The Six Sigma program: an empirical study of Brazilian companies

Journal of Manufacturing Technology Management The Six Sigma program: an empirical study of Brazilian companies Marly Monteiro de Carvalho Linda Lee Ho Silvia Helena Boarin Pinto

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JMTM 25,5

The Six Sigma program: an empirical study of Brazilian companies

602

Marly Monteiro de Carvalho, Linda Lee Ho and Silvia Helena Boarin Pinto

Received 20 April 2012 Revised 18 December 2012 1 February 2013 Accepted 5 February 2013

Production Engineering Department – Polytechnic School, University of Sa~o Paulo, Sa~o Paulo, Brazil Abstract


Purpose – The purpose of this paper is to assess the status of Six Sigma’s status in Brazilian companies and understand the integration of this program with other quality management approaches. Additionally, the critical success factors (CSFs) for Six Sigma implementation and primary Six Sigma program characteristics were identified. Finally, the results of the used of Six Sigma were analysed. Design/methodology/approach – An extensive literature review illustrates the primary Six Sigma characteristics and its relationship with other quality approaches. The research methodology encompasses survey development and statistical analyses. Questionnaires are distributed to 1,000 large firms in the manufacturing and service industries in Brazil. Altogether, a total of 198 firms, of which 46 companies adopted the Six Sigma program, participated in this study. Findings – The results suggest a synergic and incremental pattern of quality model implementation. The study reveals that companies that have adopted Six Sigma have a long history of implementing quality programs, which suggests a certain level of quality maturity. The studied companies perceive in Six Sigma an incremental evolution, which can be combined with earlier initiatives and provides strong synergy with ISO 9000. The findings of this study confirm the distinctive Six Sigma role structure suggested by several authors. However, three possible configurations of the role structure were found that differ in terms of training and the dedication of human resources involved in the Six Sigma program. Research limitations/implications – This study demonstrates the inherent limits of the research method adopted, the use of a non-probabilistic sample and a reliance on self-reported perceptions, which introduces bias to the analysis. Practical implications – Important managerial implications of this study are related to the Six Sigma structure adopted. The capillarity of the program in the organisation as a whole can be related to the type of role structure configuration adopted. This structure can have an impact in terms of both numbers and employees’ and managers’ degree of involvement, as well as the type of training and resources provided. Originality/value – The diffusion of Six Sigma in Brazilian companies is less widespread than in other countries. Three possible configurations of the role structure were found that differ in terms of the training and dedication of human resources entailed by the Six Sigma program. Three CSFs factors were identified: organisation, infrastructure and human resources. Keywords Six Sigma, Quality management Paper type Research paper

Journal of Manufacturing Technology Management Vol. 25 No. 5, 2014 pp. 602-630 r Emerald Group Publishing Limited 1741-038X DOI 10.1108/JMTM-04-2012-0045

1. Introduction Many authors recognise the difficulty of defining the constructs and boundaries of Six Sigma but emphasise that the program has singular aspects with respect to other The authors wish to thank the CNPq and the CAPES for supporting this research. The authors wish to express gratitude to the reviewers who contributed to the improvement of this paper.


quality management approaches (Klefsjo¨ et al., 2001; McAdam and Lafferty, 2004; Lloreńs-Montes and Molina, 2006; Schroeder et al., 2008; Linderman et al., 2003; Choo et al., 2007). Nevertheless, some authors argue that there is nothing significantly new regarding the Six Sigma approach (Clifford, 2001), so it has assumed characteristics of a managerial fad (Abrahamson, 1996). This argument is based on the lack of significant differences between the constructs of Six Sigma and those outlined in TQM (Saraph et al., 1989, Dale et al., 1994; Flynn et al., 1994; Ahire et al., 1996; Zeitz et al., 1997; Black and Porter, 1996; Powell, 1995; Martıńez-Lorente et al., 1998; Motwani, 2001; Douglas and Judge, 2001). The sensation of “de´ja` vu” experienced with respect to the Six Sigma literature is very evident. In between these controversial streams, some authors state that the Six Sigma program is leveraged by the prior implementation of other improvement approaches. Furthermore, the Six Sigma program depends on the foundations of quality improvement models previously implemented, as corroborated by various authors (Benner and Tushman, 2002; Shankar, 2003; Shah et al., 2008; Zu et al., 2008; Kumar and Antony, 2008; Kumar et al., 2011; Timans et al., 2012). Despite academic discussion, companies have tested the Six Sigma program. Through the use of the impressive earnings figures obtained and disseminated by companies who pioneered its implementation, such as Motorola, General Electric, Allied Signal and Citibank, the program was publicised, particularly among large companies (Mitchell, 1992; Harry, 1998; Harry and Schroeder, 2000; Pande et al., 2001; Basu, 2004). This program was brought to Brazil by subsidiaries of these organisations and has exhibited increasing rates of diffusion and implementation (Pinto et al., 2008). In this context, this study aims to assess the status of Six Sigma in Brazilian companies and understand its integration with other quality management approaches. Additionally, the critical success factors (CSFs) of Six Sigma implementation and primary Six Sigma program characteristics were identified. Finally, the results of the use of Six Sigma were analysed. The methodological approach adopted was a surveybased research. This paper is organised as follows. Section 2 presents the theoretical background for Six Sigma and the research assumptions. The implementation patterns associated with the Six Sigma program are presented in Section 3. Section 4 describes the research methods used and the primary research questions. Section 5 contains the results and a discussion of the field research. Finally, the last section provides conclusions and recommendations for future work. 2. Literature review Six Sigma was created by Motorola and the approach was first diffused using American companies and later disseminated globally by their subsidiaries (Mitchell, 1992; Harry, 1998; Harry and Schroeder, 2000). A survey with respondents from the three countries (the Netherlands, the UK and the USA) performed by Van Iwaarden et al. (2008) noted that the meaning conferred the Six Sigma approach varies little among organisations, which suggests that it is a transnational concept. However; McAdam and Lafferty (2004) caution that the degree of coverage provided by what organisations call Six Sigma varies significantly, particularly for those that have simultaneously adopted other programs.

