The TQM Magazine

The TQM Magazine Volume 18 Issue 5 2006-pp(433-550) Exploration into the quality septet Jagadeesh Raj (pp. 433-439) Keywords: Number theory, Quality, Total quality management Article Type : Viewpoint TQM models and their effectiveness in New Zealand water utilities services Siham El-Kafafi (pp. 440-454) Keywords: Modelling, New Zealand, Organizational change, Total quality management, Water industry ArticleType:Research paper Classification and application of problem solving quality tools: A manufacturing case study Catherine Hagemeyer, John K. Gershenson, Dana M. Johnson (pp. 455-483) Keywords: Quality systems, Six sigma ArticleType:Case study The development of an employee satisfaction model for higher education Shun-Hsing Chen, Ching-Chow Yang, Jiun-Yan Shiau, Hui-Hua Wang (pp. 484-500) Keywords: Employees, Higher education, Job satisfaction, Quality ArticleType:Research paper Progress of quality management practices in Australian manufacturing firms Daniel I. Prajogo (pp. 501-513) Keywords: Australia, Manufacturing industries, Quality management ArticleType:Research paper Selection of six sigma projects in the UK Ricardo Banuelas, Charles Tennant, Ian Tuersley, Shao Tang (pp. 514-527) Keywords: Project management, Six sigma, Surveys, United Kingdom ArticleType:Research paper Relationships of TQM practices and employees' propensity to remain: an empirical case study Keng Boon Ooi, Arumugam Veeri, Loke Kim Yin, Lorraine Subathra Vellapan (pp. 528-541) Keywords: Electronics industry, Malaysia, Total quality management ArticleType:Case study Managing cost of quality: insight into industry practice Andrea Schiffauerova, Vince Thomson (pp. 542-550) Keywords: Multinational companies, Quality costs, Quality programmes ArticleType:Case study

The current issue and full text archive of this journal is available at www.emeraldinsight.com/0954-478X.htm

VIEWPOINT

Exploration into the quality septet Jagadeesh Raj

Exploration into the quality septet

433

SDM Institute for Management Development, Mysore, India Abstract Purpose – The paper has the objective of finding why the number seven most commonly appears with respect to the number of steps, number of quality tools, and several other quality related topics including personal quality. Design/methodology/approach – The paper relies on the secondary data available through print and electronic media including the world wide web. Though this it is at least ensured to be quite broad based. Findings – No specific reason could be attributed for using only number seven as no such reasoning was provided anywhere in the literature for the various lists proposed by different authors. However, in an early paper it has been reported that there is a finite span of immediate memory and for a wide range of test materials, this span is about seven items. This postulate has been widely debated and no evidence exists to generalize the issue. Thus, in the opinion of the author that there are no valid or scientific reasons for the issue considered. Research limitations/implications – Search is not claimed to be exhaustive as all the lists have not been examined to check the use of number seven. Originality/value – Based on literature review it was found that the question “why number seven?” was not addressed and hence this paper has attempted to answer it. Secondly, no compilation of lists to demonstrate the use of number seven existed and this paper has filled the void. Keywords Quality, Total quality management, Number theory Paper type Viewpoint

Introduction Years of learning about quality exposed me to its many different facets. I made an interesting observation when discussing the tools, techniques and concepts of quality improvement. Several of these tools or concepts included the number “seven”. Naturally the mystique or magic of seven deserved exploration to satisfy the most commonly asked question “why seven?” This viewpoint attempts to unravel the mystery behind the number seven associated with many quality tools and techniques. Groups of seven The number “seven” is associated with such common things as “seven days of the week” “seven wonders of the world” “seven primary colours” “Seven notes of the musical scale” “Seven seas” “Seven continents” and the so-called seven year-itch in marriage. Two popular Hollywood movies I remember are “The Magnificent Seven” and “Seven Samurai”. An excellent listing of things associated with number seven are given in www.answers.com/topic/7. It also provides details

The TQM Magazine Vol. 18 No. 5, 2006 pp. 433-439 q Emerald Group Publishing Limited 0954-478X DOI 10.1108/09544780610685430

TQM 18,5

434

about application or use of number seven in various fields. Similarly, www. afgen.com describes the spiritual and religious importance of seven and its associations. Quality and number seven In the world of “quality” the number seven finds many associations representing a number of tools or steps or principles. Quality crusaders quickly notice the magical spell of seven when they examine the extant literature. Why seven? And how many septets (septet (Latin) ¼ a group of seven) are there? Research resulted in the compilation presented below. Seven QC tools or basic tools The first set of seven refers to the seven quality tools described as “The Magnificent Seven” by Wadsworth et al. (1986). These are given below: (1) cause and effect diagram; (2) control chart; (3) check sheet; (4) flow chart; (5) pareto diagram; (6) histogram; and (7) Scatter plot. Second set of seven graphical tools Wadsworth et al. (1986) have also proposed a second set of graphical tools as follows: (1) barplots; (2) boxplots; (3) stars; (4) glyphs or trees; (5) faces; (6) weathervanes; and (7) quantile-quantile plots. Seven management tools The second set of QC Tools is commonly called the seven management tools. Mizuno (1988) suggested that following tools be regarded as the advanced seven QC tools: (1) relations diagram; (2) K J methods (affinity diagrams); (3) systematic diagram; (4) matrix data analysis; (5) process decision program chart;

(6) arrow diagram; and (7) matrix diagram. Seven steps quality improvement process Shiba et al. (1993) have suggested a seven step improvement process that synchronizes with the seven QC tools. The seven steps are: (1) select theme; (2) collect and analyze data; (3) analyze cause; (4) plan and implement solution; (5) evaluate effects; (6) standardize solution; and (7) reflect on process (and next problem). Seven-steps benchmarking process There are several approaches suggested for benchmarking and in the context of the present paper the following procedure is adopted here to illustrate a typical case. According to Chang and Kelly (1999) benchmarking can be accomplished through a series of seven steps. (1) determine what functions to benchmark; (2) define appropriate metrics; (3) identify best practice companies; (4) measure own and best practice performance; (5) estimate performance gaps; set goals; (6) implement improvement plan; and (7) monitor results. Seven steps to quality According to www.koalatee-bear.com/quality.htm, the seven steps to quality are: (1) define the mission of your company; (2) understand your product or service; (3) define your business operating system; (4) write operating procedures; (5) train employees; (6) track the “costs of quality;” and (7) perform quality audits.


435

TQM 18,5

436

Seven principles of hazard analysis critical control point (HACCP) HACCP is a systematic approach to the identification, evaluation, and control of food safety hazards based on the following seven principles (www.cfsan.fda.gov/ , comm/ nacmcfp.html): (1) conduct a hazard analysis; (2) determine the critical control points (CCPs); (3) establish critical limit(s); (4) establish a system to monitor control of the CCP; (5) establish the corrective action to be taken; (6) establish procedures for verification to confirm that the HACCP system is working effectively; and (7) establish record keeping and documentation concerning all procedures and records. Seven wastes detrimental to quality Taylor and Brunt (2001) state that seven commonly accepted wastes detrimental to quality, as recognized by Toyota production system (TPS) are as follows: (1) overproduction; (2) waiting; (3) transport; (4) inappropriate processing; (5) unnecessary inventory; (6) unnecessary motion; and (7) defects Seven value stream mapping tools to enhance quality Hines and Rich (1997) discuss value stream management to deal with the different wastes in an organization. These tools are: (1) process activity mapping; (2) supply chain response matrix; (3) production variety funnel; (4) quality filter mapping; (5) demand amplification mapping; (6) decision point analysis; and (7) physical structure mapping. Seven criteria for Malcolm Baldrige national quality award Applications for the Baldrige Award demonstrate achievements and improvements in seven assessment categories (Calingo, 2001). The seven criteria categories, and their corresponding point values, are as follows: (1) leadership; (2) strategic planning;

(3) (4) (5) (6) (7)

customer and market; information and analysis; human resource focus; process management; and business results.

Deming’s seven deadly diseases W. Edwards Deming (www.deming.org/theman/teachings02.html) proposed 14 points for achieving quality. It is interesting to note that 14 happen to be two times 7! Further, Deming has also identified 7 “diseases” which are detrimental to quality in any organization: (1) Lack of constancy of purpose to plan product and service that will have a market and keep the company in business, and provide jobs. (2) Emphasis on short-term profits: short-term thinking (just the opposite of constancy of purpose to stay in business), fed by fear of unfriendly takeover, and by push from bankers and owners for dividends. (3) Personal review systems, or evaluation of performance, merit rating, annual review, or annual appraisal, by whatever name, for people in management, the effects of which are devastating. (4) Mobility of management; job hopping. (5) Use of visible figures only for management, with little or no consideration of figures that are unknown or unknowable. (6) Excessive medical costs. (7) Excessive costs of liability. Seven deadly sins of quality management Dew (2003) proposes seven deadly sins of quality management, as follows: (1) placing budgetary considerations ahead of quality; (2) placing schedule considerations ahead of quality; (3) placing political considerations ahead of quality; (4) being arrogant; (5) lacking fundamental knowledge, research or education; (6) pervasively believing in entitlement; and (7) practicing autocratic behaviours, resulting in “endullment.” Seven most common surprises Porter et al. (2004) commented on the seven surprises that one would face after joining an organization. Quality practitioners should remember them! (1) you cannot run the company; (2) giving orders is very costly;


437

TQM 18,5

438

(3) (4) (5) (6) (7)

it is hard to know what is really going on; you are always sending a message; you are not the boss; pleasing shareholders is not the goal; and you are still only human.

Seven personal quality parameters Now let us look into personal quality. To be an acceptable person, an individual should have certain virtues. Similarly the “defects” in a person can be categorised as vices, from which the individual has to be free to be a noble person. The Seven Traits of an individual are given in the Table I (www.rushman.org/ seven/). Seven habits of highly effective people Continuing on self-improvement, one of the best selling books has been “The Seven Habits of Highly Effective People” a popular book written by Stephen Covey. Of course an 8th habit has recently appeared !. The original seven habits are: (1) be proactive: principles of personal vision; (2) begin with the end in mind: principles of personal leadership; (3) put first things first: principles of personal management; (4) think win/win: principles of interpersonal leadership; (5) seek first to understand, then to be understood; (6) synergise principles of creative communication; and (7) sharpen the saw: principles of balanced self-renewal. Concluding remarks The different lists provided in this paper are evidence to the generic use of number seven in various tools and techniques developed to improve personal or organizational quality. It cannot be claimed that these lists are exhaustive. However, a satisfactory answer to the question “why only seven” has not been achieved by this study. The plausible reason I offer is that the word “QUALITY” consists of “Seven Letters”!

Table I. Seven traits of an individual

Virtues (to have)

Vices (not to have)

Love/charity Hope Faith Temperance Justice Courage Wisdom

Lust Gluttony Avarice/greed Sloth Wrath Envy Pride

References Calingo, LuisMaR. (2001), “The US Malcolm Baldrige national quality award: recent developments, processes, and applicability to the Asian setting. The quest for global competitiveness through national quality and business excellence awards”, Report of the Symposium on Quality and Business Excellence Awards, Nadi, Fiji, September 18-20. Chang, R.Y. and Kelly, K.P. (1999), Improving Through Benchmarking, Pfeiffer, San Diego, CA. Dew, J. (2003), “The seven deadly sins of quality management”, Quality Progress, pp. 55-65, September. Hines, P. and Rich, N. (1997), “The seven value stream mapping tools”, International Journal of Operations & Production Management, Vol. 17 No. 1. Mizuno, S. (1988), Management for Quality Control – The Seven New QC Tools, Productivity Press, Portland, OR. Porter, M.E., Lorsch, J.W. and Nohria, N. (2004), “Seven surprises for new CEOs”, Harvard Business Review, October. Shiba, S., Graham, A. and Walden, D. (1993), A New American TQM, Productivity Press, Portland, OR. Taylor, D. and Brunt, D. (2001), Manufacturing Operations and Supply Chain Management, Thomson Asia Limited, Singapore. Wadsworth, H.M., K, S. and Godfrey, B.A. (1986), Modern Methods for Quality Control and Improvement, Stephens, Wiley, New York, NY. Further reading Baker, W.M. and Harris, A.L. “Empirically assessing students’ perceptions of the importance of student characteristics”, Journal of Information Systems Education, pp. 41-6. US Department of Agriculture (n.d.), Hazard Analysis And Critical Control Point Principles And Application Guidelines US Food and Drug Administration, US Department of Agriculture, National Advisory Committee on Microbiological Criteria for Foods, Adopted August 14, 1997, available at: www.cfsan.fda.gov/ , comm/nacmcfp.html

Corresponding author Jagadeesh Raj can be contacted at: drrjagadeesh@yahoo.co.uk

To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints


439


TQM 18,5

TQM models and their effectiveness in New Zealand water utilities services

440

Siham El-Kafafi Manukau Business School, Manukau Institute of Technology, Manukau City, New Zealand Abstract Purpose – The purpose of this paper is to investigate the organizational change taking place within New Zealand water utilities as a result of implementing Total Quality Management (TQM) models (i.e. TQM experts’ teachings, ISO 9000 standards, and quality awards). Implementation was intended to enhance their performance and the quality of drinking water provided to the community. Design/methodology/approach – This study was conducted by investigating the quality management system in three different case studies from the Waikato Region of New Zealand. The main study methodology is involved in methodological triangulation in which the researcher used more than one technique for data collection and data analysis. This paper reports on two of those techniques: face to face interviews conducted with the managers of the three case studies under investigation; and participant observation at the water treatment plants of the same three territorial local authorities (TLAs). Findings – The comparative analysis drawn between the three different cases showed that two of the case studies are applying TQM models but at different stages, while the third case study is not implementing any of the TQM models. The difference between the performances of TLAs adopting a TQM model versus the TLAs who are not is related to their organizational strategy. This in turn has an impact on the sustainability of the quality of water provided to the community of the Waikato Region. Practical implications – The paper emphasises the importance of breadth and depth of organizational change in the three TLAs in view of the following themes: training personnel in quality systems, customer satisfaction with water quality, purchasing equipment/chemicals, process control, inspection and testing, calibration, corrective and preventive action where drinking water is below standard (non-conformance) and control of quality records. Originality/value – The paper provides a useful case of TQM application in water utilities services. Keywords Organizational change, Total quality management, New Zealand, Modelling, Water industry Paper type Research paper


Introduction The last few decades have witnessed a major transformation in how business is conducted. Organizations whether large or small, public or private, have been striving for high productivity with an emphasis on quality, innovation and value. Hence, those organizations developed and implemented approaches to optimally link the organization’s work and employees for improved business results. Some of the factors accounting for that change are competitive challenge, the rate of technological innovation and change, increased knowledge and capability of the workforce, research and writings of leading social scientists, quality management resources and business consultants (Cohen and Brand, 1993). Total Quality Management (TQM) has become the mantra of many reform-minded business leaders hoping to capitalize on the sources of competitive

advantage embodied in the principles and practices of TQM (Sureshchandar et al., 2001; Hsieh et al., 2002). TQM is a philosophy aiming at continuous improvement and involvement of the whole organization starting from the top of the hierarchy and ending at the bottom level of employees (Kanj and Asher, 1993, 1999). TQM is an integrated approach that emphasizes management commitment, employee involvement and teamwork, customer satisfaction, and competitive benchmarking (Ross, 1993). There has been myriad of research conducted on quality management in the manufacturing industry which investigated the various dimensions, techniques and organizational requirements for effective implementation of TQM (Sureshchandar et al., 2001). On the other side of the continuum there has not been a lot of research conducted on service quality in New Zealand and especially on the water utilities. Accordingly this research paper investigates the implementation of TQM, its models/approaches exemplified in the ISO 9000 Certification, ISO 14000 Certification, and the quality awards (i.e. the Malcolm Baldrige National Quality Award and its New Zealand equivalent The Business Excellence Quality Award). The paper analyses organizational change that took place at three territorial local authorities (TLAs) of the Waikato Region of the North Island in New Zealand by concentrating on the following dimensions: top management commitment and leadership, quality policy, training, product and service design, supplier quality management, process management, quality data and reporting, employee relations, customer focus, employee involvement, corporate quality culture. In other words, the paper considers organizational change taking place in public organizations that care about the quality of their service to the community through the use of a service quality approach. The main interest in this research is to investigate if there is a difference between cases where such management systems were adopted as compared to cases where they were not. The paper starts by giving a brief description of the Waikato Region of New Zealand where the three cases studies were conducted. It proceeds by describing the research methods of data collection and data analysis used to investigate three different TLAs, the Waikato Region. It then presents the three case studies under investigation, and finally reports on the research findings, lessons learned from this experience and how they relate to service quality practice in relation to the adoption of TQM approach. The Waikato Region Waikato Region covers 25,000 square kilometres in the central North Island of New Zealand. It contains a rich diversity of natural resources including snow-capped mountains, extensive rivers and lake systems, forests, geothermal fields and productive farmland. A human population of 357,726 live in the Waikato Region mostly urban areas (Statistics New Zealand, 2005). Within the Waikato region are the rohe, or tribal areas, of a number of iwi[1]. Waikato Iwi include Tainui, Tuwharetoa and Ngati Tahu (Waikato Regional Council, 1994, 1998, 2004). The Waikato Region is well endowed with water resources as shown in Table I. The Waikato Region is an area of New Zealand, which is highly dependent on surface water from rivers and lakes to supply its drinking water needs. Accordingly the TLAs with the assistance of Environment, Waikato gives great importance to the following issues: . maintaining and improving water quality; . maintaining and enhancing flow regimes;

TQM models

441

TQM 18,5

442

. .

efficient use of water; and enhancing public access (Waikato Regional Council, 1994, 1998).

Research methodology This research engaged in methodological triangulation which encourages the sequential or simultaneous use of two or more qualitative methods. The aim was to gain an holistic view of the setting while keeping the analysis separate and the methods not muddled (Stern, 1994 in Morse, 1994). The main research utilised two types of triangulation, data triangulation (face-to-face interviews, observations, and document review) and methodological triangulation (qualitative and quantitative data collection and analysis). The rationale behind the choice of using triangulation is that the researcher agrees with Denzin (1998) that no single method adequately solves the problem of rival causal factors. Hence, by the use of multiple methods, the researchers aspire to reveal the different aspects of empirical reality and at the same time help validate the research findings. Moreover, triangulation is the best means of answering the following four sub-questions of the research which have both qualitative and quantitative aspects: (1) What perceptions do water utilities managers have about quality management in general and TQM in particular? (2) To what extent are TQM practices actually applied in the water utilities? (3) Is there a relationship between the use of specific TQM procedures/models and water quality? (4) What other quality factors do managers in water utilities identify as crucial for improvement of water quality? This paper reports on two types of data collection for the three case studies under investigation, i.e. face to face interviews conducted with the managers of the three TLAs and participant observations at the water treatment plants of the same three TLAs. The three TLAs under study were chosen due to their different approaches of applying quality management systems. There is a range of approaches to sampling which can be used (El-Kafafi, 2001). Snowball, chain or network sampling (Patton, 1990) is the form of purposeful sampling used in this research. The researcher identified the participants through contacting people in the different TLAs and asking about the most suitable and knowledgeable person in the area to be interviewed. Owing to their knowledge from their daily contact in the field, managers of water, drainage and refuse and the water

Table I. Key Waikato water resources

Rivers and lakes

Description

Waikato River

The longest river in New Zealand and is considered an important natural resource for the Region Contributes to extensive flood plains in the north Extensive flood plains in the north Extensive flood plains in the north Exceptional water quality

Waipa River Piako River Waihou River Lake Taupo

Source: Waikato Regional Council (1998)

treatment managers of the different TLAs of the three case studies under investigation were selected. Since, TLA “A” serves a bigger community five managers were identified for interviewing while only two managers were identified in TLA “G” and TLA “H” due to the size of community they serve. After conducting the initial interviews with the management team, it was found out that two of the TLAs were adopting some of the TQM models while the third one was not adopting any. This facilitated a comparative analysis to decipher the difference between the performance of TLAs adopting TQM models and TLAs who are not embracing its implementation. Data collections methods The following section reports on the two methods utilized in data collection. Face-to-face interviews The researcher used interviewing technique as the main data collection instrument because this yields rich insights into people’s experiences, opinions, aspirations, attitudes and feelings (Brenner, 1985; Lindolf, 1995; May, 1997). In accordance with the research requirements, the researcher formed structured interviews to serve both quantitative and qualitative dimensions that vary from the formal standardized example of surveys (May, 1997). Hence, the researcher created a situation in which respondents (i.e. TLA managers) were encouraged to answer questions in their own terms. Each person was asked the same question in the same way so that any differences between answers are held to be real ones and not the result of the interview situation itself. Hence, the neutrality of the researcher’s role is maintained (Fontana and Frey, 1994). This part of the questionnaire (i.e. open-ended questions was conducted to answer sub-research questions 1 and 4. On the other hand, the closed questions (in which this paper is reporting on) were designed on a five Likert scale where the response categories were determined in advance where 0 was the lowest score and 4 was the highest score. Those questions were conducted for the qualitative part to reply to the other two sub-research questions, i.e. number 2 and 3. The quality variables used for the closed questions were: . training personnel in quality systems; . customer satisfaction; . purchasing equipment/chemicals; . process control; . inspection and testing; . calibration of equipment; . corrective/preventive action; and . control of quality records. Those quality variables were chosen in accordance with ISO 9000 elements as an indicator of the extent of actual adoption of TQM practices in the water utilities under investigation. Participant observation Collecting data through observation is referred to as “participant observation” (Merriam, 1998; Dane, 1990; Fetterman, 1998). The researcher used the observation

TQM models

443

TQM 18,5

444

method deliberately by visiting the water treatment plant of each TLA under investigation as a means of check and control on validity and reliability as part of the data triangulation process. This also served as a means of supporting the answers to the research question by relating the analysis derived from the face-to-face interviews (i.e. what the managers said about their organization) to the observations conducted (how management really does function and act in the real setting). The following sections expand on the three case studies of this research. Case study 1 (TLA “A”) This TLA serves a population of 120,000. Five managers were interviewed from this TLA. Although the works and services group serves different communities, it operates one standardised water supply system. It was the first TLA in the region to adopt quality management systems and use the TQM improvement techniques and tools. It has been ISO 9002 certified for six years and since March 2000, it has been ISO 9001 certified. Moreover, this TLA is working towards incorporating the elements of The Business Excellence Quality Award (i.e. equivalent to The Malcolm Baldrige National Quality Award). Data collection and analysis Face-to-face interviews The interviews were conducted during the months of September, October and November 2000. The questions related to the following quality management variables were coded and analysed on an excel spread sheet to get the mean of each criteria of the personal assessment tool for each TLA. Figure 1 shows the results of qualitative analysis of the

Figure 1. TLA “A”. Average mean of all quality variables

face-to-face interviews in accordance with the eight quality variables mentioned earlier. It also shows to what extent TQM and its models are actually applied in TLA “A”. The data was coded on a Likert scale where 0 was the lowest score and 4 was the highest score. According to this analysis, “customer satisfaction” criteria scored the highest (i.e. 4) while “training in quality systems” scored the lowest (i.e. 2.75).

TQM models

Participant observation The observations were conducted at the TLA’s single water treatment plant between the months of July 2001 and February 2002. Further visits were conducted in 2004 for updating information. At this stage, the observations were related to only one aspect of the face-to-face interviews conducted with the TLA managers, i.e. the quantitative eight quality variables mentioned in the previous section (Table II).

445

Relating the observations to the quantitative analysis The researcher related the observations conducted in the water treatment plant to the eight variables (Figure 1) that were chosen for the quantitative analysis to relate between the theory and practice of the TQM models. The following was the outcome of the analysis: . Training. Water treatment technicians get trained by going to workshops and on job training. . Customer satisfaction. It is the main focus of the whole organization, which is regularly conducting surveys for the sake of feedback to improve on their shortcomings. The TLA has been conducting customer surveys since 1990, which is an indicator of using the TQM feedback loop. . Purchasing equipment/chemicals. Quality plays a great role but sometimes price constrains the choice of quality. . Process control. The process is always monitored during working hours and the technicians are on pager systems in case any problem arises after hours. . Inspection and testing. The TLA has both an internal and external auditing system to support quality assurance of the system. . Calibration. Equipment is calibrated correctly, regularly maintained and data documented. . Corrective/preventive action. The TLA employees endeavour to use quality improvement tools, e.g. fish bone and statistical analysis to find out the source of problems and take the right measures to prevent them in future. . Control of quality records. Every step of the process is documented and the important steps are then compiled to be fed into a computer system on a weekly basis to enable easy access and retrieval whenever information is required. Case study 2 (TLA “G”) This TLA serves a population of 17,992. Two managers were interviewed from this TLA as they were the only experts in the field. TLA “G” has eight water supply systems and eight water treatment plants. This TLA is different from the previous one not only in population size but also in the fact that the water services are provided through an internal sub-contractor. They have been ISO 9001 certified since 1997. They have not yet upgraded to ISO 9002.

Table II. Relating the eight quality variables with the participant observations across the three case studies

Case study 1 (TLA “A”)

TLA

446

Score 2.75. Management gets on job training and attending workshops. Plant operators obtain minimum “C Grade” certification for water treatment.

Score 4. The whole organization is totally driven by customer satisfaction and their requirements.

Score 2.9. Price plays Score 3.2. a role in managerial Although the score in this case decisions. is not that high, in practice (as indicated through participant observations) it is the highest of the three when it comes to process control.

Score 3.6. Although this case scores the lowest among the three cases, in practice, the quality assurance system is in place. It is supported by regular internal and external auditing.

Score 3. Is practiced regularly and according to set schedules

Score 3.5. The council endeavours to use the quality tools to find out the main source of the problem. This helps in tailoring a corrective action that also helps preventing the recurrence of the same problem in the future.

Score 3.5.Employee abide by filling al the required forms to document all steps of all processes taking place in the water treatment plant. The whole system is computerised for easy access and retrieval of information (continued)

Corrective/preventive Quality record Inspection and Purchasing Customer control action testing Calibration equipment/chemicals Process control satisfaction Training in QS (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity)

TQM 18,5

Score 2.65. Council is separate in this case from plant operators who work for a sub-contractor. Not sure if all operators have got a “C Grade” certification for water treatment.

