Supply chain strategies, capabilities, and performance.
The choice of a supply chain strategy and value focus should be supported by specific enterprise capabilities and ultimately result in intended logistical performance. For excellent firms, a demand focus on customer service and proactive quality is more apparent at both the capability and performance levels than a supply focus on cost, productivity, distribution, and speed. Reasons are offered. Strategic intent and normative value congruency for competitive advantage also mean that customer closeness strategies such as customized logistics and agility tend to be supported particularly by demand-side capabilities, while operational excellence strategies such as time-based strategies (e.g., JIT) or lean networks tend to be supported more by supply-side capabilities. While on-time performance and absence of loss-and-damage are minimum order qualifiers, other logistical performance outcomes are order winners depending on the chosen value discipline. "Doing it right the first time" is more important than problem r ecovery, yet service failures do provide valuable information for problem diagnosis, organizational learning, and future improvements. Similarly, advanced notification of problems to customers and total performance measurement like overall customer satisfaction are also characteristic of best-in-class firms.
A review of managerial literature and practice reveals that supply chain strategies, capabilities, and performance are increasingly important topics for practitioners and researchers alike. (1) Supply chain capabilities are the building blocks for supply chain strategy and a source of competitive advantage for firm success. This strategy/capabilities/performance paradigm or framework is schematically represented in Figure 1. Two major classes of supply chain strategies are operational excellence and customer closeness. (2) Each of these distinct strategies will be discussed in turn with examples. They will also be evaluated empirically by the present research in the context of supporting supply chain capabilities and resultant performance.
Operational excellence strategies can support business strategies of overall cost leadership through total cost reduction, efficient and reliable supply, and high levels of basic service. (3) Operational excellence is sometimes referred to as a supply management focus in logistics strategy literature, (4) and is represented in Figure 1. It has been stated that "companies pursuing operational excellence are indefatigable in seeking ways to minimize costs, to eliminate intermediate production steps, and to reduce transaction and other 'friction' costs." (5) Suppliers are frequently selected based primarily on cost, reliability, and ease of doing business, while production and logistics systems are operated for efficiency and zero defects. The output emphasis of the supply chain is on "hassle-free" basic products and services that are standardized rather than customized. (6) However, when quality problems do occur, problem recovery may be especially important to satisfy customers, possibly even beyond a trouble-free outcome. (7)
One would expect operational excellence to be supported by supply chain capabilities such as low logistics costs, distribution coverage and availability, dependability, standardization of operations, time-definite deliveries, and delivery speed. A sampling of these capabilities is shown in Figure 1. As such, the objective of operational excellence is usually to lead an industry in price, reliability, convenience, and speed. (8) For customers, this means efficiently delivering reliable products and services at competitive prices and with minimal difficulty and inconvenience. (9) This reflects total cost minimization for customers, not only because of lower prices but also because of reductions in customer costs from optimal order fulfillment and supply chain time compression. As such, operational excellence may emphasize using total supply chain cost as a marketing weapon both to retain existing downstream customers and to attract new customers.
Examples of operational excellence include time-based strategies (10) such as just-in-time (JIT) deliveries (11) and lean supply chains. (12) These strategies are shown in Figure 1. Time-based and lean strategies will be investigated in the present research as to their relationships with supporting supply chain capabilities. JIT supply chains emphasize time-definite deliveries (i.e., known leadtimes of low variability). This can reduce buffer inventory and safety stocks. JIT may also involve more frequent deliveries of smaller shipments, which can increase inventory throughput or velocity. In turn, this can lower in-transit inventory and cycle stocks. Other contemporary logistics operations that can facilitate JIT and thereby also reduce inventories include cross-dock operations, synchronizing and sequencing transportation with production, delivering commodities to exact points on the production line using flexible transportation equipment and containers, in-transit acceleration and deceleration to regulate t he flows, and direct delivery.
Turning to lean networks, lean supply chains reduce all types of waste, errors, unnecessary assets, and cycle times by continuously seeking perfection and operational efficiencies throughout the supply chain network. (13) Types of logistics-related waste that can add cost but no value include waiting, rectification of mistakes, excess processing, unnecessary warehousing, extra handling, excess transport and terminals, and excess stock. (14) Innovative logistical solutions may involve outsourcing, using postponement strategies, redesigning processes, optimally locating facilities, reducing or redeploying network assets, and having resident suppliers' production lines and employees physically on premise through early supplier involvement and development (i.e., JIT II for resident buyers or JIT III for resident production).
The second major category of supply chain strategies relates to customer closeness, (15) which will also be investigated in this research. Customer closeness strategies can support business strategies of differentiation through high levels of value-added customer service, proactive quality (i.e., "do it right the first time"), and collaborative communications and interactions with customers. Customer closeness is sometimes referred to as a demand management focus in supply chain strategy literature, (16) and is represented in Figure 1.
Customer closeness means selling the customer not just a product or service, but rather total customer satisfaction through augmented solutions that include ongoing help, high levels of support, and interactive advisory service. (17) Firms following this strategic approach increasingly become experts on their customers' businesses and continuously elevate the relationships. This may mean advancing through levels of customer service, to customer satisfaction, to customer success (the three S's). As "internal consultants" within their customer's organization, they continually search laterally for additional opportunities to improve supply chain processes and to add value. (18) Rather than just meeting customer expectations, they try to stay ahead of these expectations by guiding the customer to appropriate change. In total, such proactive demand management attempts to go beyond the typical market offerings and outcomes of standardized variety, reactive problem solving and recovery, and even mere satisfaction of existing customer expectations. Managerially delighting the customer means that the unexpected should gradually become the expected. (19)
One would expect supply chain strategies involving customer closeness to be supported by demand-management capabilities such as responsiveness to key customers, special value-added customer services, customization and innovative solutions, flexibility, proactive quality and communications, intermodal transfers, and again dependability. This is schematically illustrated in Figure 1. Customer closeness also requires interactive long-term relationships with a firm's customers, suppliers, and partners. There is recognition by cooperating firms that the supply chain is part of the total product offering and that they must act in a concerted way to assure value for final consumers. (20) There is also an emphasis on using the supply chain as a proactive marketing weapon to achieve growth objectives. For example, some supply chain firms do marketing research on the needs of their customers' customers. (21) There is an awareness that if their customers succeed, then everyone in the supply chain will grow.
Major examples of customer closeness as supply chain strategies include customized logistics and agility, which are shown in Figure 1. Logistical customization and agility strategies will be evaluated in the present research in terms of identifying their relationships with potential supporting capabilities. Extant logistical strategy literature suggests that customized logistics tailors supply chain capabilities and value-added services to specific customer needs. (22) These distinct and responsive offerings represent specific solutions directed at what individual customers or segments want, rather than general solutions reflecting what the market wants. (23) However, this does not necessarily mean a proliferation of logistical capabilities. Supply chain firms can offer a predetermined service menu of capabilities, value-added services, and attributes. (24) From this service menu, customers can choose their preferred services and attributes. Although the combination may be unique to each customer, the inputs and capabilities themselves are not unique since they were thought out, prespecified, and developed beforehand.
Agility takes this one step further by quickly and flexibly adjusting supply chain capabilities and their combinations to changing customer needs and evolving competitor offerings over time. (25) This may require a flexible and dynamic supply chain network that can recombine, reconfigure, and resequence logistical capabilities and participating firms in changing and creative ways. Since transportation and third-party logistics firms may operate throughout the supply chain, they may be in the best position to coordinate and integrate capabilities in the network. Information on customer required capabilities and performance tracking become critical to success, possibly necessitating high levels of communications and collaborations with customers.
