THE COMPETITIVE ADVANTAGE OF USING ISO-9000 FOR FORTUNE 100 COMPANIES ABSTRACT

THE COMPETITIVE ADVANTAGE OF USING ISO-9000 FOR FORTUNE 100 COMPANIES David Flores University of Texas-Pan American, College of Business Administration 1201 West University Dr, Edinburg, TX 78541 Office 956-316-7955 Fax 956-381-2867 dfloresy18@broncs.utpa.edu ABSTRACT Fortune 100 companies with the ISO 9000 quality management systems can give the organization a competitive advantage by using ISO program. This paper analyzes financial performance data in the short run and long run to determine the effect Longevity of ISO9000 program has on firm performance using MANOVA, SEM, and multiple regression analysis. The interaction of short run performance times longevity of the ISO program on long run performance yielded a correlation with an R squared of 0.69 however more data should be gathered to better support MANOVA and SEM. LITERATURE REVIEW Quality may be defied as fitness for use or how well a product or service meets or exceeds the customer s expectations. How do organizations assure their customers about the quality of their products in a cost efficient manner? In the past companies would have to conduct expensive external supplier audits to verify a supplier s product conformed to product specifications using a total quality management (TQM) approach. In 1987 ISO 9000 was created by a committee in Europe to help set quality measurement standards. The word ISO is Greek, which means the same. ISO in this paper refers to the International Organization for Standardization. ISO is a network of the national standards institutes of 157 countries, based on one member per country, with a Central Secretariat in Geneva, Switzerland, that coordinates the system. The standards establish by the organization are also referred to as ISO standards. The ISO 9000 standard allows a registrar company to conduct outside audits of a company s quality management system (QMS), which certifies the implementation and compliance of the QMS to the ISO 9000 standard (Anderson, Daly, and Johnson 1999). The ISO 9000 certified company can achieve a competitive advantage over its rivals by closely following the ISO requirements listed in the ISO 9000 requirements manual and tailoring it to fit internal processes. 644

A brief description of the ISO 9000 process can be summarized from reviewing the ISO 9000 standard which was originally issued in 1987 then revised in 1994 and again in 2000. ISO 9000 initially was made of 20 clauses for management to follow. The ISO standards board revised the ISO 9000 standard to 8 clauses in the ISO 9001:2000 version. Companies do not have to be in manufacturing to use the latest version of the ISO 9001:2000 standard (www.iso.org). ISO 9000 will be referring to the new ISO9001:2000 version for the remainder of the paper. ISO 9000 requires organizations to document, review, and continually improve their business processes which also forces the firm to look at its institutional context and resource decisions as seen in Figure 1 taken from page vi of the ISO 9000 standard. In the ISO model the resource management along with measurement, analysis, and improvement of internal processes cover the resource based decisions. Management responsibility incorporated with information flow from the customer and the internal process procedures provide the institutional context. Oliver 1997 posits corporations may have a sustainable competitive advantage by combining institutional and resource based views. 645