Score4. Special care is given to customer requirements even in their treatment process, e.g. chemicals are added or not added upon community request.

Source: Author’s figure

Case study 2 (TLA “G”)

Score 3.5. Price affects the decision of purchasing.

Score 3.5. Owing to the fact that employees are working part-time on water treatment, not all plants are monitored all the time. Nevertheless, the pager system compensate for that.

Score 4. Although the score is the highest on the scale, it is very difficult to generalise since this case has got nine different water treatment plants with employees travelling from one site to the other. Score 3.75. Quality is Score 3. Process is Score 4. What is Score 3. Council Case Score 2.5. Plant not monitored all in favour of this a second criteria has got a study operator has case is that the the time since already got the “C compliant system because price is 3 source of the considered the main employees have to which they (TLA Grade” to travel from one water is of high criteria. record customer “H”) certification plant to the other quality so it does before joining the complaints and not require a lot of and only three attend to it. work force on treatment; hence plant operators council. No are scheduled to results are budget allocated take care of four favourable with for quality minimal effort. water treatment management. plants.

TLA

Score 3.5. Daily, weekly, and monthly tests are manually documented. The information is faxed by the subcontractor to the main office of the council.

Score 3.5. Forms for weekly and monthly maintenance is filled and circulated manually.

Score 3.25. Some of the employees here tend to follow instructions than acting creatively.

Score 3.2. No quality tools are used to decipher the main reason behind the problem. Consultation among employees takes place to gain from personal experience.

Score 3. Is done through the help of subcontractors due to the fact that not all the employees of this case is have the required qualifications.

Score 3. It is done through the help of supplier because employees tend to forget how to work the equipment since they did not get enough training on how to use it.

Corrective/preventive Quality record Inspection and Purchasing Customer control action testing Calibration equipment/chemicals Process control satisfaction Training in QS (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity) (score/conformity)

TQM models

447

Table II.

TQM 18,5

Data collection and analysis Face-to-face interviews Figure 2 shows the extent TQM and its models are applied in TLA “G”. According to this analysis both “customer satisfaction” and “inspection and testing” criterions scored the highest (i.e. 4) while “training in quality systems” scored the lowest (i.e. 2.65).

448

Participant observation This TLA is different than the previous one since it has eight water treatment plants scattered around the different residential communities in the area. Relating the observations to the quantitative analysis The following were the results of participant observations: . Training. Plant operators in this TLA do not get a lot of training since they are actually working for another contractor who is utilising them in other work and services. They are not specialised in water treatment. . Customer satisfaction. Plant operators are keen on measuring water supply to meet the community requirements in the different towns around this district. Moreover, in one of the water treatment plants fluoride is not added while treating the water in compliance with the community request who are refusing it. TLA “G” has been conducting customer surveys since 1990, which is an indicator of using the TQM feedback loop. . Purchasing equipments/chemicals. Is in the hands of management who provide the chemicals for the daily tests. Other sophisticated tests (e.g. faecal coliform) are conducted through a contract with a certified laboratory in a bigger city.

Figure 2. TLA “G”. Average mean of all quality variables

.

.

.

.

.

Process control. Is not closely monitored since most of the plant operators work part-time. To compensate for this issue, all plant operators are reached through a pager system that is connected to an alarm system in cases of problems and disasters arising either during the day or after hours. Inspection and testing. Is conducted in accordance with the New Zealand drinking water standards, i.e. daily in some plants and three times a week in the other small plants that serves a smaller population size. Calibration. Simple laboratory equipment (e.g. thermometers, pH meters) is maintained regularly by plant operators, while other sophisticated machines are calibrated every three months as required. It was observed that some of the newly installed equipment was not functioning for nearly six months. An example of non-compliance by contractors. Corrective/preventive action. There is no collaboration between the plant operators and the supervisory team. An example is that one of the water treatment plants has an ongoing blockage problem with its filters especially during the raining season. No preventive action has been taken. Corrective action is usually taken to solve the problem temporarily but the problem persists. Control of quality records. All employees are documenting the quality control process on the required forms.

Case study 3 (TLA “H”) TLA “H” serves a population of 22,714. Two managers were interviewed from this TLA as they were the only experts in the field. One department is responsible for four water treatment plants serving different sized communities. The plants are run and maintained by the TLA. TLA “H” is different from both the previous two cases as they have not adopted any of the TQM models. They are abiding by the New Zealand drinking water standards. Data collection and analysis Face-to-face interviews Figure 3 shows the extent TQM and its models are applied in the “Council H”. According to this analysis, “inspection and testing” criteria scored the highest (i.e. 4) while “training in quality systems” scored the lowest (i.e. 2.5). Relating the observations to the qualitative analysis The following were the results of data analysis: . Training. Minimal training is given on the use of equipment when provided by the supplier; when the operator cannot work it out they have to call the supplier. It is a requirement for plant operators to acquire a minimal of a “C Grade” of water treatment certificate (i.e. a 12 week course to obtain a diploma in water treatment). . Customer Satisfaction. In some areas of this district the water source (e.g. spring water or mountain creeks) differs and it is originally pure and of good quality; therefore, minimal treatment is required. TLS “H” conducted only one customer survey on 1999.

TQM models

449

TQM 18,5

450

Figure 3. TLA “H”. Average mean of all quality variables

. .

.

.

.

.

Purchasing equipments/chemicals. Is done through a contractor. Process control. Regular control in accordance with the New Zealand water drinking standards. Internal annual audits to check compliance with the annual plans of the council. Inspection and testing. Differs among plants. One of the plants is visited only once a month since the source of water is of high quality. The system is connected to an alarm system that is connected to a pager system to notify the plant operators whenever a problem arises. Calibration. Conducted regularly in accordance with a specific schedule provided by the supplier. Corrective/preventive action. There is no specific system applied here other than meeting together whenever a problem occurs and discussing how to solve it. Control of quality records. Forms of water testing are recorded in weekly plant maintenance check sheets.

Comparing the findings of the three case studies Figure 4 shows the results of the quality variables across three case studies. Table II summarises the research findings after analysing the data and relating the eight quality variables with the participant observations conducted across the three case studies.

TQM models

451

Figure 4. Average mean of all quality variables across the three case studies

Furthermore, the analysis established the following similarities and differences among the three case studies. Similarities . Plant operators work on a roster basis through the week and week-end. . Each plant has an alarm system connected to a telemetry paging system that is provided to all plant operators on duty to notify them in cases of problems. . Each TLA shares the same goal of providing treated water to their communities. Differences . Water sources differ not only from one TLA to the other, but also among the different plants in a specific TLA. . Not all the water treatment plants are run directly by the TLA, i.e. in one of the cases work is sub-contracted out. . Water treatment processes differ not only among the three cases, but also from one treatment plant to the other depending on the plant size and the population that it serves. . Plant operators work fulltime only in one of the plants. In the other two cases, the plant operators dedicate only part of their work time to water treatment. . In two of the cases, there is a lot of travel by the plant operators between treatment plants which consumes a lot of their time. It also affects promptness in dealing and resolving customers’ problems which impacts on their satisfaction. . Some of the water treatment plants are located in remote locations.

TQM 18,5

452

.

Some of the plants are very basic with no technology at all; hence, most of the phases of the process are done manually which can be a source of human error.

Conclusion In conclusion, there are two different kinds of organizations according to this research paper. One organization is still using the old paradigms of management; hence using the same old techniques, which is exemplified in Case study 3 (TLA “H”). On the other hand, the second type organization is adopting the new paradigm of management theories, i.e. adopting TQM and its models. This is exemplified in Case study 1 (TLA “A”). It is also worth mentioning that Case study 2 (TLA “G”) is considered at the middle range since it is new in its implementation of TQM and its models. Figure 5 shows the model adopted by TLAs in their process to achieve high performance, with the goal of providing a substantially improved business result, in this case, a better quality of drinking water delivered to the community. This study revealed that organizational change adopted by Case study 1 and 2 has lead to an improvement of the service and quality of water provided to the community of those respective areas. Those TLAs who are adopting the TQM model have employed the following elements: . focus on adding value for the customer by providing a high quality service; . utilize values and principles versus rules; . leading by example; . respect and expect everyone to contribute (i.e. management and all staff); . collaborate and work in teams to deliver quality results; . continuous improvement; and . achieve data driven business results. Accordingly, the results shows a correlation between the adoption of TQM and its models and the service quality provided to the community in the shape of quality drinking water leading to customer satisfaction. It is recommended that the TLA not adopting TQM should consider revisiting their quality system to encompass full utilization of TQM tools as a means of solving their organizational problems. This can only be achieved if TQM philosophy is adopted fully by top management and becomes embedded in organizational policies.

Figure 5. TQM model

Note 1. Maori in New Zealand identify with and are identified through three levels of organization – Iwi – tribal level, hapu – clan and whanau – extended family References Brenner, M. (1985), “Intensive interviewing”, in Brenner, M., Brown, J. and Canter, D. (Eds), The Research Interview: Uses and Approaches, Academic Press, London. Cohen, S. and Brand, R. (1993), Total Quality Management in Government: A Practical Guide for the Real World, Jossey-Bass, San Francisco, CA. Dane, F.C. (1990), Research Methods, Brooks/Cole Publishing Company, Pacific Grove, CA. Denzin, N.K. (1998), Research Act: A Theoretical Introduction to Sociological Methods, 2nd ed., McGraw-Hill, New York, NY. El-Kafafi, S. (2001), “Use of mixed methods in assessing the role played by TQM in water utilities in New Zealand”, Proceedings of the Conference of the University of Malaya Centre for Continuing Education Qualitative Research Convention 2001: Navigating Challenges, Kuala Lumpur, Malaysia, October, pp. 24-6, available at: www.geocities.com/efmr2001 Fetterman, D.V. (1998), “Ethnography”, Applied Social Research Methods Series, 2nd ed.,Vol. 17, Sage, London. Fontana, A. and Frey, J.H. (1994), “Interviewing: the art of science”, in Denzin, N.K. and Lincoln, Y.S. (Eds), Handbook of Qualitative Research, Sage, London. Hsieh, A.T., Chou, C.H. and Chen, C.M. (2002), “Job standardization and service quality: a closer look at the application of total quality management to the public sector”, Total Quality Management, Vol. 13 No. 7, pp. 899-912. Kanji, G.K. and Asher, M. (1993), Total Quality Management: A Systematic Approach, Carfax, Oxford. Kanji, G.K. and Asher, M. (1999), 100 Methods for Total Quality Management, Vol. 1, Sage, New Delhi. Lindlof, T.R. (1995), “Qualitative communication research methods”, Current Communication: An Advanced Text Series, Vol. 3, Sage, London. May, T. (1997), Social Research: Issues, Methods and Process, 2nd ed., Open University Press, Buckingham. Merriam, S.B. (1998), Qualitative Research and Case Study Applications in Education, Jossey-Bass Publishers, San Francisco, CA. Morse, J.M. (1994), “Designing funded qualitative research”, in Denzin, N.K. and Lincoln, Y.S. (Eds), Handbook of Qualitative Research, Sage, London, pp. 220-35. Patton, M. (1990), Qualitative Evaluation and Research Methods, Sage, Newbury Park, CA. Ross, J. (1993), Total Quality Management: Text, Cases and Readings, St Lucie Press, Delray Beach, FL. Statistics New Zealand (2005), Waikato District Census 2005, available at: www.stats.govt.nz (accessed 26 April). Sureshchandar, G.S., Rajendran, C. and Anantharaman, R.N. (2001), “A conceptual model for total quality management in service organizations”, Total Quality Management, Vol. 12 No. 3, pp. 343-64. Waikato Regional Council (1994), Environment Waikato Strategic Plan 1998-2008, Waikato Regional Council, Hamilton.

TQM models

453

TQM 18,5

454

Waikato Regional CouncilM (1998), Environment Waikato Strategic Plan 1998-2008, Waikato Regional Council, Hamilton. Waikato Regional Council (2004), Delivering a Sustainable Future: Long Term Council Community Plan 2004-2014, Waikato Regional Council, Hamilton. Corresponding author Siham El-Kafafi can be contacted at: siham.elkafafi@manukau.ac.nz



Classification and application of problem solving quality tools

Problem solving quality tools

A manufacturing case study Catherine Hagemeyer and John K. Gershenson Department of Mechanical Engineering – Engineering Mechanics, Michigan Technological University, Houghton, Michigan, USA, and

Dana M. Johnson

455 Received January 2005 Revised March 2006 Accepted June 2006

School of Business and Economics, Michigan Technological University, Houghton, Michigan, USA Abstract Purpose – The complexity of problem solving requires use of quality tools to assist in the organization and analysis of information and data surrounding the concern. A proposed classification scheme for problem-solving tools allows the user to identify the correct tool at the proper time in the problem-solving process. This may assist the problem solver to efficiently and effectively work toward problem solution. The classification scheme, in the form of a matrix, identifies, organizes, and defines tools of the six sigma problem-solving process as taught and implemented at a large manufacturing company. Design/methodology/approach – Development of a problem-solving matrix to enable more efficient and effective use of tools applied to a six sigma project in a large manufacturing company. Findings – The application of the methodology to a case study in a large manufacturing company related to an Air Conditioning (A/C) No Fill concern. The exercise of applying the six sigma tools matrix to this project would have been improved if conducted at the beginning of the six sigma Belt training and start of the A/C No Fill project. Research limitations/implications – Since, the matrix was not fully completed at the start of either the training or the project, the team was unable to begin using the developed matrix until midway through both. This posed some limitations in judging the efficiency and effectiveness of the matrix. Although it is believed that both were improved, the maximum benefit may not have been achieved because of timing in application. Future application of the matrix should commence at the beginning of the project to enable maximum results for more efficient and effective problem solving and identification of proposed solution. Practical implications – Manufacturing and service organizations can improve their problem-solving methodology by using the approach outlined in this paper. It will enable companies to better “match” the tools necessary to solve real-life business problems. Originality/value – Although this approach uses existing quality management and problem-solving tools, its novel application in the development of a more thorough approach to problem solving, aided by the classification of problem-solving tools may enable companies to more successfully and expeditiously reach proposed solutions. Keywords Six sigma, Quality systems Paper type Case study

Introduction The complexity of problem solving requires use of quality tools to assist in the organization and analysis of information and data surrounding the concern. A proposed classification scheme for problem-solving tools allows the user to identify the correct


TQM 18,5

456

tool at the proper time in the problem-solving process. This may assist the problem solver to efficiently and effectively work toward problem solution. The classification scheme, in the form of a matrix, identifies, organizes, and defines tools of the six sigma problem-solving process as taught and implemented in a large manufacturing company. The use of the six sigma tools matrix allows the problem solver to: . select the usage from a set of attributes and provide the tool(s) that would be applicable based upon the selections; . understand the availability and purpose of some of the more common problem-solving tools; . identify the correct tool to use in the problem-solving process and when to apply the tool during the process; . understand a tool can be used in more than one step in the process and may often be used throughout the entire problem-solving process; and . become aware of the interrelationship of the tools and how they may feed into each other. In the formation of the six sigma tools matrix, 20 quality tools were selected from the seven basic quality tools and the six sigma Program. These tools were then classified into attributes – characteristics that describe and define the six sigma tools to provide the user with a description of the tool, how it performs, what it can be used for, inputs and outputs of the tool, and other aspects of the tool. Subcategories of attributes, called needs, were also determined and the tools classified within them to further describe and define the quality tool. The six sigma tools matrix was then applied to an Air Conditioning (A/C) No Fill project. Through this application, the effectiveness of the matrix is shown and the classifications of the attributes and needs verified. This case study of the classification and application of quality tools demonstrates how to best utilize quality tools for problem solving and the appropriate timing. Problem solving is a systematic process of reaching a solution or solutions to a concern or difficulty. The chosen process of problem solving is often determined by the degree of complexity of the concern presented. When the concern is relatively simple, an informal process occurs. However, as the concern grows in complexity, a more formalized, systematic process is followed. Even with a formal problem-solving method and tool set, the problem solver still may experience difficulty in the application of the method. Usually the method of the problem-solving process is straightforward with steps of “how to” outlined. However, the ambiguity comes in the application of the tools to assist in the process: The keys are to understand what you want from a particular tool or technique, its prerequisites, benefits and obstacles in implementation are critical to success and use (Spring et al., 1998).

Because there are many tools to select, the problem solver needs an understanding of the tool and how and when it is to be used. When implementing the six sigma process, especially as a new Black Belt or Green Belt, there is an opportunity for the quality tools to be misused. This could slow down the problem-solving process, lead to flawed conclusions, or even make the problem worse. Implementation difficulties have existed with many problem-solving programs. They include:

. . . . .

not knowing what quality tool to use; using a quality tool incorrectly; using a quality tool for the wrong application; not knowing when to use a quality tool; and not using one of the quality tools when one is needed.

During six sigma training, the explanations surrounding the selection, use, and application of the tools presented are not always adequately addressed. Many tools are taught in a relatively short time. Therefore, although “how” to use the tool is usually discussed at some length, there is no order to help sort the tools so that they can be properly applied and executed. During the training, it would be helpful to have a roadmap presented or discussed that would assist the beginning six sigma Black Belt or Green Belt to understand what tools are available and what the tools could or should provide. Literature review As companies embark on their problem-solving journey, they need to be aware of the multitude of different programs, tools, and approaches to organize their methodology. Although the literature outlines a multitude of different problem solving and quality improvement approaches, the primary sources reviewed focused directly on improving the efficiency and effectiveness of utilizing various tools in the context of a six sigma process. The literature review highlights the key problem-solving programs and tools, along with some methods for organization of six sigma tools. Problem-solving programs There are numerous problem-solving/quality processes. Some of those used at large manufacturing companies include: . The improvement process (Harrington, 1987). . Business process improvement (Harrington, 1991). . Quality improvement (Deming, 1986). . Process improvement (Ishikawa, 1987). . Juran on quality improvement (Juran, 1986). . Quality improvement through defect prevention (Crosby, 1986). . Six sigma implementation and training (Institute of Industrial Engineers, 2002). Most problem-solving programs contain the same or very similar core concepts, techniques and tools but what differs is the name of the program and the “angle” which promotes the program as something “new and improved” to solve the woes of a company. What differs in most programs is the order of the steps or the degree of detail involved in each of the steps. It is interesting that the programs span from 1987 to present; yet, in those years represented there are not many “real” differences to the programs. Problem-solving tools The Table I highlights the quality tools (the seven basic quality tools and the six sigma program quality tools arranged alphabetically) used by each of the quality programs listed above. The blocks (shown as X) depict the tools that are specifically mentioned


457

Table I. Quality tools used with problem-solving processes

The improvement process (Harrington, 1987) Business process improvement (Harrington, 1987) Quality improvement (Deming, 1986) Process improvement (Ishikawa, 1987) Juran quality improvement journey (Juran, 1986) Quality improvement through defect prevention (Crosby, 1986) Six sigma implementation and training (Institute of Industrial Engineers, 2002) X

X

X

X

Capability analysis

X

X

X

X

X

Check sheet

X

Cause and effect diagram or matrix

X

X

X

Control plan

Tools or techniques

X

X

X

X

X

Cost benefit Design of analysis experiments

X

X

FMEA

X

X

X

X

X (continued)

X

X

X

X

X

Gage repeatability and reproducibility Histogram

458

Box plot

Problem solving programs

TQM 18,5

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X

X

X

Note: Marked (X) areas indicate quality tools referenced in that problem solving program

The improvement process (Harrington, 1987) Business process improvement (Harrington, 1987) Quality improvement (Deming, 1986) Process improvement (Ishikawa, 1987) Juran quality improvement journey (Juran, 1986) Quality improvement through defect prevention (Crosby, 1986) Six sigma implementation and training (Institute of Industrial Engineers, 2002)

Tools or techniques

X

X

X

X

X

X

X

X

X

X

X

X

Mistake Process flow SPC control Thought Hypothesis proofing/automated Multivariate Pareto diagram/process Scatter charts process testing control chart diagram map diagram map

Problem solving programs

X

X

X

X

X

X

X

X

X

X

Additional tools

X

X

Trend/run chart


459

Table I.

TQM 18,5

460

as being a problem-solving tool for that program. That does not mean that the other tools cannot be used or are not used in that problem-solving program, just that there was no direct mention of the tool in the research of the problem-solving program. As the Table I illustrates, not every quality tool is used for every program nor does any single program use all the tools. Some of the earlier programs center on statistical process control (SPC) and some of the less complex quality tools. As the knowledge base of SPC and quality tools grew, the problem-solving programs embraced more of the quality tools and incorporated some of the more complex tools. Organization of six sigma tools Lending organization to the myriad of six sigma tools is necessary for the correct and efficient implementation of the problem-solving process. One instrument that organizes the six sigma tools is the “Tools and the Deliverables” matrix (Figure 1). The “Tools” section of this matrix lists the six sigma quality tools used during the DMAIC process. Pictorial examples of the tools are also included. The “Deliverables” section contains the steps of the six sigma process. This guide is too basic for a more experienced six sigma user. The arrangement of the tools to the six sigma steps and the pictures provided could aid in the tool selection process. But, if all these tools were tried, and the user is still not reaching a solution to the problem, the matrix does not provide any additional quality tools that could be applied or have multiple uses of the quality tools. Rarely is a tool mentioned in more than one step. This supports the incorrect idea that a quality tool is good for only one step of the DMAIC process. The Six Sigma Pocket Guide by Rath and Strong (2000) (Figure 2) lists an assortment of quality tools down the y-axis. For each tool, dots indicate where in the DMAIC process the tool is most commonly used. Beside each tool, a reference of the chapter and page number is provided for the user to seek additional information for that quality tool. In addition, to the numerous quality tools contained in the list, some organizational tools are also added. The guide indicates that the tools can be used in multiple steps of the DMAIC process. Using the guide requires that the user have some familiarity with the tool or take the time to reference the tool to know if this is the correct tool for the application. Although these guides for six sigma tools are useful, they do not present a clear roadmap for the six sigma tools. What would be useful and thus the object of this research is to create a matrix of core problem-solving and six sigma quality tools that identifies the characteristics and attributes of each tool. This would allow the problem solver to: . select the usage from a set of attributes and provide the tool(s) that would be applicable based upon the selections; . understand the availability and purpose of the some of the more common problem-solving tools; . identify the correct tool to use in the problem-solving process and when to apply the tool during the process; . understand a tool can be used in more than one step in the process and may often be used throughout the entire problem-solving process; and . become aware of the interrelationship of the tools and how they may feed into each other.


461

Figure 1. Six sigma tools and deliverables matrix

What many problem-solving programs lack is a structured methodology for the selection of quality tools. This structured methodology would be a logical method with which to outline quality tools so that the user knows what the tool is, how it is to be used, and when it is used in the problem-solving process. Such information allows the user to apply the correct quality tool to organize/analyze the data and thus assist in problem resolution. Anyone who is trying to solve a problem with the use of the six sigma quality tools could benefit from such a structured methodology for applying tools. This information could be provided as a matrix, a pocket guide, or an online system. The literature review served as the basis to map the six sigma tools and create the six sigma tool matrix.

TQM 18,5

462

Figure 2. Six sigma pocket guide matrix


463

Figure 2.

Methodology development – mapping of the six sigma tools and creation of the six sigma tools matrix Following are the tasks followed to create the six sigma tools matrix. .

Form a team. Assemble a group of knowledgeable individuals to aid in the creation of the six sigma tools matrix.

.

Select the six sigma tools. Determine which of the quality tools from the six sigma process to use for this research.

.

Select attributes that pertain to and describe the tools. Determine the criteria set to apply to the above tools to provide definition and distinction to the tools.

.

Select needs that pertain to and describe the attributes. Define sub-categories that further describe how an attribute behaves in a particular tool.

.

Map the selected six sigma tools into attributes. Assign needs to each of the quality tools for each of the attributes.

.

Arrange the six sigma tools and attributes to comprise the six sigma tools matrix. Compile the information of quality tools, attributes and needs into the matrix format. This matrix would be for the user that knows the name of the tool, but not necessarily if it applies to their application. Tools are identified vertically, then for each tool attributes and needs within those attributes were assigned to the tools.

TQM 18,5

Form a team These individuals consisted of current six sigma Black Belts working on manufacturing and process projects, a six sigma Master Black Belt, and six sigma Green Belts. Consultation also occurred with the director of quality at the large manufacturing company, a statistical expert, and individuals directly impacted by the outcome of six sigma projects.