SUPPLY CHAIN PERFORMANCE, STRATEGIC INTENT, AND VALUE CONGRUENCY
Supply chain performance is the "bottom line" for supply chain strategies such as customer closeness versus operational excellence and their enabling capabilities. Further, supply chain capabilities eventually devolve into supply chain performance. These relationships are summarized in Figure 1. They imply that there should be a normative "fit" or value congruency between supply chain strategies, capabilities, and performance; e.g., a supply management focus on operational excellence or a demand management focus on customer closeness. Managerial strategic intent means that this value congruency should permeate everywhere in the supply chain and ultimately in performance. It has been stated that the choice of a value discipline focus "shapes everything a company does, colors the whole organization, and defines the very nature of a company." (26)
Four major types of supply chain performance are logistical cost and productivity versus customer service and quality. The first two can be classified as primarily supply-focused performance, while the latter two can be characterized as primarily demand-focused performance. Descriptive strategy literature on value disciplines suggests that firms must first meet industry standards or minimum acceptable levels on all four of these performance dimensions in order to be order-qualified. However, beyond these minimum standards or thresholds, firms can and should focus primarily on one value discipline. (27) This value focus will prevent dilution of firm resources, assets, employee attention, and market image or message. Furthermore, to be successful, this theory predicts that the chosen value emphasis should be apparent and consistent at both the capability and performance levels. (28) This managerial strategic intent reflects value congruency and is implied in Figure 1. For example, if best practice firms stress a supply-focus on operational excellence, then this should be apparent in both their capabilities and performance. In contrast, if excellent firms stress a demand-focus of customer closeness, then this focus should be visible in both their capabilities and performance. Again, minimum supply-side and demand-side threshold standards to qualify as potential suppliers should be achieved first and be visible for excellent firms in their data. However, their dominant supply chain focus should be much more visibly pronounced across their strategies, capabilities, and performance. This supply chain value congruency will be evaluated in the present research.
Based on the previous literature review and theory, the following research questions are tested:
1. Is there evidence of value congruency across supply chain strategies, capabilities, and performance for leading firms? For example, is there a supply focus on operational excellence versus a demand focus on customer closeness congruency?
2. Are supply-side or demand-side capabilities and performance more important for supply chain success?
A. Are cost and productivity or customer service and quality more important?
B. Are some capabilities "order qualifiers"?
3. Which capabilities support which supply chain strategies?
A. Which capabilities support strategies of operational excellence versus customer closeness?
B. Which capabilities support time-based and lean network strategies versus logistics customization and agility strategies?
4. Is proactive or reactive quality more important for supply chain success?
A. Is problem avoidance or problem recovery more important?
B. Do excellent firms evaluate problem recovery as more important to customer satisfaction than the original outcome, as suggested in some literature?
5. What are the characteristics of performance measures evaluated as most important and available to excellent firms?
A. e.g., sophisticated or basic measures?
B. e.g., attribute specific or total performance measures such as total cost or total quality?
To address these research questions and to investigate supply chain strategies, capabilities, and performance, the research methodology had four phases. The research had other related research objectives as well, as determined by the multiple member research team. In the first phase, a survey instrument was developed and mailed to approximately 7,000 firms in the United States and Canada in order to assess supply chain management practices and trends. The survey instrument was first individually field pretested for content validity and reliability with executives from numerous participating firms in both countries. An expert panel of twenty leading supply chain practitioners was also used to review the questionnaire and to make additional recommendations. Based on both types of feedback, the survey instrument was modified and improved. The scale items were of the Likert-type and are indicated at the bottom of each table.
The survey instrument was mailed to almost the entire memberships of the leading logistical professional association in each country: the Council of Logistics Management (CLM) in the United States and the Canadian Association of Logistics Management (CALM) in Canada. However, certain member groups such as consultants and educators were excluded from the mailing since the focus of the research was on firm level best practices. These two professional associations have broad industry, group, and geographic memberships, and represent most major firms in their respective countries.
The questionnaire was mailed to the top-level member executive of each company as identified by the respective professional association, along with the professional association's cover letter of support. A total of 6,887 surveys were mailed and 1,358 were returned, for a response rate of approximately 20 percent in each country without follow-up. Investigation of characteristics of respondents and non-respondents did not identify significant differences.
The second phase of the research was completion of a 24-page, multi-survey workbook by a select group of ill companies. These firms were selected based on the expert panel judgment that the firms exhibited world class best practices in supply chain management and logistics. Thus, multiple source informant agreement was utilized.
The third research phase consisted of in-depth interviews with these same 111 companies. These interviews were conducted in each country by logistics and supply chain management professors. An index of excellence was developed by the research team, and each interviewer rated each of their companies in ten areas of logistical and supply chain expertise based on their interview notes and other information on the company. The range of scores was 70 to 185 points out of a possible 200 points. Thus, each firm received an index excellence score. The top third on this index can be termed the best-of-the-best or the best-in-class benchmark. (29) This benchmark group is also referred to in this study as the top third excellent firms. Extant benchmarking literature defines the top third group as the most managerially relevant and the best benchmark since maximum learning results from studying the best-of-the-best firms, rather than those of moderate success or those "stuck in the middle." (30) The goal of leapfrogging the competition is also sometimes put forth as additional justification. Thus, comparisons are made between the top third and bottom third firms in order to differentiate and clearly identify distinct best practices. The fourth phase of the research consisted of additional survey replications so that trends could be assessed over time.
Importance of Supply Chain Capabilities
Table 1 shows the importance rankings for seven major types of supply chain capabilities, which can be thought of as core competencies. Customer service and quality rank first and second in importance, respectively. Information support and distribution flexibility are in the middle, while low logistics cost, productivity, and delivery speed rank lower in importance. Thus, in general, demand-side capabilities of customer service and quality tend to be ranked more important for supply chain success than supply-side capabilities such as cost, productivity, and delivery speed. However, the absolute level of scores possibly implies that firms must meet minimum acceptable levels on all of these capabilities to be order-qualified or to be certified as acceptable suppliers.
Relationships Between Supply Chain Capabilities and Firm Excellence
At a more detailed supporting level, supply chain capabilities were also looked at in greater depth for the previous general categories of capabilities or core competencies using a different questionnaire. Table 2 shows the correlation of performance on 26 different supply chain capabilities, with an excellence index that is described in the methodology section. The definitions of these 26 capabilities that were provided to respondents are shown in Appendix 1.
Demand-side capabilities again consist of customer service and quality variables. As shown in Table 2, six of the seven customer service capabilities are positively and significantly related to firm excellence. Order flexibility followed by value-added services show the strongest relationships to the firm excellence index. For the quality category, the four proactive capabilities (i.e., "do it right the first time") are significantly related to the firm excellence index, while the three reactive capabilities are not. The four proactive capabilities in decreasing order of statistical strength include delivery dependability, order fill consistency, avoiding disruptions in supply, and problem avoidance. Similarly, advanced customer notification of problems is also positively related to firm excellence. However, the reactive quality capabilities do not achieve statistical significance with firm excellence and include problem and complaint resolution, product substitution, and product recall. Thus, none of these p roblem recovery capabilities are statistically associated with firm excellence.
For supply-side capabilities, low logistics cost and standardization of operations are marginally yet significantly related to firm excellence. In turn, none of the five distribution capabilities nor the two logistical speed capabilities are significantly related to firm excellence.
In summary, the more demand-oriented capabilities of customer service and quality are most strongly related to firm excellence. However, for the quality category, it appears to be primarily the proactive capabilities that are significantly related to firm excellence, rather than reactive quality capabilities or problem recovery. In turn, supply-side capabilities of low logistics cost and productivity are less strongly related to firm excellence, while distribution and logistics speed are not related at all in this analysis.
