What Is the Bullwhip Effect?
The bullwhip effect refers to a scenario in which small changes in demand at the retail end of the supply chain become amplified when moving up the supply chain from the retail end to the manufacturing end.
This happens when a retailer changes how much of a good it orders from wholesalers based on a small change in real or predicted demand for that good. Due to not having full information on the demand shift, the wholesaler will increase its orders from the manufacturer by an even larger extent, and the manufacturer, being even more removed will change its production by a still larger amount.
The term is derived from a scientific concept in which movements of a whip become similarly amplified from the origin (the hand cracking the whip) to the endpoint (the tail of the whip).
The danger of the bullwhip effect is that it amplifies inefficiencies in a supply chain as each step up the supply chain estimates demand more and more incorrectly. This can lead to excessive investment in inventory, lost revenue, declines in customer service, delayed schedules, and even layoffs or bankruptcies.
- The bullwhip effect refers to the amplification of variability in demand as you move up the supply chain from retailers to manufacturers.
- When a retailer incorrectly forecasts demand, this mistake is often magnified as orders are sent to distributors and manufacturers, eventually leading to massive discrepancies between inventory produced and demand.
- Bullwhip effects can lead to excess inventory, lost revenue, and overinvestment in production.
Understanding the Bullwhip Effect
The bullwhip effect typically travels from the retail level up the supply chain to the manufacturing level. If a retailer uses immediate sales data to anticipate a strong increase in demand for a product, the retailer will pass a request for additional product to its distributor. The distributor, in turn, will communicate this request to the maker of the product. This alone is an aspect of supply chain operations and is not necessarily reflective of a bullwhip effect.
The bullwhip effect generally distorts this process in one of two ways. First is when the original order change by retailers is due to an inaccurate demand forecast. The size of this error tends to grow as it progresses further up the supply chain to the manufacturer. The second is when a retailer has the correct information about demand, but it leads to incorrect conclusions about information as to the reason and details of the retailer's order change are lost, leading to incorrect assessments by wholesalers, which are then magnified further up the chain.
Example of the bullwhip effect
For instance, imagine a retailer selling hot chocolate that typically sells 100 cups a day in the winter. On a particularly cold day in that area, that retailer sells 120 cups instead. Mistaking the immediate increase in sales for a broader trend, the retailer requests ingredients for 150 cups from the distributor. The distributor sees the increase and expands its purchase order with the manufacturer to anticipate increased requests from other retailers as well. The manufacturer increases its manufacturing run in anticipation of greater product requests in the future.
At each stage above, demand forecasts have been increasingly distorted. If the retailer sees a return to normal hot chocolate sales when the weather returns to normal, it will suddenly find itself with more supplies than needed. The distributor and manufacturer will have even more excess inventory.
Another reason for the lack of information is that larger logistics operations at the wholesale level take longer to change, meaning that the conditions that caused a change in demand at the retail level may have passed by the time a wholesaler has reacted. As changing manufacturing output takes longer still and information from retailers is even more delayed in getting to manufacturers, the difficulty of reacting correctly to changes in demand increases even more so.
Even if the retailer had accurately assessed demand, for example, due to the start of a local hot chocolate festival, the bullwhip effect can still occur. The distributor, not being fully aware of local conditions, may assume this is due to a broad increase in the demand for hot chocolate, rather than specific conditions for that retailer. The manufacturer, being even more removed from the situation, would be even less likely to understand and correctly react to the change in demand.
Asset manager and famed "Big Short" investor Michael Burry made headlines in June of 2022 when he warned investors about the bullwhip effect for big-box retailers and others.
Impacts of the Bullwhip Effect
In the example above, the manufacturer may be stuck with a significant surplus of product. This can lead to disruptions to the supply chain and to that manufacturer's business—increased costs associated with storage, transportation, spoilage, losses of revenue, delays to shipments, and more. The distributor and the retailer in this example may also see similar problems.
What Does a Bullwhip Effect Indicate?
A bullwhip effect indicates that a small error in assessing consumer demand has been amplified through a supply chain. This means communication between firms in a supply chain is imperfect leading to firms up the supply chain missing important information.
How Do You Identify a Bullwhip Effect?
The bullwhip effect can be difficult to identify in real time, in part because it is caused by a lack of communication throughout a supply chain. Frequently, it is a phenomenon that is observed after the fact, when inefficiencies have already been created.
How Do You Prevent a Bullwhip Effect?
There are many things firms in a supply chain can do to prevent, or at least reduce the likelihood and severity of, a bullwhip effect. First and foremost they can ensure clear and consistent communications between companies up and down the supply chain. This will help avoid temporary or localized shifts in supply from being misinterpreted as broader than they are. Firms can also make sure to take a wider viewpoint when making forecasts for demand to reduce the effect of any temporary or limited shifts. Finally, companies can work to increase the speed at which they are able to respond to shifts in demand, meaning that they can readjust more easily if they incorrectly assess demand. This also reduces the need to overproduce or overorder to have a buffer in case of demand shifts.