464 Select the six sigma tools There are a great number of quality and problem-solving tools from which to choose. To narrow the scope, the tools selected were the seven basic quality tools and tools emphasized in the six sigma program and training. The seven basic quality tools were selected because these are the most commonly known, promoted, and used of the quality tools (Gabor, 1990; Ceridwen, 1992). These seven tools (1999 Sigma Consultants, LLC, 2000; Ishikawa, 1987; Juran and Gryna, 1988; Rath and Strong, 2000) are shown in Table II. The other tools selected for the matrix are the quality and organizational tools from the six sigma process. The quality tools selected were those commonly referenced in various six sigma publications (Rath and Strong, 2000; Harry, 1997, 1999 Sigma Consultants, LLC, 2000), especially those in the six sigma program. The set of tools can easily be expanded as it is the method of presentation that is the key to this work. Alphabetically, these tools include (1999 Sigma Consultants, LLC, 2000; Duncan, 1995; Hart, 1992; Ishikawa, 1987; Juran and Gryna, 1988; Rath and Strong, 2000; Samuel, 2000) those in Table III. The check sheet is the only basic quality tool which is not called out as a six sigma tool also; yielding 20 total tools. Select attributes that pertain to and describe the tool The attributes describe what a tool does or provides and from those inputs it could be determined which tool to use. There could be hundreds of needs, or sub-categories, within each attribute, to give the quality tool further definition. Following are the descriptions of the six sigma attributes: Tool

Table II. The seven basic quality tools

Definition

Cause and effect diagram A schematic tool that resembles a fishbone that lists causes and sub-causes as they relate to a concern, also known as Fishbone diagram or Ishikawa diagram Check sheet A form used to collect, organize, and categorize data so it can be easily used for further analysis Histogram A graphic display of the number of times a value occurs Pareto diagram A bar chart that organizes the data from largest to smallest to direct attention on the important items (usually the biggest contributors) Process flow diagram A graphical illustration of the actual process Scatter diagram A graphical tool that plots one characteristic against another to understand the relationship between the two SPC control chart A graph of time-ordered data that predicts how a process should behave

Tool

Definition

Box plot

A graphical display of data in a box format that displays the median and variation of the data A calculation used to establish the proportion of the operating window taken up by the natural variation of the process A schematic tool that lists causes as they relate to a concern – also Fishbone diagram, Ishikawa diagram A matrix to understand and correlate customer requirements to process input variables A written description of the systems for controlling parts and processes A summary analysis that weighs the cost of improvement to the customer against the cost of the change to the process A systematic set of experiments that permit the evaluation of the effect of one or more factors on a response A structured approach to identify the way the product or process can fail and eliminate or reduce the risk of failure to protect the customer Statistical and graphical analyses to determine whether the measurement system and precisely measure the characteristic in question A graphic display of the number of times a value occurs Data driven tests that answer the question: “Is there a real difference between A and B?” using relatively small sample sizes to answer questions about the population An approach that emphasizes the detection and correction of mistakes before they become defects delivered to the customers A graphical tool that through logical sub-grouping analyzes the effects on the impact of categorical X’s on a response (continuous Y) A bar chart that organizes the data from largest to smallest to direct attention on the important items A graphical illustration of the actual process A graphical tool that plots one characteristic against another to understand the relationship between the two A graph of time-ordered data that predicts how a process should behave A graphical representation of the logical sequence in which the Black Belt will solve the problem using six sigma methodology A graphical display of data over time to understand what the process is doing based on the pattern of the data

Capability analysis Cause and effect diagram Cause and effect matrix Control plan Cost benefit analysis DOE Failure mode and effects analysis

Gage repeatability and reproducibility Histogram Hypothesis testing

Mistake proofing/automated control Multivariate charts Pareto diagram Process flow diagram Scatter diagram SPC control chart Thought process map Trend/run chart


465

Table III. Selected quality tools

TQM 18,5

466

(1) Six sigma phase. It provides the user with where in the six sigma process (define – measure – analyze – improve – control) the tool can or is most often used. A single or multiple six sigma phases may be identified for a tool. . Needs: Define – output characteristics are selected and key process input and output variables are identified. Measure – performance standards are defined, and the measurement system is validated. Analyze – product capability is established, the performance objectives defined and the variation sources identified. Improve – potential causes are screened, the variable relationships are discovered and the operating tolerances are established. Control – on-going measurement system is validated, improved process capability is determined, and on-going process controls are implemented. (2) Type of tool. It describes the function of the quality tool to the information that is being input into the tool. This attribute allows a secondary narrowing process by having the user understand how the function of the tools for the input, data. Only one of these needs will pertain to each tool. . Needs: Statistical – takes information, usually numerical, and manipulates or arranges the data. Analytical – takes complex information (perhaps numerical) and breaks it down to simpler, more basic elements. Clerical – takes information, usually non-numerical, and organizes it for improved documentation and flow. (3) Skill of User. It describes the statistical/problem-solving skill level needed of the problem solver, allowing the user to determine if they have the skill level necessary to implement the tool. Only one of these needs will pertain for each tool. . Needs: Novice – little or no prior knowledge of this tool. Intermediate – basic knowledge of the tool, training in the tool, or general knowledge in statistics/problem-solving; output requires moderate interpretation. Advanced – well versed in the tool and statistics/problem-solving; tool is complex and may incorporate several quality tools or concepts; output needs interpretation and analysis. (4) What is needed for tool use. It describes the information input needed to use the tool. A single or multiple needs may be identified for a tool. . Needs: Data collection – data, usually numerical, must be gathered and input into the tool.

(5)

(6)

(7)

(8)

(9)

Numerical analysis – numerical data must also be manipulated in some mathematical fashion. Process knowledge – knowledge of the process is an input for this tool. Quality tools needed prior to using this tool – Informs the user of what other six sigma tool(s) are needed to feed into this tool and use it most effectively. A single or multiple six sigma tools may be identified as feeding into a tool. . Needs:The 20 six sigma tools. What the tool works with. It describes what the tool needs in the way of type of information. Only one of these needs will pertain for each tool. . Needs: Ideas – thoughts, concepts, or process information. Numbers – numerical data. Tool function – It describes what the tool does with input data. A single or multiple needs may be identified for each tool. . Needs: Decides – uses Ideas to arrive at a solution. Generates – uses Ideas to promote new thoughts and/or concepts. Groups – uses Ideas to chunk thoughts and concepts by like properties. Implements – uses Ideas to direct the path of what to do next. Counts – uses Numbers to ascertain the status and extent of the concern. Measures – uses Numbers to analyze the concern. Tool classification. It describes practical methods, skills, or tools to provide change or improvement when applied to particular tasks. This identifies what we are qualifying as quality tools to a more defined group of a tool, technique or document. This classification allows the user to understand what the output will consist of in general terms. Only one of these needs will pertain for each tool. . Needs (McQuater et al., 1996): Tool – has a clearly defined application, often narrow in its focus and frequently used on its own. Technique – a process with a wider application usually requiring more conceptual thoughts and advanced skills; a collection of tools. Document – an organizational element that allows the problem solver to categorize, organizes, and maintains the flow of the problem-solving method. Physical outcome. It describes what the tool actually produces to assist the problem solver in the process. Only one of these needs will pertain to each tool. . Needs: Change in process – output of the tool suggests that the process/product is altered. Chart – output of the tool is a chart or charts.


467

TQM 18,5

468

Diagram – output of the tool is a diagram or diagrams. Matrix – output of the tool is a matrix or matrices. Numerical Comparison – output of the tool is a set of numerical outcomes of data or data sets that are used to make a decision about the process or product. (10) What the tool does with the information. It describes what the tool does with the information provided and when completed, how the tool should assist the problem solver. A single or multiple needs may be identified for each tool. . Needs: Analyzes – dissects the information to understand the elements and gain various perspectives on the information. Classifies – assigns the information into an arrangement of groups or categories. Compares – examines information against other information for decisional purposes. Organizes – arranges the information to bring order to it. Predicts – assists the problem solver in foretelling the outcome by making educated guesses based upon the information provided. Prioritizes – assists the problem solver in organizing the information in a manner so that ranking or precedence can be given to some information over other information. Provides status – allows the problem solver the ability to understand the current situation of the problem/process/product. Arrange the six sigma tools and attributes to comprise the six sigma tools matrix Once all of the quality tools were defined with attributes and needs, the next step was to organize this information for ease of use in a matrix (Table IV). The matrix is organized for a user that knows the name of the tool, but not necessarily if it applies to their application. In electronic form, it is searchable by other variables. Tools, on the y-axis, are separated into assessment tools (aid in analyzing or organizing the facts of the process to determine next steps and actions) and data tools (are used to analyze and interpret data collected in a process to make decisions and take actions). The tools are arranged how a problem solver might follow from the beginning to the end of the six sigma process. The attributes and needs for each tool are arranged in the matrix across the x-axis. For classification purposes, the attributes were placed into categories (tool origin, categorizations, inputs to tools, and output to tools). Discussion of results – application of the six sigma tools matrix The six sigma tools matrix was created to help determine which quality tools to use in the six sigma problem-solving process. To highlight its usefulness, the matrix was applied to a six sigma project at a large manufacturing company. The team compared the six sigma tools matrix against the standard six sigma Black Belt process to solve an A/C No Fill concern. The goal was to see how the matrix would have affected the work on and the outcome of the completed project.

Pareto diagram

Six sigma

Capability analysis

Define/ measure/ improve Define/ measure/ analyze/ improve Define/ measure /analyze/ improve/ control Define/ measure/ improve

Define/ measure

Define

Novice

Skill of user

Analytical Advanced

Analytical Novice

Analytical Novice

Analytical Novice

Analytical Novice

Clerical

Type of tool

Process knowledge

Process knowledge

Process knowledge

Process knowledge

Data collection

Process knowledge

Attributes

Ideas

Ideas

Ideas

Check sheet

Numbers Counts

Measures/ counts

Generates/ groups/ decides

Generates/ groups/ decides/ implements

Generates/ groups/ implements Generates/ groups/ implements

Generates/ groups/ decides/ implements Numbers Counts

Ideas

Control Ideas plan/C&E matrix/process map Control charts Numbers

None

None

Process map

None

None

What the tool Quality tools needed prior to works using this tool with Tool function

Inputs to tool

What is needed for tool use

Measure/ Statistical Intermediate Data collection analyze/ improve Basic Measure/ Analytical Novice Data collection quality analyze/ tool/six improve/ sigma control

Six sigma

Basic quality tool/six sigma Basic quality tool/six sigma

FMEA

Process flow diagram/process map

Cause and effect diagram

Cause and effect matrix

Basic quality tool Six sigma

Six sigma

Assessment tools Thought process map

Check sheet

Tool origin

Quality tool

Six sigma phase

Categorizations

Tool

Tool

Technique

Tool

Tool

Document

Tool

Document

Organizes/ classifies/ prioritizes Organizes/ classifies/ prioritizes Organizes/ classifies/ prioritizes

Matrix

Organizes/ classifies/ prioritizes Analyzes/ compares Organizes/ classifies/ prioritizes

Matrix

Numerical analysis Diagram

(continued)

Organizes/ prioritizes

Diagram

Diagram

Matrix

Organizes

What the tool does with the information

Matrix

Tool Physical classification outcome

Outputs of tool


469

Table IV. Six sigma tools matrix

Table IV.

Six sigma

Mistake proofing/automated control Data tools Gage repeatability and reproducibility

Histogram

SPC control charts

Trend/run chart

Six sigma

Control plan

Measure/ Statistical analyze

Clerical

Novice

Advanced

Skill of user Data collection/numerical analysis

What is needed for tool use Multivariate analysis/C&E diagram or matrix None

Control charts

None

None

None

Numbers Counts/ measures



Numbers Measures

Generates/ groups/ implements Implements

Implements

Numbers Measures

Process Ideas knowledge/numerical analysis Improve/ Clerical Intermediate Process knowledge C&E Ideas control matrix/process map Control Analytical Advanced Process knowledge None Ideas

Improve

Analyze/ Statistical improve

Type of tool

Intermediate Data collection/numerical analysis Six Measure/ Analytical Novice Data collection sigma analyze/ improve/ control Basic Measure/ Statistical Intermediate Data quality analyze/ collection/numerical tool/six improve/ analysis sigma control tool Basic Measure/ Statistical Novice Data collection quality analyze tool/six sigma tool

Six sigma

Cost benefit analysis

Six sigma

Six sigma

DOE

Tool origin

Attributes What the Quality tools tool needed prior to works Tool function using this tool with

Inputs to tool

Tool

Tool

Tool

Technique

Technique

Document

Document

Technique

Organizes/ prioritizes/ implements Implements

Organizes/ classifies/ compares/ prioritizes Compares/ prioritizes

What the tool does with the information

Diagram

Chart

Chart

(continued)

Organizes/ provides status

Provides status/ predicts/ compares Provides status/ predicts/ compares

Numerical Compares/ analysis/charts proves

Change in process

Matrix

Numerical analysis

Matrix


Outputs of tool

470

Quality tool

Six sigma phase

Categorizations

TQM 18,5

Six sigma Six sigma

Multivariate charts

Hypothesis testing

Box plot

Basic quality tool/six sigma tool Six sigma

Tool origin

Scatter diagram

Quality tool

Type of tool

Analyze/ Statistical control Measure/ Statistical analyze/ improve



Six sigma phase

Advanced

Data collection/numerical analysis

Intermediate Data collection


Attributes

Control charts

Control charts

Control charts

None

Tool

Numbers Counts/measures Tool


Numbers Measures

Outputs of tool

Organizes/ provides status Organizes/ compares Organizes/ compares

Diagram

Numerical analysis

Diagram

Organizes/ provides status

What the tool does with the information Diagram



What the Quality tools tool needed prior to works Tool function using this tool with

Inputs to tool

What is needed for tool use


Skill of user

Categorizations


471

Table IV.

TQM 18,5

472

The A/C No Fill concern project was undertaken at a manufacturing plant in October 2000 and was completed in September 2001. The A/C No Fill concern was the need to eliminate or reduce the number of A/C systems that did not fill with refrigerant or did not fill entirely with refrigerant at the A/C evacuation and fill operation. In the six sigma training, a subset of tools was learned and then applied each week correlating with the phase being covered in the DMAIC process. Table V shows the quality tools used during the project in tool matrix order. The six sigma phase column shows when tools were used. Each tool’s effectiveness (high, medium, low) was then rated by the team of experts. The reasoning behind the rating is given in the last column. The six sigma tools matrix was then applied to the A/C No Fill project to assess its content and usability as an aid in the problem-solving process. The application of the matrix to the project occurred after the project. The team went through the project one more time from the beginning using the matrix, rather than the six sigma training guide, to dictate the selection of quality tools. The solution from this application of the six sigma tools matrix to the A/C No Fill project resulted in the selected quality tools in Table VI. An “X” indicates the tool was selected for use and the last column shows when in the six sigma process they were used. The team of experts then compared the six sigma tools matrix solution to the Black Belt solution for the A/C No Fill project (Table VII). This table indicates which of the tools were actually used in the project based on the six sigma training and which tools would have been used based on the six sigma tools matrix. Specifically, the team reviewed the attributes contained under the six sigma tool matrix classifications of, “Categorizations” and “Inputs to the Tool.” If the criteria were applicable, the tool was selected as one that would be useful for the A/C No Fill project. Finally, an explanation was offered as to why differences occurred or if the tool was not used at all for the project. A comparison was conducted of tools that were used on the project with the tools that should have been used according the information from the six sigma tools matrix. Noted were tools used that were not recommended by the matrix, tools the matrix recommended that were not used, and explanations of the differences. To highlight the relative effectiveness of the six sigma tools matrix, analysis was conducted on which of the tools were used for the A/C No Fill project compared to which of the tools were selected using the six sigma tools matrix. This comparison showed the increased effectiveness of the matrix in addressing the values and needs of the six sigma tools and the six sigma phases where they were applied. This is evidenced in the last column of Table VII. Through the comparison of the six sigma tools matrix, results to the A/C No Fill project results the team confirmed that the attributes and needs selected and defined for the matrix were robust descriptors of the quality tools. The matrix provided the information needed to select a quality tool for six sigma project use. It also provided the six sigma phase in which to apply the tool to provide the most value to the problem solver. The six sigma tools matrix also assists the user in obtaining a basic understanding of a quality tool to better determine if it is needed and if any other quality tools must precede its use. This was evidenced in the A/C No Fill project as each tool was analyzed against each attribute and determined if the criteria warranted the tool’s application on the project. The analysis determined that although the Pareto diagram was a benefit to

X

Define/measure/improve

FMEA

X


Process flow diagram/process map

X

Define/measure


X

Define/measure


X

Not included in six sigma training

Define


Low

High

Medium

Low

Low

Tool used in A/C No Fill Effectiveness project rating

Check sheet

Six sigma phase from training

Quality tool This tool proved to be confusing and of no personal value. The more informal method we eventually used for our project proved more effective and was less time consuming. Used for class presentation purposes. Replaced it with a simple action matrix, which was easier to use and update This tool was not included in six sigma training but is included in the six sigma tools matrix This tool has you assign values to the C&E ideas in order to numerically rank the ideas. Felt this tool was too subjective and was not helpful in obtaining root cause of the concern. This became a time consuming exercise for the six sigma class. The cause and effect diagram was sufficient Effective “core” tool for sorting out thoughts and brainstorm ideas Effective “core” tool for understanding the process and the elements involved especially after “walking” the process. Maps reality. Good reference tool in the project Although started this tool, it did not seem to fit in this project and, therefore, did it as a time consuming exercise for the class and not for value in solving the problem (continued)

Explanation of rating


473

Table V. Effectiveness of the six sigma tools for the Black Belt solution to the A/C No Fill project

Analyze/improve

Improve Improve/control

Control

DOE


Control plan

Mistake proofing/automated control Measure/analyze

Measure

Pareto diagram

Data tools Gage repeatability and reproducibility

Measure/analyze

Capability analysis

Table V. Six sigma phase from training

X

X

X

X

X

X

High

High

Medium

High

High

Low


(continued)

Necessary tool in order to believe the data

Basis of six sigma program but there is the assumption of normality with little emphasis placed on options if it is not, in our case it was not a true measure of the improvement needed in the process. Pareto and Run charts of internal and external indicators proved to be more effective measure of before/during/after performance Simple yet effective tool to prioritize the concerns. Used many times throughout our project This tool was not used because it is complex and there was not enough time or knowledge of the process to incorporate it when it was presented in the six sigma training Provided a means for presenting a business case Effective tool because it is the plan for the on-going implemented control actions, however, it is dependent on management commitment and their diligence at maintaining control plan checks Necessary in any improvement process


474

Quality tool

TQM 18,5

Six sigma phase from training Measure/analyze Measure/analyze

Measure/analyze

Measure/analyze Measure/analyze

Control Measure/analyze

Quality tool

Trend/run chart

SPC control charts

Histogram

Scatter diagram

Box plot

Multivariate charts

Hypothesis testing X

X

X

X

X

Medium

Medium

High

High

High


Personally, one of the most effective methods for analyzing and understanding time ordered data Effective “core” tool for understanding the process using data to understand the effects that changes may have on the process Simple yet effective tool in understanding the distribution of the data and its relationship to specification or other targets. Applied this many times throughout the project This tool was not used because there was not an apparent application for it in the A/C project Tool was effective but did not provide extraordinary understanding past what was already known. There were other tools, which provided the same information This tool was not used because there was not an apparent application for it in the A/C project This proved to be effective in a decision-making process, but need to insure that the correct comparison information is available



475

Table V.

TQM 18,5 Quality tool

476

Table VI. Quality tools selected based on the application of the six sigma tools matrix

Thought process map Check sheet Cause and effect matrix Cause and effect diagram Process flow diagram/process map FMEA Capability analysis Pareto diagram DOE Cost benefit analysis Control plan Mistake proofing/automated control Gage repeatability and reproducibility Trend/run chart SPC control charts Histogram Scatter diagram Box plot Multivariate charts Hypothesis testing

Tool selected based on the six sigma tools matrix criteria

Six sigma phase tool actually used in

X

Measure/improve

X X

Define Define/measure/analyze

X X X X X X X X X

Measure/improve Improve Control Control Measure Measure/analyze/improve/control Measure/analyze/improve/control Measure/analyze/improve

X

Analyze

the project, time and effort could have been saved if a check sheet had been used instead of the Pareto (Table V). In addition, the matrix allowed for multiple uses of a tool in different phases. The team concluded that if the six sigma tools matrix had been available at the time of the A/C No Fill project execution, it could have: . Alleviated the frustration of using unnecessary tools – Some of the tools used for the A/C No Fill project were mandated by the six sigma Black Belt training with their application toward problem solution was minimal. . Improved the time to implement corrective actions for the A/C No Fill concern – Time was spent using tools that offered little or no value to A/C No Fill problem solution. By elimination of these tools and replacement with more effective tools, such as those called out by the six sigma tools matrix, total project time could have been saved and corrective actions for the A/C No Fill concern implemented sooner. . Created a better first impression of six sigma – Since, there are many aspects to six sigma, negative focus on one aspect can cloud the impression of the entire program. By easing the implementation of tool selection and usage, increased attention could be given by the Black or Green Belt on the methodology and underlying philosophy of six sigma. The exercise of applying the six sigma tools matrix to the A/C No Fill project would have been improved if conducted at the beginning of the six sigma Black Belt training and the start of the A/C No Fill project. However, the comparison proved to be valuable and allowed for showcasing the application of the six sigma tools matrix.



Check sheet


Quality tool Define

Define/measure

Define/measure

X

X


X

Tool used based on six sigma training

X

X

Define

Measure/improve

Tool used based on six sigma tools Six sigma phase tool matrix actually used When going through the attributes/needs criteria, this was not a tool, which applied to this project. It is classified as a “Clerical” tool under “Type of Tool”, and would not have been needed to organized information This tool would have proved useful in order to collect and categorize some of the data gathered. It would have proved to be a useful pre-step to the Pareto chart This tool is a “Document” under “Tool Classification” and was not necessary in order to analyze the cause and effect diagram This is an effective “core” tool for analyzing the types of causes that may have an effect on the problem (continued)

Explanation of difference


477

Table VII. Comparison of quality tools used based on the six sigma training versus the six sigma tools matrix for the A/C No Fill project

Table VII. X

X

Capability analysis

Pareto diagram

DOE


X

Analyze/improve

Measure

Measure/analyze


X

Process flow diagram/process map FMEA


X

X

X

Measure/improve

Define/measure/analyze

Tool used based on six sigma tools Six sigma phase tool matrix actually used

Effective “core” tool for understanding the process This type of project did not lend itself to a FMEA and the six sigma tools matrix indicated that The data collection initially for this project was not the correct measure of the process capability. For lack of better measurables, it is what was used. The six sigma process assumes that the correct measurables are in place, when in fact many times they are not Effective “core” tool for understanding and comparing the process This tool was not used, however, based on the matrix it would have been a valuable tool. The time constraints of the training did not allow this tool to be used (continued)


478

Quality tool


TQM 18,5

X X X

Trend/run chart

SPC control charts

Histogram

X

Mistake proofing/automated control X

X

Control plan

Data tools Gage repeatability and reproducibility

X


Quality tool


Measure/analyze

Measure/analyze

Measure/analyze

X

X

X

X

X

Control

Measure/analyze

X

X

Provided a means for presenting a business case. Following the attributes of the matrix confirmed the use of this tool Matrix indicated it is a good implementation tool Necessary in any improvement process confirmed by the matrix attributes


Effective “core” tool for proving the reliability of the gage and the data it produces Measure/analyze/improve/control Effective “core” tool for analyzing data as indicated by the matrix Measure/analyze/improve/control Effective “core” tool for analyzing data as indicated by the matrix Measure/analyze/improve Effective “core” tool for analyzing data as indicated by the matrix (continued)

Measure

Control

Control

Improve


Improve/control

Improve



479

Table VII.

Table VII. Measure/analyze

Hypothesis testing X

Control

Multivariate charts

Measure/analyze

Box plot X

Measure/analyze

Scatter diagram


X

Analyze


This tool was not used in the project and the matrix indicated it was not necessary when applying the criteria against it Matrix indicated this would be a tool that could be used This tool was not used in the project and the matrix indicated it was not necessary when applying the criteria against it The matrix did not indicate that this would be a tool that would be necessary to be used


480

Quality tool


TQM 18,5

Implications for practitioners For years companies have struggled with how to make their problem-solving methodologies more efficient and effective. As teams begin their problem-solving journey, they often struggle with identifying the most appropriate tools to use and when to use them. Since, a number of companies in both the manufacturing and service sectors are moving to utilizing six sigma methodology and process, the timing of this paper will allow companies to improve their approach to minimize the time to conduct problem solving and alternative evaluation. This approach represents a continuous improvement effort in large manufacturing company’s problem-solving methodologies. The experiences gained by this application can be transferred to other industries wanting to improve their problem-solving methodologies. This novel approach to problem solving sets a standard for those just implementing a problem-solving approach as well as those interested in continuous improvement of existing problem-solving methodologies. This well outlined, step-by-step methodology can also be applied outside the constraints of a six sigma process. Conclusion The six sigma tools matrix, by its basic construction, provides the user with an initial list of six sigma quality tools from which to select. Through the comparison of the six sigma tools matrix to the case study of the A/C No Fill project, the team verified that the attributes and needs selected and defined for the matrix are indeed correct descriptors of these quality tools and do provide the user with the information needed to select the correct quality tool at the correct six sigma phase. The six sigma tools matrix also assists the user in obtaining a basic understanding of a quality tool to determine if that is the correct tool to be used and if any other quality tools must precede its use. As also shown in the comparison, a tool may be used in more than one step in the six sigma process and may even be used throughout the entire problem-solving process. The six sigma tools matrix presents a clear roadmap for the problem solver, especially if the problem solver is a novice Black Belt or Green Belt. The matrix offers a limited number, but most often used, set of quality tools. It could easily be expanded to a wider set of tools. The attributes and needs within the matrix describe the tools to aid in the identification of the correct tool based on function, application, or problem-solving stage. Through the use of the six sigma tools matrix the problem solver can: . select the usage from a set of attributes and provide the tool(s) that would be applicable based upon the selections; . understand the availability and purpose of some of the more common problem-solving tools; . identify the correct tool to use in the problem-solving process and when to apply the tool during the process; . understand that a tool can be used in more than one step in the process and may often be used throughout the entire problem-solving process; and . become aware of the interrelationship of the tools, and how they may feed into each other.


