Developing a framework for
evaluating the logistics costs in
global sourcing processes
An implementation and insights
Amy Z. Zeng
Department of Management, Worcester Polytechnic Institute, Worcester, Massachusetts, USA, and
Christian Rossetti
Department of Supply Chain Management, College of Business, Arizona State University, Tempe, Arizona, USA
Keywords Sourcing, Transportation, Logistics, Performance measures, Case studies AbstractGlobal sourcing is becoming a prerequisite for companies competing in today’s market. The logistics costs often comprise a large portion of the total global sourcing cost, thereby determining the effectiveness of this procurement strategy. However, evaluating the logistics cost in a global context is frequently difficult. This paper presents a five-step evaluation framework and illustrates how this framework can be implemented using a case study at a leading firm in the US aviation industry and its part supplier in Chengdu, China. The framework not only identifies the key logistics cost items, but also suggests a way of quantifying each of the cost elements. The computational part of the framework can be easily implemented on spreadsheets and offers substantial flexibility to accommodate assessment of various transportation alternatives and sensitivity analysis.
1. Introduction
Improved technology and intensified competition have enabled and forced companies to expand their markets worldwide. The most successful companies often develop their products in Europe and the USA, manufacture in Asia and Latin America, and sell worldwide (Burnson, 1999). As one of the consequences of this trend, global sourcing has rapidly arisen as a prerequisite for companies competing in today’s market. Defined by Monczka and Trent (1991), global sourcing is the integration and coordination of procurement requirements across worldwide business units, looking at common items, processes, technologies, and suppliers. This procurement strategy has extended organizations’ supply chains to a global scale.
The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at
http://www.emeraldinsight.com/researchregister http://www.emeraldinsight.com/0960-0035.htm
The authors would like to thank APICS – the E&R Foundation and Supply Chain Council for their financial support for this project (Grant #2000-3) and the inputs and participation of the two companies. The authors would also like to extend their gratitude to the reviewers for their thoughtful and constructive comments, which have helped improve the quality of this paper.
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International Journal of Physical Distribution & Logistics Management Vol. 33 No. 9, 2003 pp. 785-803
qMCB UP Limited 0960-0035 DOI 10.1108/09600030310503334
Logistics processes form the critical loops of supply chains and oversee the flows of materials, information and cash, which are the essential elements of fulfilling customers’ orders. As greater distances, currencies and cultures separate markets, suppliers and manufacturers, logistics plays a more critical role in the success of the supply chains. As a result, total logistics cost has become one of the most important economic indicators of supply chain efficiency. Gilmore (2002) explicitly points out that there is a growing recognition of the role that transportation and logistics excellence plays in achieving a world-class supply chain and that transportation costs represent a substantial component of overall supply chain and corporate spend for many companies.
The costs associated with logistics activities normally consist of the following components: transportation, warehousing, order processing/customer service, administration, and inventory holding (e.g. Lambert et al., 1998; Saccomano, 1999). Not surprisingly, total logistics costs often represent a large portion of total supply chain costs, especially when the supply chain is extended to the global market. For example, previous studies have found that logistics costs have ranged from 4 to over 30 percent of sales (Ballou, 1999). As more organizations are outsourcing their products or services to global suppliers, it becomes increasingly critical to understand and evaluate the various logistics cost components in order to assure the profit margin.
However, the existing methodologies for evaluating the total logistics cost, especially of global supply chains, are sparse due in large part to the complexity of a global logistics system and the variety of cost items involved. This paper relies on the practices, experiences, and data of a leading firm in the US aviation industry and one of its part suppliers in China to derive and implement an evaluation framework for assessing the total logistics cost. As requested by the companies, we will disguise their identities and refer to the parent company in the USA as company P and its joint venture in China as JV throughout the paper.
There are numerous items that define a successful outsourcing relationship. The two companies must confront issues that include forecasting, differences in internal operations, coordination of business activities, previous partnerships, and relationships between the providers of raw materials, freight forwarders and end customers. In addition, outsourcing to China involves the increased difficulties associated with differences in culture, language, poor inland transportation and antiquated customs procedures.