The context and process of resource selection have an important influence on firm heterogeneity and sustainable competitive advantage(oliver 1997). ISO 9000 requires firms to examine its resources and follow the established regulations. A firm s sustainable advantage depends on its ability to manage the institutional context of its resource decisions. Both resource capital and institutional capital are indispensable to achieve a sustainable competitive advantage (Oliver 1997). Oliver also introduces a model of sustainable competitive advantage that combines resource-based and institutional factors at the individual, firm, and interfirm levels of analysis. The process model in ISO9000 is similar to Oliver's model because it also requires management to take into consideration the context of the institution factors and effective use of the organization s resources. The management of a company can be modeled based on the resource based view using the ISO 9000 quality management system standard not only for production but for other departments within the organization as well as service organizations. The resource based view (RBV) states four criteria to sustain a competitive advantage, the company's resources: 1. add positive value to the firm 2. must be unique or rare 3. imperfectly imitable and 4. cannot be substituted with another resource by competitors (Wright and McMahan 1992). These competitive advantages can be achieved using the ISO 9000 quality system not only within the manufacturing departments of the company but also in other departments such as, service, sales, marketing, human resources, and accounting using continual process improvement. Many company executives believe that their organization can gain a competitive advantage if they achieve ISO 9000 certification. Wayhan, Kirche, and Khumawala (2002) measured return on assets for the financial performance of ISO 9000 certified companies and reported the impact of ISO 9000 certification on return on assets was minimal and does not last over time. In a previous analysis management effectiveness of the companies was measured as ROA, ROI, and ROE and compared as two groups, ISO 9000 certified companies versus Non- ISO 9000 certified companies which was analyzed using simple ANOVA. The results for comparison of the means for ROA, ROI, and ROE did not show a significant difference using the simple ANOVA analysis although the average of ISO certified companies was slightly higher than non-certified companies. Performance improvement depends on the level of assimilation of the ISO 9000 program and the degree to which an organization goes beyond the minimal requirements (Naveh and Marcus 2005). The ISO 9000 program once implemented requires the company to train all personnel in the use of the approved written quality management system (QMS) procedures. As persons use and learn the organizational routines such as written company policies the more likely the persons in the organization are to use the written rules and policies (Cohen and Bacdayan 1994). Longevity in this study is the time in years that a company has been ISO9000 certified. Therefore the more years a company has used ISO 9000, the longer the longevity of ISO 9000, the more likely the organization will effectively use ISO9000 and gain a competitive advantage. A sustained competitive advantage depends on the resource endowments controlled by the firm (Barney 1991). ISO9000 allows companies to control their resource endowments as shown in the previously mentioned figure 1. ISO9000 certified companies are required to recertify their system every 3 years which ensures companies are keeping up with any new standard revisions. The recertification process requires the entire company QMS to be completely audited by an 646

external auditor. The recertification ensures that the ISO9000 certified company is using all aspects of its QMS and therefore the benefit of ISO 9000 longevity continues. In some industries, like the automotive industry, ISO 9000 has become a minimum requirement for competing. The key for each individual company to stay competitive is to make sure that its particular ISO9000 QMS is uniquely tailored to its internal processes to maximize the efficient use of its particular resources. If a company just becomes ISO9000 certified using generic procedures it will not achieve a competitive advantage because the generic procedures are not unique and therefore no sustained competitive advantage can be achieved by the company using generic procedures. Resources and process become imperfectly imitable when the ISO9000 system is uniquely tailored which gives the firm a sustained competitive advantage due to the social complexity (Barney 1991) of its QMS. DATA ANALYSIS This paper will use Multivariate techniques to analyze financial performance data in the short run and long run to determine advantage of ISO 9000 and the effect Longevity of ISO9000 program has on firm performance using MANOVA, SEM, and multiple regression analysis. Data analysis was done by gathering data from the 2006 Fortune 100 list, Reuters Financial 2006, and QSU Publishing 2006. A one year average is used for short run return and a five-year average is used for a long run return. The companies that had complete data available via Reuters Financial were included in the analysis. The companies with incomplete data were excluded from the analysis and reduced the sample size from the original 100 United States Fortune 100 companies to 82 United States Fortune 100 companies. The financial data was obtained from Reuters Financial, which presents three different ratios return on assets (ROA), return on investment (ROI), and Return on Equity (ROE) to measure management effectiveness. All three ratios use Net Profit as the measure of return. The differences in the ratios are how the amount of capital employed (assets, investments, or equity) in the business is measured. Reuters Financial recommends using the one year performance data to get a sense of whether the present is a strong or sluggish period. Use 5-year average return to assess how effectively management utilizes the capital available to it over time. A multi-group analysis was done to see if the ISO 9000 certification can show a significant effect on company s performance as measured by the returns. The research model in the study looked at the type of company and ISO 9000 certification. There are 8 type of sectors found in the sample of fortune 100 companies which are Basic Materials, Conglomerates, consumer goods, financial, healthcare, industrial goods, services, and technology. The 8 types of sectors can be grouped into the 2 general groups of Manufacturing (Basic Materials, Consumer Goods, Industrial Goods, and Technology) and Services(Financial, Healthcare, and Services) conglomerates were not include due to the fact that they typically have different divisions that may be classified into either the manufacturing or services each sector then analyzed. The manufacturing sector performed better then the service sector but no interaction affect was found from the lone variable of being ISO 9000 certified when compared to the service sector. METHODOLOGY 647