481

TQM 18,5

482

Future research opportunities This valuable case study provides the foundation for the application of quality tools. The six sigma tools matrix has proven to be a useful aid. Black Belts, as well as other problem solvers, have expressed an interest in an aid such as this. It is the intent to automate the tool selection process to facilitate quick selection of the appropriate tools, thereby reducing the time to solve a problem and implement a solution. As a part of the automation, a database will keep track of tools used by problem type and serve as a “lessons learned” archive for future use in similar or related problems. Once a database has been implemented, reevaluation of the entire process should occur to discover the benefits realized from automating the process. Additionally, the “lessons learned” archive can serve as a basis to help modify the matrix, by either expanding or reducing the tools included. Since, this application was limited to a manufacturing location, further study of how the matrix is applied in the service industry could prove beneficial. Many of the techniques employed in manufacturing are now being applied to the ever-growing service sector. “Lessons learned” in service application, where there is heavy utilization of human capital versus physical capital, would provide an interesting case study and analysis. References 1999 Sigma Consultants, LLC (2000), Six Sigma Process Black Belt Training: Weeks 1-4, Revision 1.0, 1999 Sigma Consultants, LLC., Dearborn, MI. Ceridwen, J. (1992), “Using quality’s tools: what’s working well?”, The Journal for Quality & Participation, Vol. 15 No. 2, pp. 92-8. Crosby, P. (1986), Quality Improvement through Defect Prevention, Philip Crosby Associates, Inc., Winter Park, FL. Deming, W.E. (1986), Out of the Crisis, Massachusetts Institute of Technology Press, Cambridge, MA. Duncan, W. (1995), Total Quality Key Terms and Concepts, Luftig & Warren, New York, NY. Gabor, A. (1990), The Man Who Discovered Quality: How W. Edwards Deming brought the Quality Revolution to American – The Stories of Ford, Xerox and GM, Times Books, New York, NY. Harrington, H.J. (1987), The Improvement Process: How America’s Leading Companies Improve Quality, McGraw-Hill, Inc., New York, NY. Harrington, H.J. (1991), Business Process Improvement: The Breakthrough Strategy for Total Quality, Productivity, and Competitiveness, McGraw-Hill, Inc., New York, NY. Harry, M.J. (1997), The Vision of Six Sigma: Tools & Methods for Breakthrough, 5th ed., TriStar Publishing, Phoenix, AZ. Hart, M.K. (1992), “Quality tools for decreasing variation and defining process capability”, Production and Inventory Management Journal, Vol. 33 No. 2, pp. 6-11. Institute of Industrial Engineers (2002), Six Sigma Implementation and Training, Institute of Industrial Engineers, Norcross, GA. Ishikawa, K. (1987), Guide to Quality Control, 2nd ed., Nordica International Limited, Tokyo. Juran, J.M. (1986), Juran on Quality Improvement Workbook, 5th Ed., Juran Institute, Inc., Wilton, CT.

Juran, J.M. and Gryna, F.M. (1988), Juran’s Quality Control Handbook, 4th Ed., McGraw-Hill, New York, NY. McQuater, R.E., Dale, B.G., Boaden, R.J. and Wilcox, M. (1996), “The effectiveness of quality management tools and techniques: an examination of the key influences in five plants”, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 210, pp. 329-39. Rath and Strong (2000), Six Sigma Pocket Guide, Rath & Strong Management Consultants, Lexington, MA. Samuel, P. (2000) Thought Process Map – Six Sigma Black Belt Workshop, PowerPoint presentation from six sigma training – week 1, Dearborn, MI. Spring, M., McQuater, R., Swift, K., Dale, B. and Booker, J. (1998), “The use of quality tools and techniques in product introduction: an assessment methodology”, The TQM Magazine, Vol. 10 No. 1, pp. 45-50. S&W Associates, Inc. (1999), The Breakthrough Methodology, S&W Associates, Inc., Dearborn, MI. Corresponding author Dana M. Johnson can be contacted at: dana@mtu.edu



483


TQM 18,5

The development of an employee satisfaction model for higher education

484

Shun-Hsing Chen Department of Industrial Engineering, Chung-Yuan University, Chung-Li, Taiwan, Republic of China and Department of Industrial Engineering and Management, Chin-Min Institute of Technology, Chung-Li, Taiwan, Republic of China

Ching-Chow Yang and Jiun-Yan Shiau Department of Industrial Engineering, Chung-Yuan University, Chung-Li, Taiwan, Republic of China, and

Hui-Hua Wang Department of Applied Foreign Languages, Chin-Min Institute of Technology, Chung-Li, Taiwan, Republic of China Abstract Purpose – Most studies on higher education focus on students as customers, and evaluate student levels of satisfaction/dissatisfaction with their programs, while generally neglecting teacher work satisfaction. Thus, this study evaluates how employee dissatisfaction with various investment items determines the improvement priority. Design/methodology/approach – This study used the academic literature to establish a satisfaction model for higher education employees. The model is divided into six dimensions: organisation vision, respect, result feedback and motivation, management system, pay and benefits, and work environment. Using a questionnaire based on the model, 248 teachers were surveyed to investigate and analyze their importance-satisfaction level. The importance-satisfaction model (I-S model) was then applied to place each quality attribute into the I-S model, and thus determine the improvement strategy. Findings – The analytical results showed that higher education employees focus on high salaries and fair promotion systems. Investigations of the job satisfaction of college teachers in Europe and America have produced similar results. Originality/value – The employee satisfaction model for the higher education sector not only considers satisfaction levels but also degrees of importance in deciding the improvement strategy. Keywords Employees, Job satisfaction, Higher education, Quality Paper type Research paper


Introduction Improving customer satisfaction not only raises company profits, but also facilitates company development (Dubrovski, 2001). Previous studies have proposed that employees are the greatest assets of a company, and that satisfied customers must satisfy employee requirements (Nebeker et al., 2001). Employee satisfaction influences organisational performance as much as customer satisfaction. Employees are the internal customers of the business; they satisfy the current working environment and

are willing to cooperate with the business to accomplish business goals. Teachers are the employees of education organisations, and teacher satisfaction with the working environment can promote teaching and research quality. Therefore, teacher requirements must be fulfilled to improve the working environment and enable teachers to achieve outstanding research and teaching performance. In higher education, most studies focus on students as “customers”, and evaluate their level of satisfaction/dissatisfaction with their programs of study (Comm and Mathaisel, 2000), while generally neglecting teacher work satisfaction. While several employee satisfaction studies have been performed, very few deal with university teachers or academics in general (Ward and Sloane, 1998). Since employee satisfaction has been found to be as important as customer (student) satisfaction (Oshagbemi, 1997a), research on higher education quality has now also begun to considering academic satisfaction (Comm and Mathaisel, 2003). The literature on employee satisfaction remains immature compared to that on customer satisfaction. Therefore, employee satisfaction surveys, particularly on employee satisfaction in the higher education sector, still require study and survey. Questionnaires, as well as employee interviews can also be applied to survey employee satisfaction. Businesses frequently design questionnaires from the perspective of managers, and thus the questionnaire items generally do not reflect real employee requirements (Comm and Mathaisel, 2000); thus, the survey results do not improve actual employee satisfaction levels. Consequently, this study evaluates how employee dissatisfaction with various investment items determines the improvement priority. Literature review Employee satisfaction for higher education Organisations strongly desire job satisfaction from their employees (Oshagbemi, 2003). Job satisfaction has been found to significantly influence job performance, absenteeism, turnover, and psychological distress (Andrisani, 1978; Davis, 1992; Spector, 1997). Dissatisfied workers are prone to excessive turnover and absenteeism. Understanding job satisfaction thus may be linked to performance, organisational productivity and other issues, including labour turnover (Dickter et al., 1996; Lee et al., 1999; Melamed et al., 1995; Sekoran and Jauch, 1978). Employee satisfaction is as important as customer satisfaction in influencing organisational performance. Lee (1988) showed that job satisfaction is among the best predictors of turnover. Job satisfaction also influences customer perceptions of service quality (Rafaeli, 1989; Schneider and Bowen, 1985). Additionally, Williams (1995) found that employee benefits influence job satisfaction. Indirect costs associated with job dissatisfaction include training, recruiting and learning curve inefficiencies, as well as reduction in the client base (Brown and Mitchell, 1993). Conversely, employee satisfaction can improve productivity, reduce staff turnover and enhance creativity and commitment. Therefore, employee satisfaction should not be ignored and yet very few businesses seriously consider employee satisfaction (Ulmer et al., 1999). The objectives of higher education are to provide in-depth knowledge, seek academic development, educate students, and coordinate national development demands (Johnes and Taylor, 1990). Perkins (1973) proposed that university teachers fulfill three major functions, namely teaching, researching and administration and management. Consequently, university teacher satisfaction is related to the functions of higher

Employee satisfaction model 485

TQM 18,5

486

education. Dalton and Pica (1998) found that the quality of faculty and instruction are important elements for satisfying business undergraduates and graduates, and that business placement and services were important to students. Similarly, in the higher education sector, Oshagbemi (1997a) investigated job satisfaction among university professors. Hagedorn (1994) examined the satisfaction of academic staff using various variables, including salary, perceived support from colleagues, satisfaction with administration, enjoyment of student interaction and perceived stress levels. Employee importance and satisfaction survey The purposes of employee satisfaction surveys are not only to discover employee satisfaction levels, but also to determine necessary improvements via the results of employee satisfaction surveys. Employee satisfaction surveys commonly apply questionnaire and complaint analyses. However, complaint analysis is a passive method, which cannot fully determine employee satisfaction. Recently, firms have increasingly started using questionnaire surveys (Yang, 2003a). Some businesses apply customer satisfaction survey models when devising employee satisfaction surveys (Lam et al., 2001), as in this study. The SERVQUAL model (Parasuraman et al., 1985, 1988, 1991) is the best-known service quality measurement model. SERVQUAL measures the gap between customer perceptions and expectations of service quality to determine perceived service quality. Comm and Mathaiael (2000) applied SERVQUAL to devise employee satisfaction surveys, and define “employee satisfaction” as the gap between the works related perceptions and expectations of employees. Some studies apply the SERVQUAL method to carry out employee satisfaction surveys, which replace the expectation values with the importance values, and cite the theory of McDougall and Levesque (1992). The author of this study recently conducted a study referring to customer satisfaction surveys in business, and showed that the importance and expectation values are not equivalent; therefore expectation values should not be replaced with importance values. Yang (2003b) also found that the importance and expectation values were not synonymous. As scholars study service quality, and businesses measure employee satisfaction, SERVQUAL is generally applied as an investigative tool. However, the SERVQUAL method is difficult to apply to business. Yang (2003b) indicated that the SERVQUAL questionnaire design has a number of limitations. Customers and employees have difficulties in answering the SERVQUAL questionnaire, particularly the “expectations” section. Taiwanese businesses generally apply traditional satisfaction surveys instead. For the above reasons, this study applies the I-S model rather than SERVQUAL to analyses employee satisfaction. Importance-satisfaction model (I-S model) Low-quality attributes should not be the only consideration when designing improvement plans. Usually, the customer (employee) measures the quality of goods or services based on several important attributes or elements (Berry et al., 1990; Deming, 1986). The customer (employee) evaluates product or service quality by considering several important quality attributes; therefore firms must take actions to improve the attributes that are important to the customer but which have low satisfaction levels. Figure 1 shows the analytical results of an I-S model survey conducted by Yang (2003a). The results for each quality attribute are placed in the model and then improvement strategies are considered based on the position of each item.


Figure 1. Importance-satisfaction model

Establishment of employee satisfaction model The most commonly used methods for importance-satisfaction surveys are to examine the thoughts and satisfaction of subjects via questionnaires; the dimensions of the questionnaires are used to explain the determinants. The dimensions of the determinants for employee satisfaction surveys vary among different businesses or organisations, but the differences are not obvious; moreover, the structure of employee satisfaction models for higher education is also identical. The following documents were referred to in discussing the determinants of employee satisfaction in the field of higher education. Oshagbemi (1997b) measured job satisfaction for 566 college teachers, as shown below: . teaching; . research; . administration and management; . present pay; . promotions; . supervision/supervisor behaviour; . behaviour of co-workers; and . physical conditions/working facilities. Fosam et al. (1998) analysed police organisations to find a suitable employee satisfaction model taking the South Yorkshire Police (SYP) as an example. As shown in Figure 2. Comm and Mathaisel (2000) used SERVQUAL to conduct questionnaire surveys on 606 employees of a private higher education organisations to identify the determinants of satisfaction within educational organisations. The findings were as follows: . workload; . work atmosphere; . decision-making; . ethics/fairness;

TQM 18,5

488

Figure 2. Employee satisfaction model . . . . . .

customer focus; supervision; goals and objectives; training and development; pay; and benefits.

Ku¨sku¨ (2001) proposed applying employee satisfaction surveys to the employees of a Turkish college, and applied the following dimensions for measuring their satisfaction: . general satisfaction; . management satisfaction; . colleagues; . other working group satisfaction; . job satisfaction; . work environment; and . salary satisfaction. Metle (2003) conducted employment satisfaction surveys on female employees in the Kuwaiti public government sector (KGS), and identified the following employment satisfaction factors: . overall job satisfaction; . pay and security; . co-workers; . supervision; . promotion; and . content of work.

Since the satisfaction of higher education employees has many contributing factors, no complete models can be followed. To establish an employee satisfaction measurement model for the higher education sectors this study applied the employee satisfaction model designed by Fosam et al. (1998), the needs theory of Maslow et al. (1998), and the two-factors theory of Herzberg (1966). This model is designed for university teachers only, and excludes office employees, owing to the different quality attributes of teachers and office employees. The quality attributes for teachers are divided into six dimensions (Figure 3): (1) organisation vision; (2) respect; (3) result feedback and motivation; (4) management system; (5) pay and benefits; and (6) work environment.


Methodology Case study Chin-Min Institute of Technology (CMIT) is a private university located in middle Taiwan. The school was established in 1985, and the campus has an area of 9 ha. However, due to serious adverse changes in the external environment and financial difficulties in the management of the school’s assets, which resulted in 1.1 billion NT$ dollars of long-term and short-term debts, the institution became unable to continue operating normally. The school thus came under the control of the Ministry of Education (MOE) in 2001. Questionnaire design and structure In order to measure the satisfaction levels of higher education teachers, their requirements must be determined before designing the questionnaire. These requirements, termed “quality attributes” in this study, are also the items that teachers emphasise most strongly. Different businesses have various management models and business cultures, and thus also have different employee requirements.

Figure 3. Employee satisfaction model for higher education sector

TQM 18,5

490

Therefore, different businesses cannot apply the same measurement model. Table I shows the factors used for measuring employee satisfaction with higher education obtained from understanding the functions of higher education and discussing with experts, schools’ personnel directors and 14 teachers, and then eliminating the unnecessary or inappropriate quality attributes. The following findings were obtained: . organisation vision (seven items); . respect (four items); . result feedback and motivation (five items); . management system (eight items); . pay and benefits (six items); and . work environment (nine items). This questionnaire was divided into three parts, as follows: (1) Demographics. Including sex, age, qualifications, years of service, and years at present school. (2) Importance survey. The importance survey scale ranged from 1 to 7 (with 1 representing extremely low importance and 7 representing extremely high importance). (3) Satisfaction survey. The satisfaction survey scale ranged from 1 to 7 (with 1 representing extremely dissatisfied and 7 representing extremely satisfied). Data collection and analysis This study issued a questionnaire to all teachers at CMIT. A total of 248 questionnaires were issued and 192 were returned (a response rate of 77.42 percent). Analysis of reliability and validity Reliability is generally measured by Cronbach’s (a; the Cronbach’s a of employee measurements for higher education was calculated using the statistical software, SPSS. The Cronbach’s a of employee importance was 0.9425, and the Cronbach’s a of employee satisfaction was 0.9587. The differences between these two figures are small, among 0.94 , 0.95, which indicates that the questionnaires administered in this study are highly reliable. After the questionnaire was retrieved, the analysis of reliability and validity on the six dimensions of satisfaction model was conducted first. According to Gay (1992), a reliability coefficient exceeding 0.8 for any test or scale was the minimum acceptable reliability coefficient. In terms of validity, the questionnaire was designed to acquire data according to the theory-model related studies. This study also conducted interviews with HR directors and discussions with teachers. The feedback obtained indicated that the questionnaire had extremely high reliability and validity (Table II). Importance and satisfaction quality attribute analysis The importance of requirements represents the levels of significance of the quality attributes for all teachers. Normally, teachers would hope that schools would provide the highest service standards for the important quality attributes. The importance of quality attributes can reflect teacher requirements. This study ranked all of the quality attributes in order of importance and satisfaction.

Social needs

Esteem needs

Self- actualization needs

Needs theory of Maslow

Motivation factor

Two factors theory of Herzberg

Management systems

Result feedback and motivation

Respect

Organisation vision

Evaluation dimensions

School’s entire development plan School’s reputation and image School’s participation in local culture or public welfare activities School principal’s perspective School principal’s and directors’ ambition Help teachers develop self-visions Participation in school’s major policy decisions Professional knowledge is respected Mutual respect among teachers Respect for their teachers by students Students’ outstanding performances Achievements of teaching and research Rewards and glorification for outstanding performances Provision of achievements rewards Support for the results of teaching and research Allow teachers to know school’s operating conditions Provision of fair promotion systems Provision of good management systems Clear system of rewards and penalties Directors with leadership and managerial capacity Open system of directors’ assignation Provision of smooth communication channels Introduction of innovation management systems Provision of high-quality service processes (continued)

Evaluation items of quality elements


Table I. Evaluation dimensions and attributes of teacher satisfaction, and the relationship between needs theory and two-factor theory

Hygiene factor

Safety needs

Work environment

Pay and benefits

Evaluation dimensions

Provision of good salaries systems Provision of working security systems Provision of affiliated kindergartens Provision of good retirement systems Provision of lodging, travel related welfare allowances Provision of subsidies for further education Provision of abundant library facilities Provision of complete teaching instruments Provision of convenient parking Provision of dining diversity Independent and spacious research space Provision of hygienic dining environments Provision of educative and training environments Provision of abundant research resources Provision of advanced information

Evaluation items of quality elements

492

Physiological needs

Two factors theory of Herzberg

Table I.

Needs theory of Maslow

TQM 18,5

Analysis of importance quality attributes The top five quality attributes for higher education employees (marked with a) as listed in Table III, were: provision of good salary systems (6.839); provision of fair promotion systems (6.821); provision of good retirement systems (6.664); provision of work security systems (6.658), and provision of abundant research resources (6.513). The bottom 35-39 in terms of importance ranking were as follows (marked in a gray background): provision of good management systems (4.756); provision of convenient parking (4.302), provision of lodging, travel related welfare allowances (4.236); provision of hygienic dining environments (4.062), and provision of dining diversity (4.029). Teachers are most concerned with salaries and work security, and wish to have stable jobs and salaries. Teachers are concerned with promotion opportunities to a higher level, so fair promotion systems are very important. Additionally, good retirement systems and long-term work security enhance teacher confidence at school; research is fundamental to the work of teachers, and thus abundant research resources are also crucial. The analytical results demonstrate that teachers focus on salaries and fair promotion, and care little about welfare and working environments.


Analysis of satisfaction quality attributes The top five quality attributes (marked with a) in the satisfaction ranking are as follows (Table III): provision of convenient parking (6.575); respect for their teachers by students (5.677); support for the results of teaching and research (5.664); school participation in local culture or public welfare activities (5.569), and provision of further education subsidies (5.568). The bottom 35-39 items in the satisfaction ranking was as follows (marked in a gray background): provision of abundant library facilities (3.553); provision of affiliated kindergartens (3.511); provision of work security systems (3.256); provision of fair promotion systems (3.152), and provision of good salaries for teachers (3.098). This case study is located in the suburbs in Taiwan, and thus parking was the area with highest teacher satisfaction. Additionally, due to the strict school regulations, students are extremely respectful and obedient to their teachers. Thus, teachers are highly satisfied with student behaviours. The school encourages teachers to produce high quality research by providing monetary incentives; for example, there is a reward of NT$60000 for teachers who successfully publish papers in international journals. The school focuses on communication between business and public welfare activities; thus teachers, businesses and the wider community frequently interact, enhancing the practical experience of teachers. The school encourages further education for teachers by providing flexible schedules and a NT$5000 monthly allowance. The above requirements are the five most important items for teacher satisfaction.

Dimensions Organisation vision Respect Result feedback and motivation Management systems Pay and benefits Work environment

Importance survey Cronbach’s a

Satisfaction survey Cronbach’s a

0.905 0.917 0.911 0.865 0.872 0.819

0.894 0.885 0.909 0.837 0.874 0.828

Table II. Reliability and validity for the six dimensions of employee importance and satisfaction survey

TQM 18,5

494

No.

Items

1 2 3

School’s entire development plan School’s reputation and image School’s participation in local culture or public welfare activities School principal’s perspective School principal’s and directors’ ambition Help teachers develop self-visions Participation in school’s major policy decisions Professional knowledge is respected Mutual respect among teachers Respect for their teachers by students Students’ outstanding performances Achievements of teaching and research Rewards and glorification for outstanding performances Provision of achievements rewards Support for the results of teaching and research Allow teachers to know school’s operating conditions Provision of fair promotion systems Provision of good management systems Clear system of rewards and penalties Directors with leadership and managerial capacity Open system of directors’ assignation Provision of smooth communication channels Introduction of innovation management systems Provision of high-quality service processes Provision of good salaries systems Provision of working security systems Provision of affiliated kindergartens Provision of good retirement systems Provision of lodging, travel related welfare allowances Provision of subsidies for further education Provision of abundant library facilities Provision of complete teaching instruments Provision of convenient parking Provision of dining diversity Independent and spacious research space Provision of hygienic dining environments Provision of educative and training environments Provision of abundant research resources Provision of advanced information

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Table III. Analysis of importance and satisfaction quality attributes

30 31 32 33 34 35 36 37 38 39

Importance Ranking Satisfaction Ranking 5.877 6.042

18 13

4.766 4.964

19 12

5.104 6.473 5.809 5.926 5.766 6.269 5.964 5.304 5.162 6.435

30 6 19 16 20 8 14 28 29 7

5.569 4.899 4.768 4.951 5.385 5.567 4.722 5.677 4.026 5.033

4a 15 18 14 7 6 21 2a 28 11

6.074 5.936 6.133

12 15 10

5.258 3.655 5.664

8 33 3a

5.023 6.821 4.756 5.087

32 2a 35 31

4.568 3.152 3.745 3.589

23 38 30 34

5.313 4.897 5.356 5.632 5.74 6.839 6.658 6.221 6.664

27 33 26 24 22 1a 4a 9 3a

3.795 3.679 4.959 4.762 4.375 3.098 3.256 3.511 4.869

29 31 13 20 24 39 37 36 16

4.236 4.859 6.122 5.896 4.302 4.029 5.667 4.062 5.394 6.513 5.753

37 34 11 17 36 39 23 38 25 5a 21

5.054 5.568 3.553 3.668 6.575 5.081 4.084 4.684 4.353 4.359 4.869

10 5a 35 32 1a 9 27 22 26 25 17

Note: aReveals the top five quality attributes

Teachers are dissatisfied with the lack of library facilities, and with the teaching and research requirements. Additionally, no kindergartens are affiliated with the school, so teachers must spend significant time and money on taking care of their children. Furthermore, owing to the growth of new universities in recent ten years and declining

birthrates, many schools have had difficulty in recruiting students; the inability of schools to provide working security is concerning teachers. In educational working environments, teachers are most concerned with the prospects for promotion; however, the artificial factors in the promotion systems usually cause teachers to feel unfairness, mirroring the findings of research by other scholars (Oshagbemi, 1996). Studies of higher education employees in European and American demonstrate that salaries are the main item of dissatisfaction of teachers (Comm and Mathaisel, 2000; Ku¨sku¨, 2001; Oshagbemi, 1997a, b) and then the promotion systems (Oshagbemi, 1996), demonstrating that the items of dissatisfaction for university teachers are the same in Eastern and Western countries. These analyses can help education providers to fulfill teacher requirements and focus on improving those quality attributes that they are most dissatisfied with. Importance-satisfaction model (I-S model) applications The purpose of employee satisfaction surveys is to determine the improvement quality attributes from the results of the analyses, in situations where the low quality attributes are usually those that must be improved. However, whether this objective is correct remains uncertain. For school satisfaction surveys, the most important work after statistics analyses and related discussions are to determine which quality attributes must be improved to raise employee satisfaction. For organisations with abundant resources then more improvements can be made, but for those with limited resources it is necessary to prioritize certain attributes. Selecting the low-quality attributes is not the proper method since teachers measure their satisfaction by the importance of quality attributes; thus, the attributes that schools most need to improve should be the quality attributes that are rated as important by teachers and yet for which satisfaction scores are low. The I-S model is the best application model for this. In the I-S model all quality attributes were placed in the model, and improvement strategies are then determined according to the position of each attribute. I-S model results Those quality attributes were placed in the I-S model, as shown in Figure 4: (1) Excellent area: 1. School’s entire development plan. 2. School’s reputation and image. 4. School principal’s perspective. 5. School principal and directors’ ambition. 6. Help teachers develop self-visions. 7. Participation in school’s major policy decisions. 8. professional knowledge is respected. 9. Mutual respect among teachers 12. Achievements of teaching and research. 13. Rewards and glorification for the outstanding performances. 15. Support for the results of teaching and research. 28. Provision of good retirement systems. 39. Provision of advanced information.


TQM 18,5

496

Figure 4. I-S model applications

(2) To be improved area: 14. Provision of achievements rewards. 17. Provision of fair promotion systems. 24. Provision of high-quality services process. 25. Provision of good salaries systems. 26. Provision of working security systems. 27. Provision of affiliated kindergartens. 31. Provision of abundant library facilities. 32. Provision of complete teaching instrument. 35. Independent and spacious research space. 38. Provision of abundant research resources. (3) Surplus area: 3. School’s participation in local culture or public welfare activities. 10. Respect for their teachers by students. 16. Allow teachers to know school’s operating conditions. 22. Provision of smooth communication channels. 23. Introduction of innovation management systems. 29. Provision of lodging, travel related welfare allowances. 30. Provision of subsidies for further education. 33. Provision of convenient parking. 34. Provision of dining diversity. 36. Provision of hygienic dining environments.