Recently many authors have attempted to provide a framework for a more holistic view of outsourcing relationships; however, in this paper, we have limited our focus to the cost-effectiveness of the companies’ global logistics systems. Thus, the major objectives of this study are three-fold and explained as follows. First, the major cost components of the global logistics systems are identified and documented for analysis. Company P, a partial sponsor of this
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research, requested that the cost components remain valid regardless of the national origin of the outsourcing partner, therefore, these components retain a generality that allows their transference to future research and case analyses. Second, a framework for classifying and evaluating the logistics cost components is presented. Finally, we demonstrate how this framework can be implemented on spreadsheet using the data we have collected from the two companies. Furthermore, we provide examples of sensitivity analysis to illustrate the flexibility of this spreadsheet-based evaluation procedure and the robustness of the framework.
This paper is organized in the following manner. In section 2, a brief description of the background and history of these two companies is given. Their business relationships and the characteristics of the global logistics system are also provided. Section 3 contains a review of existing literature related to logistics cost analysis. In section 4, the categories of the logistics cost items resulting from the case study are presented, followed by a detailed description of our five-step evaluation framework. In section 5 we discuss the implementation of our evaluation procedure on the spreadsheet, sensitivity analysis, and a summary of managerial implications. Finally, concluding remarks including a discussion of the limitations of the newly developed evaluation framework and future research direction are given in section 6. 2. The companies
2.1 Background
Company P is a leader in the design, manufacture and support of engines for commercial, military and general aviation aircraft, and space propulsion systems. The demand for company P’s products in today’s competitive aviation industry is thrust at the lowest possible cost with the highest level of reliability. In a business that shrinks the globe, company P is truly worldwide, having established partnerships and joint ventures that reach to Asia and Europe and have kept the company at the forefront of flight.
Given the complexity and history of aircraft engine development, vertical integration was traditionally the dominant form of business structure in the aviation propulsion industry. However, potential market penetration, high cost of development, and fierce competition from foreign suppliers have fueled the desire of several large aircraft engine manufacturers in the USA to go global. The competitive bidding procedure used in purchasing company P’s engines by government owned airlines often requires company P to accept different forms of payment or requirements not usually found in normal purchase agreements. In our case study, as company P attempted to penetrate the Chinese market in the early 1990s, the Chinese government asked for job opportunities for Chinese workers and technology transfer for its own aviation industry. Company P complied by forming a joint venture (JV) in Sichuan Province in 1996. Company P supplied the initial capital investment and
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machinery for the project and continues to provide technical assistance and tooling for the JV. The JV has since become the primary manufacturer of four types of engine parts: burner cans, pin disks, shrouds, and shroud vane assemblies.
Due to the high reliability necessary for safe air transportation, the raw materials (such as metal sheets) for any engine parts and subassemblies must satisfy the stringent standards set forth by the Federal Aviation Association. The current certified suppliers of the raw materials are only located in North America and Europe. In addition, not only is China unable to provide these raw materials, but due to United States national security laws, company P cannot help the JV develop internal sources. As a result of this and the desire by company P to limit cash held by the JV, the two companies have formed a vendor-required-material (VRM) relationship since the first day of operation of the JV. In this VRM relationship, company P purchases the raw materials from one of its licensed suppliers and sends the materials through a preferred freight forwarder to the JV. It also holds the financial responsibility for shipping the material to and from the JV and paying the value-added service provided by the JV. Adding to this heavy financial burden is the major transportation mode that is currently adopted by company P: the raw materials as well as the finished engine parts are primarily shipped by air between its headquarters and Chengdu, China, due to various reasons. As company P outsources more parts to its joint venture located in the Far East, it is increasingly concerned with the logistics costs associated with moving raw materials and finished products. For this reason, one of the major challenges confronted by company P is the proper evaluation of the cost and profitability associated with the aircraft engine parts outsourced in China and other countries.