MANOVA-Multivariate Analysis of Variance MANOVA is Multivariate ANalysis Of Variance and looks at the relation between two or more dependent variables and two or more independent variables looking for statistical significance of differences between groups with MANOVA. The null hypothesis tested is the equality of vectors of means on multiple dependent variables across groups. In other words the null hypothesis (H o ) = all the group mean vectors are equal; they come from the same population. Mathematically H o : μ 11, μ 21,...μ p1 = μ 12, μ 22,...μ p2 =...= μ 1k, μ 2k,...μ pk (1) μ pk = means of variable p, group k The null hypothesis expects the groups' means to not have a significant difference between groups no matter what variation of characteristics a group may have. Hair, Black, Babin, Anderson, and Tatham (2006) describe MANOVA as a six step process which was followed in this part of the analysis. MANOVA gives a structured method for specifying the comparisons of group differences on a set of dependent measures in this case Fortune 100 ISO9001:2000 certified companies performance versus non ISO certified companies performance is analyzed using MANOVA. In this case we have 6 variables (one year and five year ROA, ROE, and ROI) for Fortune 100 companies performance data versus non ISO certified companies performance is analyzed using MANOVA with 82 companies in the sample. For sample size each group should have at a bare minimum more data points than the number of variables, preferably more than 20 observations per group, and the number of observations should also increase with the number of dependent variables. The number of treatments or independent variables is limited by the number of cells or groups formed by the combination of independent variables. If you have a two category nonmetric variable (e.g. ISO certified and Non-ISO certified company) combined with a two category nonmetric variable(service-industry, and manufacturing-industry) will result in a 2 by 2 design with four cells or groups which would require 80 samples if you obtain the minimum 20 samples per group which this study just meets with 82 samples. The data was accepted as is without removing outliers, the auto industry, which showed very poor performance and was ISO 9000 certified because the researcher did not want to exclude data. Estimation of the MANOVA model and assessing overall fit was accomplished using SPSS software. Effect Intercept MAJOR_SE ISOCERT MAJOR_SE * ISOCERT Pillai's Trace Wilks' Lambda Hotelling's Trace Roy's Largest Root Pillai's Trace Wilks' Lambda Hotelling's Trace Roy's Largest Root Pillai's Trace Wilks' Lambda Hotelling's Trace Roy's Largest Root Pillai's Trace Wilks' Lambda Hotelling's Trace Roy's Largest Root Multivariate Tests c a. Computed using alpha =.05 b. Exact statistic c. Design: Intercept+MAJOR SE+ISOCERT+MAJOR SE * ISOCERT Partial Eta Noncent. Observed Value F Hypothesis df Error df Sig. Squared Parameter Power a.739 33.533 b 6.000 71.000.000.739 201.197 1.000.261 33.533 b 6.000 71.000.000.739 201.197 1.000 2.834 33.533 b 6.000 71.000.000.739 201.197 1.000 2.834 33.533 b 6.000 71.000.000.739 201.197 1.000.218 3.299 b 6.000 71.000.006.218 19.794.913.782 3.299 b 6.000 71.000.006.218 19.794.913.279 3.299 b 6.000 71.000.006.218 19.794.913.279 3.299 b 6.000 71.000.006.218 19.794.913.036.437 b 6.000 71.000.851.036 2.624.170.964.437 b 6.000 71.000.851.036 2.624.170.037.437 b 6.000 71.000.851.036 2.624.170.037.437 b 6.000 71.000.851.036 2.624.170.080 1.022 b 6.000 71.000.418.080 6.134.378 648.920 1.022 b 6.000 71.000.418.080 6.134.378.086 1.022 b 6.000 71.000.418.080 6.134.378.086 1.022 b 6.000 71.000.418.080 6.134.378