The Six Sigma program

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2.1 Distinctive characteristics of Six Sigma Schroeder et al. (2008) highlight four elements that are distinctive to Six Sigma with respect to TQM: “the focus on financial and business results is to some extent unique”, “the use of a structured method for process improvement or new product and service introduction is also not entirely distinctive”, “the use of specific metrics is also new with Six Sigma”, and “the use of a significant number of full-time improvement specialists in Six Sigma is new to many organisations” ( p. 13). Furthermore, Zu et al. (2008) identified three of the four elements suggested by Schroeder et al. (2008) as significant in empirical research: “the Six Sigma role structure, the Six Sigma structured improvement procedure, and the Six Sigma focus on metrics” ( pp. 641-642). Braunscheidel et al. (2011) utilise institutional theory by determining influence mechanisms (coercive, mimetic and normative) to assess motivation for the adoption of Six Sigma. Lloreńs-Montes and Molina (2006) highlight the following primary distinctive principles of Six Sigma: strategic focus, statistical thinking and systematised methodology. Several authors corroborate the notion that one of the distinctive aspects most often highlighted by authors is the Six Sigma strategic vision (Harry, 1998; Klefsjo¨ et al., 2001; Sanders and Hild, 2000; Connor, 2003; Snee, 2004). Similarly, statistical thinking and the structured method are other highly praised distinctive aspects of Six Sigma for many authors (Basu, 2004; Snee and Hoerl, 2002; Ingle and Roe, 2001; Pande et al., 2001; Snee, 2004; Choo et al., 2007; Zu et al., 2008). The structured method encompasses common metrics, adherence to a stepwise problem-solving approach, and analysis using a set of tools (Choo et al., 2007; Zu et al., 2008). The most widespread Six Sigma structured method is the DMAIC, so called because of the following phases: Define, Measure, Analyse, Improve and Control (Dale et al., 2000; Hahn et al., 2000). This method is used as a managerial process improvement practice, focusing on variance reduction and increased process control, which lead to organisational efficiency and effectiveness (Harry and Schroeder, 2000). The most common Six Sigma metric is the capability index, which supplies the program’s name and entails the goal of achieving six standard deviation (6s), that is, 3.4 parts per million defects, allowing for 1.5 SD (shift sigma) in the nominal value (Harry, 1998). In contrast to other approaches, which advocate costs for quality and discuss the trade-offs between prevention and evaluation ( Juran, 1962); the Six Sigma approach emphasises gains in quality, calculated on the basis of the results of Six Sigma projects. De Feo (2000) also stresses that Six Sigma projects are oriented towards achieving a return on investment (ROI). Schroeder et al. (2008) emphasise that the Six Sigma performance metrics include multiple levels and can be characterised as customeroriented metrics or financial metrics, whereas Linderman et al. (2003) explore the goal-theoretic perspective of Six Sigma in terms of its relationship to performance and task strategies, commitment and effort, and persistence and direction. Goela and Chen (2008) link the metrics for business process reengineering (BPR) to the metrics employed in the Six Sigma program. The surveys conducted by Davison and Al-Shaghana (2007), Zu et al. (2008) and Kumar and Antony (2008) identify the focus on metrics and performance evaluations based on quality-related criteria as significant differences between Six Sigma and non-Six Sigma firms, which confirms the theoretical assumption previously discussed (Linderman et al., 2003; Schroeder et al., 2008; Goela and Chen, 2008).


2.2 Six Sigma and other quality management initiatives The broad dissemination of quality management models created an evolutionary perspective, in which each new program inherits characteristics of its predecessor models, i.e. are built upon the foundations of models previously implemented (Lascelles and Dale, 1993; Garvin, 1988). Firms adopt a sequential implementation process in which distinctive approach generations coexist, because a firm’s absorptive capacity increases incrementally and each implemented approach facilitates the implementation of another related improvement program (Benner and Tushman, 2002). Thus, the intersection among these programs is significant. Using absorptive capacity perspective, McAdam and Hazlett (2010) suggest that there is evidence of an emerging theoretical underpinning regarding Six Sigma’s borrowing from an eclectic range of organisational theories. This study’s underlying assumption is that the Six Sigma program is leveraged by the prior implementation of other improvement approaches. Furthermore, the Six Sigma program depends on the foundations of quality improvement models previously implemented. Previous studies corroborate this assumption (Benner and Tushman, 2002; Shah et al., 2008; Shankar, 2003; Zu et al., 2008; Kumar and Antony, 2008; Kumar et al., 2011; Timans et al., 2012). Zu et al. (2008, p. 445) state that Six Sigma “key practices work with other QM practices to enhance the organisation’s ability of improving quality”. Shankar (2003) sustains that the diverse approaches to quality, such as quality awards (Malcolm Baldrige, National Prize for Quality and The Deming Prize), Six Sigma and the ISO 9001:2000 norms, are not independent of one another, i.e. they can and should coexist harmoniously, free of the need to abandon one approach to implement another. Furthermore, these authors suggest that there should be a sequence for implementation: first, ISO 9001:2000 norms and, later, Six Sigma. Additionally, Shankar (2003) argues that quality awards allow for integration, whereas Six Sigma improves control and ISO 9001:2000 norms focus on the basics. Other authors have explored the convergence of Six Sigma and Lean Management (Arnheiter and Maleyeff, 2005; Shah et al., 2008; Thomas et al., 2008; Chen et al., 2010; Delgado et al., 2010). Kumar and Antony (2008) note that ISO may be the foundation of lean management or Six Sigma in small and medium-sized enterprises (SMEs). The majority of the SMEs surveyed possessed ISO certification before lean and Six Sigma implementation. Thomas et al. (2008) also identify the benefits of lean Six Sigma (LSS) implementation in a small engineering company. Nabhani and Shokri (2009) suggest the application of a simplified version of LSS in a food service SME. Kumar et al. (2011) present a Six Sigma implementation framework for SMEs that is deployed into five phases: readiness for Six Sigma, prepare, initialise, institutionalise and sustain. During phase 2, initialise, they suggest the identification of core business processes and explore adherence to ISO 9000 and lean. More recently, Timans et al. (2012) studied LSS implementation in Dutch manufacturing engineering SMEs, and no distinct separation between lean manufacturing and Six Sigma were identified. Van Iwaarden et al. (2008) identified prerequisites for successful Six Sigma implementation, such as an existing quality culture and a certain level of quality maturity. Arauz and Suzuki (2004) corroborate this finding and suggest an incremental pattern of quality model implementation in Japanese ISO 9000 certified companies. Conversely, in organisations in which programs are implemented in an isolated package, it is observed that human and financial resources are dissipated, leading to


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unnecessary competition for resources and the discrediting of employees (Hammer, 2002; Hoerl, 2001). 2.3 Six Sigma diffusion and CSFs The literature on Six Sigma is replete with success cases of world-class companies, among them the pioneers: Motorola, General Electric and Allied Signal (Eckes, 2001; Pande et al., 2001; Snee and Hoerl, 2002; Ingle and Roe, 2001). These cases are primarily related to Six Sigma implementation in large companies and include a predominance of manufacturing organisations. However, there is a lack of empirical surveys in this field, which has been fulfilled in recent years through the use of surveys performed in several countries, such as the UK (Antony and Banuelas, 2002; Antony, 2004; Kumar and Antony, 2008; Van Iwaarden et al., 2008; Antony et al., 2008), the USA (Van Iwaarden et al., 2008; Zu et al., 2008; Shah et al., 2008), Japan (Arauz and Suzuki, 2004) and Saudi Arabia (Alsmadi et al., 2012). One of the pioneer surveys on Six Sigma was performed by Antony and Banuelas (2002) in large size manufacturing and service companies in the UK. Eleven key success factors were researched: management involvement and commitment; cultural change; organisational infrastructure; training; project management skill; project prioritisation and selection, review and tracking; understanding Six Sigma methodology, tools and techniques; a link to business strategy; a link to the customer; a link to human resource; and a link to supplier. The most important success factors for the surveyed firms was “involvement and commitment of top management to the program”, as was also stressed by several authors ( Johnson and Swisher, 2003; Kwak and Anbari, 2006; Yeung et al., 2006; Davison and Al-Shaghana, 2007; Zu et al., 2008; Antony et al., 2008). The success factors that scored higher than average were the following: project prioritisation and selection, reviews and tracking, and the linking of Six Sigma and the customer. In further research, Kumar and Antony (2008) and Antony et al. (2008) also identified the importance of linking Six Sigma to customers. Other authors emphasise project selection and leadership, as well as project management and project performance, as being critical to the success of Six Sigma (Kwak and Anbari, 2006; Johnson and Swisher, 2003). The least relevant factor was found to be “linking Six Sigma to human resources”, which is controversial in other studies (Davison and Al-Shaghana, 2007; Buch and Tolentino, 2006). Davison and Al-Shaghana (2007) identified significant relationships between Six Sigma and non-Six Sigma firms considering some organisational factors related to human resources such as training, employee participation and creating an awareness of quality. Buch and Tolentino (2006) also stated that employees believe that their participation in a Six Sigma program will lead to valued outcomes for themselves and their organisations. In addition, the rewards associated with their participation are more intrinsic, social, and organisational than extrinsic, which can lead to the attraction and retainment of program participants. Kumar and Antony (2008) also identified differences between Six Sigma and ISO-certified SMEs in the UK with regard to knowledge transfer to employees. According to Antony and Banuelas (2002), the three factors considered less important by the surveyed firms were: “linking Six Sigma to business strategy”, “understanding the Six Sigma methodology” and “tools and techniques”. However, in new studies, the importance of linking Six Sigma to business strategy has been highlighted (Antony et al., 2008).