Benchmarking Supply Chain Capabilities of Best-in-Class Firms
For a managerial orientation, Table 3 provides a different but related benchmarking analysis. It compares the capability performance of the top third excellence index firms with the bottom third. The top third benchmarked firms are the best-of-the-best benchmark, (31) as discussed in the methodology section. From a managerial perspective, what is important and of prime interest to management is benchmarking against the best-of-the-best firms, rather than against those of moderate success or those "stuck in the middle." (32)
The benchmarking results in Table 3 are analogous to Table 2, and provide additional corroboration of results for management. In general, the more demand-side capabilities in the categories of customer service, proactive quality, and advance information to customers again more successfully distinguish top third excellence index firms than do reactive quality or supply-side capabilities. Specifically, proactive information capabilities of both advance notification of problems and advance shipment information now also significantly distinguish top third firms. For supply-side capabilities, standardization still does, but low logistics cost does not, significantly differentiate between the two groups in this particular analysis.
Importance and Availability of Demand-Side Performance Measures
Eventually supply chain strategies and supporting capabilities devolve into performance outcomes as represented in Figure 1. At the performance outcome level, Tables 4 and 5 evaluate demand-side and supply-side performance measures, respectively. Table 4 benchmarks the demand-side performance measurement practices of top third firms versus the bottom third on customer service and quality performance measures. Again, the relevant managerial benchmark is the best-in-class performers. (33) As such, both availability of performance information and its managerial importance are evaluated against these top firms.
Table 4 shows that the first four customer service performance measures and the first six quality measures statistically differentiate top third firms from the bottom third on either information availability or importance. For example, top third excellence index firms attribute both greater importance and information availability to fill rate, complete orders, and credit claims. These measures are available to over 90 percent of top third firms and can be characterized as basic performance measures. In contrast, more esoteric measures such as backorder performance, complaints from the salesforce, and response time to customer inquiries do not distinguish top third from bottom third firms in Table 4.
Some customer service and quality measures in Table 4 appear to be minimum hurdles in that they are available a to very high percentage of bottom third firms. These include on-time deliveries, number of customer returns, delivery consistency, and damage frequency. Apparently, these basic attributes are order qualifiers to be even considered as a potential supplier or partner. Thus, they would not significantly differentiate between groups.
The far right column of Table 4 also shows the relative importance rankings given by top third firms to measures of customer service and quality, respectively. In general, the most important rankings tend to be for basic, proactive, positive, and total performance measures. Specifically, the top four out of eleven customer service measures in descending order of importance are stockouts, fill rates, on-time delivery, and overall customer satisfaction. These basic and primarily proactive performance attributes reflect whether the firm's customers got what they wanted, where and when they wanted it, and in the condition they wanted it. In turn, the top four quality measures out of nine, in decreasing order of importance to top third firms, are picking and shipping accuracy, overall reliability, delivery consistency, and invoicing accuracy. These quality attributes are also proactive measures that represent positive performance (i.e., "do it right the first time"). In contrast, the less important quality variabl es are primarily reactive and negative performance measures and include shipping errors (ranked fifth), number of customer returns (seventh), number of credit claims (eighth), and damage frequency (ninth and last). It should also be noted that both overall customer satisfaction and overall reliability are total performance measures that are ranked very important by best-in-class firms, the implications of which will be discussed in the conclusions section. In summary, the customer service and quality performance rankings show that basic, proactive, positive, and total performance measures are deemed most important by benchmarked top third firms.
However, it is also interesting to compare importance rankings of top third firms with their information availability rankings in Table 4. Specifically, the least important quality ranked variables are some of the most highly tracked quality measures. In terms of information availability, these quality rankings include number of customer returns (ranked first in availability), number of credit claims (second), shipping errors (fourth), and damage frequency (sixth). Thus, despite being less important, these reactive quality measures are tracked at a relatively high level by the best-in-class firms. This finding will be discussed subsequently in the conclusions section and relates to service failures being particularly useful and easy sources of information.
Importance and Availability of Supply-Side Performance Measures
Table 5 benchmarks the top third firms on the importance and information availability of supply-side performance measures in the categories of cost and productivity. Both the first six cost measures (out of seventeen) and the first six productivity measures (out of nine) significantly distinguish the benchmarked top third firms from the bottom third firms on either greater importance or greater information availability. All twelve of these cost and productivity measures are basic performance measures. In contrast, more esoteric and sophisticated performance measures such as cost of returned goods, cost of service failures, and cost of customer segments do not significantly distinguish top third from bottom third firms.
Turning to the importance rankings of top third firms for cost in the far right column of Table 5, total cost and cost trend analysis rank first and second, respectively. These measures are followed in importance by outbound freight cost, cost per unit, comparison of actual cost versus budget, and cost as a percentage of sales, in that order. It is informative to note that each of these first six highest ranked cost measures is a basic and relative measure that allows for easy comparison with a readily available standard or its own incorporated benchmark. For example, total cost typically has a comparative objective function of simultaneously minimizing the sum of several cost tradeoffs. Thus, minimizing total cost is relative to itself or to its previous calculation as a standard (i.e., as long as the first derivative of the cost function is less than zero). For productivity importance rankings in the bottom right section of Table 5, a total productivity index is ranked first by top third firms, followed by warehouse labor productivity, units shipped per employee, and comparison to historical standard. Again, these high rankings reflect basic and relative performance measures in that they have internal or easily available benchmarks. Similar to the previous customer service and quality results, total cost (ranked first for cost) and total productivity index (ranked first for productivity) are total performance measures that are especially important to top third firms. The implications will be elaborated upon subsequently in the conclusions section.
It is again worth comparing the importance rankings with the information availability rankings of the benchmarked top third firms. Analogous to the earlier reactive quality results, Table 5 shows that some of the least important cost measures are tracked by a large percentage of top third firms. Specifically, "cost of damage" is ranked fifteenth in importance and "cost of returned goods" is ranked seventeenth and last, yet both are available to more than 80 percent of the top firms. Thus, similar to the previous reactive quality findings, these reactive or negative performance measures appear less important than "doing it right the first time," but apparently provide quite useful information to top firms regarding problems.
Value Congruency and Strategic Intent
As discussed in the introduction, value congruency predicts that what excellent firms do at the capability level should be visibly consistent with what these same top firms do at the performance level. Indeed, managers' strategic intent should culminate in value congruency or consistency across all levels of strategy, capabilities, and performance, as implied in Figure 1. Table 5 shows that the top third firms' mean importance rating for all cost performance measures is 3.98, while for all productivity measures it is 3.76. In contrast, Table 4 shows that the mean importance rating for all customer service measures is 4.18 and for all quality measures is 4.12. Thus, viewing performance measures as a whole, demand-side measures in the areas of customer service and quality are viewed by top third firms as more important than supply-side performance measures. These results are consistent with the earlier findings for supply chain capabilities, and thus support the expected value congruency for leading firms. In e ssence, top third firms evaluate both demand-oriented capabilities and demand-oriented performance measures as most important for supply chain success.
Value congruency also predicts that supporting demand-oriented capabilities should be most strongly associated with customer closeness strategies. In contrast, supporting supply-oriented capabilities should be more strongly associated with operational excellence strategies. However, it is again worth noting the expectation that firms must meet minimum standards of acceptability on both demand-side and supply-side capabilities in order to be order qualified as an acceptable supplier or partner before focusing on one value discipline; and that this should also be visible in their data.