Table 1: MANOVA Results Table 1 shows the interaction effect of major industry sector and ISO certification is not significant. The major industry sector alone is significant which means that the performance difference between manufacturing sector and service sector is significant for Fortune 100 companies. The results were examined to see how each independent variable affects the dependent measures. Interactions must be examined closely if found to be statistically significant however in this case the interaction effect was not significant. Structured statistical tests can be used to look at group differences across specific pairs for one or more dependent measures. Validating the results by replication could be done by gathering more data. Any ANOVA design on a single dependent variable can be extended to a MANOVA design. MANOVA has the flexibility to enable the researcher to select the test statistics most appropriate for the question of concern. MANOVA can examine several dependent variables simultaneously. Its strength is the ability to handle multiple dependent measures but you should have a good conceptual or theoretical basis for using MANOVA. MANOVA can help maintain control over the experiment wide error rate. The experiment wide error rate range increases when you use ANOVA to do a several similar analyses that could be done at one time using MANOVA. For example if you wanted to analyze five dependent variables separately with ANOVA using an alpha of 0.05 instead of simultaneously with MANOVA, Hair etal p400...the probability of a Type I error lies somewhere between 5 percent, if all dependent variables are perfectly correlated, and 23 percent (1-.95^5), if all dependent variables are uncorrelated. Also the dependent variables for MANOVA should be selected based on good theoretical basis and not just guesses. SEM Path Analysis The Longevity of the ISO program, how many years the Fortune 100 company has been ISO9000 certified, was gathered to determine if the longevity had a moderating effect on the firms endogenous variables short run performance and long run performance. The short run performance (1year) was reflected in the 1 year ROA, ROE, and ROI and long run performance (5 year) was reflected in the 5 year ROA, ROE, and ROI performance as shown in figure 1. The covariance matrix was generated using SPSS with 7 variables and then SEM analysis was performed with AMOS which resulted in significant findings for the default model in all variable interactions except longevity of ISO9000 on short run performance. However due to the small sample size this should only be used for reference only. Data and path diagram can be provided upon request. Regression Analysis 649

The SEM analysis was followed by a multiple regression analysis predicting the average long run performance using average short run performance, longevity of ISO and the interaction term of short run performance times longevity of ISO after discussion with a colleague. The average short run performance was taken as the average of the 1year ROA, ROE and ROI. The average long run performance was taken as the average of the 5year ROA, ROE, and ROI. The common regression approach was used to find out the effect of the interaction term on the long-run performance "variable" which can be seen in figure 3 with an R 2 =0.69 using Excel. The data was also analyzed with SPSS regression analysis and the model summary, ANOVA, and coefficient results, are given in the tables 2 to 4. 60.00 50.00 40.00 y = 0.1235x + 1.5889 R 2 = 0.6893 30.00 Average % Return 20.00 10.00 0.00-50.00 0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00-10.00-20.00-30.00 Interaction Short Run * Longevity F igure 2: Interaction Term and Long Run Performance Change St atistics Model R Adj. R Std Error of F Sig. F Durbin R square square Estimate R square Change Df1 Df2 Change Watson 1.785(a).616.605 4.90025.616 59.279 1 37.000 1.733 a Predictors: (Constant), LongevityISO*ShortRunPerformance b Dependent Variab le: AverageLongRun Table 2: Model Summary Common Regression Approach (b) 650

