Bullwhip Effect in Supply Chain
Supply Chain Class Module 2, Lesson 3 Question #1 Develop a small group consensus on the impact (increases, decreases, no effect) of the Bullwhip Effect on two of the following six supply chain performance measures: manufacturing cost, inventory cost, replenishment lead time, transportation cost, shipping and receiving cost, level of product availability profitability. One of the two measures that your team chooses must be inventory cost. For inventory costs, be certain to be specific about the kinds of inventory costs impacted (in-storage cycle stock carrying costs, ordering costs, stockout costs, or safety stock carrying costs).
Clearly explain your group’s reasoning or rationale for the impact you have agreed to; that is carefully explain why the bullwhip effect either increases, decreases of has no effect on the given performance measure. In each of your explanations, drill down into the factors that drive each measure, explaining how those factors are affected by the Bullwhip effect. MANUFACTURING COSTS It is the consensus of Team 10 that the bullwhip effect increases costs associated with the manufacturing of products.
We know that the bullwhip effect results in an amplification of the variation of product and material demand as one travels upstream in the supply chain from consumer to material suppliers. In most cases the manufacturer of products will be removed from the actual consumer by multiple layers in the supply chain. The variation in demand (variation in orders) that the manufacturer will experience will be significantly greater than the variation in demand from the actual consumers. There are several costs incurred in the manufacturing of products. Among these costs are direct material costs, direct labor costs and overhead costs.
The increased variability in quantity of products demanded from the manufacturer has an impact on each of these items. For most manufactured products, the cost of materials is a significant portion of the cost of the end item. As the demand for products varies from the manufacturer, these swings in demand are amplified and passed on to the material suppliers and various other sub-suppliers. During periods of high demand, the manufacturer is more likely to be forced to pay the material suppliers and sub-suppliers additional fees to expedite shipments.
During periods of low demand, the manufacturer is more likely to find itself with a huge stock of unused material on hand. These variations also make it more difficult to negotiate competitive prices with the suppliers, further adding to the cost of the bullwhip effect. In an effort to protect against some of this variation, manufacturers will often stockpile materials, adding further warehousing and capital costs. Labor costs are another key component of the total cost of most products, including products which may be manufactured offshore in low-wage countries.
In periods of extremely high demand, manufacturers are faced with an option of either hiring more employees or working their existing employee’s longer hours and paying overtime. Most companies are extremely reluctant to hire additional workers, particularly if they have reason to believe that the spike in demand will only be temporary. As a result, companies will typically choose to work longer hours and pay overtime wages to their employees. Paying overtime is costly, not only from a wage standpoint but also from an effectiveness standpoint.
Employees are not robots, and diminishing marginal return should be expected when working employees longer hours. As hours go up, productivity typically declines at a rate that increases as the severity of the work schedule increases. The result is an increasing cost per unit of the products produced. Likewise, when product demand is extremely low, employees are not able to be utilized as effectively and labor cost per unit also increases. Further, there are the overhead costs which are affected by the variation in demand amplified by the bullwhip effect.
When manufacturers create facilities and purchase processing equipment, they often “size” their operations based upon what they believe will be the highest levels of demand for their products. When demand for products varies greatly, the frequent result is that the processes, equipment and facilities are excessively large (and costly) compared to what the “legitimate” demand might actually require. This results not only in excessive costs to set up these operations, but it also can create a scenario where it becomes difficult to operate these facilities efficiently when the production requirements are lower.
Another element for consideration is the “cost of quality. ” Manufacturing operations thrive on consistency. When manufacturers have to contend with wildly-varying production schedules, there is an increase in the “state of flux” in the operations. This can take the form of delayed maintenance on machines, fatigued workers, using alternate suppliers for materials, etc. All of these elements that are exacerbated by large swings in production schedule can contribute to higher scrap rates, manufacturing errors, equipment downtime and, potentially, product defects that reach the consumer.
