the “peak order amplification”, Zhang
for the Bullwhip Effect
Giovanni Miragliotta
In this article, Giovanni Miragliotta has two main purposes. The first one is to strengthen the knowledge on the dynamics of a supply chain via a deep review of the Bullwhip Effect. The second one is to build a new framework abled to classify the causes of the Bullwhip effect. Furthermore, this framework can distinguish layers and mechanisms that lead to Bullwhip Effect and so help managers to better understand the causes of this effect and to implement the better solution to reduce the Bullwhip Effect.
The concept of Bullwhip effect has been introduced by Simon (1952) and Forrester (1961) but it was the role-playing simulation game developed by the MIT, the beer Game, which revealed this effect to the world.
Review of the literature about the BE (stat-of-the art knowledge about this subject)
In 1961 Burbidge introduced the first accurate definition of the Bullwhip Effect which was completed by Towill (1997) who identified two different factors for the demand variations; the demand variations amplification effect and the rogue seasonality. All those improvements can lead to a general definition of the Bullwhip Effect: “a supply chain phenomenon revealed by a distortion (variability amplification and/or rogue seasonality) of the demand signal as it is transmitted upstream, from retailers to suppliers.”
The purpose of the literature review is to list the available knowledge on the Bullwhip Effect and to prove that a new framework is mandatory.
The Bullwhip Effect is most commonly measured and detected by the variance ratio - the ratio between the demand variance at the downstream and at the upstream stages.
Nevertheless other measurement procedures exist and they concentrate more or less on some factors as for instance the final demand data set, the seasonality coefficient and the coefficient of variation. In 2004, to avoid the “peak order amplification”, Zhang