Principle (Bullwhip Effect): Demand at the top (manufacturing) level of a supply chain tends to exhibit more variability than demand at the bottom (retail)level due to batch ordering, forecasting errors, promotional pricing, and gaming behavior by customers.

Identifying these as the main causes of the bullwhip effect suggests that the following are options for mitigating it:

1. Reduce Batching Incentives: Since batch orders amplify demand variability, policies that facilitate replenishment of stock in smaller quantities will reduce this effect. These include:

  • Reduce the cost of replenishment order: If it costs less to place an order (e.g., because the participants in the supply chain make use of electronic data interchange (EDI)), smaller orders will become economical.
  • Consolidate orders to fill trucks: If a wholesaler or distributor orders a product in full truckloads, this is good for transportation cost but bad for batch size. So, if instead they allow multiple products to share the same truck, transportation costs can be kept low with smaller batch sizes. Third party logistics companies can facilitate this.

2. Improve Forecasting: Since forecasts made on the basis of local demand (e.g.,that seen by the distributor or manufacturer) instead of actual customer demand aggravates the bullwhip effect, policies that improve visibility to demand will reduce demand volatility. These include:

  • Share demand data: A straightforward solution is to use a common set of demand data at all levels in the supply chain. In intra-firm supply chains (i.e., owned by a single firm) this is fairly simple (although not automatic). In inter-firm supply chains, it requires explicit cooperation. For example, IBM, HP, and Apple all require sell-through data from their resellers as part of their contracts.
  • Vendor-managed inventory: Manufacturers control the resupply of the entire supply chain in vendor-managed inventory (VMI) systems. For example, Proctor & Gamble controls inventories of Pampers all the way from its supplier (3M) to its customer (Wal-Mart). Hence, demand data is automatically shared and inventory can be pooled more effectively across the levels of the supply chain.
  • Lead time reduction: Because safety stocks increase with replenishment lead time, shorter lead times will cause less amplification of demand spikes. Variability reduction, postponement strategies, and waste elimination policies can be used to achieve shorter lead times.

3. Increase Price Stability: Since price fluctuations cause customers to accelerate or delay buying, policies that stabilize prices will reduce demand volatility.

These include:

  • Everyday low pricing: Eliminating or reducing reliance on promotional pricing and shifting to “everyday low prices” or “value prices” is a straightforward way to reduce price swings. Such schemes can also be part of effective marketing campaigns.
  • Activity-based costing: By accounting for inventory, shipping, and handling, activity-based costing (ABC) systems can show costs of promotional pricing that do not show up under traditional accounting systems. Hence, they can help justify and implement an everyday low pricing strategy.

4. Remove Gaming Incentives: Since gaming behavior distorts customer orders, policies that remove incentives for this kind of behavior can reduce the distortion and the resulting effect on demand variability.

These include:

  • Allocate shortages according to past sales: By allocating the supply of a scarce product on the basis of historical demand, rather than current orders, the supplier can remove the incentive for customers to exaggerate orders.
  • Restrict order cancellation: Many firms make use of frozen zones and/or time fences that limit customers' freedom to cancel orders. (Generally, the options for changing an order diminish as time draws closer to the order due date.) This serves to make gaming strategies become more costly. How far a supplier can go with such strategies depends, however, on the importance of flexibility in the market.
  • Lead time reduction: Long lead time components tend to aggravate gaming behavior because customers know that manufacturers must order them well in advance, often before they have firm orders for the products that will use them. Therefore, to be sure that the manufacturer won’t run short of these components, customers have an incentive to inflate demand projections for distant future periods and then reduce these when it comes time to convert them into firm orders. Of course, if the frozen zone or time fence policy prohibits such changes in customer orders, this cannot occur. But lead times on components are frequently longer than a frozen zone that customers would tolerate. Hence, working with suppliers of such components to reduce lead times may be the most practical alternative.

Source: supply chain science