Model Sum of Squares Df Mean Square F Sig. 1 Regression 1423.425 1 1423.425 59.279.000(a) Residual 888.459 37 24.012 Total 2311.884 38 a Predictors: (Constant), Long*SR b Dependent Vari able: AvgLR Table 3: ANOV A Common Regression Approach (b) Model Unstandardized Coefficients Std. Coef. Std. B Error Beta T Upper Bound 95% Confidence Interval for B Correlations Collinearity Statistics Zeroorder Std. Partial Part Tolerance VIF B Error 1 Constan 3.179 1.225 2.596.013.698 5.660 LongSR.046.006.785 7.699.000.034.058.785.785.785 1.000 1.000 a Dependent Variable: AvgLR Table 4: Common Regression Approach Coefficients(a) The multigroup appro ach was used to find out the effect of longevity on the "relationship" b etween the short-run performance and long-run performa nce. Change Statistics Model Std Error R Adj R of R Sig. F Durbin R Square Square Estimate square F Change Df1 Df2 Chang Watson 1.793(a).629.598 4.94777.629 19.813 3 35.000 1.792 a Predictors: (Constant), longevity-yrs, AvgSR, LongSR b Dependent Variable: AvgLR Table 5: Multigroup Reg ression Model Summary (b) Model Sum of Squares df Mean Square F Sig. 1 Regression 1455.069 3 485.023 19.813.000(a) Residual 856.814 35 24.480 Total 2311.884 38 a Predictors: (Constant), longevity-yrs, AvgSR, LongSR b Dependent Variable: AvgLR Table 6: Multigroup Regression ANOVA(b) Model Unstandardize d Coefficients B Stnd. Coef. Std. Error Beta T Upper Bound 95% Confidence Interval for B Correlations Collinearity Statistics Zeroorder Std. Partial Part Tolerance VIF B Error 651

1 Const. 1.567 6.721.233.817-12.078 15.211 LongSR.059.042.997 1.397.171 -.027.144.785.230.144.021 48.06 AvgSR Longevi ty-yrs -.177.502 -.239 -.351.727-1.196.843.724 -.059 -.036.023 43.82.172.568.059.303.764 -.982 1.326.346.051.031.276 3.63 a Dependent Variable: AvgLR Table 7: Multigroup Regression Coefficients(a) The individual variables of short run performance average(standardized beta = -.239) and longevity of ISO (standardized beta =.059) appear to have an opposite effect on the dependent variable long run performance averag e which can be seen in table 7. The multigroup model t values in Table 7 are in bold lettering and not significant. However it should be noted for future research increasing the sample size to the included the ISO9001:2000 certified companies in the Fortune 500 may yield a significant result. IMPLICATIONS The results are somewhat inconsistent with each other, so the interpretations are different. They are two approaches to examining the moderating effects: interaction approach that emphasizes the effect on the dependent variable vs. multigroup approach that emphasizes the effect on the relationship. Most commonly, researchers assume that a continuous moderator variable alters the relationship between the independent and dependent variables in a linear function. (Kim etal 2001). The interaction term regressed with dependent variable alone does show a significant relationship as well as having significant t values (Table 4). The data suggest that short run and long run performance are moderated by the longevity of the ISO 9000 program. When the data was regressed including the short run, longevity of ISO 9000 to predicted long run performance no significance was found indicating longevity of ISO is a moderator. The inconsistent results may be due to the fact that the sample size, N=39 for this analysis, was to small for this analysis to show the effect of the relationship so at this point we cannot compare these two approaches and discuss their own strengths and weaknesses. They may be able to supplement each other if we can gather more data perhaps extending the samples to include the Fortune 200 or 500. Relating the analyses to the theory how longevity of the ISO 9000 enhances the performance of certified companies shows that the interaction term is significant not only in the model but also in the t values of the coefficients so this indicates that longevity of ISO interacting with short run performance does positively affect long run performance. Gupta 2000 found statistically significant differences in quality management practices between ISO 9000 and non-iso 9000 organizations operating in India. Gupta examined four categories training, using quality in the strategic planning, product design, and team building. Perhaps as Fortune 100 companies use ISO 9000 they also have positive affects in Gupta s four categories. FUTURE RESEARCH 652