Antony et al. (2008) and Kumar and Antony (2008) study Six Sigma implementation in SMEs. Kumar and Antony (2008) identified a ranking of 13 CSFs, adding the following to Antony and Banuelas (2002) list: communication, vision and plan, Information Technology (IT) and innovation. It is important to note that no significant difference in CSF importance between Six Sigma and ISO-certified companies was identified. Furthermore, they discovered a gap between the CSF importance and actual implementation within a company. A recent study by Timans et al. (2012) provides an analysis of CSFs and impeding factors on LSS implementation in Dutch manufacturing/engineering SMEs. The highest ranked CSFs were the following: linking to customer, vision and plan, communication and management involvement and participation. Conversely, the strongest impeding factors were internal resistance, resource availability, a changing business focus and a lack of leadership. Timans et al. (2012) propose three new CSFs: personal LSS-experience of top management, development of the project leader’s soft skills and supply chain focus. Kumar and Antony (2008) note that the majority of the SMEs surveyed provide in-house training to their employees rather than seeking the external help of consultants. However, in contrast to ISO-certified firms, the SME firms that apply Six Sigma prefer to utilise external consultants. Scott et al. (2009) conducted a survey on continuous improvement programs in the Canadian food sector, identifying more widespread use of Six Sigma among large organisations (50.0 per cent) than small ones (9.1 per cent). Similar results were found for Japanese companies (Arauz and Suzuki, 2004), in which the focus on Six Sigma was found only among large companies. Antony (2004) surveyed service companies in the UK, the majority of which were large (80 per cent). In the service sector, the Six Sigma program had been implemented with the primary goal of reducing and controlling costs, and the key success factors highlighted by the surveyed firms were the following: linking Six Sigma to business strategies, maintaining a focus on customers, competent project management, executive leadership and top management commitment, organisational infrastructure and project selection and prioritisation (Antony, 2004). Alsmadi et al. (2012) compared Six Sigma with other initiatives and the findings suggest that there is no significant difference in the level of most of Six Sigma practices between manufacturing and service firms. Antony and Banuelas (2002) identified the following as the quality tools most often adopted for Six Sigma: the cause and effect diagram, control charts and the Pareto diagram, regression analysis, quality function deployment (QFD), hypothesis testing and failure mode and effects analysis (FMEA). For Shah et al. (2008), the practices that significantly impact Six Sigma program are as follows: quality management, continuous improvement, process capability, a pull system, error proofing and statistical process control (SPC). These tools and practices are also related to other approaches. For Arauz and Suzuki (2004), distinctive trends exist that depend on organisation size. Small companies focus on two variables (motivational issues and implementation procedures), whereas medium-sized companies emphasise these two variables, as well as maintenance activities and integration with previous/existent quality measures. In addition to the four variables considered by medium companies, large firms also emphasise three others: the significance of employees’ involvement and understanding, information systems and Six Sigma. More recently, Alsmadi et al. (2012) presented a survey on Six Sigma implementation conducted with fortune 100 manufacturing and


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service firms in Saudi Arabia. Six Sigma implementation occurs among o32 per cent of respondents. 2.4 Six Sigma and performance As previously mentioned, distinctive Six Sigma characteristics include the focus on performance and the belief that Six Sigma firms’ stock prices should be higher (De Feo, 2000; Linderman et al., 2003; Schroeder et al., 2008; Goela and Chen, 2008; van Iwaarden et al., 2008), but in recent studies the impact of Six Sigma program on organisational performance and stocks was analysed in depth (Goh et al., 2003; Kumar and Antony, 2008; Choi et al., 2012; Swink and Jacobs, 2012). Goh et al. (2003) studied the stock prices’ reaction in two contexts: the day on which Six Sigma activities were publicised and long-run stock performance. In the first case, no significant differences were found regarding the event day. Similarly, a study on six firms demonstrates that in the long run, the stock performance of Six Sigma companies did not significantly outperform Standard & Poor’s 500. For Kumar and Antony (2008) a significant difference in strategic and operational measures of organisational performance between Six Sigma and ISO-certified companies was identified. Using a structural equation model, Choi et al. (2012) explore the relationship between Six Sigma and corporate competitiveness in the affiliated companies of Samsung Group in Korea. The empirical results demonstrated that Six Sigma activities do contribute to revitalised process management, improved quality and, finally, lead to corporate competitiveness. Swink and Jacobs (2012) also investigate the operational impacts of Six Sigma in larger firms, comparing financial data for 200 Six Sigma adopters and a control group, using criteria such as return on assets (ROA), industry and size. They found that Six Sigma adoption has a both statistically and economically significant positive impact on ROA that arises primarily from significant reductions in indirect costs, whereas no significant improvements in direct costs and asset productivity were identified. The dimensioned effect equals at least 0.2-0.3 percentage points on ROA each year on average; although it is significant, its magnitude is lower than that discovered in other studies conducted in quality fields. The literature review was organised so that the primary aspects of Six Sigma characteristics, other quality management approaches, CSFs, practices and impacts on results were clustered, as shown in Table I. 3. Research design As previously mentioned, this study aims to assess Six Sigma’s status among Brazilian companies. Furthermore it investigates the integration between Six Sigma and other quality management approaches. Additionally, the CSFs for Six Sigma implementation, the primary Six Sigma program characteristics and the tools applied were identified. Finally, the results of Six Sigma use were analysed. Given the nature of the research issues, the exploratory research strategy adopted was a survey-based approach, which included a non-probabilistic sampling plan and the use of eligibility criteria to select valid responses based on the information collected (Hair et al., 1995). In this study, self-applied questionnaires were sent by conventional and electronic mail to those responsible for the quality sections of the organisations. A pre-test was conducted with two organisations prior to sending the questionnaires, which made it possible to revise the instruments by shortening it, as well as rewording


Constructs

Variables

References

No.

