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Solution Manual for Business Logistics/Supply Chain Management, 5th Edition

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    Business Logistics/ Supply Chain Management Planning, Organizing, and Controlling the Supply Chain Fifth Edition Solution Manual Ronald H. Ballou Weatherhead School of Management Case Western Reserve University

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    ii CONTENTS Preface iii Chapter 1 Business Logistics/Supply Chain  A Vital Subject……… 1 2 Logistics/Supply Chain Strategy and Planning…………… 2 3 The Logistics/Supply Chain Product...…………………… 4 4 Logistics/Supply Chain Customer Service…..…………… 9 5 Order Processing and Information Systems………………. 13 6 Transport Fundamentals………………………………….. 14 7 Transport Decisions………………………………………. Fowler Distributing Company………………………….. Metrohealth Medical Center……………………………. Orion Foods, Inc………………………………............... R & T Wholesalers……………………………………... 17 35 41 48 52 8 Forecasting Supply Chain Requirements…………….…… World Oil……………………………………………….. Metro Hospital …………………………………………. 65 84 88 9 Inventory Policy Decisions……………………………….. Complete Hardware Supply, Inc….…………………….. American Lighting Products……………………………. American Red Cross: Blood Services………………….. 94 121 124 131 10 Purchasing and Supply Scheduling Decisions……………. Industrial Distributors, Inc……………………………… 134 144 11 The Storage and Handling System………………………... 147 12 Storage and Handling Decisions………………………….. 148 13 Facility Location Decisions………………………………. Superior Medical Equipment Company……………….... Ohio Auto & Driver’s License Bureau…………………. Southern Brewery ……………………………………… 162 186 190 198 14 The Logistics Planning Process…………………………... Usemore Soap Company………………….…………….. Essen USA………………….…………….. 204 208 217 15 Logistics/Supply Chain Organization……………………. 229 16 Logistics/Supply Chain Control……………..……………. 230

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    1 CHAPTER 1 BUSINESS LOGISTICS/SUPPLY CHAIN  A VITAL SUBJECT 12 (a) This problem introduces the student to the evaluation of alternate channels of production and distribution. To know whether domestic or foreign production is least expensive, the total of production and distribution costs must be computed from the source point to the marketplace. Two alternatives are suggested, and they can be compared as follows. Production at Houston: Total cost = Production cost at Houston + Transportation and storage costs = $8/shirt  100,000 shirts + $5/cwt.  1,000 cwt. = $805,000/year Production at Taiwan: Total cost = Production cost in Taiwan + Transportation and storage costs from Taiwan to Chicago + Import duty + Raw material transportation cost from Houston to Taiwan = $4/shirt  100,000 shirts + $6/cwt.  1,000 cwt. + $0.5/shirt  100,000 shirts + $2/cwt.  1,000 cwt. = $458,000/year Producing in Taiwan would appear to be the least expensive. (b) Other factors to consider before a final decision is made might be: (i) How reliable would international transportation be compared with domestic transportation? (ii) What is the business climate in Taiwan such that costs might change in favor of Houston as a production point? (iii) How likely is it that the needed transportation and storage will be available? (iv) If the market were to expand, would there be adequate production capacity available to support the increased demand?

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    2 CHAPTER 2 LOGISTICS/SUPPLY CHAIN STRATEGY AND PLANNING 13 The purpose of this exercise is to allow the student, in an elementary way, to examine the tradeoffs between transportation and inventory-related costs when an incentive transportation rate is offered. Whether the incentive rate should be implemented depends on the shipment size corresponding to the minimum of the sum of transportation, inven- tory, and order processing costs. These costs are determined for various shipping quantities that might be selected to cover the range of shipment sizes implied in the problem. Table 2-1 gives a summary of the costs to Monarch for various shipment sizes. From Monarch's point of view, the incentive rate would be beneficial. Shipment sizes should be approximately doubled so that the 40,000 lb. minimum is achieved. It is important to note that the individual cost elements are not necessarily at a minimum at low shipment sizes, whereas order-processing costs are low at high shipment sizes. They are in cost conflict with each other. Transportation costs are low at high shipment sizes, but exact costs depend on the minimum volume for which the rate is quoted. In preparation for a broader planning perspective to be considered later in the text, the student might be asked what the place of the supplier is in this decision. How does he affect the decision, and how is he affected by it? This will focus the student's attention on the broader issues of the physical distribution channel.

