Supply Chain Chapter 7 – Flashcards

True

False

True

True

False

Fasle

False

True

True

False

True

True

True

False

False

True

False

physical distriBution

physical SUPPLY.

Flows of products. Flows of services. Information about capital. **All of these answers

lack of coordination between departments.

phantom demand.

customer demand

inventory and production flexibility.

demand that cannot normally be anticipated

a weight to each previous period

is one of the most commonly used techniques.

exponential smoothing for trends

quick response (QR) vendor-managed inventory (VMI) efficient consumer response (ECR) ***All of these answers

Two types of demand exist: independent and dependent. Independent demand is the demand for the primary item. Dependent demand is directly influenced by the demand for the independent item. For example, the demand for bicycles would be called independent. It is the demand for the primary, or finished, product and is directly created by the customer. The demand for bicycle tires would be called dependent, because the number of tires demanded is determined by the number of bicycles demanded. Most forecasting techniques focus on independent demand. For example, a bicycle manufacturer will forecast the demand for bicycles during a given period. Given that level of demand, the manufacturer knows that two tires will be required for each bicycle demanded. As such, there is no need for the bicycle manufacturer to forecast the demand for tires. From a different perspective, the tire manufacturer will need to forecast the demand for tires, because these are its independent demand items. However, the tire manufacturer will not need to forecast the demand for rims since each tire requires one rim. So, each organization in a particular supply chain will have different definitions for independent and dependent demand items. FORECASTING, however, will still usually be done at the INDEPENDENT demand item level.

Simple Moving Average The simple moving average is probably the simplest to develop method in basic time series forecasting. It makes forecasts based on recent demand history and allows for the removal of random effects. The simple moving average method does not accommodate seasonal, trend, or business cycle influences. This method simply averages a predetermined number of periods and uses this average as the demand for the next period. Each time the average is computed, the oldest demand is dropped and the most recent demand is included. A weakness of this method is that it forgets the past quickly. A strength is that it is quick and easy to use. Weighted Moving Average In the simple moving average method, each previous demand period was given an equal weight. The weighted moving average method assigns a weight to each previous period, with higher weights usually given to more recent demand. The weights must equal to one. The weighted moving average method allows emphasis to be placed on more recent demand as a predictor of future demand. However, the results from the weighted moving average method are still not very good forecasts of demand. There are three possible causes for this. First, the weights assigned to the three periods might not accurately reflect the patterns in demand. Second, using three periods to develop the forecast might not be the appropriate number of periods. Finally, the weighted moving average technique does not easily accommodate demand patterns with seasonal influences. Exponential Smoothing Exponential smoothing is one of the most commonly used techniques because of its simplicity and its limited requirements for data. Exponential smoothing needs three types of data: an average of previous demand, the most recent demand, and a smoothing constant. The smoothing constant must be between 0 and 1. Exponential smoothing forecasts will lag actual demand. If demand is relatively constant, exponential smoothing will produce a relatively accurate forecast. However, highly seasonal demand patterns or patterns with trends can cause inaccurate forecasts using exponential smoothing.

Many organizations are faced with seasons that repeat themselves during a particular period. These seasons might be by time of day (for example, demand for hamburgers at a fast-food outlet), by day of the week (for example, the demand for gasoline), by week, by the month, or by some combination of these. Adjusting a forecast for seasons basically uses a combination of seasonal factors and average demand to arrive at an adjusted forecast.

Four types of forecast error measures can be used. The first is called the cumulative sum of forecast errors (CFE). It calculates the total forecast error for a set of data, taking into consideration both negative and positive errors. This gives an overall measure of forecast error. However, taking into consideration both negative and positive errors, this method can produce an overall low error total, although individual period forecasts can either be much higher or much lower than actual demand. The second measure of forecast error is mean squared error (MSE), which squares each period error so the negative and positive errors do not cancel each other out. MSE also provides a good indication of the average error per period over a set of demand data. The third type is Mean Absolute Deviation (MAD). By taking the absolute value of each error, the negative and positive signs are removed and a good indication of average error per period is calculated. This measure is popular because it is easy to understand and provides a good indication of the accuracy of the forecast. The final measure of forecast error is mean absolute percent error (MAPE), and it elates the forecast error to the level of demand so different types of forecasts can be compared.