Six Sigma distinctive characteristics

Strategic focus The focus on financial and business results, and customeroriented metrics Statistical thinking and a structured method Use of specific metrics (the capability index) Improvement specialists in Six Sigma and Six Sigma role structure Link the metrics for business process reengineering (BPR)

Basu (2004), Braunscheidel et al. (2011), Choo et al. (2007), Connor (2003), Dale et al. (2000), Davison and Al-Shaghana (2007), De Feo (2000), Goela and Chen (2008), Hahn et al. (2000), Harry (1998), Harry and Schroeder (2000), Ingle and Roe (2001), Klefsjo¨ et al. (2001), Kumar and Antony (2008), Linderman et al. (2003), Lloreńs-Montes and Molina (2006), Pande et al. (2001), Sanders and Hild (2000), Schroeder et al. (2008), Shankar (2003), Snee (2004), Snee and Hoerl (2002), Van Iwaarden et al. (2008), Zu et al. (2008) Arauz and Suzuki (2004), Arnheiter and Maleyeff (2005), Benner and Tushman (2002), Chen et al. (2010) Delgado et al. (2010), Garvin (1988) Hammer (2002), Hoerl (2001), Kumar and Antony (2008), Kumar et al. (2011), Lascelles and Dale (1993), McAdam and Hazlett (2010), Nabhani and Shokri (2009), Shah et al. (2008), Shankar (2003), Thomas et al. (2008), Timans et al. (2012), Van Iwaarden et al. (2008), Zu et al. (2008) Alsmadi et al. (2012), Antony (2004), Antony and Banuelas (2002), Antony, et al. (2008), Arauz and Suzuki (2004), Buch and Tolentino (2006), Davison and Al-Shaghana (2007), Johnson and Swisher (2003), Kumar and Antony (2008), Kwak and Anbari (2006), Scott et al. (2009), Shah et al. (2008), Timans et al. (2012), Yeung et al. (2006), Zu et al. (2008)

23

Six Sigma and other Quality Management initiatives

ISO 9000 Lean Six Sigma Quality awards Quality culture, quality maturity (the foundations of quality improvement models previously implemented) Evolutionary perspective absorptive capacity perspective

Six Sigma critical success factors and practices (tools and techniques)

CSFs Link to business strategy Link to the customer Link to human resource Link to supplier Involvement and commitment of top management and leadership Cultural change Organisational infrastructure Training Project management skill ( project prioritisation and selection, reviews and tracking) Review and tracking Understanding the SS methodology Tools and techniques Vision and plan IT and innovation Employee participation Rewards and awareness Communication Personal LSS-experience of top management


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(continued )

Table I. Theoretical framework

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Six Sigma and performance

Table I.

Variables

References

No.

Development of the project leader’s soft skills Supply chain focus Practices The cause and effect diagram Statistical process control (control charts) Pareto diagram Regression analysis Quality function deployment (QFD) Hypothesis testing Failure mode and effects analysis (FMEA) Process capability analysis Error proofing Impact on stock prices Impact on operational performance Impact on customer satisfaction Impact on corporate competitiveness impact on return on assets (ROA)

Choi et al. (2012), De Feo (2000), Goela and Chen (2008), Goh et al. (2003), Kumar and Antony (2008), Linderman et al. (2003), Schroeder et al. (2008), Swink and Jacobs (2012), van Iwaarden et al. (2008)

10

questions that were unclear to respondents and including a glossary. The survey was performed among large Brazilian firms across the country and across sectors. The sample was extracted from the list of the one thousand largest Brazilian companies, obtained from the chamber of industry database. The questionnaire was designed based on the literature review, as summarised in Table I. This research instrument was composed of three blocks: a characterisation of the company and the interviewee; an analysis of the Six Sigma program (CSF, quality management practices, role structure); and the Six Sigma results. The five-point Likert scale was used to gather respondents’ perceptions. The summary of the questionnaire is provided in the Appendix. Data were analysed using descriptive statistics, factor analysis, and the software SPSS. To understand dependency relations among the facilitating factors in the implementation of Six Sigma, an exploratory factor analysis was applied (For more details, see Johnson and Wichern, 2007). According to Everitt (2007), in many areas of research, it is not possible to measure directly the concept of interest. Instead, researchers examine concepts indirectly by collecting other variables that can be measured or observed directly. Such related measures, referred to as manifest variables, act as indications of the concepts of the real interest, which are referred to as latent variables. The method of analysis used to uncover the relationship between the latent variables and the manifest variables is exploratory factor analysis. Essentially, such analysis can be viewed as multiple regression, in which manifest variables are used as response variables and the manifest variables and the latent variables as auxiliary variables (in this context, they are known as common factors, and the coefficients of the regression are the factor loadings). One of the restrictions on the application of factor


analysis is the presence of missing values. Thus, an alternative was used that consisted of classifying the group of facilitating factors into ad hoc dimensions and then applying a separate factor analysis for each dimension. The results are very interesting, although they should be viewed as an exploratory analysis and cannot be extrapolated to the universe of business due to the relatively small size sample and a non-probabilistic sampling plan. The covariance or correlation matrix of the manifest variables is the essential input for the factor analysis. Thus, for manifest variables measured using a Likert scale, it is possible to obtain measures of correlation such as Spearman’s, Kendall’s or even Pearson’s. In the current study, the factor analysis was applied to the matrix of correlation and the factors extracted using the principal component method. The number of factors is determined by the number of eigenvalues higher than 1. For better identification of the factors, the varimax rotation was applied to the axes of the factors. 4. Results and discussion 4.1 Six Sigma diffusion in Brazil The findings of this survey contribute to outline Six Sigma implementation patterns in Brazilian companies and compare them with previous empirical studies (Antony and Banuelas, 2002; Arauz and Suzuki, 2004; Kumar and Antony, 2008; Van Iwaarden et al., 2008; Antony et al., 2008; Zu et al., 2008; Shah et al., 2008). Of 198 valid questionnaires, only 46 (23 per cent) organisations responded that they had implemented Six Sigma. The 46 companies surveyed that implemented Six Sigma can be characterised as manufacturing companies with annual revenues of over 50 million Reals (86.7 per cent) and more than 1,000 employees (84.8 per cent). These results are consistent with the literature (Eckes, 2001; Pande et al., 2001; Snee and Hoerl, 2002; Ingle and Roe, 2001; Pinto et al., 2008) The presence of Six Sigma in 24 industrial sectors can be verified. The greatest concentration is in the manufacturing sector (87 per cent), whereas the lowest is in the service sector, which included only three companies in the sample: a hospital, a maintenance medical equipment firm, and an information service provider. Note that the sectors with the highest occurrences were the “metal-mechanics” and “automotive vehicles and auto parts” sectors, both with (15 per cent), followed by the “chemical and petrochemical” sector (8 per cent). The electric-electronic and steel sectors were tied at 6.5 per cent, followed by companies from the pharmaceutical, telecommunications and textile sectors with 4.3 per cent each. The implementation of Six Sigma in the companies of the sample is not recent; the average start of implementation was more than six years ago, which differs from others studies, in which the implementation is more recent (Zu et al., 2008). The average program adoption time was six years and nine months. Among the 46 companies in the sample, the minimum time was three years and the maximum was found for Six Sigma pioneer, which implemented the program in Brazil in 1987. The most frequent implementation time is five years. 4.2 Six Sigma characteristics Observing the belts categories, it can be seen that 50 per cent of firms have the master black belt category, 86 per cent have the black belt category and 75 per cent have green belts, whereas only 6 and 11 per cent, respectively, adopted the yellow and white belt categories.


