KEyS To IMPROVING EcONOMIC PERFORMANCE AT THE BusINESS UNIT LEVEL: BUSINESS STRATEGY, FuNCnONAL SKILLS AND KEy SUCCESS FACfORS James J. Chrisman Louisiana State University Baton Rouge, Louisiana William R. Boulton Auburn University Auburn, Alabama Strategy is generally described in terms of the fit between an organization and its environment [3]. Strategy evaluation typically includes the analysis of this fit in terms of the firm's internal strengths and weaknesses and the opportunities and threats of its external environment [46]. The quality of the resulting strategic fit is argued to af- fect a firm's economic performance ([27], [38], [33], [48]). Leading theorists further argue that at the business level, a firm's skills and distinctive oompetences are the key building blocks of strategy ([27], [36]) and that strengths in different types of skills are needed to effectively pursue different types of strategies ([32], [33], [35]). Even though both the levels and types of competitive skills are considered important to the economic success of a strategy [28], few studies have oonsidered them simultaneously in support of this oontention. Researchers have studied strategy-performance relationships in terms of oompeti- live environments ([23], [42], [15], [11], [16], [2], [49]), competitive positions ([39], [14], [50], [13]), and key functional policy decisions ([18], [9], [12], [29]). These stud- ies concentrated on how such variables affect the scope component of competitive strat- egies, the investment component of business strategies, and the firm's economic per- formance. While verifying the importance of the environment in formulating effec- tive business strategies and supporting the notion that sustainable competitive advan- tages are related to superior performance, these studies have not identified how inter- nal functional skills affect business-level performance. Studies investigating the relationships among strengths and weaknesses, strategies, and firm. performance ([to], [19], [20], [21], [22]), have generally supported the work of earlier theorists ([40], [3], [27]). They have, however, almost without exception, concentrated on corporate-level strategy issues. The only business-level studies con- ducted to date have investigated the relationships between functional strengths and strategies, strengths and performance, and strategies and performance ([6], [41], [43]). There have been no business level studies though that have investigated how a firm's functional skills moderate strategy-performance relationships. Because corporate per- formance depends on the performance of individual business units [24], studies inves- tigating the relationships between strategies, functional skills, and performance at the business-level are clearly needed. Such a study must also account for the external factors already found to have relationships with strategy and performance. 170 Journal ofBusiness Strategies Vol. 9, No.2 To fill this gap, this article explores the relationships between competitive strat- egy, functional skills, key success factors, and economic performance at the business unit level. The study analyzes 27 fmns from six industries using what Harrigan [17] called a medium-grained research methodology. It is an attempt to build theory and test the broad premise of strategic management that economic success is related to the fit between a business strategy and the competitive skills used to meet the key success factors of an industry. The research questions central to this study are: 1. Is a business unit's overall competences in its functional skills related to its economic performance? 2. Is the fit between a business unit's competitive strategy, its dominant functional skills, and its industry's key success factor related to its economic performance? The lack of research and mid-level theories concerning the relationships between competitive business strategies, functional skills, and economic performance make hypothesis testing impractical for this study. There are classification systems for business strategy [5], skills [35], and key success factors [31], but few, if any, ad- equate propositions concerning the combinations of skills and key success factors re- quired for a particular strategy to achieve superior economic performance. It is the intent of this study to generate such propositions. Conceptual Framework & Language The conceptual framework used in this study (Figure 1) can be described as fol- lows. Since strategy represents the fit between an organization's functional skills and the key success factors in its competitive environment ([24], [27], [38], [32]), a busi- ness unit's choice of strategy should be influenced by the nature of its functional skills vis-a-vis those skills that are critical to success in its chosen domain of operations. The competitive strength of such skills should further determine the effectiveness of this strategy in achieving an advantageous competitive position and superior economic performance ([3], [24], [27], [1], [32]). Functional-Area Skills This study identified the skills that form the basis for competitive strategy, and may provide an organization with its competitive advantages. Functional skills include the tasks a firm performs in creating, producing, distributing, and marketing its prod- ucts or services. Thus, four types of functional skills are used in this study: research and development (R&D), manufacturing, distribution, and marketing ([4], [44], [27]). A business unit's dominant skill is defmed as the functional skill that it performs better than any of its other