The S&OP Benchmarking Consortium in the Center for Supply Chain Research adopted a five step process in arriving at this consensus forecast. Step 1 (Run sales forecast reports) requires the development of a statistical forecast of future sales. This would be done using one or more of the forecasting techniques discussed in the previous section. Step 2 (Demand planning phase) requires the sales and/or marketing departments to review the forecast and make adjustments based on promotions of existing products, the introduction of new products, or the elimination of products. This revised forecast is usually stated in terms of both units and dollars since operations are concerned with units and finance is concerned with dollars. Step 3 (Supply planning phase) requires operations (manufacturing, warehousing, and transportation) to analyze the sales forecast to determine if existing capacity is adequate to handle the forecasted volumes. This requires analyzing not only the total volumes but also the timing of those volumes. Any capacity issues would need to be considered for both warehousing space and transportation vehicle capacity with similar resulting options if capacity does not meet demand: either curtail demand or invest in additional capacity. Step 4 (Pre-S&OP meeting) involves individuals from sales, marketing, operations, and finance. This meeting will review the initial forecast and any capacity issues that might have emerged during Step 3. Initial attempts will be made during this meeting to solve capacity issues by attempting to balance supply and demand. Alternative scenarios are usually developed to present at the Step 5 executive S&OP meeting for consideration. These alternatives would identify potential lost sales and increased costs associated with balancing supply and demand. The sales forecast is also converted to dollars to see if the demand/supply plan meets the financial plan of the organization. Finally, Step 5 (Executive S&OP meeting) is where final decisions are made regarding sales forecasts and capacity issues.

One of the most recent initiatives aimed at achieving true supply chain integration is collaborative planning, forecasting, and replenishment (CPFR). CPFR has been recognized as a breakthrough business model for planning, forecasting, and replenishment. Using this approach, retailers, distributors, and manufacturers can utilize available Internet-based technologies to collaborate on operational planning through execution. Transportation providers have now been included with the concept of collaborative transportation management (CTM). Simply put, CPFR allows trading partners to agree to a single forecast for an item where each partner translates this forecast into a single execution plan. This replaces the traditional method of forecasting, where each trading partner developed its own forecast for an item and each forecast was different for each partner. CPFR is a sequence of several business processes that include the consumer, retailer, and manufacturer. The four major processes are strategy and planning, demand and supply management, execution, and analysis. Two aspects of this model are important to note. First, it includes the cooperation and exchange of data among business partners. Second, it is a continuous, closed-loop process that uses feedback (analysis) as input for strategy and planning. CPFR emphasizes a sharing of consumer purchasing data (or point-of-sale data) as well as forecasts at retail among and between trading partners for the purpose of helping to manage supply chain activities. From these data, the manufacturer analyzes its ability to meet the forecasted demand. If it cannot meet the demand, a collaborative effort is undertaken between the retailer and manufacturer to arrive at a mutually agreed-upon forecast from which execution plans are developed. The strength of CPFR is that it provides a single forecast from which trading partners can develop manufacturing strategies, replenishment strategies, and merchandising strategies. The CPFR process begins with the sharing of marketing plans between trading partners. Once an agreement is reached on the timing and planned sales of specific products, and a commitment is made to follow that plan closely, the plan is then used to create a forecast, by stock-keeping unit (SKU), by week, and by quantity.

A channel of distribution consists of one or more organizations or individuals who participate in the flow of goods, services, information, and finances from the production point to the final point of consumption. A channel of distribution can also be thought of as the physical structures and intermediaries through which these flows travel. These channels encompass a variety of intermediary firms, including those that can be classified as distributors, wholesalers, retailers, transportation providers, and brokers. Some of these intermediary firms take physical possession of the goods, some take title to the goods, and some take both. Thus, it is critical in the design of a distribution channel to take into consideration both the logistics channel and the marketing channel. The logistics channel refers to the means by which products flow physically from where they are available to where they are needed. The marketing channel refers to the means by which necessary transactional elements are managed (for example, customer orders, billing, accounts receivable, etc.).