Table 6 shows the correlation coefficients for 1,358 United States and Canadian firms on demand-side capabilities and supply-side capabilities with supply chain strategies. As expected, demand-side capabilities are much more strongly related statistically to customer closeness strategies of both logistics customization and agility than to the operational excellence strategies. In contrast, the supply-side capabilities are more strongly related to operational excellence strategies of both time-based and lean network strategies. In essence, these findings provide additional strong support for value congruency and strategic intent. The results in Table 6 also reveal support for minimum acceptable thresholds or capabilities.
Value congruency and strategic intent also predict that similar capabilities should distinguish a particular supply chain strategy from other strategies. Table 6 allows one to compare the capabilities that especially distinguish different supply chain strategies. As might be expected, a customization strategy is characterized by tailored services and responsiveness to customers (i.e., capabilities 1 and 2 in panel A of Table 6). However, customization is also especially distinguished by customer participation in strategy formulation. As such, compared to agility, customization is more strongly related to obtaining customer input into strategy, sharing risks with customers, and measuring customer satisfaction (i.e., variables 5, 6, and 7). In contrast, agility is distinguished by frequent interactions, collaborations, and communications with customers. As such, compared to customization, agility is more strongly related to frequently contacting customers, customer involvement in alliances, frequent visits with customers, and information systems for service improvements (i.e., variables 8, 9, 10, and 11 in panel A). Remaining demand-side capabilities of flexibility for special requests and customer service significantly support both customization and agility strategies about equally.
Turning to operational excellence in panel B of Table 6, time-based strategies place greater emphasis on inventory throughput or velocity. As such, compared to lean networks, time-based strategies are more strongly related to flow-through cross docking, lead time improvement, quick replenishment, and performance measurement (i.e., variables 1, 2, 3, and 4 in panel B of Table 6). In contrast, lean network strategies place greater emphasis on minimizing total cost in the network by eliminating waste, slack resources, and avoidable assets. As such, compared to time-based strategies, lean networks are more strongly related to least total cost, efficient deployment of inventory in the network, postponement of forward inventory movement, resident suppliers (i.e., supplier employees or operations located on customer premises), and information technology (IT). These capabilities are represented by variable numbers 6, 7, 8, 9, and 10 in panel B of Table 6. Remaining supply-side capabilities of inventory reduction and process improvement significantly support both time-based and lean network strategies about equally.
In total, certain supply chain capabilities especially distinguish and support particular supply chain strategies as predicted by strategic intent and value congruency theory and literature. These distinguishing capabilities include strategic customer participation for customization, frequent customer interactions and collaborations for agility, increased inventory velocity for time-based strategies, and total cost minimization for lean network strategies.
Supply chain strategy is an increasingly important topic in an environment of deregulation, inter-firm cooperation and partnerships, strategic alliances, and technological advancements. Similarly, a new paradigm of supply chain strategies supported by particular capabilities and resulting in related performance is clearly gaining in interest to both practitioners and academicians alike. As such, strategic intent and value congruency predict that there should be a value consistency or normative fit between supply chain strategies, capabilities, and performance; e.g., a demand focus on customer closeness or a supply focus on operational excellence. (34) This focus becomes part of the competitive advantage of the supply chain that should foster member firms' success. Further, value congruency recommends that once firms have developed minimum supply-side and demand-side capabilities to be order qualified, they should then concentrate on those capabilities and performance metrics that support their chosen value fo cus. To do otherwise would waste time and resources and would dilute the firms' message and image in the marketplace. (35) In the present research, on-time performance and the absence of loss, damage, and customer returns appear to be minimum order qualifiers. In turn, other capabilities that distinguish the best-of-the-best firms from other firms in this study can be interpreted as order winners for the chosen value emphasis. Significant demand-oriented examples include value-added services and order flexibility, while significant supply-oriented examples include standardization of operations and low logistics cost.
This study does find strong evidence of value congruency between supply chain strategies, capabilities, and performance. First, for excellent firms, a demand-side focus on customer service and proactive quality is more apparent and important at both the capability and performance levels than a supply-side focus on cost, productivity, distribution, and speed. Second, demand-side capabilities and demand-side performance are most strongly related to the firm excellence index. Third, demand-side capabilities are most strongly related to customer closeness strategies such as customized logistics and agility. In contrast, supply-side capabilities are most strongly related to operational excellence strategies such as time-based strategies (e.g., JIT) and lean networks. Fourth, particular types of capabilities distinguish and support individual supply chain strategies. On the demand side, customer participation in strategy formulation distinguishes customization, while continuous interactions, collaborations, and com munications with customers characterize agility. On the supply side, inventory velocity and supply synchronization distinguish time-based strategies, while minimum total cost in the network typifies lean networks. In total, these findings support strategic intent and normative value congruency across supply chain strategies, capabilities, and performance.
The question must be addressed as to why a demand-side value focus should be much more apparent and important amongst excellent firms than a supply-side focus. The suggested answer is that only one or two firms in an industry can achieve a minimum cost advantage from supply-side capabilities. In contrast, differentiation through customer closeness can be achieved in a multiplicity of ways using demand-side capabilities. Demand-side capabilities can be reconfigured, recombined, and resequenced to meet changing requirements of specific customers, to segment and appeal to particular market segments, or to create competitive advantages that can serve as entry barriers to potential competitors and new entrants. Thus, demand-side competitive advantages may be easier to attain, be more difficult to imitate, and be more sustainable.
In this study, the most important demand-side capabilities for customer service are found to be order flexibility and value-added services, while for quality, delivery dependability is especially important. However, for all quality measures together, only the proactive capabilities that reflect "doing it right the first time" are characteristic of excellent firms. In addition to delivery dependability, these include order fill consistency, problem avoidance, and avoiding disruptions in supply. All of these proactive capabilities avoid problems in the first instance. This may also help to explain why excellent firms are found to place greater reliance on positive performance measures rather than negative performance measures. In contrast, reactive quality capabilities that reflect problem recovery do not distinguish excellent firms. These include product substitution, product recall, and problem and complaint resolution. Thus, despite current academic and practitioner enthusiasm for the concept of problem reco very, it does not distinguish excellent firms in this study.
Similarly, for demand-side performance measures, reactive and negative performance measures are evaluated as less important by excellent firms than proactive and positive performance. However, it is interesting to note that some reactive performance measures such as number of customer returns, number of credit claims, and cost of damage are tracked at much higher levels (i.e., information is readily available) than their indicated importance would dictate. The suggested explanation for this disparity is that although "doing it right the first time" is most important to excellent firms, service failures can provide valuable and easy sources of information to diagnose and resolve problems, to improve services, and to avoid future problems. (36) Analogously, some descriptive managerial literature refers to information on service failures as "golden nuggets of truth" that provide opportunities to learn from mistakes. (37) There is also evidence in this study that although trouble-free performance is best, advance notification of problems to customers is a characteristic of excellent firms.
Additional characteristics of performance measures that are stressed by excellent firms include basic rather than sophisticated measures, relative measures that have built-in comparison standards or readily available benchmarks, and total performance measures. Basic measures especially evaluate whether the firms' customers receive the right things, at the right place, at the right time, and in the right condition. For total performance measures from each of the four performance categories, the measures and their importance rankings are total cost (ranked first in importance out of 17 cost measures), total productivity index (ranked first for productivity), overall reliability (ranked second for quality), and overall customer satisfaction (ranked fourth for customer service). Thus, total performance measures are uniformly important and especially characteristic of excellent firms.