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    3 TABLE 2-1 Evaluation of Alternative Shipment Sizes for the Monarch Electric Company Current Proposed Type of cost 57 motors or 10,000 lb. 114 motors or 20,000 lb. 171 motors or 30,000 lb. 228 motors or 40,000 lb. 285 motors or 50,000 lb. Transportation R  D 9  8,750 = $78,750 5  8,750 = $43,750 5  8,750 = $43,750 3  8,750 = $26,250 a 3  8,750 = $26,250 Inventory carrying b I  C  Q/2 0.25  200  57/2 = $1,425 a 0.25  200  114/2 = $2,850 0.25  200  171/2 = $4,275 0.25  200  228/2 = $5,700 0.25  200  285/2 = $7,125 Order processing c D  S/Q 5,000  15/57 = $1,316 5,000  15/114 = $658 5,000  15/171 = $439 5,000  15/228 = $329 5,000  15/285 = $263 a Handling H  D 0.30  8,750 = $2,625 0.30  8,750 = $2,625 0.30  8,750 = $2,625 0.30  8,750 = $2,625 0.30  8,750 = $2,625 Total $84,116 $49,883 $51,089 $34,904 a $36,263 a Minimum values. b Students should be informed that average inventory can be approximated by one half the shipment size. c Demand D has been converted to units per year. LEGEND R = transportation rate, $/cwt. D = annual demand, cwt. I = inventory carrying cost, %/year. C = cost of a motor, $/motor. Q = shipment size in motors, where Q/2 represents the average number of motors maintained in inventory. S = order processing costs, $/order. H = handling costs, $/cwt.

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    4 CHAPTER 3 THE LOGISTICS/SUPPLY CHAIN PRODUCT 3 The 80-20 principle applies to sales and items where 80 percent of the dollar volume is generated from 20 percent of the product items. While this ratio rarely holds exactly in practice, the concept does. We can apply it to these data by ranking the products by sales, and the percentage that the cumulative sales represent of the total. The following table shows the calculations. The 80-20 rule cannot be applied exactly, since the cumulative percent of items does not break at precisely 20 percent. However, we might decide that only products 08776 and 12121 should be ordered directly from vendors. The important principle derived from the 80-20 rule is that not every item is of equal importance to the firm, and that dif- ferent channels of distribution can be used to handle them. The 80-20 rule gives some rational basis for deciding which products should be shipped directly from vendors and which are more economically handled through a system of warehouses. 6 (a) Reading the ground transport rates for the appropriate zone as determined by zip code and the weight of 27 lb. (rounding upward of 26.5 lb.) gives the following total cost table for the four shipments. Product code Dollar sales Cumulative sales Cumulative sales as % of total Cumulative items as % of total 08776 $71,000 $ 71,000 18.2 8.3 12121 63,000 134,000 34.3 16.7 10732 56,000 190,000 48.6 25.0 11693 51,000 241,000 61.6 33.3 10614 46,000 287,000 73.4 41.7 12077 27,000 314,000 80.3 50.0 07071 22,000 336,000 85.9 58.3 10542 18,000 336,000 90.5 66.7 06692 14,000 354,000 94.1 75.0 09721 10,000 368,000 96.7 83.3 14217 9,000 378,000 98.9 91.7 11007 4,000 391,000 100.0 100.0 Total $391,000

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    5 (b) The transport rate structure is reasonably fair, since ground rates generally follow distance and size of shipment. These are the factors most directly affecting transport costs. They are not fair in the sense that customers within a zone are all charged the same rate, regardless of their distance from the shipment origin point. However, all customers may benefit from lower overall rates due to this simplified zone-rate structure. 10 (a) This is a delivered pricing scheme where the seller includes the transport charges in the product price. The seller makes the transport arrangements. (b) The seller prices the product at the origin, but prepays any freight charges; however, the buyer owns the goods in transit. (c) This is a delivered pricing scheme where the freight charges are included in the product price, however the freight charges are then deducted from the invoice, and the seller owns the goods in transit. (d) The seller initially pays the freight charges, but they are then collected from the buyer by adding them to the invoice. The buyer owns the goods in transit, since the pricing is f.o.b. origin. (e) The price is f.o.b. origin. The buyer pays the freight charges and owns the goods in transit. Regardless of the price policy, the customer will ultimately pay all costs. If a firm does not consider outbound freight charges, the design of the distribution system will be different than if it does. Since pricing policy is an arbitrary decision, it can be argued that transport charges should be considered in decision making, whether the supplying firm directly incurs them or not. 11 This shows how Pareto's law (80-20 principle) is useful in estimating inventory levels when a portion of the product line is to be held in inventory. An empirical function that approximates the 80-20 curve is used to estimate the level of sales for each product to be held in inventory. According to Equation 3-2, the constant A is determined as follows. To zip code Catalog price UPS zone Transport cost a Total cost 11107 $99.95 2 $ 7.37 $107.32 42117 99.95 5 10.46 110.41 74001 99.95 6 13.17 113.12 59615 99.95 8 18.29 118.24 a Use 27 lb.