(4) Careless area: 11. Students’ outstanding performances. 18. Provision of good management systems. 19. Clear systems of rewards and penalties. 20. Directors have leadership and managerial capacity. 21. Open systems of directors’ assignation. 37. Provision of educative and training environments. Figure 4 shows the average teacher satisfaction value of 4.56, demonstrating that the school has acceptable operation performance. The “excellent area”, in which teachers are completely satisfied, includes 13 quality attributes; the “to be improved area”, in which teachers are dissatisfied with the quality attributes and hope that schools can actively improve them contains ten attributes; the “surplus area”, indicating that the schools have acceptable performances in this items, contains ten attributes. Furthermore, the “careless area” contains six attributes; if school resources are limited, these quality attributes have a low priority. Furthermore, if school resources are abundant, these items should also be improved. The quality attributes ranked 35-39th based on satisfaction all fell within the “to be improved area”, indicating that this model can also contain the dissatisfied quality attributes and demonstrating the practicability of the model. Two quality attributes in the improvement region are worth discussing. The first of these attributes is “Provision of good salaries systems” (No. 25). Teachers focus on salaries, and generally ignore other relevant welfare and research environments provided by the schools, or even randomly job-hop. The inability of schools to retain their core employees or to decrease employee turnover is a negative phenomenon. The other notably item is “provision of fair promotion systems” (No. 17). Promotion leads to an increased salary, and consequently this item is strongly related to monetary value. This quality attribute can easily be enhanced by establishing fair promotion systems and applying them correctly. This item is the quality attribute that is easiest to overcome with minimal investment of resources. The items referred to No. 17 and 25 are both related to monetary rewards, and can help the education providers to identify corresponding strategies for satisfying the requirements of teachers. Conclusions As organisations focus on customer relationship management, they should not forget that employees are also internal customers. Organisations have satisfied their customers only if they have also satisfied their employees. Businesses generally determine enhancement priorities based on the low satisfaction items, rather than considering actual employee requirements. Although this approach improved some dissatisfied quality attributes, these attributes are not the main focuses of employees. Consequently, considerable money is spent on improvement of dissatisfied quality attributes without improving employee satisfaction. Using higher education employees as examples, this study proposed the improvement priority based on the perspectives of importance and satisfaction, and the I-S model theory; schools, based on their own resources, can determine the improvement strategies and priorities to satisfy actual employee requirements. For education organisations, employees placing an excessive


TQM 18,5

498

value on their salaries indicate that employee may randomly job-hop to chase higher salaries, impacting school morale. This study can help education providers to understand the wishes of the teachers, which include financial satisfaction, related welfare and fair promotion systems; teacher satisfaction with schools management can benefit both teachers and schools. References Andrisani, P. (1978), “Job satisfaction among working women”, Signs, Vol. 3, pp. 588-607. Berry, L.L., Zeithaml, V.A. and Parasuraman, A. (1990), “Five imperatives for improving service quality”, Sloan Management Review, Summer, pp. 29-38. Brown, A.K. and Mitchell, T. (1993), “Organizational obstacles: links with financial performance, customer satisfaction, and job satisfaction in a service environment”, Human Relations, June. Comm, C.L. and Mathaisel, D.F.X. (2000), “Assessing employee satisfaction in service firms: an example in high education”, The Journal of Business and Economic Studies, pp. 43-53, Fairfield, Spring. Comm, C.L. and Mathaisel, D.F.X. (2003), “A case study of the implications of faculty workload and compensation for improving academic quality”, The international Journal of Educational Management, Vol. 17 Nos 4/5, pp. 200-10. Dalton, D. and Pica, J. (1998), “Student satisfaction with undergraduate and MBA DS/P/IS programs”, Decision Line, Vol. 29 No. 3. Davis, R. (1992), “Person-environment fit and job satisfaction”, in Cranny, C.J., Smith, P.C. and Stone, E.F. (Eds), Job Satisfaction, Lexington Books, New York, NY, pp. 69-880. Deming, J. (1986), Out of Crisis, MIT Press, Cambridge, MA. Dickter, D., Roznowski, M. and Harrison, D. (1996), “Temporal tempering: an event history analysis of the process of voluntary turnovers”, Journal of Applied Psychology, Vol. 81, pp. 705-16. Dubrovski, D. (2001), “The role of customer satisfaction in achieving business excellence”, Total Quality Management, Vol. 12 Nos 7/8, pp. 920-5. Fosam, E.B., Grimsley, M.F.J. and Wisher, S.J. (1998), “Exploring models for employee satisfaction-with particular reference to a police force”, Total Quality Management, No. 9, pp. 235-47. Gay, L.R. (1992), Educational Research Competencies for Analysis and Application, Macmillan, New York, NY. Hagedorn, L.S. (1994), “Retirement proximity’s role in the prediction of satisfaction in academe”, Research in Higher Education, Vol. 35 No. 6, pp. 711-28. Herzberg, F. (1966), Work and the Nature of Man, Wiley, New York, NY. Johnes, J. and Taylor, J. (1990), Performance Indicators in Higher Education: Buckingham, The Society for Research into Higher Education Open University, Buckingham. Ku¨sku¨, F. (2001), “Dimensions of employee satisfaction: a state university example”, METU Studies in Development, Vol. 28 Nos 3/4, pp. 399-430. Lam, T., Zhang, H. and Baum, T. (2001), “An investigation of employees’ job satisfaction: the case of hotels in Hong Kong”, Tourism Management, Vol. 22, pp. 157-65. Lee, T. (1988), “How job dissatisfaction leads to turnover”, Journal of Business and psychology, Vol. 2, pp. 263-71.

Lee, T., Mitchell, T., Holtom, B., McDaniel, L. and Hill, J. (1999), “The unfolding model of voluntary turnover: a replication and extension”, Academy of Management Journal, Vol. 42, pp. 450-62. McDougall, G. and Levesque, T. (1992), “The measurement of service quality: some methodology issues”, pp. 411-30, 2eme, Seminaire International de Recherche´ en Management des Activates de Service. Maslow, A.H., Deborah, C.S. and Gary, H. (1998), Maslow on Management, Wiley, New York, NY. Melamed, S., Ben-Avi, I., Luz, J. and Green, M. (1995), “Objective and subjective work monotony: effects on job satisfaction, psychological distress, and absenteeism in blue-collar workers”, Journal of Applied Psychology, Vol. 80 No. 1, pp. 29-42. Metle, M.K. (2003), “The impact of education on attitudes of female government employees”, The Journal of Management Development, Vol. 22 Nos 7/8, pp. 603-26. Nebeker, D., Busso, L., Werenfels, P.D., Diallo, H., Czekajewski, A. and Ferdman, B. (2001), “Airline station performance as a function of employee satisfaction”, Journal of Quality Management, Vol. 6, pp. 29-45. Oshagbemi, T. (1996), “Job satisfaction of UK academics”, Educational Management & Administration, Vol. 24 No. 4, pp. 389-400. Oshagbemi, T. (1997a), “Job satisfaction profiles of university professors”, Journal of Managerial Psychology, Vol. 12 No. 1, pp. 27-39. Oshagbemi, T. (1997b), “Job satisfaction and dissatisfaction in higher education”, Education & Training, Vol. 39 Nos 8/9, pp. 354-9. Oshagbemi, T. (2003), “Personal correlates of job satisfaction: empirical evidence from UK universities”, International Journal of Social economics, Vol. 30 Nos 11/12, pp. 1210-32. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), “A conceptual model of service quality and its implication for future research”, Journal of Marketing, Vol. 49 No. 9, pp. 41-50. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple -item scale for measuring consumer perceptions of service quality”, Journal of Retailing, Vol. 64 No. 1, pp. 12-40. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1991), “Refinement and reassessment of the SERVQUAL scale”, Journal of Retailing, Vol. 67 No. 4, pp. 420-5. Perkins, J.A. (1973), The University as an Organization, McGraw-Hill, New York, NY. Rafaeli, A. (1989), “When cashiers meet customers: an analysis of the role of supermarket cashiers”, Academy of Journal of Management, Vol. 30, pp. 245-73. Schneider, B. and Bowen, D. (1985), “Employee and customer perceptions of service in bands: replication and extension”, Journal of Applied Psychology, Vol. 70, pp. 423-33. Sekoran, U. and Jauch, L.R. (1978), “Employee orientation job satisfaction among professional employees in hospitals”, Journal of Management, Vol. 4 No. 4, pp. 43-56. Spector, P.E. (1997), Job Satisfaction: Application, Assessment, Cause, and Consequences, Sage, Thousand Oaks, CA. Ulmer, D., Syptak, J.M. and Marsland, D.W. (1999), “Job satisfaction: putting theory into practice”, Family Practice Management, October. Ward, M. and Sloane, P. (1998), “Job satisfaction: the case of the Scottish academic profession”, mimeo, University of Aberdeen, Aberdeen.


TQM 18,5

Williams, M.L. (1995), “Antecedents of employee benefit level satisfaction”, Journal of Management, Vol. 21, pp. 1097-128. Yang, C.C. (2003a), “Improvement actions based on the customers’ satisfaction survey”, TQM & Business Excellence, Vol. 14 No. 8, pp. 919-30. Yang, C.C. (2003b), “Establishment and applications of the integrated model of the measurement of service quality”, Managing Service Quality, Vol. 13 No. 4, pp. 310-24.

500 Corresponding author Shun-Hsing Chen can be contacted at: g9102409@cycu.edu.tw



Progress of quality management practices in Australian manufacturing firms Daniel I. Prajogo

Quality management practices 501

Department of Management, Monash University, Caulfield East, Australia Abstract Purpose – This paper aims to identify changes in quality management practices that occurred in Australian manufacturing firms between 1994 and 2001. Design/methodology/approach – This study used two sets of data drawn from two separate surveys. The first survey was conducted in 1994 by the Australian Manufacturing Council (AMC) and the second survey was conducted in the early 2001 among the members of Australian Organisation for Quality (AOQ). After screening both data sets, 336 and 101 responses were usable for analysis using MANOVA. Findings – In the year 2001, Australian manufacturing firms were investing less in training and development of employees, and saw themselves as needing to provide greater levels of leadership in pursuing best practice than in 1994. In addition, maintaining a high-quality of working environment and managing customer relationships were considered far more important in 2001 than previously, and less emphasis was placed on the standardising and documenting of internal procedures. Finally, suppliers were increasingly involved in product development, suggesting a shift of competitive advantage from an internal focus into a supply-chain orientation. Research limitations/implications – The significant discrepancy in the sample size and the different populations of the two surveys are the major limitations in generalising the findings of this study. Practical implications – The findings would be useful for practitioners who wish to track trends among Australian manufacturing firms and for those who want a benchmark against which to measure an individual firm’s performance. Practitioners may also be interested in issues such as supplier involvement and documentation. Originality/value – This study contributes new knowledge by assessing the trend of adoption of quality management practices in two separate cross-sectional studies at two different times. Keywords Quality management, Manufacturing industries, Australia Paper type Research paper

Introduction Total quality management (TQM) has been one of the most prominent developments in the management field in the last two decades. Beginning in Japan in the early 1980s, TQM has diffused into Western countries, including Australia, and reached its heyday in the 1990s as suggested by the number of publications which discuss TQM and related topics (Martinez-Lorente et al., 1998). As a set of principles, TQM has been deployed into certain practices which can be implemented in organisations. Researchers have developed various models of TQM practices and have used them to measure the level of adoption of TQM practices in the organisations (Anderson et al., 1994; Flynn et al., 1994; Grandzol and Gershon, 1998; Saraph et al., 1989). This papers aims to compare the level of adoption of TQM practices among Australian firms over an interval of time using two sets of data collected in 1994 and 2001. Specifically, the


TQM 18,5

502

paper examines the sustainability of TQM practices by identifying the changes that occurred in the adoption of these practices between those two points in time. One of the driving factors behind this study is the fact that TQM requires considerable long term effort and financial commitment before it can yield significant benefits (Hendricks and Singhal, 1996; Montes and Jover, 2004; Powell, 1995). In addition, a number of studies have reported the failure of TQM programmes, and it is commonly agreed that the rate of TQM success in the USA and Europe is less than 30 percent (Brown, 1993; Harari, 1993; Tatikonda and Tatikonda, 1996). At the same time, the change in the basis of competition which has shifted from quality into innovation, flexibility, and agility has triggered the question as to whether TQM would still be suitable for firms to compete in the twenty-first century (Rahman, 2004). Historical background of TQM in Australia Development of total quality management (TQM) practices in Australia began in the early 1980s as the manufacturing sector recognised its poor level of performance compared to its international competitors. Previously, Australian industry had experienced a strong challenge from Japanese companies, particularly on the basis of the quality of their manufactured goods. At the same time, forces of globalisation led the Australian government to change its policy from a high tariff regime which had been imposed to protect a comparatively weak manufacturing sector (Samson, 1997) to one which exposed Australian industries to international competition. The new policy forced companies to focus on improving quality and efficiency in order to compete with imported products. The quality movement in Australia gained momentum in 1987 when the federal government introduced a number of incentive schemes which encourage firms to implement TQM (Foley, 1987). For example, the federal government established the National Industry Extension Scheme (NIES) and the Australian Quality Council (AQC), formerly known as the Total Quality Management Institute, and the Australian Organisation for Quality (AOQ) to assist TQM diffusion in Australia. This council played an important role in publicising the benefits of becoming a mature quality organization by establishing and administering a national quality award. This award specified criteria for a comprehensive assessment of quality across a broad range of functions, processes and activities. The Australian Quality Award (AQA) was introduced in 1988 and has subsequently been renamed the Australian Business Excellence Framework (ABEF). During the period between the mid 1980s and the mid 1990s the quality movement (usually characterised as TQM) flourished and became a top priority throughout Australia. During this period a significant number of firms (irrespective of their size) attempted to adopt and implement TQM programs (Rahman and Sohal, 2002). The activity in this area could also be attributed to the increasing demands for quality assurance from customers (government and non-government organisations), most notably through ISO 9000 certification (Samson, 1997). After more than a decade of its diffusion, TQM and other quality initiatives appear to have become less of a priority for many firms (Rahman and Sohal, 2002). This trend away from quality can be attributed to both internal and external factors. From an internal perspective, many organisations appeared to have become so familiar with TQM that they have become either saturated by, or immune to, the message. More importantly, the source of competitive advantage was shifting from quality to other

characteristics, such as flexibility, and most notably, innovation (Hamel and Prahalad, 1994). This, however, does not mean that quality no longer has value for creating a competitive advantage for a business; indeed, improvement of quality should occur parallel with the other competitive sources. For example, Prajogo and Sohal (2003) suggests that there is cross-fertilisation between quality and innovation performance whereby each positively affects the other. There is also evidence suggesting that TQM has declined partly because firms have found TQM (and ISO 9000) disappointing, and delivering little direct value to the business despite large sums being invested (Terziovski et al., 1997). Samson (1997), however, argued that this problem was not due to the principles of ISO 9000 systems, but rather to poor implementation by organisations. He further noted that many firms in Australia had not pursued ISO 9000 certification as a strategy for improving quality, but as a means of satisfying government and other major customers who demanded certification. Empirical studies on TQM implementation in Australia Numerous empirical studies have been conducted in Australia over the past ten years to gauge the development and maturity of TQM implementation, particularly among manufacturing firms. A comprehensive source of information about these studies can be found in the work by Rahman and Sohal (2002). They found that recent studies (1995-1999) were mainly devoted to investigating the impact of TQM implementation on organisational performance (Dow et al., 1999; Samson and Terziovski, 1999). Most of these studies, however, only report the development of TQM at one point of time (i.e. cross-sectional) despite the fact, as noted earlier, that TQM must be implemented as part of a long-range strategic plan before it can yield significant benefits for organisations. In this regard, several scholars have indicated the need for longitudinal studies on TQM implementation (Mandal et al., 1999). In particular, longitudinal studies on TQM are important particularly because they will allow researchers to examine the learning process and changes experienced by firms that have implemented TQM over several years. Evidence suggests that as organisations mature in TQM, they will place greater emphasis on specific TQM practices. For example, whilst new TQM adopters tend to be more focused on the “hard” aspects of TQM such as tools, techniques, and certification, more mature TQM firms are more balanced between the “hard” and “soft” (i.e. people and culture) aspects (Rahman and Bullock, 2002; Samson and Terziovski, 1999). This learning process has also been evidenced in the fact that the understanding of quality and TQM itself has evolved, and while the focus was initially on quality as conformance, now continuous improvement in pursuit of business excellence is emphasised (Rahman, 2004). As a result, organisations will shift their emphasis regarding different aspects of TQM to suit their new strategic direction. Understanding this learning process is a critical part of sustainability of TQM implementation in organisations (Zairi, 2001). This paper presents a longitudinal study on the progress of the adoption of quality management practices among Australian firms between 1994 and 2001. The primary purpose is to provide some empirical evidence for shifts in focus and emphasis on quality management practices over this period. By employing a longitudinal approach, this study adds to a small number of studies on TQM in Australia, for example, Terziovski et al. (1999) and Van der Wiele and Brown (2001), which have adopted a similar method.


TQM 18,5

504

Research questions The empirical study was designed to assess the change in TQM implementation among Australian firms over a 7 year period (1994 and 2001). In particular, the intention is to address the following question: RQ1. Were there significant differences in quality management practices in Australian manufacturing firms between the years 1994 and 2001? The implications of this question are profound. Past studies on TQM among Australian firms have identified several common problems in the implementation process. Most notable among these are lack of leadership, inadequate training, lack of customer focus, and lack of mutual cooperation with suppliers (Sohal et al., 1992). These factors have commonly been identified as the primary impediment factors for TQM implementation. This study examines whether Australian companies learnt from this experience and made improvement in these key areas during the designated period. This study is by nature exploratory, and therefore, no particular hypotheses to be tested, although as indicated in the previous section, several changes were expected to have taken place in organisational practice as companies became more mature in TQM. Research methodology Source of empirical data This study used two sets of data drawn from two separate cross-sectional surveys. The first survey was conducted in 1994 by the Australian Manufacturing Council (AMC) and involved 3,000 manufacturing firms in Australia and New Zealand. The survey was based on the best manufacturing practices model (BMP model), focusing on an integrated approach to continuous improvement in all facets of an organisation’s operations. For this study only the data collected from Australian companies was used. About 962 Australian organisations replied giving a response rate of 32 percent. This survey consisted of 246 questions developed by a committee of academics, site managers and prominent members of the Australian Quality Awards Foundation. The second survey was conducted between November 2000 and February 2001 using a sample of 1,000 managers who were members of the Australian Organisation for Quality (AOQ). The targeted respondents were middle and senior managers in Australian companies who had knowledge of past and present organizational practices relating to continuous improvement and innovation. The survey covered various industries in both the manufacturing and non-manufacturing sectors. A total of 194 managers responded with 102 managers of these were from manufacturing firms. About 150 questionnaires were returned to the researchers. After accounting for those “returned to sender” (RTS), the final response rate was 22.8 percent. We limited the analysis on both surveys to firms which had been certified to ISO 9000 to improve their comparability. This selection criterion reduced the useable number of respondents of the AMC database from a total of 962-336 responses in comparison to 101 responses for the 2001 survey. Technically, the value of this study in a longitudinal sense is somewhat limited because of the differences between the populations of the two surveys. However, the value of comparing the data from these two sources could be justified for several reasons. First, both surveys had been randomly sent to Australian wide firms.

Second, the AMC (1994) survey focused on best practice, and specifically, on TQM which was the dominant paradigm during the decade. The fact that many other studies have used the AMC data set (Samson, 1997; Beamount et al., 1997; Terziovski et al., 1997; Samson and Terziovski, 1999; and Dow et al., 1999), confirms that it is significantly associated with TQM-related issues. Most of the respondents to the 2001 survey were managers who were involved in, and aware of, the nature and content of TQM related practices. Item selection The contents of the two surveys were screened to identify the items which were identical in terms of the wording. Eighteen items measuring organisational practices based on TQM principles were found to be identical. These organisational practices were divided into five categories following the structure of the AMC data set, namely (strategic) planning, leadership, people management, customer focus, and process management. Of the 18 identical items, four covered (strategic planning), two covered leadership, five covered people management, four covered customer focus, and three covered process management and supplier relationships. The four items of strategic planning include: (1) we have a mission statement which has been communicated throughout the company and is supported by our employees; (2) we have a comprehensive and structured planning process which regularly sets and reviews short and long-term goals; (3) when we develop our plans, policies and objectives we always incorporate customer requirements, supplier capabilities, and needs of other stakeholders, including the community; and (4) we have a written statement of strategy covering all business operations which is clearly articulated and agreed by our senior manager. The two items under the leadership category include: (1) senior managers actively encourage change and implement a culture of improvement, learning, and innovation in moving towards “excellence;” and (2) there is a high degree of unity of purpose throughout our company, and we have eliminated barriers between individuals and/or departments. Under people management, five items were included: (1) we have an organisation-wide training and development process, including career path planning, for all our employees; (2) our company has maintained both “top-down” and “bottom-up” communication processes; (3) employee satisfaction is formally and regularly measured; (4) employee flexibility, multi-skilling and training are actively used to support performance improvement; and (5) we always maintain a work environment that contributes to the health, safety and well-being of all employees.


TQM 18,5

506

Under customer focus, four items were included: (1) we actively and regularly seek customer inputs to identify their needs and expectations; (2) customer needs and expectations are effectively disseminated and understood throughout the workforce; (3) we have an effective process for resolving customers’ complaints; and (4) we systematically and regularly measure external customer satisfaction. Under process management and supplier relationships, three items were included: (1) the concept of the “internal customer” (i.e. the next process down the line) is well understood in our company; (2) we have clear, standardized and documented process instructions which are well understood by our employees; and (3) our suppliers are actively involved in our new product development process. Both survey instruments used a five-point Likert scale that represented a range of attitudes from strongly disagree (1) to strongly agree (5). Data analysis Table I presents two demographic variables of the two data sets in terms of industry sectors and organisational size measured by the number of employees. One-way multivariate analysis of variance (MANOVA) was used to test the differences between the 1994 and the 2001 data with respect to the 18 items reflecting quality management practices. The year of survey was treated as the independent variable (between groups) whilst the 18 quality management practices were treated as the dependent variables. Prior to this test, the effect of organisational size was tested to remove any possible spurious effect. The organisational size was cross-tabulated with the year of data set. The x 2 test passed the 5 percent significance level, indicating that the AMC data contains a larger sample of large organisations than the 2001 data.

ASIC subdivision

Table I. Demographic based on industry sectors and organisational size

Food and beverage Textiles Clothing and footwear Wood and wood products Paper and paper products Chemical petroleum Non-metallic mineral Basic metal products Fabricated metal products Transport equipment Other machinery Miscellaneous manufacturing Others Total

1994 data (N ¼ 336) Small (1-99) Large (. 100) 2 1 9 4 2 27 16 24 19 9 9 16 2 140

4 6 4 9 11 22 35 13 21 13 33 25 – 196

2001 data (N ¼ 101) Small (1-99) Large (.100) 2 2 1 3 2 8 1 8 5 2 7 10 11 62

5 2 1 4 – 2 1 2 4 6 5 2 5 39

Consequently, another test was needed to check if size had to be included as a factor. The effect of organisational size as a factor was tested using two-way MANOVA. The result indicated that the interaction effect between size and the year of survey data on the dependent variables was non-significant. Therefore, the organisational size was dropped from MANOVA. Before proceeding with MANOVA, several assumptions had to be met for the multivariate test procedures to be valid. First, the dependent variables need to be moderately correlated (Tabachnick and Fidell, 2001). The result of Pearson correlations indicated that this requirement was met by the data set with the correlation coefficients ranging from 0.10 to 0.62. Second, the equality of variance between the two groups needed to be tested. Tabachnick and Fidell (2001) suggest that the homogeneity of variance should be tested using Fmax ratio, the ratio of the largest cell variance to the smallest. They recommend that for moderate cell-size discrepancy (say, 3-1), the Fmax ratio should be less than 9 to indicate that there is no inflated type error. As shown in Table II, the Fmax ratios of the 18 dependent variables fall well below 3; hence, there is no evidence of a violation of the equality of variance between the two groups. The third criterion is the homogeneity of variance between the two groups. In this case, Box’s M-test indicated significant differences ( p , 0.001). This test is, however, “notoriously sensitive” according to Tabachnick and Fidell (2001), particularly given the large sample size involved (n ¼ 437). The fourth assumption concerned the normality of the dependent measures. The skewness and kurtosis of each dependent measure was computed and checked. As presented in Table II, none of the 18 variables showed any serious violation of normality. Furthermore, as suggested by Tabachnick and Fidell (2001, p. 329): . . . a sample size that produces 20 degrees of freedom for error in the univariate case should ensure robustness of the test, . . . Even with unequal n . . . a sample size of about 20 in the smallest cell should ensure robustness.

The sample size easily met this criterion, and therefore, robustness could be expected. Having met the above assumptions, one-way MANOVA was run, and the result was shown to be significant (F (18,415) ¼ 12.36, p , 0.001, partial h2 ¼ 0.35). The next step was to identify which of the 18 quality management practices were significantly different between the two groups. As presented in Table II, eight variables are significantly shown to be different at p , 0.05. However, given the result of Box-M test, caution needs to be taken in interpreting this result and a more stringent significant level was imposed. When tested at p , 0.01, only six items were considered as significantly different between the 1994 and the 2001 data. As shown in Table II, four of these indicated increased trends in their mean scores, namely the role of senior managers in developing a culture of improvement and learning, maintaining a work environment that contributes to the health, safety and well-being, effectively disseminating customer requirements throughout the workforce, and work closely with suppliers in product development, whilst the other two show a declining trend in their mean scores, namely have site-wide standardised and documented operating procedures, and are developing employee flexibility, multi-skilling and training.