There are several reasons why total performance measures would be particularly important to excellent firms. First, a total performance measure may best reflect the supply chain's overall value commitment to customers (38) and its actual level of attainment, as well as its competitive market strategy. Second, sole use of individual attribute measures can suboptimize or be misleading. For example, reduction of costs in one category can raise costs even more in another category. More broadly, reduction of costs for one supply chain member could raise costs by a greater amount for the customer or another supply chain member. The advantage of a total performance measure such as total cost is that it can potentially consider as many as possible of these cost tradeoffs simultaneously. Similar logic would apply to total performance measures that consider customer service, quality, or productivity tradeoffs. Third, viewing attribute-specific performance measures in isolation can overstate performance and create a fal se sense of success. For example, 90 percent performance on each of three attributes (e.g., 90 percent on-time, 90 percent fill rate, and 90 percent damage-free) is not 90 percent overall performance but rather only 73 percent total positive performance (i.e., 90 (3)). Thus again, total performance measures are particularly important for accurately assessing overall performance.
For the future, some supply chains are currently experimenting with "mass customization" strategies. (39) This is almost an oxymoron and is difficult to achieve. Mass customization can be thought of as a hybrid or combination of operational excellence with customer closeness strategies. As such, it attempts to obtain maximum supply-side operating efficiencies while at the same time being particularly responsive to changing demand requirements. Demand requirements can be for manufacturers, distributors, or final customers; but ideally, they should be for the supply chain as a whole using demand-based information (e.g., through collaborative forecasting, real time point-of-sale or point-of-usage information, linked and continuous replenishment, combined ERP with EDI, etc.) Examples of mass customization include postponement strategies that attempt to postpone either final production (form), forward inventory movement (temporal), or break-bulk and assembly (spatial). A major benefit is inventory reduction throug hout the supply chain. For a mass customization value focus, the overriding capability or core competency appears to be flexibility. Flexibility can be seen in such creative and emerging supply chain practices as agile manufacturing; modular product design; side-loading trailers; production line milk-runs; collapsible, returnable, and reconfigurable containers; merge-in-transit; flexible products through delayed sorting, kitting, or subassemblies; demand flow-through warehousing; intermodal transfers and containerization; in-transit acceleration or deceleration; distribution center or third-party light manufacturing; and direct-store delivery systems. Information technology is a crucial enabler for most of these flexible and integrative practices. These creative and emerging mass customization strategies and practices are trends that deserve future research and continuing observation.
It is intended that this study will both add to our knowledge and help to integrate the strategies, capabilities, and performance literatures. This study's emphasis on excellent firms also provides useful benchmarking guidance for managers. The present research has the advantage of studying supply chain strategies, capabilities, and performance across multiple industries without the usual limitations on generalizability of previous studies that focus on only one industry. Furthermore, this strategy/capabilities/performance paradigm is investigated for different types of supply chain strategies, which is also an improvement over prior research. Nevertheless, as with any study, additional research would be desirable and necessary. First, it would be useful and interesting to know how different supply chain strategies and their supporting capabilities are related to "bottom line" and "top line" type financial performance. Similarly, it would be helpful to know how interactions among various supply chain strategi es and different business strategies are related to overall business success. It is hoped that the present research makes an initial contribution to this line of inquiry.
Appendix 1. Supply Chain Capabilities
1. Responsiveness to key customers: The ability to respond to the needs of and wants of key customers.
2. Value-added services: The ability to perform additional services that add value for the customer.
3. Logistics service differentiation: The ability to differentiate logistical service offerings from those offered by competitors.
4. Customer service flexibility: The ability to accommodate special customer service requests.
5.Order flexibility: The ability to modify order size, volume, or composition during logistics operation.
6. Customization during logistics: The ability to handle product modifications while in the logistics system.
7. Innovative solutions: The ability to develop creative logistical solutions for specific situations, emergencies, or customers.
8. Delivery dependability: The ability to meet quoted or anticipated delivery dates and quantities on a consistent basis.
9. Order fill consistency: The ability to provide desired quantities on a consistent basis.
10. Problem avoidance: The ability to proactively seek solutions to logistics problems before they occur.
11. Avoid disruption in supply: The ability to accommodate supply disruption in a manner that does not adversely affect customers.
12. Problem recovery and complaint resolution: The ability to quickly resolve logistically-related customer problems and complaints.
13. Product substitution: The ability to substitute product or service offerings in the event of a delay or stockout (versus backorder or line cancellation).
14. Product recall: The ability to accommodate product recalls.
15. Advanced problem notification: The ability to notify customers in advance of delivery delays or product shortages.
16. Advanced shipment notification: The ability to notify customers in advance of delivery when products will arrive.
17. Low logistics cost: The ability to achieve the lowest total cost of logistics through efficient operations, technology, and/or scale economies.
18. Standardization of operations: The ability to provide a consistent approach to performing key logistics work.
19. Simplification of operations: The ability to simplify the overall logistical process.
20. Widespread distribution coverage: The ability to comprehensively and effectively target a given distribution region.
21. Selective distribution coverage: The ability to effectively target selective or exclusive customers.
22. Location flexibility: The ability to service customers from alternative warehouse locations.
23. Delivery time flexibility: The ability to accommodate delivery times for specific customers.
24. Reverse logistics timing: The ability to perform reverse logistics operations in a timely manner.
25. Delivery speed: The ability to reduce the time between order receipt and customer delivery to as close to zero as possible.