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    6 A X Y Y X        ( ) . ( . ) . . . 1 0 25 1 75 0 75 0 25 0125 The 80-20 type curve according to Equation 3-1 is: Y A A X X X       ( ) ( . ) . 1 1 0125 0125 This formula can be used to estimate the cumulative sales from the cumulative item proportion. For example, item 1 is 0.05 of the total number of items (20) so that: Y     ( . )( . ) . . . 1 0125 0 05 0125 0 05 0 321 Of the $2,600,000 in total annual warehouse sales, item 1 should account for 0.321  2,600,000 = $835,714. By applying this formula to all items, the following inventory investment table can be developed which shows sales by item. The average inventory investment by item is found by dividing the turnover ratio into the item sales. The sum of the average inventory value for each item gives a total projected inventory of $380,000. Inventory Investment Table Pro- duct Cumulative item pro- portion, X Cumulative sales, Y Projected item sales Turnover ratio Average inventory value 1 0.05 $ 835,714 $ 835,714 8 $104,464 2 0.10 1,300,000 464,286 8 58,036 3 0.15 1,595,454 295,454 8 36,932 4 0.20 1,800,000 204,546 8 25,568 5 0.25 1,950,000 150,000 6 25,000 6 0.30 2,064,705 114,706 6 19,118 7 B 0.35 2,155,263 90,558 6 15,093 8 0.40 2,228,571 73,308 6 12,218 9 0.45 2,289,130 60,559 6 10,093 10 0.50 2,340,000 50,870 6 8,478 11 0.55 2,383,333 43,333 4 10,833 12 0.60 2,420,689 37,356 4 9,339 13 0.65 2,453,226 32,537 4 8,134 14 0.70 2,481,818 28,592 4 7,148 15 C 0.75 2,507,142 25,324 4 6,331 16 0.80 2,529,719 22,587 4 5,647 17 0.85 2,550,000 20,271 4 5,068 18 0.90 2,568,293 18,293 4 4,473 19 0.95 2,584,884 16,591 4 4,148 20 1.00 2,600,000 15,116 4 3,779 Total $380,000 A

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    7 12 This problem involves the application of Equations 3-1 and 3-2. We can develop an 80- 20 curve based on 30 percent of the items accounting for 70 percent of sales. That is, A X Y Y X        ( ) . ( . ) . . . 1 0 30 1 0 70 0 70 0 30 0 225 Therefore, the sales estimating equation is: Y X X    ( . ) . 1 0 225 0 225 By applying this estimating curve, we can find the sales of A and B items. For example, 20 percent of the items, or 0.2  20 = 4 items, will be A items with a cumulative proportion of sales of: Y A     ( . )( . ) . . . 1 0 225 0 20 0 225 0 20 0 5765 and 3,000,000  0.5765 = 1,729,412. The A + B item proportion will be: Y A B      ( . )( . ) . . . 1 0 225 0 50 0 225 0 50 0 8448 and 3,000,000  0.8448 = 2,534,400. The product group B sales will A + B sales less A sales, or 2,534,400  1,729,412 = $804,988. The product group C will be the remaining sales, but these are not of particular interest in this problem. The average inventories for A and B products are found by dividing the estimated sales by the turnover ratio. That is, A : 1,729,412/9 = 192,157 B : 804,988/5 = 160,988 Total inventory 353,155 cases The total cubic footage required for this inventory would be 353,155  1.5 = 529,732 cu. ft. The total square footage for products A and B is divided by the stacking height. That is, 529,731/16 = 33,108 sq. ft.

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    8 13 This problem is an application of Equations 3-1 and 3-2. We first determine the constant A . That is, A X Y Y X        ( ) . ( . ) . . . 1 0 20 1 0 65 0 65 0 20 0156 and 0 75 1 0156 0156 . ( . ) .    X X Solving algebraically for X , we have: X AxY A Y x        1 0156 0 75 1 0156 0 75 0 288 . . . . . That is, about 29% of the items (0.288  5,000 = 1,440 items) produce 75% of the sales. 14 The price would be the sum of all costs plus an increment for profit to place the automotive component in the hands of the customer. This would be 25+10+5+8+5+transportation cost, or 53+ T . Based on the varying transportation cost, the following price schedule can be developed. Quantity Price per unit Discount 1 to 1,000 units 53+5=$58 0 1,001 to 2,000 units 53+4.00=57 1.7% a >2,000 units 53+3.00=56 3.5% a [(58 - 57)/58][100]=1.7%