TQM 18,5 Variables

508

Table II. MANOVA test between the 1994 data and the 2001 data

1994 (N ¼ 336) Mean SD

Planning Disseminating a mission statement to gain supports from employees 3.78 A comprehensive and structured planning process for both short and long-term goals 3.78 Incorporating the needs of other stakeholders in the company’s plans and objectives 3.88 The company’s strategy is clearly articulated in a written statement 3.60 Leadership The role of senior managers in developing a culture of improvement and learning 3.69 The role of senior managers in bringing unity of purpose in the company 3.25 People management Providing an organisation-wide training and development process 3.22 Maintaining effective both “top-down” and “bottom-up” communication processes 3.42 Measuring employee satisfaction formally and regularly 3.00 Maintaining a work environment that contributes to the health, safety and well-being 3.76 Developing employee flexibility, multi-skilling and training 3.96 Customer focus Searching and identifying customers’ requirements 3.63 Effectively disseminating customer requirements throughout the workforce 3.23 Maintaining an effective process for resolving external customers’ complaints 4.13 Systematically and regularly measuring external customer satisfaction 3.60 Process management and supplier relationship Internal customer-chain in the process 3.65 Have site-wide standardised and documented operating procedures 4.44 Our suppliers work closely with us in product development 2.98

2001 (N ¼ 101) Mean SD

Fmax

Skew

Kurt

ANOVA Sig. h2

1.04

3.74

1.19 1.32 20.91

0.32 0.82 0.00

0.91

3.53

1.10 1.45 20.74

0.26 0.02 0.01

0.94

3.84

0.95 1.01 20.74

0.26 0.70 0.00

1.10

3.49

1.20 1.18 20.56 20.54 0.43 0.00

1.21

4.04

0.88 1.89 21.62

3.08 0.01 0.02

1.22

3.50

1.10 1.22 20.90

0.63 0.09 0.01

0.95

3.02

1.08 1.27 20.16 20.69 0.06 0.01

0.88

3.58

1.05 1.44 20.41 20.29 0.15 0.00

1.00

2.97

1.18 1.39

0.87

4.37

0.80 1.19 20.76

0.48 0.00 0.08

0.74

3.61

1.01 1.84 20.98

1.36 0.00 0.03

0.99

3.90

0.97 1.04 20.86

0.59 0.02 0.01

0.95

3.84

0.85 1.25 20.30 20.30 0.00 0.07

0.67

4.27

0.90 1.78 20.93

1.04

3.52

1.11 1.15 20.48 20.45 0.63 0.00

1.01

3.68

0.98 1.06 20.67 20.01 0.92 0.00

0.61

4.05

0.83 1.84 20.92

1.13

3.35

1.23 1.19 20.26 20.54 0.01 0.02

0.00 20.83 0.61 0.00

1.55 0.10 0.01

0.90 0.00 0.06

Discussion It is interesting to see that the role of senior managers in developing a culture of improvement, learning, and innovation has increased significantly. This indicates an increased awareness by senior managers of the importance of culture in managing quality, and also points to an increased emphasis on leadership over the period between the two surveys. This is particularly encouraging given the importance placed on senior management commitment as a pre-cursor for an effective TQM program, and lack of commitment by senior management as the primary impediments for successful implementation of TQM have been reported in the past (Samson, 1997; Sohal et al., 1992). In the area of people management, the emphasis on employee flexibility, multi-skilling and training have decreased significantly, in conjunction with a declining trend in the provision of organisation-wide training and development processes (although the difference is not statistically significant). This result is somewhat surprising given quality initiatives, such as TQM, which have been noted as the most important driver of training provision in Australian firms in the 1990s (Smith et al., 2003). Also, given that the respondents were from ISO 9000 certified firms, it is very likely that they had to demonstrate the provision of formal training programs to the external auditors. However, this result may support the notion, noted earlier, that after seven years the diffusion of TQM among Australian firms may have reached “saturation point.” Firms familiar with TQM would see less need for training compared to the early 1990s when TQM was just introduced. In addition, a proportion of these firms may have dropped their TQM programmes or campaigns as they did not see significant gains yielded. In broader terms, this trend also appears to contradict the direction of Australian public policy regarding employment which places a greater emphasis on “flexible specialisation” and “multi-skilling” (Creighton and Stewart, 2005). However, the finding does follow the decline in training rates, particularly with regard to apprenticeship training, which has occurred over the last three decades among Australian firms. There has been a significant decline of 16.3 percent in the training rate between 1974 and 1992, and a decline of 10.6 percent between 1993 and 2001 (Toner, 2003). This decline, it is argued, has been driven by the increased intensity of competition due to such factors as tariff reduction and globalisation. As a result, firms have been forced to adopt strategies such as lean production, work intensification, and outsourcing in order to improve efficiency (Toner, 2003). In such a situation, firms are likely to reduce their training budget. In addition, increased job mobility, particularly among younger workers, would also have added to the reluctance to invest in training. By contrast, maintaining a work environment that contributes to the health, safety and well-being shows a significant rising trend, and this could be related to the move to integrating TQM and/or ISO 9000 with other initiatives such as the Environmental Management System (ISO 14000) and Occupational Health and Safety (ISO 18000). This concurs with Rahman and Sohal (2002) who found that employee health and safety and protection of the environment are becoming high priorities for managers in most industries. In the area of customer focus, the trend effectively disseminating customer requirements throughout the workforce is positive. The two other practices regarding customer focus philosophy also show an increase: identifying customer requirements and resolving customers’ complaints effectively, although neither passes p , 0.01.


TQM 18,5

510

This result is very positive since it indicates a better understanding among the Australian firms in managing the customer’s voice from the earliest phase (i.e. researching the needs) to the final phase (i.e. obtaining feedback) of the operations which enhances the quality of the end products (Dow et al., 1999). In the area of process management, a major decline in the emphasis of having site-wide standardised and documented operating procedures was recorded. This result is surprising given that the respondents were ISO 9000 certified firms, and therefore “under pressure” to maintain the documentation of their standardised operating procedures. However, this finding can be interpreted in a similar way to the decline of training where these ISO 9000 certified firms may have been familiar with documentation and therefore would have had less concerns about it. This finding may also indicate that Australian firms have gained a better knowledge of ISO 9000 as the standard has been around for several years. Therefore, it could be suggested that many managers have now recognised the limitations of ISO 9000 certification, as highlighted in past studies, and see the certification process as a useful contributor to long-term quality initiative (Terziovski et al., 1997). Thus, quality management needs to be seen as a dynamic operation, not as a set of static or mechanistic activities. This perspective could lead to less emphasis on the documentation of procedures which drives the attitude of compliance rather than improvement. This notion accords with the first finding which indicates an improved leadership role for senior management in pursuing continuous improvement of learning about best practices. In terms of cooperation with suppliers, the results indicate an increased level of supplier involvement in the product development process. This result is encouraging because studies have shown the increasing importance of supplier involvement which impacts on quality and innovation performance (Bozdogan et al., 1998; Handfield et al., 1999; Ragatz et al., 1997). The intensification of supplier relationships also indicates recognition of the inter-dependence between trading partners, which, again, is partly attributable to the opening of the Australian economy to external competition, and to the impact of globalisation generally. This finding, which is the strongest effect recorded, is indicative of a fundamental shift in thinking away from managing internal processes into managing networks and alliances in pursuing a wider base for competitive advantage beyond quality (Savage, 1996). Conclusion The comparison of the data from two surveys indicates that on a number of key issues the attitudes of Australian managers have shifted between 1994 and 2001 in certain areas with mixed trends. In particular, managers are investing less in the training and development of employees, which can create problems. The persistence of this trend can lead to skills shortages which will threaten the competitive position of Australian firms since skilled labour is linked to performance, including quality and innovation performance (Toner, 2003). This concern is supported by the survey conducted by the Australian Chamber of Commerce and Industry of 1685 small, medium and large companies which revealed that 79 percent of employers were concerned about their ability to recruit employees with appropriate skills (cited in Walker and Gome, 2004). In contrast to the training issue, there has been a positive trend showing that firms increasingly see themselves as responsible for providing greater levels of leadership in pursuit of best practice. Also, there is a better understanding of the customer focus

principle which is now more relational than transactional. Combining these trends, it could be inferred that firms may have embarked on strategic initiatives beyond a “traditional” notion of quality as conformance. The learning and experience in implementing quality management systems must now be effectively utilised to enhance organisational capabilities in other areas, such as innovation and knowledge management (Rahman and Sohal, 2002). Therefore, in response to the claim that TQM is “dying”, this paper concurs with Van der Wiele and Brown (2001) in arguing that it is the formality of TQM programmes and its associated jargon and hype which have declined whilst the practices of TQM as a good way of doing business have remained sustainable at least until 2001. Specifically, the changes in several TQM practices noted in this study indicates that with a sound understanding of TQM principles and practices, firms can selectively adapt in ways which are meaningful to their business operations and environmental situations rather than adopting such principles and practices as a “rigid package”. This concurs with what Zairi and Liburd (2001, cited in Zairi (2002, p. 1162)) suggest on the sustainability of TQM which depends on “the ability of an organization to adapt to change in the business environment to capture contemporary best practice methods and to achieve and maintain superior competitive performance.” Despite the variety of validating procedures and controls used in the data analysis of this study, the author still acknowledges the limitation of the findings resulting from a repeated cross-sectional study like this which cannot be considered as purely longitudinal. Nevertheless, the findings have identified a number of significant issues with regard to the maturity of TQM practices which can provide direction for future studies in this area. It would be worthwhile to replicate the AMC survey and capture a larger sample size in order to improve the generalisation of the findings. The content of the survey, however, should be reduced and focus on key practices and performance in order to improve the response rate. The analysis could also be expanded to examine any shift in the source of competitive advantage. For example, most studies on TQM in the 1990s suggest that “soft” factors are the significant predictors of organisational performance, so it would be appropriate to investigate whether this relationship still stands in today’s competitive environment. References AMC (1994), Leading the Way – A Study of Best Manufacturing Practices in Australia and New Zealand, Australian Manufacturing Council, Melbourne. Anderson, J., Rungtusanatham, M. and Schroeder, R. (1994), “A theory of quality management underlying the Deming management method”, Academy of Management Review, Vol. 19 No. 3, pp. 472-509. Beamount, N.B., Sohal, A.S. and Terziovski, M. (1997), “Comparing quality management practices in the Australian service and manufacturing industries”, International Journal of Quality & Reliability Management, Vol. 14 No. 8, pp. 814-33. Bozdogan, K., Deyst, J., Hoult, D. and Lucas, M. (1998), “Architectural innovation in product development through early supplier integration”, R&D Management, Vol. 28 No. 3, pp. 163-73. Brown, M.G. (1993), “Why does total quality fail in two out of three tries?”, Journal for Quality & Participation, Vol. 16 No. 2, pp. 80-9. Creighton, B. and Stewart, A. (2005), Labour Law, The Federation Press, Sydney.


TQM 18,5

512

Dow, D., Samson, D. and Ford, S. (1999), “Exploding the myth: do all quality management practices contribute to superior quality performance?”, Production and Operations Management, Vol. 8 No. 1, pp. 1-27. Flynn, B.B., Schroeder, R.G. and Sakakibara, S. (1994), “A framework for quality management research and an associated measurement instrument”, Journal of Operations Management, Vol. 11 No. 4, pp. 339-66. Foley, K.J. (1987), Report to the Committee of Review Standards Accrediation and Quality Control and Assurance, Department of Industry Technology and Commerce, Australian Government Publishing Service, Canberra. Grandzol, J.R. and Gershon, M. (1998), “A survey instrument for standardizing TQM modeling research”, International Journal of Quality Science, Vol. 3 No. 1, pp. 80-105. Hamel, G. and Prahalad, C.K. (1994), Competing for the Future, Harvard Business School Press, Boston, MA. Handfield, R.B., Ragatz, G.L., Petersen, K.J. and Monczka, R.M. (1999), “Involving suppliers in new product development”, California Management Review, Vol. 42 No. 1, pp. 59-82. Harari, O. (1993), “Ten reasons TQM doesn’t work”, Management Review, Vol. 82 No. 1, pp. 33-8. Hendricks, K.B. and Singhal, V.R. (1996), “Quality awards and the market value of the firm: an empirical examination”, Management Science, Vol. 42 No. 3, pp. 415-36. Mandal, P., Shah, K., Love, P.E.D. and Li, H. (1999), “The diffusion of quality in Australian manufacturing”, International Journal of Quality & Reliability Management, Vol. 16 No. 6, pp. 575-90. Martinez-Lorente, A.R., Dewhurst, F. and Dale, B.G. (1998), “Total quality management: origins and evolution of the term”, TQM Magazine, Vol. 10 No. 5, pp. 378-86. Montes, F.J.L. and Jover, A.J.V. (2004), “Total quality management, institutional isomorphism and performance: the case of financial services”, Service Industries Journal, Vol. 24 No. 5, pp. 103-19. Powell, T.C. (1995), “Total quality management as competitive advantage: a review and empirical study”, Strategic Management Journal, Vol. 16 No. 1, pp. 15-37. Prajogo, D.I. and Sohal, A.S. (2003), “The relationship between TQM practices, quality performance, and innovation performance”, International Journal of Quality & Reliability Management, Vol. 20 No. 8, pp. 901-18. Ragatz, G.L., Handfield, R.B. and Scannell, T.V. (1997), “Success factors for integrating suppliers into new product development”, The Journal of Product Innovation Management, Vol. 14 No. 3, pp. 190-202. Rahman, S. (2004), “The future of TQM is past. Can TQM be resurrected?”, Total Quality Management & Business Excellence, Vol. 15 No. 4, pp. 411-22. Rahman, S. and Bullock, P. (2002), “Soft TQM hard TQM and organisational performance relationships: an empirical investigation”, Omega, Vol. 33 No. 1, pp. 73-83. Rahman, S. and Sohal, A.S. (2002), “A review and classification of total quality management research in Australia and an agenda for future research”, International Journal of Quality & Reliability Management, Vol. 19 No. 1, pp. 26-44. Samson, D. (1997), “Progress in total quality management: evidence from Australasia”, International Journal of Quality Science, Vol. 2 No. 4, pp. 214-35. Samson, D. and Terziovski, M. (1999), “The relationship between total quality management practices and operational performance”, Journal of Operations Management, Vol. 17 No. 4, pp. 393-409.

Saraph, J.V., Benson, P.G. and Schroeder, R.G. (1989), “An instrument for measuring the critical factors of quality management”, Decision Sciences, Vol. 20 No. 4, pp. 810-29. Savage, C.M. (1996), Fifth Generation Management: Co-Creating through Virtual Enterprising, Dynamic Teaming, and Knowledge Networking, Butterworth-Heinemann, Boston. Smith, A., Oczkowski, E., Macklin, R. and Noble, C. (2003), “Organisational change and the management of training in Australian enterprises”, International Journal of Training & Development, Vol. 7 No. 1, pp. 2-15. Sohal, A.S., Ramsay, L. and Samson, D. (1992), “Quality management practices in Australian industry”, Total Quality Management, Vol. 3 No. 3, pp. 283-99. Tabachnick, B.G. and Fidell, L.S. (2001), Using Multivariate Statistics, Allyn & Bacon, Nedham Heights, MA. Tatikonda, L.U. and Tatikonda, R.J. (1996), “Top ten reasons your TQM effort is failing to improve profit”, Production & Inventory Management Journal, Vol. 37 No. 3, pp. 5-9. Terziovski, M., Samson, D. and Dow, D. (1997), “The business value of quality management systems certification: evidence from Australia and New Zealand”, Journal of Operations Management, Vol. 15, pp. 1-18. Terziovski, M., Sohal, A.S. and Moss, S. (1999), “Longitudinal analysis of quality management practices in Australian organizations”, Total Quality Management, Vol. 10 No. 6, pp. 915-26. Toner, P. (2003), “Supply-side and demand-side explanations of declining apprentice training rates: a critical overview”, Journal of Industrial Relations, Vol. 45 No. 4, pp. 457-84. Van der Wiele, T. and Brown, A. (2001), “Quality management over a decade: a longitudinal study”, International Journal of Quality & Reliability Management, Vol. 19 No. 5, pp. 508-23. Walker, J. and Gome, A. (2004), “Better with age”, Business Review Weekly, Vol. 26, pp. 52-3. Zairi, M. (2001), “Total quality management sustainability – what it means and how to make it viable”, International Journal of Quality & Reliability Management, Vol. 19 No. 5, pp. 502-7. Zairi, M. (2002), “Beyond TQM implementation: the new paradigm of TQM sustainability”, Total Quality Management, Vol. 13 No. 8, pp. 1161-72. Corresponding author Daniel I. Prajogo can be contacted at: daniel.prajogo@buseco.monash.edu.au




TQM 18,5

Selection of six sigma projects in the UK Ricardo Banuelas, Charles Tennant, Ian Tuersley and Shao Tang Warwick Manufacturing Group, School of Engineering, University of Warwick, Coventry, UK

514 Abstract

Purpose – The literature suggests that a key ingredient for the successful six sigma implementation is project prioritisation and selection. The purpose of this paper is to identify what criteria are considered for selecting six sigma projects and how six sigma projects are selected in organisations in the UK. Design/methodology/approach – Using a survey as a method of investigation, respondents were asked what criteria are considered to select projects and how potential projects are identified, prioritised, selected and evaluated. Findings – The results of the survey indicate that UK organisations tend to select projects based on criteria such as customer satisfaction, financial benefits, top management commitment and those projects integrated with the company’s strategy. Several tools and techniques such as cost benefit analysis, cause and effect matrix, brainstorming, Pareto analysis are employed to identify and prioritise projects. Research limitations/implications – This paper is limited to the selection of six sigma in the UK. Further, empirical studies using larger sample sizes and greater geographical diversity may be helpful in validating the results of this study. Practical implications – The identification of the most commonly used criteria to select six sigma projects can aid practitioners to select projects based on multiple criteria and using tools and techniques identified in this survey. Originality/value – The provision of empirical data on the criteria used to select six sigma projects and how six sigma projects are selected. Keywords Six sigma, Project management, Surveys, United Kingdom Paper type Research paper


Introduction Six sigma has evolved into a statistical oriented project driven approach to process and product quality improvement. Since projects are the means by which six sigma converts quality improvements into bottom-line financial benefits, multinational organisations such as Ford report completing as many as 10,000 projects (Ford, 2005). However, not all six sigma projects produce bottom-line benefits; many produce only local improvements (Pyzdek, 2000) and about 20 per cent of projects are cancelled (Eckes, 2001). The literature proposes that a key ingredient for successful six sigma implementation is project prioritisation and selection (Pande et al., 2000; Ban˜uelas and Antony, 2002). In addition, since different potential areas of improvement compete for scare resources, organisation should select six sigma projects in such as way that they are closely tied to the business goals and strategy (Ingle and Roe, 2001). Project selection is the process of evaluating individual projects or groups of projects, and then choosing to implement some set of them so that the objectives of the organisation will be achieved (Meredith and Mantel, 2003). Selecting a project that is

too large will cause valuable time to be lost during the define phase, as Black Belts struggle to scope their projects and develop project charters that can be addressed using six sigma. In addition, projects should be linked to the right goals and impact at least one of the major stakeholders’ issues, e.g. growth acceleration, cost reduction or cash flow improvement. Good project selection is itself a process; if it is properly carried out the potential benefits of six sigma can improve substantially (Pande et al., 2000). Authors and consultants have proposed the project selection process models and tools, and key elements in six sigma project selection producing a variety of models (Breyfogle et al., 2001; Adams et al., 2003; Pyzdek, 2003). This papers aims at identifying what models and tools are currently used in UK industry, what criteria is considering for selecting six sigma projects and how and who select six sigma projects in organisations. Consequently, this survey investigates the current status of the selection of six sigma projects in UK industry and identifies the main criteria used for project selection. The first part of this paper presents an overview of the research methodology employed. The second part of the paper discusses the results of the survey and compares them against the literature. This paper culminates by offering a brief summary of the research and directions for further research. Research methodology The research questions for this survey were: RQ1. What is the status of selection of six sigma projects in the UK organisations? RQ2. What are key criteria for project selection in the UK organisations? Sample The data for this study was gathered using a questionnaire. A national sample of UK organisations was selected from financial analysis made easy (FAME) database, which contains detailed company information on a large number of UK companies. The sample was constrained to companies with more than 300 employees since six sigma is more likely to be adopted by large organisations (Antony et al., 2005). Postal and e-mail survey was used for gathering data due to the advantage that the designed questionnaire could be sent to a large number of organisations in a limited time. A total of 300 postal and 813 e-mail questionnaires were sent out to the selected sample. The survey was targeted to quality directors, managing directors, quality managers or Black Belts, since they are directly involved in the process and have first-hand knowledge and experience of six sigma projects. Survey instrument The questionnaire used in this study consisted of three main sections: the background of the company, the project selection process and the key criteria considered for project selection. The first section was intended to determine fundamental issues such as the companies’ industry sector, the maturity of six sigma in the companies investigated in terms of the number of projects carried out and the number of years since six sigma was launched. The third section consisted of six criteria for six sigma project selection, derived mainly from the literature. Respondents were asked to rank the criteria in terms of importance for project selection on a five-point Likert scale from 1 “not important” to 5 “crucial”, with the middle denoted as “important”. It was hoped that this would give an

Selection of six sigma projects in the UK 515

TQM 18,5

516

indication of the critical criteria for the successful project selection. Moreover, the use of a Likert scale rather than a simple yes/no type of question in the questionnaire would provide a better perspective of the current six sigma practices in the UK industry. The questionnaire was pre-tested by submitting the “final” questionnaire to three types of people: colleagues, industry experts and target respondents. This tested whether the questionnaire would accomplish the study objectives, prevent the inclusion of some obvious errors and provide feedback on sample the answers ahead of the targeted respondents (Gillham, 2000). Results and discussion Characteristic of the sample A total of 95 respondents, out of 1,113, returned completed, usable questionnaires for an overall response rate of about 8.5 per cent. However, the response rate for the survey sent electronically was lower than that of the posted one (24.3 versus 2.3 per cent). Typically, the response rate of online survey is lower than those for postal surveys (Bryman, 2004). The possible reasons which result in low response rate of online/e-mail survey may be assigned to the fact that invitations to participate in research may be seen as another spam e-mail. In addition, the confidentiality of replies may be concerned by recipients in order to avoid being hacked or involved in frauds. Of those 95 responding companies, 25 were implementing six sigma and provided information which could be used for further analysis. In terms of industrial sectors, 12 of the companies pertain to the service sector whereas 13 of them were manufacturing companies. The number of the respondent companies which have implemented six sigma for more than three years is around half the companies currently running six sigma programme (Table I). In this research, the survey was answered by black belts (32 per cent), master black belts (20 per cent), quality managers (12 per cent), champions (8 per cent), green belts (8 per cent) and other quality related positions (20 per cent). Almost half of the companies implementing six sigma (48 per cent) have completed over 100 six sigma projects. About 24 per cent of them have completed between 10 and 100 six sigma projects and 28 per cent of them ten projects or less. People involved in the selection of six sigma projects According to Davis (2003) the first step of six sigma project selection is the establishment of a cross-functional team including the top management. The responsibility of the team or steering committee is to identify, prioritise, select, monitor and evaluate six sigma projects. The involvement of the top management helps to cascade down the company strategy into specific six sigma projects. In addition, it removes the obstacles and barriers more effectively (Kelly, 2002). Accordingly, in this survey respondents were asked about the people involved in the six sigma selection process. About 56 per cent involve senior managers and the “champion” in the selection of projects. In addition, 48 per cent of the companies indicated that final decision is normally made by top management. This top-bottom approach to select projects has three main advantages. Firstly, the projects would be aligned with the corporate strategy. Secondly, it is more structural and managerial and finally, it is beneficial to six sigma projects with management support (Harry and Schroeder, 2000; Lynch and Soloy, 2003).

Number Sample Post 300 E-mail 813 Total 1,113 Response post 76 Response e-mail 19 Total response 95 Companies implementing six sigma Implementing it 19 Partially implementing it 6 No implemented 70 Time since six sigma adoption Less than 1 year 4 Between 1 and 3 years 9 More than 3 years 12 Industrial sector Manufacturing 13 Service 12 Position of respondents in the company implementing six sigma Quality manager 3 Champion 2 Mater black belts 5 Black belts 8 Green Belts 2 Other 5 Projects implemented within the company Less than 10 6 Between 10 and 100 7 More than 100 12

Percentage 26.95 73.05 25.33 2.34 8.53


20 6 74 16 36 48 52 48 12 8 20 32 8 20 23 29 48

In contrast, none of 25 companies employs a bottom-up approach to select projects. In this approach, potential projects are proposed from the operational level of the corporation (Lynch and Soloy, 2003). Although this approach has the main advantage of identifying every improvement opportunity from the lower levels of the organisation (Harry and Schroeder, 2000), it has also been criticised in the literature (Klefsjo et al., 2001; Lynch and Soloy, 2003). For Klefsjo et al. (2001), six sigma methodology is a top-down, rather than bottom-up approach. In addition, adopting the bottom-top approach can result in lack of management commitment, selection of “pet” projects, an failure in incorporate both the external customer satisfaction and the business strategy (Lynch and Soloy, 2003). Nevertheless, 64 per cent indicated involving relevant process owners and heads of related departments in the selection process, but the final project selection is the responsibility of project selection committee (36 per cent), process owners or head of related department (36 per cent), quality managers (16 per cent), team members (16 per cent) and CEO (12 per cent). Identification of potential six sigma projects As is in any process, inputs are critical for a satisfactory outcome. The importance of selecting adequate sources and identifying the useful information to identify six sigma

Table I. Characteristics of the sample

TQM 18,5

518

projects is seen as key step in project selection. Adams et al. (2003) propose seven main sources for identification of potential six sigma projects, including customers, suppliers, employees, benchmarking, developments in technology, extension of other six sigma projects and waste. In this survey, respondents were asked whether they identified projects based on this classification. Six sigma projects often begin with the determination of customer requirements and it is essential to set project goals based on reducing the gap between the company’s deliverables such as quality, delivery time, reliability and customer expectations. The understanding of markets, operations, measures used and creativity to maximise value and performance are the core elements of six sigma approach (Pande et al., 2000). Consequently, the “voice of customer” (VOC) should be used to identify potential six sigma projects (Martens, 2001; Johnson, 2002; Man, 2002; Starbord, 2002). During this survey companies were asked if they identify projects from customer requirements. About 60 per cent of the companies identify potential projects from their customers. This result shows the alignment with the thinking that six sigma should internalise customers need into improvement projects (Pande et al., 2000). Of the surveyed companies implementing six sigma, 60 per cent identify potential six sigma projects from their employees. Voice from employees or internal customers can sometimes identify fundamental issues rather than from top management. The top management view of the organisation has its advantages. However, it suffers from the disadvantage of not being able to recognize the details of operational problems (Adams et al., 2003). Identifying projects from employees also has the advantage of selecting areas of opportunities which can improve quality in a short period of time. According to Adams et al. (2003), it is not unusual for a project team to find new areas of improvement after the completion of a six sigma project. Nearly, half of companies surveyed have reported finding potential six sigma projects from the extension of other projects. In this survey, 24 per cent of respondents identify projects from their suppliers. Suppliers play an important role in the quality of products and services, for Crosby (1979) suppliers account for 50 per cent of product-related quality problems. Other source of identifying six sigma projects is through the comparison of the organisation’s performance to that of world-class organisations, in order to investigate the adoption of new methods, technology and processes using six sigma (Adams et al., 2003). Benchmarking is used as a tool to drive performance of the company in all aspects of doing business In this survey, 44 per cent of the companies surveyed indicate using benchmarking to identify potential projects. Another source of potential projects is new developments in science, technology, and applications. However, only five of the twenty five companies identify six sigma projects from new developments in technology. Waste and quality are closely linked. By reducing wasteful practices such as re-work, extra inspection, defects and all the activities associated with not creating value, quality and productivity will improve. Accordingly, for Adams et al. (2003), activities that do not add value for the customer can be regarded as poor quality and six sigma can be employed to reduce waste. The results indicate that 32 per cent of the companies identify six sigma projects by detecting waste which can be reduced.