26. Expedited delivery: The ability to expedite shipments or partial shipments.
Table 1. Importance of Logistical Capabilities for Supply Chain Success Supply Chain Capabilities: Mean Score Rank 1. Customer Service 1.11 1 2. Quality 1.16 2 3. Information systems support 1.57 3 4. Distribution flexibility 1.78 4 5. Low logistics cost 2.04 5 6. Productivity 2.37 6 7. Delivery speed 2.45 7 Scale: 1=important, 5=unimportant Table 2. Pearson Product-Moment Correlations Between Supply Chain Capabilities and Firm Excellence Correlation With Supply Chain Capabilities: (a) Excellence Index p-value A. Customer Service 1. Responsiveness to key customers .214 (d) .035 2. Value-added services .289 (c) .005 3. Logistics service .159 (d) .088 differentiation 4. Customer service flexibility .247 (c) .014 5. Order flexibility .397 (b) .001 6. Customization during logistics .193 (d) .059 7. Innovative solutions .080 .247 B. Quality 1. Delivery dependability .268 (b) .001 (proactive) 2. Order fill consistency .218 (d) .029 (proactive) 3. Problem avoidance (proactive) .155 (d) .091 4. Avoid disruption in supply .178 (d) .062 (proactive) 5. Problem and complaint resolution .140 .113 (reactive) 6. Product substitution (reactive) .088 .226 7. Product recall (reactive) .107 .181 C. Information 1. Advanced problem notification .186 (d) .053 (proactive) 2. Advanced shipment notification .099 .197 (proactive) D. Logistics Cost and Productivity 1. Low logistics cost .179 (d) .068 2. Standardization of operations .151 (d) .099 3. Simplification of operations .053 .325 E. Distribution 1. Widespread distribution coverage .127 .139 2. Selective distribution coverage .120 .155 3. Location flexibility .106 .185 4. Delivery time flexibility .013 .455 5. Reverse logistics timing .129 .153 F. Logistical Speed 1. Delivery speed .122 .147 2. Expedited delivery .144 .108 (a)Scale 1 = performance worse than competitors 5 = performance better than competitors (b)p [less than or equal to] .001 (c)p [less than or equal to] .01 (d)p [less than or equal to] .10 Table 3. Supply Chain Capabilities of Top Third Excellence Index Firms Versus Bottom Third Supply Chain Capabilities: (a) Mean Performance Top Third Bottom Third A. Customer Service 1. Responsiveness to key customers 4.07 (d) 3.61 2. Value-added services 3.82 (c) 3.33 3. Logistics service differentiation 3.59 3.28 4. Customer service flexibility 3.76 3.50 5. Order flexibility 4.06 (b) 3.12 6. Customization during logistics 3.33 (c) 2.82 7. Innovative solutions 4.00 (d) 3.61 B. Quality 1. Delivery dependability 4.35 (c) 3.78 (proactive) 2. Order fill consistency 4.24 4.17 (proactive) 3. Problem avoidance (proactive) 3.82 (d) 3.44 4. Avoid disruption in supply 3.94 (d) 3.50 (proactive) 5. Problem and complaint resolution 4.06 3.78 (reactive) 6. Product substitution (reactive) 3.59 3.33 7. Product recall (reactive) 3.94 4.06 C. Information 1. Advanced problem notification 3.65 (c) 3.06 (proactive) 2. Advanced shipment notification 3.35 (d) 2.94 (proactive) D. Logistics Cost and Productivity 1. Low logistics cost 4.17 3.83 2. Standardization of operations 4.00 (c) 3.29 3. Simplification of operations 3.41 3.18 E. Distribution 1. Widespread distribution coverage 4.24 4.00 2. Selective distribution coverage 3.82 (c) 3.12 3. Location flexibility 3.65 3.35 4. Delivery time flexibility 3.94 3.94 5. Reverse logistics timing 3.53 3.43 F. Logistical Speed 1. Delivery speed 3.71 (c) 3.06 2. Expedited delivery 4.00 3.94 (a)Scale: 1=performance worse than competitors; 5=performance better than competitors (b)p [less than or equal to] .001 (c)p [less than or equal to] 0.1 (d)p [less than or equal to] .10 Table 4. Availability and Importance of Demand-Side Performance Measures for Top Third Excellence Index Firms Versus Bottom Third Percent Having Information Available Top Bottom Top Performance Measures: Third Third Third % % Rank A. Customer Service Measures 1. Fill rate 96.9 (b) 61.1 1 2. Stockouts 93.8 (d) 77.8 2 3. Cycle time 90.6 (d) 72.2 4 4. Complete orders 90.0 (b) 52.9 5 5. On-time deliveries 93.6 89.5 3 6. Backorders 79.3 76.5 6 7. Customer complaints 71.0 79.0 7 8. Overall satisfaction 58.1 55.6 8 9. Sales force complaints 42.9 33.3 9 10. Response time to inquiries 41.9 29.4 10 11. Response accuracy 32.3 22.2 11 Mean Importance B. Quality Measures 1. Number of credit claims 93.3 (c) 70.6 2 2. Picking/shipping accuracy 90.8 74.8 3 3. Shipping errors 90.6 (d) 73.7 4 4. Document/invoicing accuracy 84.4 (b) 35.0 7 5. Order entry accuracy 80.0 (b) 45.0 8 6. Overall realiability 70.0 (b) 29.4 9 7. Number of customer returns 96.8 88.9 1 8. Delivery consistency 87.8 77.8 5 9. Damage frequency 87.5 75.0 6 Mean Importance Average Importance Rating (a) Top Bottom Top Performance Measures: Third Third Third % % Rank A. Customer Service Measures 1. Fill rate 4.50 (b) 3.73 2 2. Stockouts 4.52 4.19 1 3. Cycle time 4.16 3.82 7 4. Complete orders 4.26 (c) 3.71 6 5. On-time deliveries 4.43 4.47 3 6. Backorders 3.92 3.80 9 7. Customer complaints 4.35 4.28 5 8. Overall satisfaction 4.39 4.41 4 9. Sales force complaints 3.94 3.64 8 10. Response time to inquiries 3.73 3.93 11 11. Response accuracy 3.80 4.00 10 Mean Importance 4.18 B. Quality Measures 1. Number of credit claims 3.82 (c) 3.15 8 2. Picking/shipping accuracy 4.43 (d) 3.94 1 3. Shipping errors 4.20 4.17 5 4. Document/invoicing accuracy 4.21 3.79 4 5. Order entry accuracy 4.19 4.00 6 6. Overall realiability 4.35 3.92 2 7. Number of customer returns 3.87 3.60 7 8. Delivery consistency 4.24 4.17 3 9. Damage frequency 3.80 3.56 9 Mean Importance 4.12 (a)Scale: 5=important; 1=unimportant (b)p[less than or equal to].001 (c)p[less than or equal to].01 (d)p[less than or equal to].10 Table 5. Availability and Importance of Supply-Side Performance Measures for Top Third Excellence Index Firms Versus Bottom Third Percent Having Information Available Top Bottom Top Performance Measures: Third Third Third % % Rank C. Cost Measures 1. Outbound freight cost 100.0 94.9 1 2. Cost as a percentage of sales 96.8 (d) 84.2 3 3. Direct labor 96.5 (d) 83.9 4 4. Administrative cost 93.6 84.1 6 5. Warehouse order processing 87.5 80.2 8 6. Inbound freight cost 77.4 79.0 13 7. Direct product profitability 62.5 (b) 36.8 14 8. Cost of backorder 33.3 27.8 17 9. Comparison of actual versus budget 98.5 96.5 2 10. Total cost 93.8 95.2 5 11. Cost trend analysis 92.8 90.3 7 12. Cost of damage 87.5 80.1 9 13. Inventory carrying cost 86.7 73.7 10 14. Cost per unit 83.9 83.3 11 15. Cost of returned goods 81.3 75.2 12 16. Cost of customer segments 41.9 55.2 15 17. Cost of service failures 40.6 47.4 16 Mean Importance D. Productivity Measures 1. Warehouse labor productivity 90.6 79.9 1 2. Comparison to historical std. 87.5 73.7 2 3. Units shipped per employee 83.8 (b) 57.9 3 4. Total productivity index 78.1 (c) 57.6 4 5. Equipment downtime 65.6 (b) 27.8 6 6. Orders per salesperson 50.2 (c) 55.6 9 7. Units per labor dollar 67.7 57.8 5 8. Order entry productivity 65.6 52.9 7 9. Transport labor productivity 64.5 73.6 8 Mean Importance Average Importance Rating (a) Top Bottom Top Performance Measures: Third Third Third % % Rank C. Cost Measures 1. Outbound freight cost 4.40 (b) 3.67 3 2. Cost as a percentage of sales 4.33 (d) 3.95 6 3. Direct labor 4.03 3.76 7 4. Administrative cost 3.70 (d) 3.33 14 5. Warehouse order processing 3.90 (c) 3.31 9 6. Inbound freight cost 4.00 (c) 3.50 8 7. Direct product profitability 