INVENTORY COSTS Demand variability amplification can have a significant impact on increasing inventory costs. Business Dictionary. com defines inventory costs as the cost of holding goods in stock. Expressed usually as a percentage of the inventory value, it includes capital, warehousing, depreciation, insurance, taxation, obsolescence, and shrinkage costs. Typically, the inventory costs increase due to excessive or obsolete inventory as a result of poor demand forecasting. This situation is clearly defined in an article about Cisco’s need to write-off $2. billion in inventory in 2001. However, one must dive deeper into specific inventory performance measures to better understand the effects of the bullwhip effect on inventory costs. Safety Stock Safety stock can be defined as inventory held as buffer against mismatch between forecasted and actual consumption or demand, between expected and actual delivery time, and unforeseen emergencies. From a positive standpoint, safety stock can help to potentially reduce stock out situations however is also contributes to the bullwhip effect.
Specifically with demand forecast updating using exponential smoothing, ordering of safety stock will create larger swings for suppliers and even move for orders placed to the manufacturer (Lee, p 95). Furthermore, poorly ordered safety stock that becomes excess or obsolete can lead to increased expense or in a worst-case scenario, written-off or scrapped completely. Stockout Cost Stockout cost, also called shortage cost, is defined as the economic consequences of not being able to meet an internal or external demand from the current inventory. Such costs consist of internal costs (delays, labor time wastage, lost production, etc. and external costs (loss of profit from lost sales, and loss of future profit due to loss of goodwill). One cause of stockout cost can be attributed to poorly updated demand forecast where the appropriate amount of inventory was not planned for the current demand. This is in contrast to the safety stock example which leads to an increase in inventory and excess or obsolete material. Another cause is rationing and shortage gaming where the demand for the product exceeded the supply (Lee, p97). The stockout cost is the expense of the lost sales or the potential of losing the customer loyalty completely to a fierce competitor.
Module 2, Lesson 3 Question #2 At the end of the article “Bullwhip Effect in Supply Chains” by Lee, et. al. , is Table 1. In this table Lee presents a number of initiatives, such as vendor-managed inventory, for counteracting the four causes of the Bullwhip Effect. Select one or more of the initiatives and develop a small group consensus on a list of the top five impediments to the initiatives that you have selected; five impediments in total, not five impediments for each initiative that you select. Select two impediments and for each impediment please explicitly explain why the impediment is difficult to overcome.
Finally in your group’s opinion, which of your impediments is typically the most difficult to overcome? Please explain why. BULLWHIP EFFECT COUNTERMEASURES; EDI, VMI, ECHELON-BASED INVENTORY SYSTEMS There is a range of initiatives to mitigate the effects of the “bullwhip effect,” or amplified distortions in replenishing orders. Through EDI and vendor –managed inventory (VMI), distortions may be reduced through transparent sharing of real time demand information through the entire supply chain. Demand distortion begins with faulty assumptions underlying future demand projections.
One counter-measure for this challenge is real time exchange of information and increased transparency at point of sale. Many retailers use data generated at point of sale to automatically adjust their inventories and trigger reorder as inventories are depleted. Simultaneous transmission of this data to the supplier would facilitate a clearer view of consumption and retail inventory. Point of sale EDI shared across the supply chain from the manufacturer to retail outlet, would smooth the orders and prevent demand distortion that occurs with regression driven forecasts.
Increased control of the total inventory can be achieved with echelon inventory management, through cooperative information sharing and a jointly agreed upon single point of inventory control. One model for this is vendor-managed inventory (VMI) which is a continuous replenishment of inventory based upon a push from the supply to the retail outlet based on EDI signals at point of sale and inventory depletion. ECHELON-BASED INVENTORY SYSTEMS Echelon-based inventory systems allow transparency of the inventory flow of the down-stream levels in the supply chain by the upstream levels.
This acts to reduce the bullwhip effect by preventing exaggeration of demand fluctuations by multiple levels in the chain. This is a useful policy, but it can be difficult to implement. First, one must consider the integrity of the source of the information. If an upstream member of the chain intends to rely on reports generated by the downstream member, trust must be a mutual component of the relationship. The downstream company may feel that it doesn’t want to share the information about their own inventory and/or demand, especially if it engages (or has any intention of engaging) in a practice of shortage gaming.