The four categories studied by Gupta (training, using quality in the strategic planning, product design, and team building) can be the focus of Future research to see if a statistical difference exists in the ISO 9000 certified versus the Non-ISO 9000 certified United States Fortune 100 companies. Future studies can gather more data perhaps extending the samples to include the Fortune 200 or 500 to increase the sample size of ISO certified from N=39. The data may also be extended to cover more years of financial performance data rather then the current 1 year and 5 year performance data which may lead to more findings based on a longitudinal study versus the current cross-sectional study. Future studies may focus on how well the ISO 9000 certified companies use their ISO 9000 certified Quality Management System (QMS). The researcher may gather evidence from different ISO 9000 certified companies to see if the companies practice what they preach. Examination of the companies internal ISO 9000 auditing systems would help shed light on how well they use the ISO 9000 QMS. Measures could be made of the frequency of audits, the internal auditors departmental backgrounds, how many audits findings are identified per audit, and what action is taken on the internal audit findings. The researcher may then identify how often and well the companies use the I SO 9000 QMS to gain a competitive advantage or not. Increasing the sample size to include other measurement aspects that make ISO-9000 a good tool such as Naveh and Marcus 2005 who used a survey of managers to determine the usage ISO 9000 and if ISO 9000 was used as a catalyst for change. REFERENCES Anderson, S.W., Daly, J.D., and M.F. Johnson (1999). Why Firms Seek ISO 9000 Certification: Regulatory Compliance or Competitive Advantage? Production and Operations Management 8(1), 28-43. Barney, J. (1991). Firm Resources and Sustained Competitive Advantage, Journal of Management 17(1), 99-120. Cohen, M.D., and Bacdayan P. (1994). Organizational Routines Are Stored As Procedural Memory: Evidence from a Laboratory Study Organization Science 5(4), 554-568. Fortune (2006). Largest U.S. Corporations 153 (7), April 17 p.1-20. Gupta, A. (2000). Quality Management Practices of ISO vs. Non-ISO Companies: a Case of Indian Industry Industrial Management & Data Systems 100(9), 451-455 Hair, J. F., Black, W.C., Babin, B.J., Anderson, R.E., and Tatham, R.L. (2006). Multivariate Data Analysis. Upper Saddle River, New Jersey: Pearson Prentice Hall Hand, D.J., and Taylor, C.C. (1987). Multivariate Analysis of Variance and Repeated Measures. London: Chapman and Hall. International Standard ISO9001:2000 3 rd ed 2000-12-15 Quality Management Systems Requirements, ISO copyright office Case postale 56 CH-1211 Geneva Switzerland 20 Tel. + 41 22 749 01 11 Fax + 41 22 749 09 47 E-mail copyright@iso.ch Web www.iso.ch Kim, J.S., Kaye, J., and Wright, L.K. (2001). Moderating and Mediating Effects in Causal Models Issues in Mental Health Nursing 22, 63-75. Naveh, E. and Marcus, A.A. 2005, When does the ISO 9000 Quality Assurance Standard Lead to Performance Improvement? Assimilation and Going Beyond, Engineering Management, IEEE Transactions on 51(3), 352 363. 653

Oliver, C. (1997) Sustainable Competitive Advantage: Combining Institutional and Resource Based Views Strategic Management Journal 18 (9), 697 713. QSU Publishing http://www.whosregistered.com/iso/form.php accessed October 11, 2006 Reuters Financial http://finance.yahoo.com/q/ks accessed October 13, 2006 Wayhan, V.B., Kirche, E.T., and Khumawala, B.M. (2002). ISO 9000 Certification: The Financial Performance Implications Total Quality Management 13(2), 217-231. Wright, P.M. and McMahan, G.C. (1992). Theoretical Perspectives for Strategic Human Resource Management Journal of Management 18(2), 295-320. I would also like to thank two anonymous reviewers for their helpful comments and suggestions. 654