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    9 CHAPTER 4 LOGISTICS/SUPPLY CHAIN CUSTOMER SERVICE 6 (a) This company is fortunate to be able to estimate the sales level that can be achieved at various levels of distribution service. Because of this, the company should seek to maximize the difference between sales and costs. These differences are summarized as follows. Percent of orders delivered within 1 day Contribution to 50 60 70 80 90 95 100 profit -1.8 2.0 3.5 4.0 3.4 2.8 -2.0 The company should strive to make deliveries within 1 day 80 percent of the time for a maximum contribution to profit. (b) If a competing company sets its delivery time so that more than 80 percent of the orders are delivered in 1 day and all other factors that attract customers are the same, the company will lose customers to its competitor, as the sales curve will have shifted downward. Cleanco should adjust its service level once again to the point where the profit contribution is maximized. Of course, there is no guarantee that the previous level of profits can be achieved unless the costs of supplying the service can correspondingly be reduced. 7 (a) This problem solution requires some understanding of experimental design and statistical inference, which are not specifically discussed in the text. Alert the students to this. The first task is to determine the increase in sales that can be attributed to the change in the service policy. To determine if there is a significant change in the control group, we set up the following hypothesis test. z X X s N s N          2 1 2 2 2 1 2 1 2 2 224 185 61 102 79 102 39 36 48 6118 394 . . . Now, referring to a normal distribution table in Appendix A of the text, there is a significant difference at the 0.01 level in the sales associated with the control group. That is, some factors other than the service policy alone are causing sales to increase. Next, we analyze the test group in the same manner.

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    10 z       2 295 1 342 576 56 335 56 953 5 924 2 004 10 7 2 2 , , , , . This change is also significant at the 0.01 level. The average increase in sales for the control group is 224/185 = 1.21, or 21%. The average sales increase in the test group is 2295/1342 = 1.71, or 71%. If we believe that 21% of the 71% increase in the test group is due to factors other than service policy, then 71  21 = 50% was the true service effect. Therefore, for each sales unit, an incremental increase in profit of (0.40  95)(0.50) = $19 can be realized. Since the cost of the service improvement is $2, the benefit exceeds the cost. The service improvement should be continued. Note : If the students are not well versed in statistical methodology, you may wish to instruct them to consider the before and after differences in the mean values of both groups as significant. The solution will be the same. (b) The use of the before-after-with-control-group experimental design is a methodology that has been used for some time, especially in marketing research studies. The outstanding feature of the design is that the use of the control group helps to isolate the effect of the single service variable. On the other hand, there are a number of potential problems with the methodology:  The sales distributions may not be normal.  The time that it takes for diffusing the information that a service change has taken place may distort the results.  The products in the control group may not be mutually exclusive from those in the test group.  The method only shows the effect of a single step change in service and does not develop a sales-service relationship.  It may not always be practical to introduce service changes into on-going operations to test the effect. 8 (a) The optimum service level is set at that point where the change in gross profit equals the change in cost. The change in gross profit:  P = Trading margin  Sales response rate  Annual sales = 1.00  0.0015  100,000 = $150 per year per 1% change in the service level The change in cost:  C = Annual carrying cost  Standard product cost   z

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    11  Demand standard deviation for order cycle = 0.30  10.00  400  z Now, set  P =  C and solve for  z . 150 = 1200  z  z = 0.125 From the tabulated changes in service level with those changes in z , the service level should be set between 96-97%. (b) The weakest link in this analysis is estimating the effect that a change in service will have on revenue. This implies that a sales-service relationship is known. 9 The methodology is essentially the same as that in question 7, except that we are asked to find X instead of Y . That is,  P = 0.75  0.0015  80,000 = 90 and  C = 0.25  1,000  500  z = 1250  z Then,  P =  C 90 = 1250  z  z = 0.072 From the normal distribution (see Appendix A), the z for an area under the curve of 93% is 1.48, and for 92%, z is 1.41. Since the difference of 1.48  1.41 = 0.07, we can conclude that the in-stock probability should be set at 92-93%. Of course, the change in z is found by taking the difference in z values for 1% differences in the area values under the normal distribution curve for a wide range of area percentages. 10 Apply Taguchi’s concept of the loss function. First, estimate the loss per item if the target level of service is not met. We know the profit per item as follows.

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    12 Sales price $5.95 Cost of item -4.25 Other costs -0.30 Profit per item $1.40 Since one-half of the sales are lost, the opportunity loss per item would be /item 70 . 0 $ 880 (1/2)(880) $1.40 loss y Opportunit    Next, find k in the loss function. L k y m k k k       ( ) . ( ) . ( ) . 2 2 0 70 10 5 0 70 25 0 03 Finally, the point where the marginal supply cost equals the marginal sales loss is % 67 . 1 ) 03 . 0 ( 2 10 . 0 2 ) 5 (     k B y % 67 . 6 5 67 . 1    y The retailer should not allow the out-of-stock percentage to deviate more than 1.67%, and should not allow the out-of-stock level to fall below 1.67 + 5 = 6.67%. Profit per item Sales lost Current sales Target % out-of-stock % at point where ½ sales are lost

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    13 CHAPTER 5 ORDER PROCESSING AND INFORMATION SYSTEMS All questions in this chapter require individual judgment and response. No answers are offered.

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