functional skills. We use the concept of dominant skill to supple- ment the concept of distinctive competence [40] because not every firm has a compe- tence so distinctive that it provides it with a competitive advantage ([3], [27], [41]). By contrast, a dominant skill is the key functional skill upon which the business unit Falll992 Chrisl1Ul1l & Boulton: Keys to Improving Performance 171 has based its strategy. By definitio~ every fum has a dominant skill whether or not it provides a basis for competitive advantage. Figure 1: Conceptual Framework KEY SUCCESS FAcroRS IN COMPETITIVE ENVIRONMENT BUSINESS UNIT'S DOMINANf FUNCTIONAL AREA SKILLS BUSINESS UNIT'S COMPEI'lTlVE STRATEGY BUSINESS UNIT'S COMPETITIVE POSmON BUSINESS UNIT'S ECONOMIC PERFORMANCE The Competitive Environment How does an industry's environmental context determine if a firm's functional skills and strategy provide it with sustainable competitive advantages? Most authoIS would suggest that strategy evaluation must compare the business unit's dominant skills or distinctive competences with its industry's key success factolS to determine whether it can develop competitive advantages ([46], [4], [3], [24], [27], [36], [32], [31]). The term "key success factor" denotes the functional skill that is considered critical to success in an industry [31] even though other skills might be more important in cer- tain segments of an industry. Research has sliown that business performance is re- lated to a firm's ability to develop strengths in areas that are key to success in its industry [43]. For the purpose of this study, the four functional skills used to clas- sify and identify the key success factor in each industry are research and development, manufacturing, marketing, and distnbution. Competitive Strategies Business strategies determine the fit between an organization's dominant functional skills and competences (i.e., corresponding strengths and weaknesses) and the key 172 Joumal ofBusiness Strategies Vol. 9, No.2 success factors in its competitive environment (i.e., corresponding opportunities and threats) as it pursues its objectives [27]. Realized strategies are, of course, the fit that actually is achieved [30]. Business strategies consist of three substrategies (investment, competitive, and political) which describe the nature of the strategic fit with the in- dustry ([24], [27]). Competitive strategies describe how resources are committed to functional skills and used to attain competitive advantages in the industry. Competitive strategies consist of three primary components: scope, segment dif- ferentiation, and competitive weapons ([1], [33]). Consistent with the work of Chrisman, Hofer, and Boulton [5], this study integrates the generic strategy classifica- tion schemes developed by Abell (differentiated, undifferentiated, and focus) and Por- ter (cost leadership, differentiation, and focus) to account for all three components of strategy. Both Abell's and Porter·s schemes are described below. According to Abell [1], a business can be defined by the scope of its offerings and the extent to which its offerings are differentiated across market segments. Busi- ness definition, therefore, consists of both the scope and segment differentiation com- ponents of strategy. At the business level scope can be described by the number and breadth of the total product-market segments a company serves in an industry. Seg- ment differentiation describes the extent to which an organization tailors its products, services, or operating methods (competitive weapons) to meet the unique needs of the various segments its serves. Using the terminology of Chrisman, Hofer, and Boulton [5], Abell's three types of business definition strategies have been adapted for this study as follows: mass-market businesses have broad scopes and use the same competitive weapons in all product-market segments they serve; segmented businesses also have broad scopes, but use different competitive weapons to serve different product-market segments; focused or niche-oriented businesses target only one or a few of the prod- uct-market segments in an industry. Competitive weapons refer to the way in which a business unit's functional skills are used to meet customer needs and combat rivals. Porter's [32] differentiation strat- egy is based on the use of benefit-oriented weapons appealing primarily to the non- economic needs of buyers. In this study, this strategy will be referred to as a benefit strategy. Porter's cost leadership strategy is based on the use of cost-oriented weap- oDS appealing primarily to the economic (price) needs of customers. Utility-oriented weapons refer to the balanced use of both costs and benefits, thereby meeting both economic and non-economic needs of the marketplace. In this study we refer to si- multaneous use of cost and benefit weapons as a utility strategy. Although Porter suggests that the majority of firms that attempt to develop a utility strategy based on the use of both cost and benefit weapons end up "stuck-in-the-middle" with no last- ing competitive advantage, research has shown that such an attempt can lead to supe- rior economic performance ([11], [7], [47]). The combination of Abell's business definitions with these three types of com- petitive weapons yields nine possible generic strategies: (1) focused cost; (2) focused utility; (3) focused benefit; (4) segmented cost; (5) segmented utility; (6) segmented benefit; (7) mass-market cost; (8) mass-market utility; and, (9) mass-market benefit Fall 1992 Chrisman & Boulton: Keys to Improving Performance 173 Competitive