The Bullwhip effect highlights the amplification of variability during a process : Low variability In process input produces high variability at the end of the process.
This effect was put forward by Jay Forrester in his paper ” Industrial Dynamics ” (1961). It is also often referred to as the “Forrester effect“, or “the Whip Effect“.
This effect raises the problem related to the variability of the customer demand. Jay Forrester shows the effect of a variability in customer demand for a business and demonstrates that the inability to define and make customer demand stable can have adverse effects.
The graph below shows us this effect:
A small variation in customer demand is reflected by amplifying throughout the value chain.
Consequences and impact
The first impact of the Bullwhip effect is the increase in security stocks in anticipation of variability. This degrades cash in proportion to induced stocks.
The Bullwhip effect has a heavy impact on the management of the company. Without a clear demand for customer needs, it becomes difficult to drive the company that is facing the following issues:
- Human Resources: How many operators are needed?
- Material: are investments in current or new machines necessary?
- Shopping: How many raw materials should I order to my subcontractors?
All these consequences lead to a constant management of the urgency where the difficulty of planning the production does not allow an efficient organization, generating many costs:
- Allowances for emergency external resources.
- Additional transport for the missing and the delays.
The root causes of the Bullwhip effect are linked to difficulties in identifying and managing the client demand. We find:
- The production data is taken only from the upstream or downstream Position and not according to the customer’s final request.
- Another effect amplifying this phenomenon, the batchsize. For the sake of economies of scale, companies have tendencies to accumulate orders before they produce them to buy in larger quantities. This results in a variation of the demand (reduction of the delivery time, an order coming at the last moment…) which amplifies the problem. This is also the case through the use of the Wilson’s formula of calculating the economic batch size. This effect is better known as the Burbidge effect1.
- As the initial application is not precise, it is gradually and at each level. The applicant will pass on this variability by summing up his own or taking into account a safety factor. At the end of the chain, no one knows the initial request.
- Another potential cause is the Houlihan effect2 : Finding delays in delivery or stock failures, customers then increase their order levels, amplifying the phenomenon by adding distortion in demand Actual customer.
- In order to win markets, companies are confronted with the fact that they cannot meet the high demand, and find themselves in a disability. In order to overcome this problem, they take strategic choices of investment in means (human, machinery…). These choices, if the assumptions prove to be bad, have the consequences of amplifying the variability.
- Finally, the effect of promotions and price changes3. By setting up promotions systems, we generate significant variations in customer demand, resulting in an increase in the Forrester effect.
In theory, the Bullwhip effect does not exist if we are in a just-in-time system. Your first goal is to strive towards such a system by putting in place devices to predict as far as possible the demand of customers. This can go through:
- Set up partnerships with your customers and subcontractors.
- Put in place logistics contracts.
- Improve the flexibility of your company: SMED,Shojinka…
- Use the Foresight tools.
- Reduce batch size to minimum: Mizusumashi, Kanban…
- Improve business processes by avoiding the search for sale for sale.
- Train logistics to this notion.
- Make a statistical analysis and follow-up of order to identify forecast parameters.
1-J. L. Burbidge (1991)-Period Batch Record (BPC) with GT-the way forward from MRP
2-J. B. Houlihan (1987)-International Supply Chain Management
3-H. L. Lee, V. Padmanabhan, S. Whang (1997)-Information distortion in a Supply Chain: the Bullwhip Effect
J. W. Forrester (1961)-Industrial Dynamics
F. Gay, Mr. Sali (2011)-The whip effect in the supply chain: a contingent and incomplete literature
Y. Pimor, M. Fender (2008)-Logistics
R. Le testifies (2013)-Supply Chain Management