3.81 3.79 10 8. Cost of backorder 3.71 (c) 3.18 13 9. Comparison of actual versus budget 4.34 4.40 5 10. Total cost 4.56 4.35 1 11. Cost trend analysis 4.41 4.42 2 12. Cost of damage 3.55 3.26 15 13. Inventory carrying cost 3.79 3.39 11 14. Cost per unit 4.38 4.06 4 15. Cost of returned goods 3.45 3.17 17 16. Cost of customer segments 3.52 3.94 16 17. Cost of service failures 3.78 3.73 12 Mean Importance 3.98 D. Productivity Measures 1. Warehouse labor productivity 4.13 (d) 3.65 2 2. Comparison to historical std. 3.93 (c) 3.29 4 3. Units shipped per employee 4.07 3.86 3 4. Total productivity index 4.15 (c) 3.57 1 5. Equipment downtime 3.64 (b) 2.92 7 6. Orders per salesperson 3.00 (c) 3.54 9 7. Units per labor dollar 3.60 3.77 8 8. Order entry productivity 3.69 3.29 5 9. Transport labor productivity 3.68 3.69 6 Mean Importance 3.76 (a)Scale: 5=important; 1= unimportant (b)p [less than or equal to] .001 (c)p [less than or equal to] .01 (d)p [less than or equal to] .10 Table 6. Pearson Product-Moment Correlations Between supply Chain Strategies and Capabilities Customer Closeness Supply Chain Capabilities: Strategies Customization Agility A. Demand-Side Capabilities 1. Responsiveness to customers .567 (a) .301 (a) 2. Tailored services .344 (a) .316 (a) 3. Flexibility for special .246 (a) .253 (a) requests 4. Customer service .190 (a) .182 (a) 5. Customer input into strategy .343 (a) .207 (a) 6. Share risk with customers .349 (a) .180 (a) 7. Measure customer satisfaction .343 (a) .255 (a) 8. Frequently contact customers .175 (a) .285 (a) 9. Customer involvement in .278 (a) .301 (a) alliances 10. Visit customers frequently .193 (a) .222 (a) 11. Information systems for service .148 (a) .211 (a) improvement Operational Excellence Supply Chain Capabilities: Strategies Time- Lean Based Network A. Demand-Side Capabilities 1. Responsiveness to customers .081 .029 2. Tailored services .090 (c) .041 3. Flexibility for special .101 (c) -.017 requests 4. Customer service -.031 .032 5. Customer input into strategy .097 (c) .089 6. Share risk with customers .113 (b) 072 7. Measure customer satisfaction .032 .014 8. Frequently contact customers .070 .112 (b) 9. Customer involvement in .177 (a) .108 (c) alliances 10. Visit customers frequently .052 .086 11. Information systems for service .041 .003 improvement Operational Excellence Strategies Time- Lean Based Network B. Supply-Side Capabilities 1. Flow through cross-docking .291 (a) .196 (a) 2. Lead time improvement .189 (a) .145 (a) 3. Quick replenishment .223 (a) .203 (a) 4. Performance measurement .316 (a) .166 (a) 5. Inventory reduction .179 (a) .165 (a) 6. Least total cost .117 (b) .343 (a) 7. Efficient inventory deployment .142 (a) .264 (a) 8. Postpone inventory movement .101 (c) .163 (a) 9. Resident suppliers .088 .206 (a) 10. Information technology .148 (a) .249 (a) 11. Process improvement .158 (a) .134 (a) Customer Closeness Strategies Customization Agility B. Supply-Side Capabilities 1. Flow through cross-docking .136 (b) .123 (b) 2. Lead time improvement .124 (b) .171 (a) 3. Quick replenishment .110 (c) .160 (a) 4. Performance measurement .069 .098 (c) 5. Inventory reduction .054 .124 (b) 6. Least total cost .134 (a) .104 (c) 7. Efficient inventory deployment .111 (c) .110 (c) 8. Postpone inventory movement .059 .047 9. Resident suppliers .042 .004 10. Information technology .144 (a) .149 (a) 11. Process improvement .042 .087 (a)p [less than or equal to] .0001 (b)p [less than or equal to] .001 (c)p [less than or equal to] .01 n = 1358
(1.) David E. Feeny and Leslie P. Willcocks, "Core IS Capabilities for Exploiting Information Technology," Sloan Management Review, Vol. 39, No, 3 (Spring 1998), pp. 9-22; Daniel F. Lynch, Scott B. Keller, and John Ozment, "The Effects of Logistics Capabilities and Strategy on Firm Performance," Journal of Business Logistics, Vol. 21, No. 2 (2000), pp. 47-67; George S. Day, "The Capabilities of Market-Driven Organizations," Journal of Marketing, Vol. 58, No. 3 (October 1994), pp. 37-52; Andrew Bartmess and Keith Cerny, "Building Competitive Advantage Through a Global Network of Capabilities," California Management Review, Vol. 35, No. 2 (Winter 1993), pp. 78-103; George Stalk, Philip Evans, and Lawrence E. Shulman, "Competing on Capabilities: The New Rules of Corporate Strategy," Harvard Business Review, Vol. 70, No. 2 (March-April 1992), pp. 57-69; see also: Jeffrey S. Conant, Michael P. Mokwa, and P. Rajan Varadarajan, "Strategic Types, Distinctive Marketing Competencies, and Organizational Performance," St rategic Management Journal, Vol. 11, No. 5 (September 1990), pp. 365-383; Michael A. Hitt and R. Duane Ireland, "Corporate Distinctive Competence, Strategy, Industry, and Performance," Strategic Management Journal, Vol. 6, No. 3 (July-September 1985), pp. 273-293.
(2.) Michael Treacy and Fred Wiersema, The Discipline of Market Leaders, (Reading, MA: Addison-Wesley Publishing Co., 1995); Marshall L. Fisher, "What is the Right Supply Chain For Your Product?", Harvard Business Review, Vol. 75, No. 2 (March-April 1997), pp. 105-116; Edward A. Morash and Steven R. Clinton, 'The Role of Transportation Capabilities in International Supply Chain Management," Transportation Journal, Vol. 36, No. 3 (Spring 1997), pp. 5-17.
(3.) Treacy and Wiersema (1995); Global Logistics Research Team at Michigan State University, World Class Logistics: The Challenge of Managing Continuous Change, (Oak Brook, IL: Council of Logistics Management, 1995); Donald J. Bowersox, David J. Closs, and Theodore P. Stank, 21st Century Logistics: Making Supply Chain Integration a Reality, (Oak Brook, IL: Council of Logistics Management, 1999).
(4.) Edward A. Morash, Cornelia Droge, and Shawnee Vickery, "Strategic Logistics Capabilities for Competitive Advantage and Firm Success," Journal of Business Logistics, Vol. 17, No. 1 (1996), pp. 1-22.
(5.) Michael Treacy and Fred Wiersema, "Customer Intimacy and Other Value Disciplines," Harvard Business Review, Vol. 71, No. 1 (January-February 1993), pp. 84-93.
(6.) Gloabl Logistics Research Team at Michigan Slate University (1995); Donald J. Bowersox, David J. Closs, and Theodore P. Stank, 21st Century Logistics: Making Supply Chain Integration a Reality, (Oak Brook, IL: Council of Logistics Management, 1999).
(7.) Richard A. Spreng, Gilbert D. Harrell, and Robert D. Mackoy, "Service Recovery: Impact on Satisfaction and Intentions," Journal of Services Marketing, Vol. 9, No. 1 (1995), pp. 15-23; Christopher W.L. Hart, James L. Heskett, and Earl W. Sasser, Jr., "The Profitable Art of Service Recovery," Harvard Business Review, Vol. 68, No. 4 (July-August 1990), pp. 148-156.
(8.) Treacy and Wiersema (1995); (1993).
(9.) Treacy and Wiersema (1995).
(10.) Michael A. Cusumano and David B. Yoffie, Competing on Internet Time, (New York, NY: Touchtone, Simon & Schuster, 1998); George Stalk, Jr. and Thomas M. Hout, Competing Against Time: How Time-Based Competition is Reshaping Global Markets, (New York: The Free Press, 1990); George Stalk, Jr., "Time-The Next Source of Competitive Advantage," Harvard Business Review, Vol. 66, No.4 (July-August, 1988), pp.41-51.
(11.) Stalk and Hout (1990); Edward A. Morash and John Ozment, "The Strategic Use of Transportation Time and Reliability for Competitive Advantage," Transportation Journal, Vol. 36, No. 2 (Winter 1996), pp. 35-46; Morash and Clinton (1997).