2.2 Transportation and distribution
The JV is located in Chengdu, Sichuan province, China. Chengdu is an inland city with population of 9.5 million and surrounded by mountains that make land transportation difficult even under the best conditions. Because of the disparity between global transportation and transportation within inland China we have divided the logistics network into two major segments: outside of China and within China. After careful consultation with the two companies, several freight forwarders, and a series of long-haul drivers, we present the backbone of the global sourcing process in the form of possible transportation routes and modes as illustrated in Figure 1. This figure is valid for inbound shipments of raw material and outbound shipments of finished goods. Of mode possibilities, we see from Figure 1 that air can be used entirely between the two companies and that, if water is chosen for transport between company P and Shanghai, then either truck or rail can be utilized to move materials between Shanghai and Chengdu. Note that
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Shanghai is a major port city in China and about 1,000 kilometers from Chengdu. Therefore, three potential transportation modes, namely all air, water-rail combination, and water-truck combination, are possible. In addition, both full container load (F) and less-than container load (L) for truck and rail should be examined. As a result, a total of five potential transportation alternatives, namely water-rail full container load (WRF), water-rail less-than container load (WRL), water-truck full container load (WKF), water-truck less-than container load (WKL), and air, become potential candidates for moving raw materials and finished goods.
3. Evaluating total logistics cost: literature review
The majority of prior research on logistics costs can be grouped into two streams. One stream focuses on strategic aspects of the logistics costs, and the
Figure 1.
The transportation routes for the material flow
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other deals with optimized cost-effective logistics decisions. There is a large body of literature pertinent to the strategic role logistics plays in creating value and its relationship to a company’s financial performance. As reported by Richardson (1995) and later stressed by Gilmore (2002), logistics controls a significant amount of assets and has direct impact on cash flow and the bottom line, adds value through continuous productivity and service improvements, and possesses a strong relationship with a firm’s customer service level and revenues. As global sourcing is rapidly arising as an important business strategy, capturing and evaluating the logistics costs involved in the global supply chain appears as increasingly critical and important as uncovering the strategic benefits (Fagan, 1991). Numerous factors can drive up logistics costs substantially, which may offset the benefits of doing business with the international suppliers.
The techniques utilized to analyze the logistics cost can be summarized into four categories: recurrence-based, regression-based, activity-based, and optimization-based. For example, a previous study completed by Fera (1998) attempts to identify and classify the relevant cost factors for evaluating the feasibility of the international outsourcing strategy for company P. A comprehensive list of recurring and non-recurring cost items accounting for international sourcing is provided for future analysis. Zoroya (1998) presents a regression model to measure the cost drivers of shippers’ transportation expenses, where three time-based factors are used to examine what influences the price of a transportation lane. The activity-based costing approach to accounting for the logistics costs is presented by van Damme and van der Zon (1999), which helps top management analyze the financial information in order to make logistics decisions.
The other stream, using the optimization-based method, comprises a large body of literature on analyzing the system logistics costs. This technique normally attempts to optimize the total logistics cost including transportation in conjunction with inventory and purchasing decisions. The earliest studies of transportation and logistics costs arose from economic analyses relating to the cost of perfect competition between firms competing in the same market but producing in different locations. It was not until the early 1970s, however, with the promotion of air movement that comprehensive comparisons of inter-modal freight options, which considered the inventory holding cost associated with transportation time, were presented. Table I provides an overview of a number of topical areas that have been covered in existing studies. The optimization-based method has significant limitations with respect to the number of cost items, the effect of international trade, and the possibility of finding the closed-form or easy solutions.