Position A business unit's competitive position will be determined by its ability to develop distinctive competences in its functional skills that fit its industry's key success factors, and the degree to which its strategy effectively exploits and enhances this fit ([3], [27). Thus, the types of functional skills a business possesses and its level of capability in them should be assessed relative to both its major competitors in the same businesses and its industry's key success factors ([44], [6], [10], [41], [19], [21], [22]). In this study, the level of competitive skill of a business unit in any functional area will be classified as strong, average, or weak, relative to its major competitors. A business unit's overall level of competitive capability is assessed in terms of its combined capability in its functional skills relative to its major competitors. In the world motorcycle industry, for example, the British competitor, Norton Villiers Triumph (NVf), was competitively weak in all major functional areas. However, NVT's domi- nant skill was in research and development. Even though R&D was NVT's dominant skill, Japanese competitors had much greater R&D strengths. NVT, therefore, had no significant competitive strengths; in other words, it possessed no distinctive competences. Business Unit Performance A business unit's competitive position results from its ability to develop and exploit competences that fit its industry's key success factors through the application of its competitive strategy. The resulting competitive position will determine its economic (financial and market) performance relative to its competitors. Business unit imancial performance has been measured in a variety of different ways such as by return on assets (ROA), return on equity (ROE), return on sales (ROS), and return on value added (ROVA), to name but a few [25]. Objective measures were used to determine rela- tive performance where data were available. However, it was also necessary to use subjective measures because business level performance data are much more difficult to obtain than corporate level performance data. Therefore, to compensate for this problem, a business unit's performance was ranked as superior, average, or inferior relative to competition, based on both objective measures and subjective assessments, as discussed below. Methodology To understand the nature of the relationship between competitive strategy, skills and competences, key success factors, and performance, a longitudinal analysis of 27 business units from six different industries was conducted. Both qualitative and quantitative data were collected and analyzed. Research Design & S8IDple Selection Hofer [24] argued that the stage of industry evolution is the most fundamental variable for determining an appropriate business-level strategy. He also suggested that 174 JOUT1IDI ofBusiness Strategies Vol. 9, No.2 the introduction, shake-out, and decline might be most strategically important to a business in developing its competitive strategy. Because past studies have supported Hofer's contention on the importance of the stage of an industry's evolution in deter- mining business unit performance ([2], [45]), this criterion was used as the primary basis for sample selection. III selecting the sample for this study, businesses competing in industries in the shake-out, maturity (usually the longest and most prevalent stage observable in an industry's life cycle), and decline stages of evolution were selected. Industries in the introductory stage were excluded after initial analysis showed a lack of sufficient data. For each stage of industry evolution studied, two consumer manufacturing industries were selected: one where buyer needs were considered to be primarily benefit-oriented and one where buyer needs were considered to be primarily cost-oriented [24}. In total, 27 businesses from six industries were studied. Market growth rates and the assessments of industry observers were used to identify each industry's stage of evo- lution. To ensure an adequate mix of functional competences amongst the sample, indus- tries were selected that included at least one firm with a dominant skill in R&D, manufacturing, and marketing or distribution. Descriptions of 24 industries and more than 100 companies, found in a total of 46 casebooks, industry analyses, and research monographs, were thoroughly reviewed to ensure that the industries selected met the research design criteria. Table 1 lists the six industries and 27 businesses included in this study as well as the time periods over which they were analyzed. Table 1: Industries & Businesses Selected for the Study SHAKE OUT MATURITY DECLINE Personal Computers Motorcycles Receivin~ Tubes 1980-1985 1967-1975 1967-1978 Apple BMW General Electric Commodore Harley-Davidson GTE Sylvania mM Honda RCA Osborne Norton Villiers Tandy Texas Instruments Fall 1992 Chrisman & Boulton: Keys to Improving Performance Table 1: Industries & Businesses (Continued) 175 SHAKE OUT MATURITY DECLINE Writing Instruments Watches Cigars 1968-1973 1968-1973 1964-1978 Bic Pen Bulova American Cigar Gillette Hamilton Watch Bayuk Cigar Scripto Seiko Consolidated Cigar The Swiss Culbro Timex Havatampa Jno. H. Swisher Data Gathering Methods A total of 119 secondary sources of information, including previously published case studies, articles in business periodicals and books, company documents, and reference books were content analyzed to obtain data for the study. General information about each industry and company was collected, as well as published statements from industry