Some elements of the shared data can be filtered, if this is found to be helpful to the downstream member. If the downstream member engages in price hedging or shortage gaming, the increased transparency to the upstream member would inhibit or completely prevent the downstream company from harnessing the perceived buffer that the practice enables. Some elements of the shared data can be filtered, if mutually agreeable to all members of the supply chain. Through non-disclosure agreements and data parsing, streams of proprietary data can be “cleansed” to be less sensitive.
Connectivity of various operating systems is another hurdle. Many suppliers and retailers will not allow “direct feed” of data into their core operating systems, requiring a data merge in a safe environment that then can share data between the operating systems of the companies exchanging data. The work of scrubbing data and developing the necessary connectivity also requires IT resources. One must also consider the utility of information that is constantly changing. The value of inventory data to the upstream member could be limited as it changes continuously and obsolesces almost as soon as it’s generated.
The upstream member must always be willing to loosely interpret the inventory and demand data since an unusually large order, or an unusual decline in orders, could occur at any time. Also, downstream members’ transparency leads the upstream member to increase the frequency with which they update their demand forecasting. Frequently updating these forecasts is itself a bullwhip effect-exacerbating practice, so the upstream member would need to exercise discretion in its policies on how it reacts to the information that it receives from downstream.
Implementation of these initiatives requires addressing and overcoming certain impediments: Trust between supply chain partners or perceived competitive risk Data integrity challenges with changing/obsolete data Reduced downstream gaming ability (shortage and price hedge forward buying) Information technology resources to facilitate connectivity Increased frequency of upstream re-forecast due to downstream transparency The two most difficult impediments are the first two; trust amongst supply chain partners, and the challenges of sharing meaningful data.
Trust – Perceived Competitive Risk The challenge with establishing trust amongst supply chain partners is one of competitive risk. The real time data on point of sale, inventories held, or pricing activities engaged are all considered proprietary. The sharing of that data requires trust through the entire supply chain, and a willingness to incur significant legal, technological, and analytical resources to develop and deliver data that is accurate and meaningful.
Lack of transparency and trust on the part of down stream members is the primary driver of the shortage and price gaming, to build inventories and prevent stock-outs or hedge for future price increases. In order to share transparent information through the supply chain, legal and technological hurdles must be addressed to reduce competitive risk, and allow necessary trust through protective agreements (NDA) and safe systems connectivity. Through non-disclosure agreements and data parsing streams of proprietary data can be “cleansed” to be less sensitive and reduced competitive risk. ) Data Integrity – Changing and Obsolete Information The real time exchange of information supports accurate forecasts and timely order replenishment only if that data is meaningful. Data is meaningful if it clearly conveys the supply/demand picture. Upstream suppliers must be able to see the sale/demand data and existing inventory data in real time in order to push order replenishment. If downstream members obscure the inventories to retain shortage gaming power, this will impact the accuracy of the inventory replenishment trigger to the upstream supplier.
Connected systems are susceptible to cross-system failures. Errant data in one system pollutes the forecast assumptions of the connected systems. Cadence of exchange, or timing of the data flows is a factor in relevance. If sales or order cancellations have changed inventories significantly since the last update, the information exchanged can be obsolete. The “bullwhip effect” is culmination of iterative forecast variations, and self-protecting defensive actions on the part of supply chain members to hedge uncertainty. With increased trust and transparency, the forecast variations and uncertainty can be reduced.
With collaboration through the entire supply chain, trust can be built, real time, meaningful data exchanged, and the cost of surplus inventories taken out of the chain. ——————————————– [ 1 ]. Comments on Information Distortion in a Supply Chain: The Bullwhip Effect” by Lee, H. L. Padmanabhan, V. and Whang, S. , p 1888 [ 2 ]. http://www. businessdictionary. com/definition/safety-stock. html#ixzz286djGuPB). [ 3 ]. http://www. businessdictionary. com/definition/stockout-costs. html#ixzz286iDNySD