In this paper we extend the logistics cost categorization proposed by Maltz and Ellram (1997) and present a new way to classify the cost items based on the global logistics system of the two companies under investigation. The logistics
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Topics covered Selected authors Remarks Comparison of air freight with other modes Slijper (1979) Total logistics cost is used as a criterion Incorporating transportation costs in supply chain management decisions Carter and Ferrin (1995) An integrative approach is utilized Optimization of total cost Scharty and Larsen (1995) Only transport and inventory costs are considered Freight cost estimation in logistics decisions Swenseth and Godfrey (1996) Five estimation methods are presented Freight cost structure and the cost of locating manufacturing facilities in a foreign country Liao (1997) The only international factors included in the total cost model are those of duties and taxes Cost and service tradeoff Tyagi and Das (1997) A mathematical programming model based on analytic hierarchy process Joint optimal decisions of purchasing, inventory holding and transportation Tyworth and Zeng (1998) Only one transportation mode is considered There is no international factor Modeling the effects of uncertainties in global logistics systems Vidal and Goetschalckx (2000) The sensitivity of key cost drivers such as exchange rate and lead time on minimum total cost is evaluated A multi-modal transport cost model is used to clarify routing alternatives Banomyong and Beresford (2001) A confidence index is introduced for each route, transport modes and nodal links Direct and cross-elasticity estimates of the demands for three freight transportation modes: rail, road and inland waterways Beuthe et al . (2001) Ten different categories of goods with a detailed multi-modal network model of Belgian freight transports are evaluated An optimization model incorporating various global logistics items is developed Zeng (2002) Six categories of logistics cost items are incorporated in the model and the only decision variable is the shipping weight Table I. Examples of optimization-based research on logistics cost
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cost includes not only the classic cost components, but also items associated with international transportation. After these cost items are identified, we propose a framework for evaluating the effectiveness of various transportation alternatives, and then demonstrate how this framework can be easily accomplished by spreadsheets.
4. Proposed evaluation framework
4.1 Cost categories
The common concerns that many companies engaged in global sourcing have may include the most cost-effective transportation mode and the total amount spent on sourcing from foreign countries. It is generally agreed that manufacturing cost is significantly lower in developing countries; however, the extended distance, the coordination between the partners, and numerous other problems related to international trade often complicate the profit picture. Here we only address the logistical aspect of global sourcing. Currently, company P does not have a well-developed procedure for analyzing the associated data, nor has it established any centralized database to store and retrieve the information. Based on the data we have collected, we classify the logistics costs into six categories: transportation, inventory holding, administration, customs charges, risk and damage, and handling and packaging. Each category comprises a number of cost elements. The complete description of the categories is reported in Table II.
4.2 The evaluation framework
Once the logistics cost items are identified, we propose an evaluation procedure for assessing the costs associated with each available transportation alternative. The complete procedure can be depicted in Figure 2. The five steps involved in the procedure are explained as follows:
(1) Step 1. Identify the objective, which is to examine the logistics cost associated with global sourcing. The results will not only aid decision making in transportation mode selection, but also help the buying organization understand the costs and benefits associated with global sourcing.
(2) Step 2. Establish a set of possible modes and combination of modes available for transporting raw materials and finished goods in and out of the global manufacturer. As discussed before, for the companies under study, five alternatives need to be evaluated and compared simultaneously.
(3) Step 3. Develop the minimum number of input parameters required to ascertain the costs associated with the previously mentioned six logistics cost categories. For our study we were able to reduce the input parameters used to describe the operations of the two companies to nine variables, as listed below:
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Logistics cost category Brief definition
(1) Transportation Freight charge Cost incurred during delivery using various transportation modes Consolidation The fee for combining small
shipments to form larger shipments Transfer fee Cost incurred during the transfer of goods between different modes of transportation
Pickup and delivery Transportation charges incurred between shipper’s warehouse and air, rail consolidator’s terminal (2) Inventory holding Pipeline holding Holding cost during the transfer
Safety stock Holding cost of safety stock (3) Administration Order processing Salaries of employees responsible for
purchasing and order management Communication Telephone, fax and information
transfer related costs associated with international logistics
Overhead Rent paid by the international logistics group
(4) Customs Customs clearance Fee imposed by local customs to clear goods
Brokerage fee Charge levied by an agent acting on behalf of the shipper or the receiver depending on the delivery terms Allocation fee Per house-bill
(5) Risk and damage Damage/loss/delay Percentage of the value of each unit shipped that will be lost, damaged or delayed
Insurance Min $25 or $0.50 per $100.00 insured value
(6) Handling and packaging
Terminal handling Material handling fee charged by the transportation company
Material handling Cost of labor and equipment used to move goods within the shipper’s or receiver’s warehouse
In/out handling Material handling charge levied by the freight forwarder for use of its facilities
Disposal charge Fee for taking away an empty container from the receiver’s warehouse
Packaging/supplies materials Cost of preparing goods for shipment Storage Rental fee of the warehouse space
Table II.