Tools used to identify potential six sigma projects Six Sigma teams employ different tools to identify potential projects from several sources, i.e. customers, waste, employees, suppliers, technology or extension of projects. Respondents were asked which tools they six sigma currently employ to this end. The majority of them (76 per cent) use brainstorming (Figure 1). Critical-to-quality (CTQ) tree, focus group, interview are employed by around one third of the surveyed companies. Customer visits, quality function deployment (QFD), Kano analysis, surveys are used for 20 to 30 per cent of surveyed companies. A small number of respondents implement value stream mapping, balance scorecard and Hoshin Kanri as an aid in the identification of projects. It was also noticed that most of the companies, 80 per cent, employ more than one tool to identify potential projects.


Criteria for six sigma project selection Effective project selection is based on identifying the projects that best match the current needs, capabilities and objectives of organisations (Pande et al., 2000). Different authors have proposed measurements, rules and standards that guide the six sigma project selection in the form of generic criteria. During this survey the criteria found in the literature were grouped into six main criteria as is shown in Table II. Respondents were asked to rank the six critical criteria for six sigma project selection according to Likert nine point scale (1 ¼ not important, . . . , 5 ¼ relatively important, . . . , 9 ¼ very important). The Cronbach’s a test was carried out to determine the level of internal reliability for a set of questions related to the criteria for project selection. Generally, a Cronbach’s a factor of 0.60 or higher is though to indicate an acceptance level of internal consistency (Black and Porter, 1996). All the criteria in this survey have an a coefficient above 0.60, showing a good internal reliability.

Figure 1. Tools and methods used to identify potential projects

Table II. Criteria for selection of six sigma projects

Customer impact Financial impact Top management commitment Measurable and feasible Learning and growth Connected to business strategy and core competence p

p

p

Pande et al. (2000) p p p p p

Harry and Schroeder (2000) p p

p

p

p

Snee (2001)

p

p

p

Goldstein Breyfogle et al. (2001) (2001) p p p

p

p

Pyzdek (2000, 2003) p p

p

Lynch and Soloy (2003) p p

520

Critical criteria

p

p

Antony (2004) p p

TQM 18,5

The scores of the criteria were averaged to determine the importance of each criterion in the project selection process. It can be seen from Figure 2 that four criteria, connected to business strategy, customers, finance and top management commitment, have a mean score higher than the important level of seven according to the scale employed. This is aligned with previous studies of critical success factors for six sigma implementation, where customer focus, linkage to business strategy, top management commitment and financial benefits are considered as essential factors for the successful implementation of six sigma (Ban˜uelas and Antony, 2002; Antony, 2004). The results also revealed that companies who have been implementing six sigma for more than six months tend to prioritise differently the criteria to select projects than those companies who embarked on six sigma for less than six months, as shown in Figure 3. In order to test if the differences between these groups of companies are statistical significant, analysis of variance (ANOVA) was conducted. As a result, it was concluded criteria connected to business strategy and core competency and learning and growth, are statistically significant (P , 0.05). Thus, it can be said that companies implementing six sigma for a short period of time tend to put less emphasis in learning and growth and the linkage between projects and business strategy. Instead, these companies tend to base the project selection on financial benefits and the measurability and feasibility of the projects. This can be attributed to the fact that the first projects


Figure 2. Scores on each six key criteria for six sigma project selection

TQM 18,5

522

Figure 3. Progression of perception on key criteria for six sigma project selection

tend to be pilot projects, which are characterised by initial or small-scale effort designed to test the applicability of six sigma. Pilot projects are usually undertaken with the intention of replicating or widening the scale of implementation at a later stage or further projects. In addition, they tend to focus on quick wins with a high probability of success. The selection of six sigma projects is considered a multi-criteria decision where most of the information relevant to the problem is complex and conflicting in nature. Selection criteria need to be prioritised so that those that are most critical to the overall success of the organisation will have the most impact on the project selection. Sometimes, a particular criterion is a useful gauge of how well a project will deliver several outcomes. Prioritisation of potential six sigma projects To help practitioners to deal with the complexity of the selection of six sigma projects, different authors have proposed different techniques. These techniques aim at organising and synthesising information in a manner that leads to the optimisation of a multiple and conflicting criteria to be handled at the same time over a set of feasible projects. These approaches seek to take explicit account of multiple criteria in helping individuals or groups explore decisions that matter and provide a focus to sharpen up discussion and balance and challenge intuition, however, it does not replace judgments or experience. Accordingly, many six sigma authors have proposed one or several tools that can be used into project selection, as shown in Table III.

Respondents were asked to select the tools used for project prioritisation out of eight tools identified in the literature. The results are shown in Figure 4. The most used tools are cost-benefit analysis, Pareto chart, and cause-effect matrix. The rest of them such of Pareto priority index (PPI), un-weighted scoring models, theory of constrains (TOC) and non-numerical models, are adopted by 12 to 16 per cent of respondents. Analytic hierarchy process (AHP) is used only by 8 per cent of companies. The results also indicate that more than 70 per cent of the companies that answered the questionnaire employ more than two tools for prioritising projects.


Post-project evaluation Post-project evaluation is beneficial to six sigma due to four main reasons (Adams et al., 2003): save time for next six sigma projects, identification of new projects, share the Author

Proposed methods or tools to prioritise six sigma projects

Larson (2003) De Feo and Barnard (2004)

Pareto analysis Reviewing data on potential projects against specific criteria for project selection six sigma Project ranking matrix Project selection matrix QFD Project assessment matrix PPI, AHP, QFD, TOC

Adams et al. (2003) Kelly (2002) Pande et al. (2002) Breyfogle et al. (2001) Pyzdek (2000, 2003)

Table III. Methods to prioritise six sigma projects

Figure 4. Tools and methods to prioritise six sigma projects

TQM 18,5

524

success and gain project experience. Accordingly, in this survey, 96 per cent of the companies that answered the questionnaire and are implementing six sigma have fully or partially applied post-project evaluations. A key part of post project evaluation is the establishment of metrics to monitor the project against the criteria used to select them in the first place. Over half of the organisations that answered the questionnaire use net cost savings, defects per million opportunities (DPMO), cost of poor quality (COPQ) and cycle time as main metrics to evaluate and monitor project success, refer to Figure 5. These metrics are aligned with the criteria to select projects, i.e. customer and financial focus. Learning and design effectiveness are embraced lower than 10 per cent of the companies implementing six sigma, which aligns with the criteria regarded as less important. The results also show that manufacturing companies put more emphasis on CTQ’s such as Scrape rate, FTY, COPQ, or capability index, whereas service-based companies due to their intrinsic characteristics put more emphasis on critical-to-service (CTS’s) such as cycle time. Nevertheless, manufacturing and service organisations tend to adopt net cost saving as the main metric used to evaluate six sigma projects. On the other hand, metrics such as employees learning and design effectiveness are adopted by a small number of companies neither in manufacturing sector or service sector. Conclusions In the quality field projects are often perceived as a way to breakthrough performance. Juran and Gyrna (1970) state that breakthroughs are achieved project by project, and

Figure 5. Metrics used to evaluate six sigma projects

in no other way. Accordingly, six sigma is a statistical oriented project driven approach to process and product quality improvement. Since, projects are the means by which six sigma converts quality improvements into bottom-line financial benefits, project selection is seen as a key to success. A national UK survey was carried out aimed at investigating the current status of the selection of six sigma projects and identifying the main criteria used for project selection. The results of this survey indicate that: . Most of the companies that answered the questionnaire adopt a hybrid, top-bottom and bottom-up, approach for the identification of six sigma projects. . The main sources to identify six sigma projects are customers (60 per cent), employees (60 per cent), extension of other projects (48 per cent), benchmarking (44 per cent), waste (32 per cent), suppliers (24 per cent), and inspired by developments on technology (20 per cent). . Most of the companies (80 per cent) employ more than one tool to identify potential projects, including brainstorming, CTQ tree, focus group, interviews, customer visits, QFD and Kano analysis, among others. . It was found that the main criteria to select six sigma projects are customer satisfaction, financial benefits, linkage to business strategy and top management commitment. Companies implementing six sigma for short period of time tend to put less emphasis in the linkage between projects and business strategy and in learning and growth. . The most used tools to prioritise projects are cost-benefit analysis, Pareto chart, and cause-effect matrix. . 96 per cent of the companies that answered the questionnaire applied post-project evaluations. This study was carried out with some boundaries such as the number of companies, available resources and it is also limited to UK organsations. An important limitation of this paper is the respondent rate, however, the response rate is similar to other surveys on six sigma. For example, a survey on the benefits of six sigma carried out by Dusharme (2006) had a response rate of 10 per cent. Antony et al. (2005) had a response rate of around 14 per cent for a survey on the implementation of six sigma in SMEs. Nevertheless, it is recommended that further empirical studies should use a larger sample sizes and greater geographical diversity in order to validate the results of this study. Another area of future research should be to expand on this study and include more variables affecting the selection of six sigma projects. References Adams, C., Gupta, P. and Wilson, C. (2003), Six Sigma Deployment, Butterworth-Heinemann, Oxford. Antony, J. (2004), “Six sigma in the UK service organisations: results from a pilot survey”, Managerial Auditing Journal, Vol. 19 No. 8, pp. 1006-12. Antony, J., Kumar, M. and Madu, C. (2005), “Six sigma in small- and medium-sized UK manufacturing enterprises: some empirical observations”, International Journal of Quality & Reliability Management, Vol. 22 No. 8, pp. 860-74.


TQM 18,5

526

Ban˜uelas, R. and Antony, J. (2002), “Critical success factors for the successful implementation of six sigma projects in organisations”, The TQM Magazine, Vol. 14 No. 2, pp. 92-9. Black, S. and Porter, L. (1996), “Identification of the critical factors of TQM”, Decision Science, Vol. 27 No. 1, pp. 1-21. Breyfogle, F., Cupello, J. and Meadws, B. (2001), Managing Six Sigma, Wiley Inter-science, New York, NY. Bryman, A. (2004), Social Research Methods, Oxford University Press, Oxford. Crosby, P. (1979), Quality is Free, McGraw-Hill, New York, NY. Davis, A. (2003), “Six sigma for small companies”, Quality, Vol. 42 No. 11, p. 20. De Feo, J. and Barnard, W. (2004), “Juran institute’s six sigma breakthrough and beyond”, Quality Performance Methods, McGraw-Hill, New York, NY. Dusharme, D. (2006), “Survey: six sigma packs a punch”, Quality Digest, available at: http:// qualitydigest.com/nov03/articles/01_article.shtml (accessed 14 February). Eckes, G. (2001), The Six Sigma Revolution, Wiley, New York, NY. Ford (2005), available at: www.ford.com (accessed 23 March). Gillham, W. (2000), Developing a Questionnaire, Continuum, London. Goldstein, D. (2001), “Six sigma program success factors”, Six Sigma Forum Magazine, Vol. 1 No. 1. Harry, M. and Schroeder, R. (2000), Six Sigma: The Breakthrough Management Strategy Revolutionising the World’s Top Corporations, Currency, New York, NY. Ingle, S. and Roe, W. (2001), “Six sigma black belt implementation”, TQM Magazine, Vol. 13 No. 4, pp. 273-80. Johnson, A. (2002), “Six sigma in R&D”, Research Technology Management, Vol. 45 No. 2, pp. 12-6. Juran, J. and Gyrna, F. (1970), Quality Planning and Analysis, McGraw-Hill, New York, NY. Kelly, M. (2002), “Three steps to project selection”, ASQ Six Sigma Forum Magazine, Vol. 2 No. 1, pp. 29-33. Klefsjo, B., Wiklund, H. and Edgeman, R. (2001), “Six sigma seen as a methodology for total quality management”, Measuring Business Excellence, Vol. 5 No. 1, p. 31. Larson, A. (2003), Demystifying Six Sigma, American Management Association, New York, NY. Lynch, D. and Soloy, B. (2003), “Improving the effectiveness of six sigma project champions”, paper presented at ASQ’s Six Sigma Conference 2003. Man, J. (2002), “Six sigma and lifelong learning”, Work Study, Vol. 51 Nos 4/5, pp. 197-201. Martens, S. (2001), “Operationally deploying six sigma”, ASQ’s Annual Quality Congress Proceedings, pp. 751-5. Meredith, J. and Mantel, S. (2003), Project Management: A Managerial Approach, Wiley, New York, NY. Pande, P., Neuman, R. and Cavanagh, R. (2000), The Six Sigma Way: How GE, Motorola and Other Top Companies are Honing their Performance, McGraw-Hill, New York, NY. Pyzdek, T. (2000), “Selecting six sigma projects”, Quality Digest, available at: www.qualitydigest. com/sept00/html/sixsigma.html (accessed 16 March 2005). Pyzdek, T. (2003), The Six Sigma Project Planner, McGraw-Hill, New York, NY.

Snee, R. (2001), “Dealing with the Achilles’ heel of six sigma initiatives”, Quality Progress, Vol. 34 No. 3, pp. 66-9. Starbord, D. (2002), “Business excellence: six sigma as a management system: a Dmaic approach to improving six sigma management processes”, Quality Congress. ASQ’s Annual Quality Congress Proceedings, pp. 47-55. Corresponding author Ricardo Banuelas can be contacted at: banuelas@yahoo.com




TQM 18,5

Relationships of TQM practices and employees’ propensity to remain: an empirical case study

528

Keng Boon Ooi Perak Institute of Technology, Ipoh, Malaysia

Arumugam Veeri School of Management, University of Science, Penang, Malaysia, and

Loke Kim Yin and Lorraine Subathra Vellapan Carsem (m) SDN. BHD, Ipoh, Malaysia Abstract Purpose – The main purpose of this study is to explore the relationship between total quality management (TQM) practices and employees’ propensity to remain within a large Malaysian semiconductor packaging organization. Despite extensive research on TQM practices, none examines this scope of investigative study. Therefore, the proposed model was developed with the intention of examining this relationship. Design/methodology/approach – Original research using self-completed questionnaires, distributed to all staff within this organization is thoroughly reported. The study sample consisted of 230 employees, resulting in a response rate of 76.6 percent. A questionnaire developed by Udo, Guimaraes and Igbaria was adapted for ascertaining the level of employees’ propensity to remain. Data were analyzed by employing correlation and simple linear regression analysis. Findings – The results revealed that customer focus, organizational trust, organizational communication, employee involvement and empowerment are positively associated with employees’ propensity to remain. It is also found that where organizational trust was perceived as a dominant TQM practice; improvements in employees’ propensity to remain levels were significant. Further, the result of the simple linear regression analysis supports the proposed model based on the empirically validated soft TQM instruments, which are reliable and valid. Originality/value – The study contributes in advancing the TQM literature to a better understanding of the influence of TQM on the propensity to remain among employees within a major semiconductor sector. Keywords Total quality management, Malaysia, Electronics industry Paper type Case study


Introduction Total quality management (TQM) has been an important theme in management and business research for the past few decades due to its potential to affect a range of organizationally and individually desired outcomes. Research has confirmed that TQM programmes have produced an impressive list of claimed benefits and continue to accumulate converts to this philosophy (Guimaraes, 1997). Many firms concluded that the effective implementation of TQM can produce improvements in the area of competitive abilities and provide strategic advances in the marketplace and return on investment (Cole, 1992; Philips et al., 1983), lower manufacturing costs and improved productivity (Garvin, 1983) and improved the area of strategic performance (Zhang, 1999).

Semiconductor packaging manufacturing is the spotlight of the global manufacturing industries and is considered to be one of the major contributors to the global economy, quality management is strategically and tactically important for gaining a competitive advantage (Yang et al., 2003). Despite the considerable body of TQM literature that has evolved to examine the relationship between TQM and employees’ propensity to remain in various countries as well as industries (Guimaraes, 1996, 1997; Garner and Carlopio, 1996; Boselie and Wiele, 2002; Sommer and Merritt, 1994), there is no existing literature that recognizes TQM studies within the context of the Malaysian semiconductor packaging industry, particularly on how the propensity to remain with (or leave) the organization amongst employees were affected by TQM practices that have otherwise attracted considerable attention in TQM literature. Since, Malaysia is one of the major suppliers of global semiconductor products, its quality management practices have a global impact (Yang et al., 2003). Moreover, the Semiconductor packaging industry is unique because the products are built strictly compliant to customers’ specification and quality requirements. It differs from other industries in terms of their organizational structures, responses to the environment, managerial styles and the ways in which they compete against other firms. Also, the semiconductor packaging industry tried to find a good person-organization (p-o) fit by making certain that its employees embraced the culture. This reduced conflict and costs (i.e. rehiring, time loss, etc) for these organizations while on the other hand, employees themselves were happier at work because they felt a sense of belonging to a team that shared organizational values (Dunham, 2003). The importance of the TQM culture is enhanced through its impact on employee morale and work attitudes (Dose, 1997). Consequently, employees’ propensity to remain is likely to be influenced by aspects of TQM. In order to bridge the gap and provide organizations with practical assistance in dealing with this issue, this research uses a sample of a major organization within the Malaysian semiconductor packaging industry to examine, whether the application of TQM practices result in an improvement of employees’ working conditions that inevitably contributes towards their propensity to remain. Many commentators argue that in order to be fully successful and self-sustaining TQM requires an extensive refashioning of “softer” practices (Schonberger, 1994; Dale et al., 1994), whose elements consist of essentially dimensions of human resource management (HRM) (Wilkinson et al., 1991; Wilkinson, 1992; Dale et al., 1994). Powell (1995, p. 15) concluded that “organizations that acquire the soft elements of TQM can outperform competitors without the accompanying TQM ideology.” In previous TQM literatures there seems to be a general understanding regarding the type of TQM activities that contribute to the development of “business excellence” and dealing with people. Many of the basic TQM elements dealing with people have been examined in previous studies such as: teamwork, reward and recognition, customer focus, organizational trust, extensive training, high level of communication, management commitment at all levels, employee involvement, empowerment and organizational culture (Guimaraes, 1996, 1997; Noorliza and Zainal, 2000; Noorliza, 1999; Dale, 1999; Boselie and Wiele, 2002; Oakland and Oakland, 1998, 2001; Morrow, 1997). This study contributes to the literature, by attempting to satisfy the clear need for an analytical study that examines recognizable soft elements of TQM, and linking TQM and employees’ propensity to remain, using appropriate statistical methods (i.e. data analyses were used based on both descriptive and inferential methods)

Relationships of TQM practices

529

TQM 18,5

530

applied in a major Malaysian semiconductor packaging organization selected. Based on an extensive study of previous research on TQM, five core elements of soft TQM have been identified as key practices, which support an organization’s business strategy towards the improvement of employees’ propensity to remain. These elements of TQM are: employee involvement, organizational trust, organizational communication, customer focus and empowerment. Dale (1999) further enumerates that the above key practices are relevant to organizational excellence and people-oriented aspects from a TQM’s perspective. In view of the absence of such research on these relationships, therefore, this paper reports the results of a survey that was designed to address two research questions: RQ1. What essential TQM principles should be developed that would prove to be an effective guide in the measurement of employees’ propensity to remain? RQ2. Does TQM affect employees’ propensity to remain? This research is particularly important, and seeks to explore the degree of impact, in which the influence of TQM practices poses to benefit the organization’s employees, and thus measuring its impact on propensity to remain, apart from identifying problem areas and, respectively, their possible remedies and prominent improvements The purpose of this investigation is two-fold. Firstly, to identify a set of soft TQM principles that would prove to be an effective guide in the measurement of employees’ propensity to remain. Secondly, it is to explore the relationship between TQM practices and employees’ propensity to remain within the organization. In the next section we provide a review of the literature on TQM and employees’ propensity to remain. This leads to the development of hypothesis to be tested in this study. We then provide further details concerning the data used in this study, including some descriptive information on our sample of Malaysian semiconductor packaging organization. The fifth section provides a discussion of the results from analyzing this data, and is followed by our conclusions, implications and suggestions for future research. Review of literature TQM has been widely implemented in various firms worldwide. To date, literature examining the relationship between the institutionalization of TQM and employees’ turnover intentions has been mainly anecdotal (Morrow, 1997). TQM has been illustrated by several studies and can be credited to the decrease in staff turnover rates (Guimaraes, 1997, 1996; Boselie and Wiele, 2002) and is found to have an important influence on an individual’s affective reactions (especially turnover intentions) to organizational life within a TQM environment. Empirical reviews of TQM that affect employees’ turnover intentions are discussed in this section. For example, Gardner and Carlopio (1996) conducted a survey on employees’ affective reactions (i.e. job satisfaction, commitment, and turnover intention) towards organizational quality efforts. The respondents of the survey consist of 228 employees of a large bank in Australia. The results indicated that employees’ participation of organizational quality efforts would be significantly related to employees’ affective reactions, with those perceiving a greater degree awareness of organizational quality efforts seen exhibiting the more positive reactions, thus, increasing intention to stay within the organization.

Boselie and Wiele (2002) conducted a study, in year 2000 with the support of International Survey Research (London, UK) on employees’ perception of TQM/HRM and the effect on overall satisfaction and intention to leave in the Netherlands. This survey led to a response group of approximately 2,300 records (response rate was 50 percent). The analysis reveals that a positive perception of individual employees on the TQM/HRM concept leads to a higher level of satisfaction and thus, reducing intention to leave the organization. The finding of both Gardner and Carlopio (1996) and Boselie and Wiele (2002) are supported by Guimaraes (1996) when he conducted a study on TQM’s impact on employees’ attitudes. The results show that intention to stay with the company had increased. Therefore, the implementation of TQM has changed the working environment; thus, employees’ attitudes have been improved. As a result, employees may increase their levels of satisfactions and deliberate willfulness to stay with the organization. Another study conducted by Sommer and Merritt (1994) was to measure the impact of TQM intervention on workplace attitudes in a health-care organization. The results indicated that turnover intentions during the 12th month pre-intervention period which was initially 40.27 percent, was reduced to 30.37 percent for the year following the first year of TQM training. Another significant impact of the TQM programme involved the improvement of employees’ attitudes on several dimensions of the work group climate. Evidently, the implementations of TQM have a positive impact on employees’ intention to stay within the organization. The above review indicates that TQM practices have a significant relationship on employees’ propensity to remain. Given that there is a limited amount of rigorous research focusing on the discussion, this study chooses to examine the relationship between TQM and employees’ propensity to remain specifically within a major Malaysian semiconductor packaging organization. The researcher purports that the implementation of TQM practices in such organization is able to yield better and long-lasting results on this area of prominent impact. Hypothesis development Based on the extensive study of previous research, it would, therefore, suggest that TQM improves employees’ propensity to remain. As such, the following hypothesis is proposed: H1. TQM practices such as employee involvement, empowerment, organizational communication, customer focus and organizational trust are positively associated with employees’ propensity to remain within the organization. Methodology In this section, we discuss sample and data collection procedures and operational measures of variables used in the study as well as the statistical tests used to evaluate the hypothesis. Sample and procedures Data were collected from employees within various departments of a large award-winning TQM semiconductor packaging organization located in the state of


531

TQM 18,5

532

Perak, Malaysia. The company was selected and viewed as the best and most valid representation of the entire semiconductor packaging industry in Malaysia for the exploratory survey in this study for two main reasons. Firstly, the company is Malaysia’s largest foundry representing its sales revenue, ranking among the top ten in the world. Secondly, the company is also the second-largest semiconductor packaging player in the world in terms of volume production, responsible for some 5.2 billion units in 2004 (Khadpe, 2005). As this firm is considered to be one of the major contributors to the Malaysian economy with such merits, this research chose to examined the degree of application of TQM elements, and then investigate the relationship between TQM implementation and employees’ propensity to remain within a Malaysian semiconductor packaging organization’s context. The survey was conducted between the months of February till June 2004. The questionnaire survey was the main form of data collection. The questionnaires were distributed to all employees from different job levels and functions within the organization. They were distributed through an officer/coordinator from the human resource department within the organization. A covering letter explaining the purpose of this study was attached together, assuring them of the confidentiality of their responses, and instructing them to complete the questions, seal and return the completed questionnaires using the attached envelope. Out of the 300 questionnaires distributed to employees in this organization, 230 usable questionnaires were returned, yielding a response rate of 76.6 percent, which is considered acceptable. There were 152 female and 78 male respondents. The age range of the sample was from 21 to 45 years with a mean of 33 years. Out of 230 respondents, 82 (over 35 percent) had achieved at least a high school qualification. Employees from four types of occupational groups are represented in the sample (i.e. operators, n ¼ 134; staff, n ¼ 69; executives, n ¼ 21; managers, n ¼ 6). The operator positions included resource and production groups personnel. The staff positions included administrative personnel and general clerks. The executive classification included engineers, supervisors, accountants and programmers. The managerial group included middle and senior managers responsible for a single section or several work areas. Variable measurements Independent variables: TQM practices. This measure is based on the five dimensions of TQM developed by Zhang (1999) and Lau and Idris (2001). The five dimensions, which consist of 20 items, namely organizational communication, customer focus, employee involvement, organizational trust and empowerment. Sample items include “Top management delegates their authority to employees in decision-making process” (empowerment), “Employees are encouraged to fix problems they have encountered” (employee involvement), “The company’s employees’ communication is effective in communicating things that are relevant to them” (organizational communication), “The company always conducts market research in order to collect suggestions for improving its products” (customer focus), and “Openness, honesty and constructive feedback are highly valued and demonstrated as organizational traits” (organizational trust). Responses to these items were made on a five-point Likert format ranged from 1 – strongly disagree to 5 – strongly agree. Dependent variable: propensity to remain. Propensity to remain was measured by a single item adapted from Udo et al. (1997). A sample item include:

Given that you have significant knowledge regarding the company in which you are currently employed and the type of work you enjoy, what will an approximately duration of your tenure be with your company.


