The Bullwhip Effect

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The Bullwhip Effect

• Henry C. Co
• Technology and Operations Management,
• California Polytechnic and State University

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Variability increases as one moves up the supply
chain
Source Johnson Pike, 1999
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The Bullwhip Effect
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The Beer Game

• Role-playing simulation developed in the 1960s
  at MITs Sloan School of Management
• Production and distribution of beer.
• Players divide themselves into groups Retailer,
  Wholesaler, Distributor, and Brewer.
• Weekly consumer demand simulated by a deck of
  cards
• Retailer sells from his inventory and reorders
  from the Wholesaler, who sells from his inventory
  and reorders from the Distributor, who in turn
  sells from his inventory and reorders from the
  Brewer, who finally sells from his inventory and
  restocks from his production.
• Order processing delays Shipping delays
• Inventory carrying costs Stockout costs
• Players base their decisions strictly on the
  orders they receive from their respective buyers.

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• During the game emotions run high. Many players
  report feelings of frustration and helplessness.
  Many blame their teammates for their problems
  occasionally heated arguments break out.
• In virtually all cases, the inventory levels of
  the retailer decline, followed in sequence by a
  decline in the inventory of the wholesaler,
  distributor, and factory. As inventory falls,
  players tend to increase their orders. Players
  soon stock out. Backlogs of unfilled orders grow.
  Faced with rising orders and large backlogs,
  players dramatically boost the orders they place
  with their supplier. Eventually, the factory
  brews and ships this huge quantity of beer, and
  inventory levels surge. In many cases one can
  observe a second cycle.

John Sterman, one of the original proponents of
the Beer Game
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• Stakeholders along supply chain
• Have different and frequently conflicting
  objectives.
• Often operated independently.
• The network can oscillate in very large swings as
  each organization in the supply chain seeks to
  solve the problem from its own perspective.

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Consequences of the Bullwhip Effect

• Lower revenues.
• Stockouts and backlogs mean lost sales, as
  customers take their business elsewhere.

• Higher costs.
• High carrying cost
• Stockout cost
• Distributors need to expedite orders (at higher
  shipping expenses)
• Manufactures need to adjust jobs (at higher
  setups and changeover expenses, higher labor
  expenses for overtime, perhaps even higher
  materials expenses for scarce components.)
• All entities in the supply chain must also invest
  heavily in outsized facilities (plants,
  warehouses) to handle peaks in demand, resulting
  in alternating under or over-utilization.

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• Worse quality.
• Quirky, unplanned changes in production and
  delivery schedules disrupt and subvert control
  processes, begetting diverse quality problems
  that prove costly to rectify.

• Poorer service.
• Irregular, unpredictable production and delivery
  schedules also lengthen lead time, causing delay
  and customer dissatisfaction.

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Causes of Bullwhip Effect
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• Demand variability, quality problems, strikes,
  plant fires, etc.
• Variability coupled with time delays in the
  transmission of information up the supply chain
  and time delays in manufacturing and shipping
  goods down the supply chain create the bullwhip
  effect.

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• Overreaction to backlogs
• Neglecting to order in an attempt to reduce
  inventory
• No communication up and down the supply chain
• No coordination up and down the supply chain
• Delay times for information and material flow

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• Order batching - larger orders result in more
  variance. Order batching occurs in an effort to
  reduce ordering costs, to take advantage of
  transportation economics such as full truck load
  economies, and to benefit from sales incentives.
  Promotions often result in forward buying to
  benefit more from the lower prices.
• Shortage gaming customers order more than they
  need during a period of short supply, hoping that
  the partial shipments they receive will be
  sufficient.

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• Demand forecast inaccuracies everybody in the
  chain adds a certain percentage to the demand
  estimates. The result is no visibility of true
  customer demand.
• Free return policies

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Countermeasures to the Bullwhip Effect
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• Countermeasures to order batching
• Countermeasures to shortage gaming
• Countermeasures to fluctuating prices
• Countermeasures to demand forecast inaccuracies
• Free return policies

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Order Batching

• High order cost is countered with Electronic Data
  Interchange (EDI) and computer aided ordering
  (CAO).
• Full truck load economics are countered with
  third-party logistics and assorted truckloads.
  Random or correlated ordering is countered with
  regular delivery appointments.
• More frequent ordering results in smaller orders
  and smaller variance.
• However, when an entity orders more often, it
  will not see a reduction in its own demand
  variance - the reduction is seen by the upstream
  entities.
• Also, when an entity orders more frequently, its
  required safety stock may increase or decrease
  see the standard loss function in the Inventory
  Management section.

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Shortage Gaming

• Proportional rationing schemes are countered by
  allocating units based on past sales.
• Ignorance of supply chain conditions can be
  addressed by sharing capacity and supply
  information.
• Unrestricted ordering capability can be addressed
  by reducing the order size flexibility and
  implementing capacity reservations.
• For example, one can reserve a fixed quantity for
  a given year and specify the quantity of each
  order shortly before it is needed, as long as the
  sum of the order quantities equals to the
  reserved quantity.

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Fluctuating Prices

• High-low pricing can be replaced with every day
  low prices (EDLP). Special purchase contracts can
  be implemented in order to specify ordering at
  regular intervals to better synchronize delivery
  and purchase.

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Demand Forecast Inaccuracies

• Lack of demand visibility can be addressed by
  providing access to point of sale (POS) data.
• Changes in pricing and trade promotions and
  channel initiatives, such as vendor managed
  inventory (VMI), coordinated forecasting and
  replenishment (CFAR), and continuous
  replenishment can significantly reduce demand
  variance.

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Free Return Policies

• Free return policies are not addressed easily.
• Often, such policies simply must be prohibited or
  limited.

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Vendor Managed Inventory
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• Popularized in the late 1980s by Wal-Mart and
  Procter Gamble, VMI became one of the key
  programs in the grocery industrys pursuit of
  efficient consumer response and the garment
  industrys quick response.
• Successful VMI initiatives have been trumpeted by
  other companies in the United States, including
  Campbell Soup and Johnson Johnson, and by
  European firms like Barilla (the pasta
  manufacturer).

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The VMI Partnership

• The supplierusually the manufacturer but
  sometimes a reseller or distributormakes the
  main inventory replenishment decisions for the
  consuming organization.
• The supplier monitors the buyers inventory
  levels (physically or via electronic messaging)
  and makes periodic resupply decisions regarding
  order quantities, shipping, and timing.
• Transactions customarily initiated by the buyer
  (like purchase orders) are initiated by the
  supplier instead.
• The purchase order acknowledgment from the
  supplier may be the first indication that a
  transaction is taking place an advance shipping
  notice informs the buyer of materials in transit.

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The manufacturer is responsible for both its own
inventory and the inventory stored at is
customers distribution centers.