Total logistics cost elements
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. raw material costs ($/unit); . finished product cost ($/unit);
. holding cost percentage at the JV (%). . holding cost percentage at company P (%); . total yearly demand (units/year);
. weight of raw material (kg/unit); . weight of finished part (kg/unit);
. shipment frequency of raw materials per year; and . shipment frequency of finished products per year;
Figure 2.
The evaluation procedure of the total logistics cost
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It should be pointed out that since the JV manufactures multiple engine parts, aggregated values of the above parameters should be used for calculation.
(4) Step 4. Re-classify the cost elements into three groups: weight-based, value-based, and shipment frequency-based based on the dimensions of the cost elements and input parameters. Using current freight rate structures, the cost of capital and operating procedures for the companies can all be converted to dollar values.
(5) Step 5. Calculate the annual total logistics cost for moving materials between the parent company and the JV for each particular transportation mode, and construct a cost matrix containing the logistics cost of moving materials in both directions. As an immediate result, the most economic transportation mode can be identified from the cost matrix.
In addition to the cost matrix, the computational results can also help obtain a series of percentages of the logistics cost relative to the values of raw materials, value-added services, or the finished parts, respectively. These percentages are extremely useful in evaluating the effectiveness of sourcing alternatives as well as providing increased awareness of the importance of the total logistics costs. These percentages can be calculated in the following way:
vr¼
Annual logistics costUS!CNð$Þ=Annual demandðunitsÞ
Original value of a raw materialð$=unitÞ ; ð1Þ
vVA ¼
Annual logistics costCN!USð$Þ=Annual demandðunitsÞ
Added value by the JV ð$=unitÞ ; ð2Þ
vf ¼
Annual total logistics costð$Þ=Annual demandðunitsÞ
Value of finished partð$=unitÞ : ð3Þ
5. Implementation of the framework
The preceding section has described the evaluation framework of total logistics costs in detail. In this section we will explain and demonstrate how the quantitative part of the framework, step 5, can be implemented on spreadsheets, such as MS-Excel.
5.1 The spreadsheet model
For the purpose of illustration, we will only show how step 5 is completed for air shipment. The computations for other transportation alternatives follow the same routine, and hence will not be repeated and demonstrated. The related data are collected from the two companies but are slightly modified for the protection of confidentiality.
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The entire calculation consists of four sections, as shown and explained in Table III-VI. The first section is the input area, which is common for all transportation options under evaluation. There are two parts in this section. The first contains the nine general input parameters, which serve as inputs for subsequent analysis and are used for all computations for each transportation mode of interest. An important parameter in this part is the annual shipping frequencies of raw materials and finished parts. Although this could be a decision variable that deserves a great deal of investigation, we assume that the values are known and determined by the logistics managers. For our demonstration we assume that the inbound and outbound annual shipping frequency equals 150, which is close to the current practice of company P. The effect of the shipping frequency on the logistics cost and mode selection will be discussed in the section of sensitivity analysis. The second part contains immediate results derived from the data in the first block.
Raw material costs $/unit 1,000
Finished product price $/unit 3,000
Cost of capital JV (%) 10
Cost of capital parent company (%) 12
Total yearly demand (units) 2,900
Weight of finished part (kg) 29
Weight of raw material (kg) 30.5
Shipments raw material/year 150
Shipments finished parts/year 150
Manufacturing time (wks) 6
Value raw material per shipment ($) 19,333
Value finished part per shipment ($) 58,000
Weight of raw material shipment (kg) 590
Weight of finished part shipment (kg) 561
Equivalent raw material/shipment 19
No. finished parts/shipment 19
Shipments raw material/year 150
Shipments finished parts/year 150
Manufacturing time (wks) 6
Table III.