Integrated fulfillment means the retailer operates one distribution network to service both channels. In a typical distribution center for this model, both store orders and consumer orders are received, picked, packed, and shipped. One advantage to this model is low start-up costs. If the retailer has an established distribution network that handles store orders and then decides to develop an Internet presence, the existing network can service both. In other words, new distribution centers need not be built. This would also eliminate the need to have a duplicate inventory to handle the Internet orders. Another advantage to this model is workforce efficiency because of consolidated operations. The existing workforce now has an opportunity to move more volume through a fixed-cost facility. However, this model has several challenges. First, the order profile will change with the addition of consumer Internet orders. While store orders would probably be picked in case and/or pallet quantities, consumer orders would require eaches in smaller order quantities. Second, products might not be available in consumer units (eaches).

Dedicated Fulfillment Another option for the retailer that desires to have both a store and an Internet presence is called dedicated fulfillment. Dedicated fulfillment achieves the same delivery goals as integrated fulfillment but with two separate distribution networks. Having a separate distribution network for store delivery and consumer delivery eliminates most of the disadvantages of integrated fulfillment. However, now the retailer is faced with duplicate facilities and duplicate inventories. This assumes that the retailer offers exactly the same product offering through both channels. However, many retailers offer many more products on their Internet sites than they offer in their stores. This makes dedicated fulfillment a more logical choice.

Outsourced Fulfillment While both integrated and dedicated fulfillment assume that the retailer will perform the fulfillment itself, outsourced fulfillment assumes that another firm will perform the fulfillment. One advantage of this outsourcing is low start-up costs for the retailer to service the Internet channel. Also, possible transportation economies could result from using outsourced fulfillment for Internet orders. A major disadvantage often cited with outsourcing fulfillment is the loss of control the retailer might experience over service levels. So, the major benefit of outsourced fulfillment is the ability to use existing external expertise in fulfillment. The major disadvantage of this model is the potential loss of control.

Drop-shipped fulfillment is also referred to as direct store delivery. In this model, the manufacturer delivers its product directly to a retailer's stores, bypassing the retailer's distribution network. A major advantage of this model is the reduction of inventory in the distribution network. This occurs because the retailer does not need to stock the vendor's inventory in its distribution centers. Another major advantage to the vendor is the direct control of its inventories at the store level. A disadvantage to the retailer is the possible reduction of inventory visibility of the vendor's products since the retailer does not "touch" these products in its distribution network. This type of model requires close collaboration and agreement between the manufacturer and retailer for several reasons. First, not every retailer supplier can do drop-shipped fulfillment. From a practical perspective, if every supplier to a store delivered direct on a daily basis, the number of delivery vehicles and manufacturer personnel in a store would cause overwhelming congestion at the store. Second, the retailer and manufacturer need to agree on the types and timing of information shared on inventory levels to provide the retailer with the proper level of inventory visibility. Finally, drop-shipped fulfillment works best for products that have a short shelf life and/or where freshness is a requirement. As such, this model makes sense for a limited number of products sold in a retail store.

Store Fulfillment For a retailer that has both a storefront as well as an Internet presence, store fulfillment can offer several opportunities. In this model, the order is placed through the Internet site. The order is sent to the nearest retail store where it is picked and put aside for the customer to pick up. Several advantages exist for this type of fulfillment. First, there is a short lead time to the customer, if the item is in stock. Second, there are low start-up costs for the retailer. Inventory is already in place in close proximity to the consumer. Third, returns can be handled in the usual manner through the retail store. Finally, the product will be available in consumer units. Store Fulfillment For a retailer that has both a storefront as well as an Internet presence, store fulfillment can offer several opportunities. In this model, the order is placed through the Internet site. The order is sent to the nearest retail store where it is picked and put aside for the customer to pick up. Several advantages exist for this type of fulfillment. First, there is a short lead time to the customer, if the item is in stock. Second, there are low start-up costs for the retailer. Inventory is already in place in close proximity to the consumer. Third, returns can be handled in the usual manner through the retail store. Finally, the product will be available in consumer units.

Flow-Through Fulfillment The main difference between the two is that in flow-through fulfillment the product is picked and packed at the retailer's distribution center and then sent to the store for customer pickup. Again, this is a common method used in the consumer electronics retailing industry. The flowthrough model eliminates the inventory conflict the store might realize between store sales and Internet sales. Because the consumer is providing the pickup service, the retailer avoids the cost of the "last mile." The retailer also does not need store level inventory status in the flow-through model. Returns can be handled through the existing store network, as in store fulfillment. Storage space at the store for pickup items remains an issue.