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As highlighted in the literature, the use of a belts’ parallel-meso structure to operate Six Sigma was observed in the companies studied; a similar nomenclature to refer to the specialists was adopted, as suggested by several authors (Schroeder et al., 2008; Sinha and Van de Ven, 2005; Barney, 2002). However, this study identified different Six Sigma role structures. Although the literature review presents a three-level structure, composed of champions, black belts and green belts (Schroeder et al., 2008; Barney, 2002; Sinha and Van de Ven, 2005), the findings obtained in this study suggest three configurations, as shown in Figure 1. The first configuration, which represents a quarter of the studied companies, is similar to the hierarchical structure described in the literature in which the champions support key Six Sigma projects, whereas the black belts are the project leaders, as well as the mentors of green belts, who are heavily involved in project execution. The second configuration, and the most common in the large Brazilian companies studied, includes an additional 4th level in the structure, occupied by the master black belt, who handles the Six Sigma program as a whole and aids the champion in following up key projects. The third configuration is rarer (6 per cent) and involves several types of belts (white, yellow, green and black) and differences in the Six Sigma training program. In synthesis, there are three possible configurations for this structure; the most common utilises three levels of belts (master, black and green), who report to a champion (see Figure 1). These different structures reveal differences in the training process and in the amount of time dedicated by the specialist to the Six Sigma program. Configuration 1 involves well-trained and skilled specialists, who are charged with strategic projects, but these projects do not cascade down through the organisation. Configuration 2 appears to be more balanced than others. Configuration 3 (a)

(b)

(c)

Champion Master Black Belts Champion Black Belt

Champion Master Black Belts Black Belt

Green Belt

Black Belt Green Belt

Green Belt Yellow Belt White Belt

number of levels

hours of training

Figure 1. Configurations of the Six Sigma structure

Notes: (a) Configuration 1:25 per cent of the sample; (b) configuration 2:50 per cent of the sample; (c) configuration 3:6 per cent of the sample


involves a broader set of people, because Six Sigma training and involvement in projects cascade down from high levels to individual business units, but the scope of projects and the skills of the specialists (belts) are limited, as the amount and content of training are significantly less than that in configuration 1. Another interesting issue relates to the meaning of Six Sigma, because it appears to be distinctive, according to the role structure configurations. In configuration 3, the term “Six Sigma philosophy” is widespread, whereas in other configurations, the terms “program” and “improvement method” are more often used. Thus, it is important to perform new research to allow for comparison with the findings of Van Iwaarden et al. (2008) and relation to the Six Sigma structure configuration in the organisation. There is strong employees’ involvement and commitment to the program in all configurations, because employee receptiveness was considered high by the majority of respondents, which corroborates the findings of Buch and Tolentino (2006). It is important to note that the receptivity of the employees involved in Six Sigma program was rated as “high” by the majority of respondents (84.2 per cent). Furthermore, 72.5 per cent of companies intended to expand the programs in the coming years, with only one company reporting that it intended to reduce its scope. When analysing the major departments that have implemented Six Sigma programs at the companies studied, it is observed that the majority of projects are concentrated in the “manufacturing” and “financial” areas. With respect to the average number of projects, there is wide variation among the companies in the sample; the greatest number of projects per year was 200, whereas the average for these companies was 14 per year. It is worth noting that 15 companies did not report the number of Six Sigma projects implemented per year. Although the questionnaire requested the number of projects implemented over a five-year period, none of the companies indicated the entire time period, demonstrating that the emergence of control of this indicator is still recent. The number of projects per year has increased by 45 per cent per year on average, considering a three-year period. The most common frequency of monitoring Six Sigma projects portfolios was by semester (28 per cent), followed by quarterly (26 per cent). However, for 46 per cent of the sample, there is no established frequency of monitoring project portfolios. Only one company reported that Six Sigma projects were being audited. Finally, it is noteworthy that 89 per cent of the companies adopted some type of award granting program and, of these companies, 22 per cent utilised a cash prize. 4.3 Six Sigma and other quality management initiatives The majority of the companies in the sample have adopted Six Sigma in combination with other quality management approaches. The most common combination is made with the ISO 9000 (84.8 per cent), followed by an association with the ISO 14000 (65.2 per cent) and an association with TQM (28.3 per cent), as shown in Figure 2. Only three companies (6.5 per cent) reported using Six Sigma alone. Moreover, 13 companies (28 per cent) report adopting Six Sigma in association with corporate programs that mix diverse improvement approaches such as lean production, best practices and total productive maintenance. It is noteworthy that the concomitant utilisation of several programs is very common, and 67.4 per cent of companies adopted three or more quality approaches. The most common combination (58.7 per cent) is that of Quality Management norms and Environmental Management (ISO 9000 and 14000) with Six Sigma. Furthermore, observe that 27 per cent of the companies in the sample enrolled to compete for quality


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Figure 2. Intersection between Six Sigma and ISO 9000:2000 and 14000 norms

Six Sigma and ISO 9000:2000 (84.8%) Six Sigma and ISO 14000 (65.2%) Six Sigma and ISO 9000:2000 and ISO 14000

awards, 50 per cent competing for the National Quality Award (PNQ) and the others for different awards, such as those of Brazilian industry associations (CNI and SESI). The hypothesis which suggesting that the organisations that implemented Six Sigma are those with the most evident tradition of quality was supported; the majority of companies surveyed adopt Six Sigma in association with other quality management approaches. A single company applies only Six Sigma. It suggests that Six Sigma dependency is related to other improvement approaches. As suggested by the literature (Van Iwaarden et al., 2008; Arauz and Suzuki, 2004; Shankar, 2003; Zu et al., 2008), this study indicates both a certain level of quality maturity and an incremental pattern of quality models implementation (Lascelles and Dale, 1993; Garvin, 1988; Benner and Tushman, 2002). The majority of the studied companies first implemented quality initiatives during the 1980s and have possessed ISO 9000 certification for more than ten years. Actually, the average adoption time for the Six Sigma program was six years and nine months, and the most frequent implementation time is five years, whereas in the Zu et al. (2008) research sample over half of the plants had been implementing the program for less than three years. Most likely, the scenario will change significantly in further studies, involving analysis from the perspective of SMEs in Brazil. 4.4 Six Sigma: motivations, CSFs and practices The motivations reported by the majority of companies surveyed to implement Six Sigma were as follows. The primary reason reported by the majority of companies was to “improve quality and productivity”, chosen with high concordance by 37 companies (average ¼ 2.92; SD ¼ 0.27), followed by the options “imposition by headquarters” (average ¼ 2.00; SD ¼ 0.85), “customer demand” (average ¼ 1.90; SD ¼ 0.98), “marketing” (average ¼ 1.83; SD ¼ 0.91) and “export” (average ¼ 1.57; SD ¼ 0.84). The majority of companies (70 per cent) also reported contracting outside consultants to facilitate the implementation of Six Sigma. Furthermore, note that 90