Calculating the logistics cost for air shipment on spreadsheets. (1) Input area Kg Min 0 45 100 250 500 1,000 2,000 USA to China $/Kg 90 4.65 4.1 3.25 3.1 2.95 2.8 2.8 China to USA $/Kg 75 5.6 5.2 4.8 4.7 4.6 4.4 4.35 Transit times (days) Loss and damage (%/$) USA to China 6 0.50 China to USA 6 0.50 Table IV.
Calculating the logistics cost for air shipment on spreadsheets. (2) Parameters for a specific transportation mode
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The second section consists of the air freight-rate schemes for both inbound and outbound shipments, transit times, and the rates of loss and damage. The data in this section should be modified based on the transportation mode being considered. The associated calculations of all cost elements re-classified as the weight-based, frequency-based, and value-based are illustrated in the third section. Note that the same calculation is required for inbound and outbound. What is shown here is the calculation of logistics cost for moving materials from the USA to China and the result is a conversion of all cost items into dollar values on a per-shipment basis.
In the last section, the logistics cost per shipment is obtained as the sum of the three classified costs. If payment frequency is not parallel with the
Weight ($) Frequency ($) Value ($) Rate (%) Units Description 1,739.52 2.95 $/kg Weight rate
294.83 16.00 0.5 $/shipment and kg Pickup delivery charge
0 $/kg Storage
60.00 60 $/shipment Brokerage fees
50.00 50 $/shipment Order processing cost
30.00 30 $/shipment Terminal handling
charge
25.00 25 $/shipment Material handling
25.00 25 $/shipment Communication cost
25.00 25 $/shipment Overhead
15.00 15 $/shipment Allocation fee
5.00 5 $/shipment Airport transfer
5.00 5 $/shipment In/out handling
483.33 (2.5) Percent value Packaging/supplies material
0 Percent value Duties/tariffs 96.67 (0.50) Percent value Damage/loss/delay
6.77 (0.035) Percent value Insurance 343.23 (1.78) Time/value Pipeline inventory
cost (transit + mfg. time)
15.47 (0.08) Time/value Safety stock holding cost
2,034.35 256.00 945.47
Table V.
Calculating the logistics cost for air shipment on spreadsheets. (3) Calculation
Logistics cost per shipment $3,236
12 mos. present value $457,209
18 mos. present value $666,051
24 mos. present value $862,736
60 mos. present value $1,824,421
Table VI.
Calculating the logistics cost for air shipment on spreadsheets (4) Conversion to present values
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shipment frequency, then the present values of logistics cost can be used for comparison. The present values can be obtained easily using the built-in function “PV” in Excel. The interest rate used for this calculation is the hurdle rate of company P since it is assumed that these costs will be compared to costs of other suppliers as well as other logistics alternatives. If comparing the total logistics costs of all available transportation alternatives is needed, then the same calculation routine exhibited in Table II should be performed for each of the alternatives. The final results can be organized into a cost matrix, as shown in Table VII. The figures in italics are the logistics cost of moving materials in one direction, whereas others are the sums of logistics costs of the two directions. In particular, the numbers on the diagonal indicate the total logistics cost if the same transportation mode is used for both directions. This cost matrix can be used to identify the most economic combination of shipping options on the assumption that the values of all required parameters are known with certainty. In this case, the lowest total cost equals $975,925 per year.
Frequently transportation/logistics managers are concerned with the percentage of the value of the outsourced parts that is spent on the logistics activities, which is also an excellent measure of the soundness of the transportation policy. To get a better perspective on the weight of logistics cost relative to the original value of raw materials, value added through manufacturing, and the finished parts, we have calculated the three percentages using the equations (1)-(3) using the spreadsheets. We have found the following results:
. The raw material logistics costs percentages range from 12 percent to 41
percent, the highest value corresponding to full container shipments via inland transport by rail due to low shipment weight and the high per-shipment cost of the full container.