analysts concerning industry key success factors, functional skills, and business strategies ([17], [34], [37]). Data covering periods ranging from ten to twenty years for each business and industry were initially collected. However, strategies, skills, and industry key success factors can change over time. Therefore, each industry and com- pany was analyzed over time periods of five to fifteen years during which key suc- cess factors, dominant skills, and strategies remained relatively stable. If more than one time period was usable, the time period with the best quality data was selected. Initial analysis aid not suggest that differences in time periods or economic cycles influenced the results of this study. A subsequent test using different time periods for a subsample of eight business units from two industries further supported this assumption. Measurement Issues & Techniques Detailed case descriptions of each industry and its competing business units were developed. The cases included data on the key success factors of each industry, as well as the functional skills, strategies, and performance of each business unit. The cases averaged over 40 pages in length. Published reports by industry analysts were critical for identifying industry key success factors, business strategies, functional skills and competences, and performance. Comparative variables, including performance, were determined by ranking the competitors. Performance evaluations were made indepen- dently after all other variables were measured to minimize the possibility of rating bias. To ensure the measurement reliability of key success factors, dominant skills and distinctive competences, and competitive strategies, a two stage procedure was followed. 176 Journal ofBusiness Strategies Vol. 9, No.2 First, the two researchers independently evaluated the cases and classified the variables of interest. Their interrater agreement was 88.9 percent. Additional research resolved the few discrepencies that occurred. Second, a panel of seven doctoral students inde- pendently reviewed the detailed cases and completed data evaluation forms. While one member of the panel evaluated all six industries, the remaining six panelists evalu- ated three industries each. Therefore, a total of four judges independently identified each industry's key success factor, and the strategies, functional skills, and performance of each business unit Overall agreement between raters on all these evaluations was 75.9 percent, as shown in Table 2. Further discussion helped to attain final consen- sus in cases where raters disagreed. Table 2: Degree Of Agreement of the Evaluations of the Panel With tile Evaluadons of the Researchers on the Variables of Interest By Industry Key Sure- Dominant Business Economic ess Factor Skill Strategy Performance Total Interrater Agreement Personal Computers (6 firms) Writing Instruments (3 firms) Motorcycles (4 firms) Watches (5 firms) Receiving Tubes (3 firms) Cigars (6 firms) TOTAL INTERRATER AGREEMENT (27 firms in six industries) 3 of 4 23 of 24 17 of 24 19 of 24 62 of 76 (75.0%) (95.8%) (70.8%) (79.2%) (81.6%) 3 of 4 11 of 12 10 of 12 12 of 12 36 of 40 (75.0%) (91.7%) (83.3%) (100.0%) (90.0%) 2 of 4 11 of 16 14 of 16 10 of 16 37 of 52 (50.0%) (68.8%) (87.5%) (62.5%) (71.2%) 3 of 4 14 of 20 17 of 20 16 of 20 50 of 64 (75.0%) (70.0%) (85.0%) (80.0%) (78.1%) . 3 of 4 12 of 12 4 of 12 8 of 12 27 of 40 (75.0%) (100.0%) (33.3%) (66.7%) (67.5%) 4 of 4 18 of 24 15 of 24 15 of 24 52 of 76 (100.0%) (75.0%) (62.5%) (62.5%) (68.4%) 18 of 24 89 of 108 77 of 108 80 of 108 264 of 348 (75.0%) (82.4%) (71.3%) (74.1%) (75.9%) Falll992 Chrisnum & Boulton: Keys to Improving Performance 177 Functional Skills The functional skill that the organization performed better than any other was considered its dominant skill and was rated as strong, average, or weak. Interrater agreement on the dominant skills of the 27 businesses analyzed was 82.4 percent Each business unit's overall competence in the four functional areas studied were then analyzed relative to major competitors and rated as strong, average or, weak. All functional areas were weighted equally to obtain the business unit's level of overall functional competences. Rater assessments yielded consistent results in 82.4 percent of the cases. Additional research was conducted to resolve the discrepancies in the cases where the evaluations did not agree. K.ey Success Factors The key success factor for each industry was determined from published reports of recognized industry analysts. Their reviews described the importance of the vari- ous functional skills for an industry as a wnole and for particular product-market seg- ments of the industry. The observations of industry experts were generally consistent. Overall interrater agreement between the panel and researchers on the key success factors in the six industries included in this study was 75 percent Competitive Strategies Competitive strategies were evaluated in terms of scope, segment differentiation, and competitive weapons. Scope measures the extent of a business unit's product- market coverage and segment differentiation measures the number and type of competitive weapons used across served product-market segments. For example, a business unit with broad scope that competed in the same way across all major seg- ments served was considered to follow a mass-market strategy. A business unit with broad scope that varied its approaches across segments served was considered to fol- low a segmented strategy. A business unit that served only one or a few small seg- ments of the