per cent of companies reported that the consultants played a facilitating role in the process of Six Sigma implementation. The most important factor for implementing Six Sigma, indicated by 69.6 per cent of respondents, was the “involvement and commitment of top management to the program”. Only five companies reported difficulties in the implementation process resulting from a lack of support from top management. Another two CSFs indicated by surveyed companies as being facilitators of implementation were “availability of financial resources” and “support from top management”, identified by 67 and 65 per cent, respectively. These CSFs were also stressed by the other studies (Antony and Banuelas, 2002; Kwak and Anbari, 2006; Johnson and Swisher, 2003; Zu et al., 2008). Among the factors that rendered the implementation of Six Sigma difficult were “availability of employees” and “complexity of the operations”, chosen by 46 and 35 per cent, respectively. As in the literature, the sample was divided with respect to “training”. A total of 57 per cent judged that training was a factor that facilitated Six Sigma implementation, whereas 43 per cent reported that it was a factor that rendered program implementation difficult. Through the factor analysis described in the previous section, three ad hoc dimensions (“human resources”, “infrastructure” and “organisational”) emerged and were deployed with factors, as presented, respectively, in Tables II-IV. Two factors, internal factors (firm human resources) and external factors (consultants), were extracted for the “human resource” dimension and explain 70.6 per cent of the total variance (47.1 and 23.5 per cent for the first and second factors, respectively). The factor loadings for each factor after the rotation of the axes (with the communalities) and the coefficients of the score of the factors are provided in Table II. Table III provides the results of the factor analysis of the facilitators related to the “infrastructure” dimension. Three factors were obtained that explain 82.3 per cent of the total variance (33.3, 25.7 and 23.2 per cent for the first, second and third factors, respectively). The first factor encompasses “IS and statistical tools”; the second

Dimension

Factor

Variables

Human resourcesa

(1) Internal

Internal training

Use of internal personnel for implementation Employees’ education levels Employee availability (2) External Consultancies used Variance % Var


615

Rotated factor loadings and communalities Factor score Varimax rotation coefficients Factor Factor 1 2 Communality 1 2 0.726

0.095

0.536

0.324

0.822

0.366

0.810

0.310 0.168

0.797

0.157

0.661

0.413

0.325

0.712 0.098 2.355 0.471

0.286 0.962 1.174 0.235

0.588 0.934 3.529 0.706

0.275 0.164

0.116 0.895

Notes: a28 cases used; 18 cases contain missing values

0.068

Table II. Factor analysis for the “human resources” dimension

(1) IS and Statistical Tools

Infrastructurea Support software Use of instruments Complexity of operations Determination of earnings Production of documents Variance %Var

Variables

Notes: 21 cases used; 25 cases contain missing values

(3) Documents

(2) Project Typology

Factor

Table III. Results of factor analysis of the “infrastructure” dimension 0.917 0.884 0.151 0.144 0.014 1.666 0.333

0.101 0.230 0.803 0.761 0.004 1.287 0.257

0.248 0.260 0.259 0.316 0.931 1.162 0.232

0.912 0.902 0.734 0.700 0.866 4.114 0.823

0.599 0.550 0.129 0.110 0.008

0.156 0.059 0.691 0.624 0.044

0.202 0.230 0.66 0.233 0.804

Factor score coefficients Factor 1 2 3

616

Dimension

Rotated factor loadings and communalities varimax rotation Factor 1 2 3 Communality


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Variable

Notes: 16 cases used; 30 cases contain missing values

Internal audits 0.944 0.043 0.131 Availability of financial resources 0.877 0.319 0.110 (2) Commitment Support from top management 0.191 0.975 0.071 (3) Quality historical Implementation history 0.028 0.068 0.995 Variance 1.697 1.058 1.024 %Var 0.424 0.265 0.256

Organizational issuesa (1) Resources

Dimension

0.910 0.883 0.991 0.995 3.779 0.945

Rotated factor loadings and communalities varimax rotation Factor 1 2 3 Communality


0.629 0.508 0.197 0.041

0.250 0.040 1.032 0.110

0.062 0.121 0.107 0.991

Factor score coefficients Factor 1 2 3


617

Table IV. Result of the factor analysis of the “organisational issues” dimension

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encompasses the complexity of the operations and determination of earnings, which was called “project typology”. Note that the loadings of these factors exhibit contradictory signs, indicating that the more complex the operations, the lower earnings should be (or vice versa). The third factor is related to the production of “documents”. The results of the factor analysis of the “organisational issues” dimension are provided in Table IV. Three of the extracted factors explain 94.5 per cent of the total variance (42.4, 26.5 and 25.6 per cent for the first, second and third factors, respectively). The first, “resources”, aggregates the availability of financial resources and the support of internal audits, the second, “commitment”, refers to support from top management and, the third, “quality historical”, measures the history of implementation of quality programs in the organisation. The quality of factor analysis was satisfactory because in all cases, the communalities were all higher than 0.5 and the factor loadings higher than 0.7, but the results should only be used in a provisional manner because of the small sample size used for each factor analysis. For this reason, we decide not to execute a confirmatory factor analysis because no inferential procedures are performed. The alternative of classifying the facilitating factors into groups promoted a larger sample size than the final sample size would most likely be if opting to exclude all missing values and then execute a factor analysis. The three groups of factors could be identified (see Table II-IV): “infrastructure”, “organisational issues” and “human resources”. Of those factors, the “organisational” aspects, which include “resources”, “commitment” and “quality historical”, have been emphasised in the literature, which encompass: Hoerl (2001), Antony and Banuelas (2002), Hammer (2002), Kwak and Anbari (2006), Johnson and Swisher (2003), Zu et al. (2008), Benner and Tushman (2002), Shah et al. (2008), Shankar (2003), Zu et al. (2008), Arnheiter and Maleyeff (2005) and Chen et al. (2010). The human resource factor group can be deployed not only internally, as suggested by Buch and Tolentino (2006), but also externally (consultants). The results show that 70 per cent of the companies surveyed use consultants to aid Six Sigma implementation and training. It was expected because our sample was composed by large firms and, as suggested by Kumar and Antony (2008), even Six Sigma SMEs have sought the help of external consultants more often for training than ISO certified firms, where in-house training was more common. Table V presents the results of seek the help of external consultants in Six Sigma companies compared with non-Six Sigma. The supports of the holding to the subsidiaries were more common in Six Sigma companies (10.9 per cent) than in non-Six Sigma (3 per cent). The last factor, “infrastructure”, is also not well covered in the literature. It should be noted that the Six Sigma project typology appears to be a relevant issue, and some contingent approach (one-size-does-not-fit-all) should be applied, as well established in the project management literature (Shenhar et al., 2005).