. The logistics costs of the value-added portion of the finished parts range
from 11 percent to 23 percent.
. The resulting total logistics cost can be as high as 29 percent of the value
of the finished product.
From China To China Air ($) WRF ($) WRL ($) WKF ($) WKL ($) One year PV ($) 717,479 1,350,363 676,922 1,097,349 613,873 Air 457,209 1,174,687 1,807,572 1,134,130 1,554,558 1,071,082 WRF 1,177,046 1,894,524 2,527,409 1,853,967 2,274,394 1,790,919 WRL 384,740 1,102,219 1,735,104 1,061,662 1,482,089 998,613 WKF 1,062,104 1,779,583 2,412,467 1,739,026 2,159,453 1,675,977 WKL 362,052 1,079,531 1,712,416 1,038,974 1,459,401 975,925 Table VII.
The cost matrix for all available transportation alternatives
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In summary, all these percentage values imply that logistics costs comprise a significant portion of the total global sourcing cost, and thus should be carefully tallied in order to understand the effectiveness of the global sourcing practice.
5.2 Sensitivity analysis
In a realistic business environment, the changing values of some of the key parameters may significantly alter the final decision regarding the mode selection and the magnitude of the logistics costs. In this section, we show that, based on the calculations presented in the preceding subsection, sensitivity analysis of the impacts of a number of the important parameters on the annual logistics cost and most economic transportation mode can be performed. The parameters chosen for examination include the shipping frequency, the annual unit demand, the weight of the product and raw materials, and the product value. The results derived from the sensitivity analyses are summarized and reported in Table VIII. In the table, “in” refers to materials movement to China, whereas “out” refers to the shipment of goods out of China, additionally, a check mark indicates the most economic transportation mode.
In the first analysis, shown in Table VIII(a), we varied the shipping frequency while keeping all other input variables constant; annual demand was 2,900 units, finished goods weight was 29kg per unit, average raw material cost was $1,000 per part and average finished part price was $3,000. As the shipping frequency increases, the shipping weight decreases, the value per shipment decreases, and the annual shipment costs increase. As would be expected, with lower frequencies, the model shows that full container shipment is most economical. As shipment frequency increases, the high cost of transporting the less-than full container far outweighs any savings derived from the flat rate structure. This has the effect of making less-than container load shipments the most economical but even at extremes, increasing shipping frequency does not promote air shipment. The second analysis, shown in Table VIII(b), reveals the effects of increasing total demand on choosing the best mode of transportation. The same inputs were used as in the previous analysis except that the shipping frequency was constant at the company’s current operating strategy – shipping raw materials 50 times per year and finished goods 150 times per year. Increasing demand caused the size of each shipment to increase in weight and value. This caused linear increases in total logistics costs for all modes of transportation. However, full container load modes increased at a lower rate showing that at high demand levels, full container loads become the most economical transportation solution independent of shipping frequency within the limits of the model.
Our third analysis, shown in Table VIII(c), demonstrates the effect of increasing the average unit weight on the best transportation mode while maintaining the inputs from the previous two analyses. This analysis also reveals the importance of part selection to the joint venture by the parent company. As the weight per unit part increases, the total logistics costs increase at a much slower rate. At a unit part weight of 175kg, the water-truck
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Mode Air WRF WRL WKF WKL
(A) The effect of shipment frequency on the choice of the best shipping mode
Frequency (in) 12 £ 24 £ 52 £ 100 £ 150 £ Frequency (out) 12 £ 24 £ 52 £ 100 £ 150 £
(B) The effect of annual demand on the choice of the best shipping mode
Demand (1,000) (in) 1 £ 2 £ 3 £ 4 £ 5 £ Demand (1,000) (out) 1 £ 2 £ 3 £ 4 £ 5 £
(C) The effect of shipping weight on the choice of the best shipping mode
Weight (in) 105 £ 131 £ 158 £ 184 £ 210 £ Weight (out) 100 £ 125 £ 150 £ 175 £ 200 £ (continued) Table VIII. Sensitivity analyses
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full container load becomes the most economical mode of inbound transportation. Furthermore, as the part weight continues to increase, the low cost outbound mode will transfer to full container load shipment.