market, had a narrow scope, and, thus, was considered to follow a fo- cused strategy. Competitive weapons were distinguished using Porter's [32] criteria for classify- ing cost leadership and differentiation (benefit) strategies. The relative costs, prices, and benefits of the competing products and services offered by each business unit were examined. For example, a business with lower-priced products of average quality followed a cost strategy, a business with higher-priced products of high quality fol- lowed a benefit strategy, and a business with lower-priced products of high quality followed a utility strategy. The proportions of each business unit's activity in low, medium, and high priced segments were also considered. H, for instance, the business unit's major source of sales revenues came from lower priced products, it was considered to follow a cost strategy. Where possible, both methods of assessment were used and tended to yield consistent results. In all, the panel agreed 71 percent of the time with the research- ers' identification of the competitive strategies of the sample. 178 Journal ojBusiness Strategies Vol. 9, No.2 Economic Performance A business unit's economic performance was rated as superior, average, or infe- rior in relation to its major competitors. To the extent possible, evaluations were based on the actual fmancial (ROE, ROS, ROA) and market share data. However, for slightly more than half of the business units studied, the performance data used were qualita- tive. In these instances, performance data were determined from reports and observa- tions of industry analysts and executives. Dess and Robinson [8] showed that such subjective measurements, although less desirable than objective measures, are reason- ably accurate. In fact, the quantitative and qualitative performance evaluations were consistent in almost 80 percent of the cases where both types of data were available. The performance evaluations of the panel were consistent in almost 75% of the cases with the researchers' assessments. Data Analysis Techniques Nominal and ordinal business unit data were cross-tabulated and analyzed in a variety of ways. Patterns of successful strategies and functional skills, key success factors, and performance were identified. The strongest pattems were statistically tested using the chi-square, Kmskal-Wallis, and Wilcoxon rank-sum nonparametric tests. Small sample sizes, the ordinal nature of the data, and non-normal distributions pre- vented the use of parametric statistics. Tests were used to investigate the research questions descnbed earlier as well as to generate specific propositions on strategy-skill- performance relationships. Analysis & Results Is a business unit's overall competences in its functional skills related to its economic performance? The first research question compared a business unit's level of overall functional competences, relative to competitors, with its economic performance. Not unexpectedly, the level of a business unit's overall competences was found to be positively related to its performance (Table 3). The performance of almost 80 percent of the business units in the sample was consistent with their overall competences, a result significantly different from chance (p < .001). Falll992 Chrisman & Boulton: Keys to Improving Performance 179 Table 3: Relationships Between the Overall Strengths of a Business Unit and Its Economic Performance ECONOMIC PERFORMANCE Superior Average Inferior RELATIVE OVERALL STRENGTIIS Strong Average Weak 8* 3 0 0 6* 3 0 0 7* ·Correct Predictions: 21 of 27 (78%) Chance Predictions: 9 of 27 (33%) Chi-square goodness-of-fit test (dJ. = 1) = 24.0 (p < .001) A Kruskal-Wallis test provided additional support for this conclusion. Significant differences were found in the performance of businesses with strong, average, and weak overall competences in their functional skills (p < .001). Multiple comparisons of the three groups using the Wilcoxon rank-sum test revealed significant performance differences between businesses with strong and weak (p < .01), strong and average (p < .01), and average and weak (p < .05), overall competences. Is the fit between a business unit's competitive strategy, its dominant functional skills, and its industry's key success factor related to its economic performance? The matrix shown in Figure 2 shows the competitive strategies, dominant func- tional skills, industry key success factors, and relative economic performance of the business units included in this study. Each business unit is positioned in the matrix according to its industry's key success factor and the type of dominant functional skill it possessed. Its strategy (e.g., SB=segment benefit) and economic performance (e.g., O=average performance) are also denoted. Strategies and economic performance of the business units were then analyzed according to their positions in the matrix. 