Table V. External consultants: Six Non-Six Sigma Sigma and non-Six Sigma Six Sigma

Yes (%)

Partial (%)

No (%)

n

44.5 60.9

25.2 22.4

30.3 16.7

152 46


The primary difficulties encountered in implementing the program were the “availability of employees”, which could indicate competition for human resources resulting from the use of distinctive improvement approaches, as suggested by Hoerl (2001) and Hammer (2002), because more than 85 per cent adopted Six Sigma concurrently with at least one other approach. All of the Six Sigma companies in the sample adopted the DMAIC cycle, and 38 per cent of the companies researched adopt in addition the Design for Six Sigma. The most frequently used quality tools were the following: analysis of variance and cause-effect diagram (84.8 per cent), FMEA, histogram and test of hypothesis (78.3 per cent each), SPC and Pareto diagrams (76.1 per cent each), dispersion diagrams (69.6 per cent), and design of experiment (DOE) (65.2 per cent). Note that even the more complex statistical tools, such as DOE, analysis of variance and statistical hypothesis testing are widely used in Six Sigma projects (more than 70 per cent), which was also identified by Antony and Banuelas (2002). In non-Six Sigma companies the use of more complex statistical tools is significant lower. Table VI presents the results of tools and techniques in Six Sigma companies compared with non-Six Sigma.


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4.5 Six Sigma impact on organisational performance The primary results of using Six Sigma reported by the companies studied were “better quality” (85 per cent) and financial gains (83 per cent). A total of 78 per cent also reported “greater productivity”, 70 per cent “greater internal customer satisfaction” and, 67 per cent “greater external customer satisfaction”. For questions that attempted to quantify the earnings obtained against investment using the Six Sigma program, only the respondents who reported both, amounts invested and financial earnings, were considered for analysis. The average point of each interval range for earnings obtained was used to calculate the average earnings obtained by the companies. The results are displayed in Table VII. It can be noted that there is no positive correlation between amount invested and earnings obtained. What is noteworthy is that companies that had lower investments had better average earnings; however, the standard deviation of this group was also large, indicating a wider variation of earnings.

Failure mode and effects analysis (FMEA) Statistical process control (control charts) Quality function deployment (QFD) The cause and effect diagram Histograms Pareto diagram Dispersion diagram Box Plot Statistical hypothesis testing Analysis of variance Nonparametric tests 5S Design of experiments (DOE) Sample (n)

Non-Six Sigma

Six Sigma

43.9% 59.8% 14.0% 81.7% 62.8% 75.6% 34.8% 7.9% 12.2% 20.7% 1.8% 56.1% 3.0% 152

78.3% 76.1% 30.4% 84.8% 78.3% 76.1% 69.6% 45.7% 78.3% 84.8% 26.1% 39.1% 65.2% 46

Table VI. Tools and techniques: Six Sigma and non-Six Sigma

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Nonetheless, it is worth noting that the majority (73 per cent) of companies studied did not consolidate their earnings through a financial division or a controller. This practice was observed in only eight companies (18 per cent). This result could explain the difficulty in determining which earnings were obtained with Six Sigma. The verification of earnings obtained from Six Sigma projects was performed using the net present value (65 per cent), followed by direct cost reduction calculated (30 per cent). Other reported indicators were as follows: indirect cost, economic value added and ROI. Despite several authors’ focus on the financial results in the literature (De Feo, 2000; Schroeder et al., 2008; Linderman et al., 2003; Zu et al., 2008), in the majority of companies studied (73 per cent), there is no system for verifying earnings obtained through the Six Sigma projects as a whole. For the companies that reported having analysed earnings obtained from and investments in Six Sigma, it was not possible to identify a positive relationship between the amount invested and the earnings obtained. Other results achieved with quality initiatives were shown in Table VIII, comparing Six Sigma and non-Six Sigma companies. 5. Conclusions The findings obtained in this survey facilitate the outlining of Six Sigma implementation patterns in Brazilian companies and allow for comparison with previous empirical studies (Antony and Banuelas, 2002; Arauz and Suzuki, 2004; Kumar and Antony, 2008; Van Iwaarden et al., 2008; Antony et al., 2008; Zu et al., 2008; Shah et al., 2008). It was verified that in Brazil, Six Sigma was diffused in 23 per cent of the surveyed companies, whereas a similar study in the UK indicated 37 per cent (Antony and Banuelas, 2002). More recently, Alsmadi et al. (2012) state that in Saudi Arabia 32

Range of amounts invested

Table VII. Average earnings by range of investment in Six Sigma

Average earnings R$ ( 103)

Standard deviation R$ ( 103)

No. of respondents

681 425 275 437.5 500

454 239 141 153 217

5 7 2 6 3

From R$50,000 to R$99,999 From R$100,000 to R$249,999 From R$250,000 to R$499,999 From R$500,000 to R$1,000,000 Over 1,000,000

Results

Table VIII. Quality programs results: Six Sigma and non-Six Sigma

Impact on financial metrics Impact on productivity Impact on quality Impact on external customer satisfaction Impact on internal customer satisfaction Impact on market share Impact on exportation Sample (n)

Non-Six Sigma

Six Sigma

81.1% 85.4% 93.9% 91.5% 87.2% 70.7% 64.0% 152

82.6% 78.3% 84.8% 67.4% 69.6% 45.7% 50.0% 46


per cent of the surveyed firms applied Six Sigma. The implementation of Six Sigma in Brazilian companies is not recent, which differs from others studies (Zu et al., 2008). The primary reason for adopting Six Sigma was to improve quality and productivity. Thus, the focus on efficacy suggested by the literature was not confirmed (Harry, 1998; Klefsjo¨ et al., 2001; Sanders and Hild, 2000; Connor, 2003; Snee, 2004), on the contrary, the results suggest an emphasis on efficiency. The results suggest a synergic and incremental pattern of quality model implementation, as suggested by the literature (Van Iwaarden et al., 2008; Arauz and Suzuki, 2004; Shankar, 2003; Zu et al., 2008). The study reveals that companies that have adopted Six Sigma have a long history of implementing quality programs, which suggest certain level of quality maturity (Lascelles and Dale, 1993; Garvin, 1988; Benner and Tushman, 2002). The studied companies perceive in Six Sigma an incremental evolution, which can be combined with earlier initiatives and strong provides synergy with ISO 9000. The findings obtained in this study confirm the distinctive Six Sigma role structure as suggested by several authors. However, three possible role structure configurations were found that differs in terms of training and the dedication of human resources entailed by the Six Sigma program. These findings have implications for top management trying to promote the strategic alignment (Prieto and Carvalho, 2011). The CSFs were clustered in three main factors: “human resources”, “organisational issues”, and “infrastructure”. The first one can be deployed in internal human resources, as suggested by Buch and Tolentino (2006), but also external (consultants). The second one, organisational issues, has been emphasised by the literature (Hoerl, 2001; Antony and Banuelas, 2002; Hammer, 2002; Kwak and Anbari, 2006; Johnson and Swisher, 2003; Zu et al., 2008; Benner and Tushman, 2002; Shah et al., 2008; Shankar, 2003; Zu et al., 2008; Arnheiter and Maleyeff, 2005; Chen et al., 2010). The second, infrastructure encompasses IT and statistic tools, project typology and document management. 5.1 Managerial implication Some important managerial implications of this study are related to the Six Sigma structure adopted. The capillarity of the program in the organisation as a whole can be related to the type of role structure configuration adopted. This structure can have an impact in terms of both numbers and employees’ and managers’ degree of involvement, as well as the type of training provided. Conversely, the impact of Six Sigma results on organisational performance was not conclusive. The relation between Six Sigma with others improvement initiatives seems to be synergic, but also conflictive because all these initiative compete for the same type of internal human resource. 5.2 Future research The results focus on large Brazilian companies and the scenario may change significantly for SMEs in Brazil, thus it should be investigated in depth in future researches. There is lack of the understanding of the role of consultants. It is an important issue because the majority of companies surveyed use consultants to aid in Six Sigma implementation and training. Thus, the role of consultants in implementing Six Sigma should be more deeply studied.