(12.) Daniel T. Jones, Peter Hines, and Nick Rich, "Lean Logistics," International Journal of Physical Distribution and Logistics Management, Vol. 27, No.3(1997), 153-173.
(13.) Jones, Hines, and Rich, "Lean Logistics," (1997), pp. 157-162.
(14.) Ibid, pp. 154-157.
(15.) Treacy and Wiersema (1995); (1993); Fisher (1997).
(16.) Edward A. Morash, Cornelia Droge, and Shawnee Vickery (1996).
(17.) Richard Normann and Rafael Ramirez, "From Value Chain to Value Constellation: Designing Interactive Strategy," Harvard Business Review, Vol. 71, No. 4 (July-August 1993), pp. 65-77; John Ozment and Edward A. Morash, "The Augmented Service Offering for Perceived and Actual Service Quality," Journal of the Academy of Marketing Science, Vol. 22, No. 4 (Fall 1994), pp. 352-363; N.P. Greis and J.D. Kasarda, "Enterprise Logistics in the Information Era," California Management Review, Vol. 39, No. 4 (Summer 1997), pp. 55-78.
(18.) Treacy and Wiersema (1995); Normann and Ramirez (1993).
(19.) Richard L. Oliver, Roland T. Rust, and S. Varki, "Customer Delight: Foundations, Findings, and Managerial Insight," Journal of Retailing, Vol. 73, No. 3 (1997), pp. 311-336.
(20.) Christian Gronroos, Service Management and Marketing, (MA: Lexington Books, 1990); Edward A. Morash and John Ozment, "Toward Management of Transportation Service Quality," The Logistics and Transportation Review, Vol. 30, No. 2 (June 1994), pp. 115-140.
(21.) Global Logistics Research Team at Michigan State University (1995); Bowersox, Closs, and Stank (1999).
(22.) Toby B. Gooley, "Mass Customization: How Logistics Makes It Happen," Logistics Management and Distribution Report, Vol. 37, No. 4 (April 1998), pp. 49-53; Edward Feitzinger and Hau L. Lee, "Mass Customization at Hewlett-Packard: The Power of Postponement," Harvard Business Review, Vol. 75, No. 1 (January-February 1997), pp. 116-121; Joseph B. Fuller, James O'Conor, and Richard Rawlinson, "Tailored Logistics: The Next Advantage," Harvard Business Review, Vol. 71, No. 3 (May-June 1993), pp. 87-98; Global Logistics Research Team at Michigan State University (1995); Bowersox, Closs, and Stank (1999).
(23.) Treacy and Wiersema (1995); D.J. Champa and G.T. Long, "The Supply Chain Perspective: The Customer Service Mix," Council of Logistics Management Annual Conference Proceedings, II, (Oak Brook, IL: CLM, October 1989), pp. 151-156; E. Feitzinger and H.L. Lee, "Mass Customization at Hewlett-Packard: The Power of Postponement," Harvard Business Review, Vol. 75, No. 1 (January-February 1997), pp. 116-121.
(24.) Steven R. Clinton, David J. Closs, M. Bixby Cooper, and Stanley E. Fawcett, "New Dimensions of World Class Logistics Performance," Council of Logistics Management Annual Conference Proceedings, (October 1996), pp. 21-23.
(25.) John D. Kasarda and Dennis A. Rondinelli, "Innovative Infrastructure for Agile Manufacturers," Sloan Management Review, Vol. 39, No. 2 (Winter 1998), pp. 7382; Global Logistics Research Team at Michigan State University (1995); Bowersox, Closs, and Stank (1999); James Aaron Cooke, "Agility Counts," Traffic Management, (August 1995), pp. 27-31.
(26.) Treacy and Wiersema (1995); See also: Michael E. Porter, Competitive Advantage: Creating and Sustaining Superior Performance, (New York: The Free Press, 1985); and Michael E. Porter, "From Competitive Advantage to Corporate Strategy," in The State of Strategy, (Boston, MA: Harvard Business School Publishing, 1991).
(27.) Treacy and Wiersema (1993); (1995).
(28.) Stanley E. Fawcett, Sheldon R. Smith, and M. Bixby Cooper, "Strategic Intent, Measurement Capability, and Operational Success: Making the Connection," International Journal of Physical Distribution and Logistics Management, Vol. 27, No. 7 (1997), pp. 410-421; Michael E. Porter, Competitive Strategy, (New York: The Free Press, 1980), pp. 35-40;Treacy and Wiersema (1995); (1993); C.W. Hofer and D. Schendel, Strategy Formulation: Analytical Concepts, (St. Paul, MN: West Publishing, 1978).
(29.) Robert C. Camp, Benchmarking: The Search for Industry Best Practices that Lead to Superior Performance, (Milwaukee, WI: ASQC Quality Press, 1989); and Robert C. Camp, Global Cases in Benchmarking: Best Practices from Organizations Around the World, (Milwaukee, WI: ASQ Quality Press, 1998).
(30.) Bowersox, Closs, and Stank (1999); Robert C. Camp, Business Process Benchmarking: Finding and Implementing Best Practices, (Milwaukee, WI: ASQ Quality Press, 1995); Frances Tucker, Seymour M. Zivan, and Robert C. Camp, "How to Measure Yourself Against the Best," Harvard Business Review, Vol. 65, No. 1 (January-February, 1987), pp. 8-10; see also: Edward R. Bruning and Edward A. Morash, "Deregulation and the Cost of Equity Capital: The Case of Publicly Held Motor Carriers," Transportation Journal, Vol. 23, No. 2 (Winter 1983), pp. 72-81; and Edward R. Bruning, "An Analysis of the Technical Efficiency of Regulated Motor Carriers," Transportation Research Forum Proceedings, Vol. 21, No. 1(1980), pp. 209-2 10.
(31.) Camp (1989); (1998).
(32.) Bowersox, Closs, and Stank (1999); Camp (1995); (1989); Tucker, Zivan, and Camp (1987); see also: Bruning and Morash (1983); and Binning (1980).
(33.) Camp (1995); (1989); (1998); Bowersox, Class, and Stank (1999).
(34.) Fawcett, Smith, and Cooper (1997), Treacy and Wiersema (1995); (1993); Porter (1980).
(35.) Porter (1980), pp. 35-40; Treacy and Wiersema (1995); (1993).
(36.) Spreng, Harrel], and Mackoy (1995); Diane Halstead, Edward A. Morash, and John Ozment, "Comparing Objective Service Failures and Subjective Complaints: An Investigation of Domino and Halo Effects," Journal of Business Research, Vol. 36, No. 2 (June 1996), pp. 107-115; Mary Jo Bitner, Bernard M. Booms, and Mary S. Tetreault, "The Service Encounter: Diagnosing Favorable and Unfavorable Incidents," Journal of Marketing, Vol. 54, No. 1 (January 1990), pp. 71-84.
(37.) James L. Heskett, Earl W. Sasser, Jr., and Christopher W. L. Hart, Service Breakthroughs: Changing the Rules of the Ganze, (New York: The Free Press, 1990); see, also: Halstead, Morash, and Ozment (1996).
(38.) Treacy and Wiersema (1995).
(39.) See, for example: Goolcy (1998); Feitzinger (1997); Cooke (1995).
Mr. Morash, CTL-AST&L, is associate professor of logistics and supply chain management, Eli Broad Graduate School of Management, Michigan State University, East Lansing, Michigan 48824-1122.
This research is part of the larger arid ongoing logistics best practices research stream being conducted at Michigan State University.