Lastly, Table VIII(d) shows the effect of increasing average unit part price on the choice of the best shipping mode while maintaining the same constants as used in the previous analyses. By varying unit part price, we are directly affecting the costs in holding pipeline inventory, damage/loss, and insurance. As expected, a higher value of the finished products favor the air shipment.
It is seen that by following the evaluation framework developed in this paper, one can easily examine the effects of any important input parameters on the resulted total logistics cost and the best shipping mode. The spreadsheet model offers substantial flexibility to accommodate any changes in the general or specific parameters, and the results provide excellent guidelines for involved trading partners to revise or evaluate their logistics decisions.
6. Discussions and conclusions
As global sourcing becomes a prerequisite for companies competing in today’s market, understanding the cost-effectiveness of this procurement strategy has drawn a great deal of interest. This paper relies on a case study at a leading company in the US aviation industry and one of its international manufacturers in China as a basis to derive an evaluation framework for assessing the effectiveness of global sourcing.
The newly developed evaluation framework consists of five steps. The implementation of the computational segment of the framework on spreadsheets in the last step is explained in detail in the previous section. As stated previously, this framework is general enough to be readily adapted for different companies and operational scenarios. For example, the logistics cost categories may remain the same but the elements of each category can vary
Mode Air WRF WRL WKF WKL
(D) The effect of product value on the choice of the best shipping mode
Value (in) 84 £ 167 £ 333 £ 1,667 £ 3,333 £ Value (out) 250 £ 500 £ 1,000 £ 5,000 £ 10,000 £ Table VIII.
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from case to case. The number of potential transportation modes may also vary in different situations. We believe that the classification of the cost items into weight-based, value-based and frequency-based provides an easy way to quantify both qualitative and quantitative factors, which can be measured on one numerical scale. In some other circumstances, distance-based factors can be added or substituted for one of the classifications. The calculations are simple routines on the spreadsheets and provide the logistics managers with various perspectives on the landscape of the global sourcing strategy.
The computational part of the framework can be easily implemented on spreadsheets and offers substantial flexibility to accommodate assessment of various transportation alternatives and sensitivity analysis. Although this spreadsheet-based evaluation procedure is established based on a particular company’s situation, it can be revised easily and is applicable to companies that are practicing global sourcing strategies.
It is necessary to mention that the newly developed framework relies on a few assumptions and has a number of limitations. First of all, the demand information on the engine parts must be a known constant, and these data also serve as one of the critical input parameters. Second, the transportation routes are predetermined and fixed. In other words, the new framework needs to be modified substantially before it can be used to evaluate and compare possible shipping routes. Third, the values of all required input parameters such as those listed under section 4.2 should be available to enable the calculations. Finally, there are many other factors critical for decision making and yet cannot be incorporated into the calculation procedures. For example, the entire transportation infrastructure in China, the reliability and reputation of the rail and trucking carriers, the regulations and local laws, the accuracy of demand forecasting, to name just a few, are extremely crucial for transportation mode selection and the evaluation of the effectiveness of global sourcing strategy. The framework developed in this paper can only provide references and supporting information for the logistics decision-making process such as all relevant logistics cost items and the ways of quantifying each of the cost elements.
The limitations discussed above indicate the directions for possible future research. The immediate expansion of the current evaluation framework can be pursued from two perspectives: one is to consider the stochastic demand to accommodate the realistic demand pattern and the forecasting accuracy, and the other is to include the evaluation of possible transport routes so that the framework allows the selection of both shipping mode and route. The study of these two areas is currently underway.
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