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In the CSFs the infrastructure is not well covered by the literature, particularly the Six Sigma project typology appears to be a relevant issue and some contingent approach should be investigated. The configuration of the role structures should be addressed by future research, since it could impact on the investments in Six Sigma program, as well as in its potential for successful implementation. Furthermore, the selection of the role structure appears to be related to the meaning of Six Sigma program in organisation. The majority of surveyed companies apply Six Sigma with the ISO 14000 for environmental management. This issue is poorly addressed by the literature and should be investigated. 5.3 Limitations This study demonstrates the inherent limits of the research method adopted, which involves a non-probabilistic sample and a reliance on self-reported perceptions, and only large companies, which introduces a bias to the analysis that could not be generalised. Nevertheless, several leading Brazilian companies in various sectors and cross-country responded to this study, the majority of which have practiced Six Sigma for more than 5 years, which permitted tracking of the analysis of the trend towards the implementation of this program in Brazil. References Abrahamson, E. (1996), “Management fashion”, Academy of Management Review, Vol. 21 No. 1, pp. 254-285. Ahire, S., Golhar, D. and Waller, M. (1996), “Development and validation of TQM constructs”, Decision Science, Vol. 27 No. 1, pp. 23-56. Alsmadi, M., Lehaney, B. and Khan, Z. (2012), “Implementing Six Sigma in Saudi Arabia: an empirical study on the fortune 100 firms”, Total Quality Management & Business Excellence, Vol. 23 Nos 3-4, pp. 263-276. Antony, J. (2004), “Six Sigma in the UK service organisations: results from a pilot survey”, Managerial Auditing Journal, Vol. 19 No. 8, pp. 1006-1013. Antony, J. and Banuelas, R. (2002), “Key ingredients for the effective implementation of Six Sigma program”, Measuring Business Excellence, Vol. 6 No. 4, pp. 20-27. Antony, J., Kumar, M. and Labib, A. (2008), “Gearing six sigma into UK manufacturing SMEs: results from a pilot study”, Journal of The Operational Research Society, Vol. 59 No. 4, pp. 482-493. Arauz, R. and Suzuki, H. (2004), “ISO 9000 performance in Japanese industries”, Total Quality Management & Business Excellence, Vol. 15 No. 1, pp. 3-33. Arnheiter, D.A. and Maleyeff, J. (2005), “The integration of lean management and Six Sigma”, The TQM Magazine, Vol. 17 No. 1, pp. 5-18. Barney, M. (2002), “Macro, meso, micro: Six Sigma”, The Industrial Organizational Psychologist, Vol. 39 No. 4, pp. 104-107. Basu, R. (2004), “Six-Sigma to operational excellence: role of tools and techniques”, International Journal of Six Sigma and Competitive Advantage, Vol. 1 No. 1, pp. 44-64. Benner, M.J. and Tushman, M. (2002), “Process management and technological innovation: a longitudinal study of the photography and paint industries”, Administrative Science Quarterly, Vol. 47 No. 4, pp. 676-706. Black, S.A. and Porter, L.J. (1996), “Identification of the critical factors of TQM”, Decision Sciences, Vol. 27 No. 1, pp. 1-21.


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(The appendix follow overleaf.)

ISO 9000 ISO 14000 TS 16949 QS 9000 Six Sigma Lean Six Sigma Quality awards Link to business strategy Link to the customer link to human resource Link to supplier Involvement and commitment of top management and leadership Cultural change Organisational infrastructure Training project management skill ( project prioritization and selection, reviews and tracking) Review and tracking Understanding the SS methodology Tools and techniques Vision and plan IT and innovation Employee participation Rewards and awareness communication, Personal LSS-experience of top management, Development of the project leader’s soft skills Supply chain focus Failure mode and effects Analysis (FMEA) Statistical process control (control charts) Quality Function Deployment (QFD)

Improvement initiatives and certifications

Tools and techniques

CSFs

Alternatives

Questions


Yes/no

(continued )

Five points Likert scale

Yes/no If yes, when started it?

Scale

Appendix


627

Table AI. Questionnaire

Table AI.

Belts role structure

The cause and effect diagram Histograms Pareto diagram Dispersion diagram Box Plot Statistical hypothesis testing Analysis of variance Nonparametric tests 5S Design of experiments (DOE) Regression analysis Process capability analysis Impact on financial metrics (ROA, etc.) Impact on productivity, operational performance Impact on quality Impact on external customer satisfaction Impact on internal customer satisfaction Impact on market share and corporate competitiveness Impact on exportation Impact on stock prices Champion Master Black Belt Black Belt Green Belt Yellow Belt White Belt

Alternatives

Yes/no

(continued )


Scale

628

Six Sigma and performance

Questions


JMTM 25,5

Champion Master Black Belt Black belt Green Belt Yellow Belt White Belt Brand image and advertising Competitive pressures Customer pressures Increasing efficiency Internal organisation improvement Marketing Opportunity of business becomes more attractive to investors Part of the strategic plan Employees’ resistance to change Difficulty in understanding the methodology, tools and techniques involved High implementation costs Lack of employees’ skills Lack of organisational infrastructure Low commitment by middle management Low support from top management

Belts dedication to Six Sigma

Difficulties to Six Sigma Implementation

External consultants Motivations to Six Sigma Implementation

Alternatives

Questions



Yes/no/partial Five points Likert scale

Full time/partial

Scale


629

Table AI.

JMTM 25,5


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About the authors Marly Monteiro de Carvalho is an Associate Professor at the University of S~ao Paulo in Brazil. She is the Coordinator of Project Management Lab (www.pro.poli.usp.br/lgp) and the Coordinator of QEP-Quality and Product Engineering research group of CNPq (Brazilian Federal Research Agency). She holds Production Engineering Degree at the University of S~ao Paulo, MSc and PhD in the same area at the Federal University of Santa Catarina, and Post Doctoral programme at the Polytechnic of Milan. Her work is within the area of quality management, project and innovation management. She has published ten books and a number of articles within the same areas. Associate Professor Marly Monteiro de Carvalho is the corresponding author and can be contacted at: [email protected] Linda Lee Ho is a Full Professor at the University of S~ao Paulo in Brazil. She is also the Editor of Produç~ ao Journal, which belong to the Production Engineering Brazilian Association (ABEPRO). She holds Statistic Bachelor Degree at the University of S~ao Paulo, MSc and PhD in Production Engineering in the same university. Her work is within the area of quality engineering. She has published a number of articles within this area. Silvia Helena Boarin Pinto is an Associate Professor in the Business Administration Department of ESEG-Superior School of Engineering and Management. She was a Post Doctoral Researcher in the Department of Production Engineering in the Polytechnic School at the University of S~ao Paulo in Brazil.

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