180 Jou17Ul1 ofBusiness Strategies Vol. 9, No.2 Figure 2: Competitive Strategies, Key Success Factors, Dominant Skills, and Economic Performance Of Consumer Products Manufacturers· KEY SUCCESS FAcroRS Product-Related R&D MFG Market-Related DST MKT R&D Product-Related MFG DOMINANT SKILL DST Market-Related MKT SU (+) I SU (0) SC (0) I SB (0)I IFB (-) I SB (-) I SB (0) I SB (-) I 1---- 1 -----~----r---- FB (0) I MU(+) FU (+) I MC(O) I SC (+) SC (-) I I FB (-) FC (-) I I SC (-) I I I. I I FB (-) I MC(+) FC (0) I SC (0) I FU (0) I I-----.J-----I-----L----l SB (+) SB (+) l MU(-) MC(+) I SC (-) I I I *Economic Performance: (+) = Superior, (0) = Average, (-) = Inferior Competitive Strategy: S = Segmented, F = Focused, M = Mass-market, B = Benefit, U = Utility. C = Cost Dominant Skills: R&D = Research & Development, MFG = Manufacturing. MKT = Market- ing, DST = Distribution The 16 cell matrix created small cell counts and made it difficult to find mean- ingful relationships. However, patterns within the matrix suggested that successful business units with dominant skills in product-related functions (i.e., R&D or manu- facturing) used different competitive strategies from than less successful firms, and from the successful firms with dominant skills in market-related functions (i.e., marketing or distribution). Likewise, successful firms with dominant skills in market-related functions used somewhat different strategies than their less successful counterparts. The same held tme when analyzing strategies and performance according to industry key success factors. These observations suggested that the matrix might be collapsed into product-related and market-related cells for further analysis. This simplified matrix Falll992 Chrisman & Boulton: Keys to Improving PerfoTl7Ulnce 181 allowed the analysis of larger sample sizes per cell. The simplified matrix is com- posed of four cells distinguished by the solid lines in Figure 2. Relationships Between Strategies And Key Success Factors No strategies were found to be superior or inferior to other strategies in all situ- ations. Analysis of the simplified matrix indicated, however, that a strategy's success was related to the key success factor in an industry. The Wilcoxon rank-sum test indicated that in industries where the key success factor was product-related, benefit strategies were significantly less successful than utility and cost strategies (p < .05). In fact, out of the six firms following benefit strategies, five (83%) experienced inferior performance vis-a-vis their major competitors. By contrast, all four firms employing utility strategies achieved at least average performance (50% achieved superior performance) and both of the firms following cost strategies attained superior perfor- mance. The inferior performance of the benefit strategies was particularly apparent when the businesses following those strategies had a product-related dominant skill. Benefit strategies were significantly more successful in industries where the in- dustry key success factor was market-related rather than product-related (p < .05). Benefit strategies also appeared more successful than cost strategies in industries with market-related key success factors, although the differences in performance were not statistically significant. Out of the nine business units following cost strategies in such industries, four (44%) experienced inferior performance, four (44%) were average per- formers, and only one (11%) achieved superior performance. By contrast, two of the four businesses (50%) following benefit strategies in those industries achieved supe- rior performance and two (50%) experienced average performance. Relationships Between Strategies And DoJDinant Skills Analysis of the simplified four-cell matrix also suggested that a strategy's success was related to the dominant skill of the business (Figure 2). The Wilcoxon rank-sum test indicated that business units following utility strategies significantly outperformed those that followed cost or benefit strategies when the dominant skill was product- related (p < .05). Thus, three of the four businesses (75%) following utility strategies achieved superior performance while only one of the six businesses (17%) followina cost strategies, and none of the seven (0%) following benefit strategies were able to do so. In fact, over half of the businesses following cost or benefit strategies experi- enced inferior performance relative to their major competitors. Cost strategies, how- ever, did seem to lead to slightly more favorable performance than benefit strategies for businesses with dominant skills in product-related functions, but this finding was not statistically significant. No strategies were found to be statistically superior for businesses with dominant skills in market-related functions. The utility strategies of the two businesses with dominant skills in market-related functions yielded average and inferior performance. On the other hand, two of the three businesses (67%) that followed benefit strategies achieved superior performance. Cost strategies also appeared to provide prospects for 182 Journal ofBusiness Strategies Vol. 9, No.2 at least average performance. Among the five firms following cost strategies, two were superior performers (40%), two were average performers (40%), and one (20%) was an inferior performer. Competitive Strategy Propositions Results indicate that successful strategies are related to both the dominant func- tional skill of a business unit and the key success factor of its 'industry. To further test such relationships, the propositions shown in Figure 3 were developed from the findings shown in Figure 2 and descnbed above. These propositions suggest what should be the best, next best, and worst strategies for a business depending on its dominant skill and the key success factor in its industry. The rationale for these propo- sitions is summarized as follows: Figure 3: Competitive Strategy Propositions· KEY SUCCESS FAcrORS Product-Related R&D MFG Market-Related DST MIcr R&D Product-Related MFG DOMINANT SKILL DST Market-Related MKT SEcrOR 1 SEcrOR 2 Best Strategy: UTILITY Best Strategy: UTILITY Next Best: COST Next Best: BENEFIT Worst Strategy: BENEFIT Worst Strategy: COST SEcrOR 3 SEcrOR 4 Best Strategy: COST Best Strategy: BENEFIT Next Best: UTILITY Next Best: COST Worst Strategy: BENEFIT Worst Strategy: UTILITY *ECONOMIC PERFORMANCE PREDICI10N: Best Strategy =Superior Performance Next Best = Average Performance Worst Strategy = Inferior Performance (1) Business units following the best strategy will usually achieve superior performance, (2) Business units following the next best strategy will usually achieve average performance, and, (3) Business units following the worst strategy will usually achieve inferior performance. Fall 1992 Chrisman & Boulton: Keys to Improving Performance 183 For example, according to the propositions in Sector 1 of Figure 3, a business with a dominant skill in a product-related function (R&D or manufacturing rows) that competes in an industry where product-related skills are key to success should be most successful using a utility strategy and least successful using a benefit strategy. In the same vein, a cost strategy should result in average pedormance. As shown in Table 4, a chi-square goodness-of-fit test indicated that in almost 75% (20 of 27) of the cases, performance predictions derived from the propositions shown in Figure 3 proved cor- rect, a result significantly different from chance (p < .001). Table 4: Competitive Strategies as Predictors of Business Unit Economic Performance ECONOMIC PERFORMANCE Superior Average Inferior APPROPRIATENESS Best OF STRATEGY SELECTED GIVEN DOMINANT SKILL Next Best AND KEY SUCCESS FACfOR Worst 6* 1 0 2 5* 1 0 3 9* ·Correct Predictions: 20 of 27 (74%) Chance Predictions: 9 of 27 (33%) Chi-square goodness-of-fit test (d.f. = 1) = 20.16 (p < .(01) Propositions About Competitive Strategy, Dominant Skills, And Performance Propositions provided in Figure 3 explain the variations in the sample's perfor- mance almost 75% of the time. However, since a business unit's relative economic performance will also be influenced by its relative overall competences (Table 3), following the correct strategy will not necessarily generate superior pedormance if the business unit's skills are weaker than its major competitors' skills. On the other hand, as Figure 3 presumes, an inappropriate strategy can reduce the economic effectiveness of even the strongest firms. A business with superior overall competences that devel- ops an appropriate strategy should be virtually guaranteed superior pedormance, and one with inferior overall competences and an inappropriate strategy should almost al- ways experience inferior performance. 184 Journal ofBusiness Strategies Vol. 9, No.2 To account for both the appropriateness of a business unit's strategy and its over- all competences relative to its competitors, the results regarding overall functional competences (fable 3) and business strategy (fable 4) were combined to develop the propositions shown in Figure 4. The actual performance of each business unit was then compared against the performance predicted by the propositions (fable 5). This approach allowed us to test the overall validity of the framework despite the fact that sample sizes were insufficient to individually test each proposition that made up the framework [26]. As Table 5 indicates, the combined framework helped explain the relative economic performance of the entire sample. While there is an obvious bias in using the same data to both develop and test a framework, the strong fit suggests that the propositions have high potential for explaining performance variations among consumer goods manufacturers. Figure 4: Strategy-Sldlls-Perlormance PropositioDS* RELATIVE OVERALL COMPETENCE OF THE BUSINESS·· STRATEGY*** Strong Average Weak BEST NEXT BEST WORST Superior Superior or Average Average or Inferior Superior or Average Average Average or Inferior Average Average or Inferior Inferior *Given the way the propositions illustrated in this matrix were formulated, performance could be correctly predicted by chance 51.9% of the tinie. "See Table 3 ·**See Figure 3 and Table 4 Fall 1992 Chrisman & Boulton: Keys to Improving Per/o17lUl1JCe 185 Table S: Actual Versus Predicted Economic Performance of the Sample of BusiDess Units· Relative Business Actual Predicted Company DS KSF Skills Strategy Performance Performance mM MId Mkt Strong Seg-Ben (+) (+) Bic Mkt Mkt Strong MM-Cost (+) (+)/(0) Honda R&D R&D Strong Seg-Util (+) (+) Timex Dst Mig Strong MM-Cost (+) (+) Seiko Mig Mig Strong MM-Util (+) (+) GTE Sylvania Mig Mig Strong Seg-Cost (+) (+)/(0) Consol. Cigar MId Dst Strong Seg-Ben (+) (+) Swisher Mig Ost Strong Foc-Util (+) (+) Apple R&D Mkt Average Seg-Ben (0) (0) Commodore Mig Mkt Average MM-Cost (0) (0)/(-) Tandy Dst Mkt Average Seg-Cost (0) (0) Gillette R&D Mkt Strong Seg-Ben (0) (0)/(+) BMW Mfg R&D Average Foe-Ben (0) (0)/(-) Bulova R&D Mig Average Seg-Util (0) (0)/(+) General Electr. Dst Mig Strong Foe-Util (0) (0)/(+) Culbro R&D O8t Strong Seg-Cost (0) (0) Havatampa Ost O8t Average Foe-Cost (0) (0) Texas Instr. Mfg Mkt Weak Seg-Cost (-) (-) Osborne Mfg Mkt Weak Foe-Cost (-) (-) Scripto Mig Mkt Weak Seg-Cost (-) (-) Harley-Dav. Ost R&D Average Foe-Ben (-) (-)/(0) NVf R&D R&D Weak Foe-Ben (-) (-) Hamilton(HMW) R&D Mig Weak Seg-Ben (-) (-) The Swiss Mfg Mfg Weak Foe-Ben (-) (-) RCA R&D Mig Average Seg-Ben (-) (-)/(0) American Cigar Mkt O8t Average MM-Util (-) (-)/(0) Bayuk Cigar Mkt Ost Weak Seg-Cost (-) (-)/(0) ·CORREcr PREDlcnONS: 27 of 27 (100%), CHANCE PREDIcnONS: 14 of 27 (51.9%). ECONOMIC PERFORMANCE Superior =(+), Average =(0), Inferior =(-) COMPETmVE SlRATEGIES Foe =Focused, MM = Mass-Marke4 Scg = Segmented, Ben = Benefi4 Util =Utility, Cost =Cost. DOMINANT SKII.J.JKEY SUCCESS FAcroR R&D = Researeh & Developmen4 Mfg = Manufacturing, Mkt = Marketing, Dst =Distribution 186 Journal ofBusiness Strategies Vol. 9, No.2 In sum, the effectiveness of the framework of propositions to predict the economic performance of the sample appears to support the theory of the field. The explana- tory power of the propositions shown in the Figure 4 framework was greater than those that considered either a business unit's overall functional competences (fable 3) or strategy (Figure 3 and Table 4) separately. Summary '" Coadusions The results of this study further support the conceptual arguments and research of the field of strategic management. Thus this study found that no generic strategy was inherently superior or inferior to other generic strategies. This study also found that successful business units had greater levels of competences in their functional skills than their less successful competitors, as well as strategies that better fit their dominant skills and the key success factors of their industries. This strongly suggests that superior performance depends upon both a business unit's ability to develop distinctive competences in its functional skills, and the strategy used to achieve fit between its dominant skills and the key success factors of its in- dustry. Neither distinctive competence nor strategy alone was as effective as both combined in predicting the relative economic performance of this sample. Thus, as strategic management theory argues, relative strengths or weaknesses in specific functional skills are important only in the context of the industry environment. It is the way in which a business utilizes these skills to support its strategy that ultimately determines its competitive position and performance. It is also interesting to note that the effective use of functional skills seems more important than either scope or degree of segment differentiation, since all the significant findings and propositions reported in this study related to the competitive weapons employed. Thus, within a given industry, how a business competes appears to be more important to its relative economic performance than where it competes. In short, this study confirms the usefulness of the concept of strategy for examining business unit performance, and the primary importance of identifying and developing distinctive competences that may lead to competitive advantage. Directioas For FutUl'e Researdl The findings of this study suggest a line of inquiry that may be generalizable to manufacturers of consumer products. First, the propositions generated from this study should be tested and refined through future research with larger samples. Replica- tions of this study in industrial manufacturing, retail, wholesale, and service businesses are clearly needed as are replications in conSumer products industries in other stages of development. Such studies sh~uld strive to improve upon the methods of sample selection, data collection, and variable measurements as these areas represent the pri- mary limitations of this exploratoty study. The development of competitive functional skills proved to be critical to attaining superior economic performance. Therefore, future studies might investigate a number Fall1992 Chrisman & Boulton: Keys to Improving Performance 187 of questions related to the nature of strategies needed to utilize, develop, and main- tain such competitive capabilities. Is it possible, for example, for a business to effec- tively change its dominant skill over time, or do initial choices determine, for all prac- tical purposes, its future in any specific industry? If it is possible, how long does it usually take for such changes to payoff! It would also be useful to investigate whether a business, can, or should, change either its strategy, dominant skills, or both when it finds that they do not match the key success factors of its industry. Similar studies to identify corporate-level competences and strategies that may either influence, or be transferrable to, the business level are also needed, as are stud- ies that relate corporate-level competences and strategies to diversification or innova- tion options. However, researchers should keep in mind that corporate-level competences are not simply aggregations of business-level competences [44]. Besides these replications and extensions, additional work is needed in improving the systems used for classifying and identifying organizational strategies, functional skills and competences, and various environmental characteristics such as key success factors. The extensive amount of time and attention paid to these areas are believed to have contributed to the generally high level of statistical significance of this study's findings despite its small sample size [36]. Implications For MlUUlgement Practice The findings of this study suggest that the most important challenges for business- level managers are (1) to develop distinctive competence in functional skills key to success in their industries, and (2) to formulate strategies that effectively utilize these functional competences. Thus, managers must appreciate the business unit's dominant skills and key success factors in its industry, and deploy the resources necessary to sustain and improve its capabilities in those areas. This suggests that a business will do better with a strategy built on its strengths than a strategy designed to compensate for its weaknesses. 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Keys to Improving Economic Performance at the Business Unit Level: Business Strategy, Functional Skills and Key Success Factors