The response options were anchored on a time-linked five-point Likert scale: (1) ¼ 1 year or less; (2) ¼ between 1 and 3 years; (3) ¼ between 3 and 5 years; (4) ¼ between 5 and 10 years and (5) ¼ 10 years or more or until retirement. A single-item measure was considered to be more robust and a more inclusive construct than a multiple-item measure (Nagy, 2002). However, internal consistency reliability could not be calculated for a single item measured (Wanous et al., 1997). The item indicates that high scores reflected stronger propensity to remain within the organization.

533

Analysis of data The statistical computer program used for the questionnaires data analysis was SPSS for Windows Version 11.0. Correlation studies were used to determine the relationship between the dependent and independent variables. TQM practices were regressed against employees’ propensity to remain. The simple linear regression analysis was used to further explain the significance of the independent and dependent variables. Results of the survey Factor analysis and scale reliabilities A principal component factor analysis with varimax rotation was conducted to validate the underlying structure of TQM practices (Table I). In interpreting the factor, only a loading of 0.5 or greater on the factor and 0.35 or lower on the other factors are considered (Igbaria et al., 1995). Results of the varimax rotated analysis indicated the existence of five significant factors with eigenvalues (i.e. 2.716) greater than one that explained 54.33 percent of the variance. The KMO measure of sampling adequacy value for the item was 0.851 indicating sufficient intercorrelations with the Bartlett’s Test of Spehericity was also found to be significant (x 2 ¼ 467.31, p , 0.001). These factors were namely employee involvement (4 items), customer focus (3 items), organizational communication (3 items), organizational trust (4 items), and empowerment (6 items), respectively. Thus, a model with five factors may be adequate to represent the data because the result of the analysis can be considered satisfactory since they do not exceed 60 per cent of the explained variance recommended in social sciences (Hair et al., 1998). Thus, we have further evidence of the factorability of the items. The results of the factor analysis are summarizes in Table I. The reliability of the questionnaire was tested according to Cronbach a measurements. The reliability coefficient (a) of each element of TQM was as follows: employee involvement (68 per cent); customer focus (70 per cent); organizational communication (69 per cent), organizational trust (83 per cent) and empowerment (80 per cent). The reliability coefficients of all the five elements of TQM were above 0.60, which concurs with the suggestion made by Nunnally (1967, p. 226). Descriptive statistics analysis Table II indicates that employees’ within the Malaysian semiconductor packaging organization perceived empowerment (with the highest mean scores, i.e. M ¼ 3.91, SD ¼ 0.53) to be the most dominant TQM implementation practice within their firms and evident to a considerable extent, followed by employee involvement

Table I. Factor analysis and scale reliabilities – independent variables (N ¼ 230) 0.419-0.851 0.531-0.945 0.700-0.795 0.583-0.678 0.520-0.761 –

4 3 4 6 3 1

Factor loading

–

0.851

KMO

–

2.716

Eigenvalue

–

54.33 percent

Variance explained

–

0.68 0.70 0.83 0.80 0.69

Reliability

Note: Factor analysis and internal consistency for the reliability test on propensity to remain could not be calculated because it stands a single item for measurement Sources: Gray et al. (2003); Wanous et al. (1997)

a

Independent variables Employee involvement Customer focus Organizational trust Empowerment Organizational communication Dependent variable Propensity to remaina

Items

534

Measure

TQM 18,5

(M ¼ 3.90, SD ¼ 0.54), organizational communication (M ¼ 3.87, SD ¼ 0.53), and organizational trust (M ¼ 3.73, SD ¼ 0.61), which were all rated as moderate practices of their firm. Customer focus (M ¼ 3.69, SD ¼ 0.60), with the lowest mean score was perceived on the overall as least practiced within this organization. Meanwhile, the degree of TQM implementation practices on employees’ propensity to remain in this organization was largely positive. The standard deviations were quite high, indicating the dispersion in a widely-spread distribution. This means that the effects of TQM practices on employees’ propensity to remain are an approximation to a normal distribution. This also indicates that respondents were in favor of employees’ propensity to remain.


535

Correlation analysis: relationships between the variables The correlation matrix in Table II further indicates that TQM practices were positively and moderately correlated with employees’ propensity to remain. The correlation coefficients between the independent variables (i.e. TQM practices) and the dependent variable (i.e. propensity to remain) were less than 0.9, indicating that the data was not affected by a collinearity problem (Hair et al., 1998). These correlations are also further evidence of validity and reliability of measurement scales used in this research (Barclay et al., 1995; Hair et al., 1998). There was a significant positive relationship between organizational trust and propensity to remain (r ¼ 0.21, n ¼ 230, p , 0.01). The positively moderate correlation were for empowerment and propensity to remain (r ¼ 0.20, n ¼ 230, p , 0.01), employee involvement and propensity to remain (r ¼ 0.19, n ¼ 230, p , 0.01) and between customer focus and propensity to remain (r ¼ 0.18, n ¼ 230, p , 0.01). The weakest correlation was for organizational communication and propensity to remain (r ¼ 0.17, n ¼ 230, p , 0.01). In other words, the results indicate that the most important TQM practice on employees’ propensity to remain was organizational trust (i.e. with the highest scores of correlation), which goes to prove that organizational trust was perceived as a dominant TQM practice; improvements in employees’ propensity to remain levels were significant. The findings displayed that the respondents who perceived a greater awareness of TQM practices exhibiting the more positive reactions in favour of propensity to remain. Thus, H1 was supported. Simple linear regression analysis Simple linear regression analysis was used to further examine the research hypothesis and the significance of the model. This analysis was undertaken to

Employee involvement Empowerment Customer focus Organizational trust Organizational communication Propensity to remain

Mean

SD

1

2

3.90 3.91 3.69 3.73 3.87 4.14

0.54 0.60 0.61 0.53 0.53 1.01

0.49 * * 0.56 * * 0.56 * * 0.48 * * 0.19 * *

0.55 * * 0.60 * * 0.38 * * 0.20 * *

Note: * *Correlation is significant at p , 0.01 level (2-tailed)

3

0.68 * * 0.51 * * 0.18 * *

4

0.61 * * 0.21 * *

5

0.17 * *

Table II. Means, standard deviations, and correlations of tqm practices and employees’ propensity to remain (N ¼ 230)

TQM 18,5

536

better understand the relative impact of TQM practices on employees’ propensity to remain. The summary of the result analysis is depicted in Table III. As noted in Table III, H1 measures TQM practices and its association with employees’ propensity to remain. Regression analysis indicates that TQM practices explain 6 percent of the variance in employees’ propensity to remain which is significant. An examination of the t-values (i.e. t ¼ 3.806, p , 0.01) shows that TQM contribute to the prediction of propensity to remain. This shows that the significant t-value gives enough evidence to reject the null hypothesis. The results from simple linear regression indicate that there is a statistically significant relationship between TQM practices and employees’ propensity to remain. Thus, an overall hypothesis of an acceptable conclusion is, “TQM practices such as empowerment, employee involvement, organizational communication, organizational trust and customer focus are positively associated with employees’ propensity to remain within the organization.” Hence, H1 was supported. Discussion The overall objective of this study was to investigate the relationship between TQM practices and employees’ propensity to remain within a major Malaysian semiconductor packaging organization. The results of this study revealed that where organizational trust was perceived as a dominant TQM practice, there was a strong association with propensity to remain. This suggests that employees require support and trust, from executives and management teams, for more TQM practices. It is important that management practice empowerment and trust their employees’ capabilities to have control over their working lives. The results are consistent with previous research which found that reduction in employee turnover was one of the advantages of trust (Costigan et al., 1998; Mishra and Morrissey, 1990; Tan and Tan, 2000). However, the findings indicate the importance of customer focus, empowerment, employee involvement and organizational communication for predicting employees’ propensity to remain. For instance, customer focus was found to have a significance influence on employees’ propensity to remain. Focusing on delivering customer value in implementing TQM, encourage managers to make the best use of their people and resources in order to create product that customer value (Chapman and Al-Khawaldeh, 2002). The significant relationship between customer focus and employees’ propensity to remain indicate that management encouraged efforts and succeed to translate its commitment into this improvement practice (Boselie and Wiele, 2002). This may be due

Model

Table III. Simple linear regression analysis of tqm practices on employees’ propensity to remain (N ¼ 230)

Constant regression Overall TQM practices F R2 Adj. R 2

Un-standardized coefficients B 2.036 0.553

Note: * *Significant at the 0.01 (2-tailed)

Std. error 0.559 0.145 14.486 * * 0.060 0.056

Standardized coefficients b

t

Significant

0.244

3.646 3.806

0.000 0.000

to well established support relationship between employees and customers. This conclusion is consistent with TQM’s theory (Dale et al., 1997). The results indicate that organizational communication had a positive association with employees’ propensity to remain. The findings further indicate that organizational communication is a critical factor in organizations, for connecting employees and permitting organizations to function, as well as an essential element to the implementation of TQM (Gray and Laidlaw, 2002). When communication is opened and continuous in three directions; up, down and across, work processes and performance increases, thereby increasing employees’ propensity to remain. The current study is consistent with previous research, which found that organizational communication is important for improving intention to stay (Boselie and Wiele, 2002). Encouraging employees to generate new ideas and make decisions regarding process improvement results in increasing their propensity to remain. The findings highlight the importance of employee involvement, which was found to have a positive relationship with employees’ propensity to remain. The results also provide supporting evidence for the views of Gardner and Carlopio (1996), which found that employees’ participation with organizational quality efforts would be significantly related to employees affective reactions, with those perceiving a greater awareness of organizational quality efforts seen exhibiting the more positive reactions, thus, increasing intention to stay within the organization. Further, the result of simple linear regression analysis confirmed that propensity to remain variable was significantly related to perceptions of TQM practices and thus implementing TQM does payoff. The result of this regression analyses also supports the proposed model based on the empirically validated TQM implementation instruments, which are reliable and valid. This study also supports the findings from previous studies conducted by Guimaraes (1996) and Gardner and Carlopio (1996) which found that with TQM practices, on average, employees reported higher levels of propensity to remain within the organization. Thus, in terms of HRM goals and objectives, one is encouraged to think that TQM programmes have a positive influence as Guimaraes (1996) indicates. Limitations and future research The authors realize that there are some limitations, which must be considered for future research. The results gathered may generally be limited, although this study was the first one aimed at developing an instrument for measuring the relationship between TQM and employees’ propensity to remain within the context of a major Malaysian semiconductor packaging firm. In order to improve external validity of the instrument, additional studies would be needed, with increased sample sizes, geographical diversity, organization type, and so on. Secondly, the findings are based on the use of self-reported survey data, which may be affected by response biases. Thirdly, cross-sectional data analysis cannot confirm the direction of causality implied in our research model, so it is necessary to be cautious in conclusions regarding causality. For example, despite the significant relationship shown between soft TQM practices and employees’ propensity to remain, the cross-sectional nature of this research precludes any conclusion of causality between TQM practices and propensity to remain. Therefore, future studies may want to utilize other analytical methods such as multi-level data to determine the reciprocal relationship among the study variables.


537

TQM 18,5

538

Fourthly, it is also important that other major constructs related to the TQM implementation process (including degree of education and training, degree of teamwork, and level of top management commitment, degree of reward and recognition and level of organizational culture) should be added to the conceptual framework underlying this study. Finally, while the measure of propensity to remain with the organization was a single-item with no reliability statistic available and thus, future research may be beneficial, if more items and better measures are developed, in relation to this outcome variable. It is also proposed that future research be conducted in other types of organizations such as manufacturing and service using a similar approach. Furthermore, a wider range of employees’ affective reactions such as task characteristics, role ambiguity, role conflict, career satisfaction, job satisfaction, job involvement and others can be incorporated into a more comprehensive study, as this study chooses to cover only one type of employee attitude. Conclusion and implications In summary, the paper reports an exploratory investigation of the relationship between TQM practices and employees’ propensity to remain within a major Malaysian semiconductor packaging organization. As claimed by some authors (Guimaraes, 1996, 1997; Boselie and Wiele, 2002; Gardner and Carlopio, 1996), TQM does have significant effects on personnel attitudes towards their propensity to remain within the organization. The development of TQM practices should provide useful measures for investigating the relationship between TQM practices and propensity to remain particularly in relation to the Malaysian semiconductor packaging organization where studies are yet to be conducted. The findings are considered to have made a significant contribution in terms of creating awareness and understanding for the development of a theoretical base for application of soft TQM practices resulting in an improvement of employees’ working conditions that inevitably contribute towards their propensity to remain. The implications of this study can be divided into three categories: theoretical contribution, robustness of research methodology, and practical contribution. In terms of theoretical contribution, this study has extended previous research conducted in most western countries and provides great potential by advancing the TQM literature to a better understanding of the influence of TQM on the propensity to remain among employees in the Malaysian semiconductor contract manufacturing sector. With respect to the robustness of the research methodology, the survey questionnaire has achieved the validity and reliability standards, thus leading to greater accuracy of results. The findings contribute by using a major semiconductor contract manufacturing organization in Malaysia which proves to be useful as an example of a methodology that might be used to track the extent of TQM efforts on employees’ propensity to remain. This firm could use this instrument to do a pre-test baseline measurement, and then periodically re-administer it to identify changes associated with TQM efforts. Regarding practical contributions, given the direct influence of certain TQM practices on employees’ propensity to remain, the top management in the organization should conduct formal TQM programs for all new employees and provide their existing employees with continuous formal training program (on-the-job as well as off-the-job) in order to gain employees’ commitment and subsequently reduce their

turnover rate. Furthermore, the higher levels of propensity to remain in the organization may give this organization an advantage over other organizations in attracting and retaining employees in a very competitive environment. It is also found that organizational trust was the decisive factor in determining the success of the increased propensity to remain amongst employees within the organization. The implication is that organizations should focus firstly on organizational trust. Another lesson to be learned is that the other elements of TQM namely, employee involvement, customer focus, empowerment and organizational communication, were provider of long-term, infrastructural benefits necessary for the continued improvement over time, but with a less significant relationship with employees’ propensity to remain. References Barclay, D., Higgins, C. and Thompson, R. (1995), “The partial least square (PLS) approach to causal modeling: personal computer adoption and use as an illustration”, Technology Studies, Vol. 2 No. 2, pp. 285-309. Boselie, P. and Wiele, T.V.D. (2002), “Employee perceptions of HRM and TQM and the effects on satisfaction and intention to leave”, Managing Service Quality, Vol. 12 No. 3, pp. 165-72. Chapman, R. and Al-Khawaldeh, K. (2002), “Quality management worldwide: TQM and labour productivity in Jordanian industrial companies”, The TQM Magazine, Vol. 14 No. 4, pp. 248-62. Cole, R.E. (1992), “The quality revolution”, Production and Operations Management, Vol. 1 No. 1, pp. 118-20. Costigan, R.D., Ilter, S.S. and Berman, J.J. (1998), “A multi-dimensional study of trust in organizations”, Journal of Managerial Issues, Vol. 10, pp. 303-17. Dale, B.G., Boarden, R.J. and Lascelles, D.M. (1994), “Total quality management: an overview”, in Dale, B.G. (Ed.), Managing Quality, 2nd ed., Prenctice-Hall, London, pp. 1-40. Dale, B.G., Cooper, C.L. and Wilkinson, A. (1997), Managing Quality and Human Resources; A Guide to Continuous Improvement, Blackwell, Oxford. Dale, B.G. (1999), Managing Quality, 3rd ed., Blackwell, Oxford. Dose, J.J. (1997), “Work values: an integrative framework and illustrative application to organizational socialization”, Journal of Occupational & Organizational Psychology, Vol. 70, pp. 219-40. Dunham, R.B. (2003), Organizational Behavior: Six Sigma Enhancing General Electric’s Organizational Effectiveness, School of Business, University of Wisconsin, Madison, p. 1, 9, available at: http://instruction.bus.wisc.edu/obdemo/may%20not%20need_2/ General%20Electric.htm Gardner, D. and Carlopio, J. (1996), “Employee affective reactions to organizational quality efforts”, International Journal of Quality Science, Vol. 1 No. 3, pp. 39-49. Garvin, D.A. (1983), “Quality on the line”, Harvard Business Review, Vol. 61, pp. 64-75. Gray, J.H., Densten, I.L. and Sarros, J.C. (2003), “A matter of size: does organizational culture predicts satisfaction in small organizations?”, working paper, Faculty of Business and Economics, Monash University, Caulfield East. Gray, J. and Laidlaw, H. (2002), “Part-time employment and communication satisfaction in an Australian retail organization”, Employee Relations, Vol. 24 No. 2, pp. 211-28. Guimaraes, T. (1996), “TQM impact on employee attitude”, The TQM Magazine, Vol. 8 No. 5, pp. 20-5.


539

TQM 18,5

540

Guimaraes, T. (1997), “Assessing employee turnover intentions before/after TQM”, International Journal of Quality & Reliability Management, Vol. 14 No. 1, pp. 46-63. Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, Prentice-Hall, Englewood Cliffs, NJ. Igbaria, M., Iivari, J. and Maragahh, H. (1995), “Why do individuals use computer technology? A Finnish case study”, Information & Management, Vol. 5, pp. 227-38. Khadpe, S. (2005), “Outsourced semiconductor assembly and test: preparing for the next boom cycle, 2006-2008”, Chip Scale Review Magazine, April. Lau, H.C. and Idris, M.A. (2001), “Research and concepts: the soft foundation of the critical success factors on TQM implementation in Malaysia”, The TQM Magazine, Vol. 13 No. 1, pp. 51-60. Mishra, J. and Morrissey, M.A. (1990), “Trust in employee/employer relationships: a survey of West Michigan managers”, Public Personnel Management, Vol. 19, pp. 443-85. Morrow, P.C. (1997), “The measurement of TQM principles and work-related outcomes”, Journal of Organizational Behaviors, Vol. 18, pp. 363-96. Nagy, M.S. (2002), “Using a single-item approach to measure facet job satisfaction”, Journal of Occupational & Organizational Psychology, Vol. 75 No. 1, pp. 77-87. Noorliza, K. (1999), “The impact of TQM practice on employees’ work-related attitudes”, MBA Unpublished Research Report, University Science Malaysia. Noorliza, K. and Zainal, A.A. (2000), “Quality practices that pay: empowerment and teamwork”, Malaysian Management Review, Vol. 35 No. 2, pp. 66-76. Nunnally, J. (1967), Psychometric Theory, McGraw-Hill, Inc., New York, NY. Oakland, J.S. and Oakland, S. (1998), “The links between people management, customer satisfaction and business results”, Total Quality Management, Vol. 9 Nos 4/5, pp. 184-90. Oakland, J.S. and Oakland, S. (2001), “Current people management activities in world-class organizations”, Total Quality Management, Vol. 12 No. 6, p. 773. Philips, L.W., Chang, D.R. and Buzzell, R.D. (1983), “Product quality, cost position business performance: a test of some key hypotheses”, Journal of Marketing, Vol. 46, pp. 26-43. Powell, T.C. (1995), “Total quality management as competitive advantage: a review and empirical study”, Strategic Management Journal, Vol. 16 No. 2, pp. 15-37. Schonberger, R.J. (1994), “Human resource management lessons from a decade of total quality management and reengineering”, California Management Review, Vol. 36 No. 4, pp. 109-23. Sommer, S.M. and Merritt, D.E. (1994), “The impact of a TQM intervention on workplace attitudes in a health-care organizations”, Journal of Organizational Change Management, Vol. 7 No. 2, pp. 53-62. Tan, H.H. and Tan, C.S.F. (2000), “Toward the differentiation of trust in supervisor and trust in organization Genetic”, Social, and General Psychology Monographs, Vol. 126 No. 2, p. 241. Udo, G.J., Guimaraes, T. and Igbaria, M. (1997), “An investigation of the antecedents of turnover intention for manufacturing plant managers”, International Journal of Operations & Production Management, Vol. 17 No. 9, pp. 912-30. Wanous, J.P., Reichers, A.E. and Hudy, M.J. (1997), “Overall job satisfaction: how good are single-item measures”, Journal of Applied Psychology, Vol. 82, pp. 247-52.

Wilkinson, A., Allen, P. and Snape, E. (1991), “TQM and the management of labor”, Employee Relations, Vol. 13 No. 1, pp. 24-31. Wilkinson, A. (1992), “The other side of quality: self issues and the human resource dimension”, Total Quality Management, Vol. 3 No. 3, pp. 323-9. Yang, T., Chen, M-C. and Su, C-T. (2003), “Quality management practice in semiconductor manufacturing industries – empirical studies in Taiwan”, International Manufacturing Systems, pp. 153-9. Zhang, Z.H. (1999), “Developing an instrument for measuring TQM implementation in a Chinese context”, SOM Research Report, University of Groningen.



541


TQM 18,5

Managing cost of quality: insight into industry practice

542

Department of Mathematics and Industrial Engineering, Ecole Polytechnique de Montreal, Montreal, Canada, and

Andrea Schiffauerova Vince Thomson Department of Mechanical Engineering, McGill University, Montreal, Canada Abstract Purpose – The objective of this paper is to present results of the study of the quality costing practices at four large successful multinational companies. Design/methodology/approach – The method of benchmarking was used for the purpose of this study. Company representatives, who were invited for a benchmarking session, described the quality management programs running at their companies. Direct observation and archival records data collection were also used to extract more precise information for the following analysis and discussion. Findings – The findings of the study show that all four companies use systematic quality initiatives; however, a formal cost of quality (CoQ) methodology was only employed at one of them. This is in agreement with the literature findings arguing that a CoQ approach is not utilized in most quality management programs. Originality/value – This paper discusses and compares the quality programs of four companies and explains the benefits of the eventual adoption of a CoQ approach in each case. The analysis provides a new insight into company practice, useful both for academic research and industry. Keywords Quality costs, Multinational companies, Quality programmes Paper type Case study


Introduction Improving quality is considered by many to be the best way to enhance customer satisfaction, to reduce manufacturing costs and to increase productivity. Any serious attempt to improve quality must take into account the costs associated with achieving quality, since nowadays it does not suffice to meet customer requirements, it must be done at the lowest possible cost as well. This can only happen by reducing the costs needed to achieve quality, and the reduction of these costs is only possible if they are identified and measured. The identification itself is not straightforward, because there is no general agreement on a single broad definition of quality costs. However, according to Dale and Plunkett (1995), it is now widely accepted that quality costs are the costs incurred in the design, implementation, operation and maintenance of a quality management system, the cost of resources committed to continuous improvement, the costs of system, product and service failures, and all other necessary costs and non-value added activities required to achieve a quality product or service. Measuring and reporting these costs should be considered a critical issue for any manager who aims to achieve competitiveness in today’s markets. There are several methods that can be used to collect, categorize and measure quality costs. The traditional P-A-F method suggested by Juran (1951) and Feigenbaum (1956) classifies quality costs into prevention, appraisal and failure

costs. Prevention costs are associated with actions taken to ensure that a process provides quality products and services, appraisal costs are associated with measuring the level of quality attained by the process, and failure costs are incurred to correct quality in products and services before (internal) or after (external) delivery to the customer. The cost categories of Crosby’s (1979) model are similar to the P-A-F scheme. Crosby sees quality as “conformance to requirements” and therefore, defines the cost of quality (CoQ) as the sum of price of conformance and price of non-conformance (Crosby, 1979). The price of conformance is the cost involved in making certain things that are done right the first time and the price of non-conformance is the money wasted when work fails to conform to customer requirements. Another formal quality costing approach is the process cost model, which was developed by Ross (1977) and first used for quality costing by Marsh (1989); it represents quality cost systems that focus on process rather than products or services. Several references propose CoQ models that include the additional category of intangible costs. These are costs that can be only estimated such as profits not earned because of lost customers and reduction in revenue owing to non-conformance. The importance of opportunity and intangible costs for quality costing has been recently emphasized in the literature. Dale and Plunkett (1999) describe a less formal method based on collecting quality costs by department. Another recently proposed CoQ methodology is a method based on a team approach, in which the aim is to identify the costs associated with things that have gone wrong in a process (Robison, 1997). No matter which quality costing approach is used, the main idea behind the CoQ analysis is the linking of improvement activities with associated costs and customer expectations, thus allowing targeted action for reducing quality costs and increasing quality improvement benefits. Therefore, a realistic estimate of CoQ, which is the appropriate tradeoff between the levels of conformance and non-conformance costs, should be considered an essential element of any quality initiative and a crucial issue for any manager. A number of organizations are now seeking both theoretical advice and practical evidence about quality-related costs and the implementation of quality costing systems. A reasonable amount of detailed information on various methods of categorization, collection and measurement of quality costs can be found in the literature (Plunkett and Dale, 1987; Williams et al., 1999; Schiffauerova and Thomson, 2006). However, there are only a few published, practical examples from industry that give specifics about the costs that are included or excluded in quality costing and about how the costs are practically collected and measured. More detailed descriptions of CoQ systems from industry can be found in Whitehall (1986), Hesford and Dale (1991) and Purgslove and Dale (1996). This paper intends to contribute to this area by providing an analysis of the quality costing practices of four successful companies. Research intent and methodology The objective of this research was to obtain and analyze data concerning the practices of successful companies in the area of quality management. Specifically, the main interest was to investigate if these companies collect, measure and monitor quality costs, which kinds of costs were considered in the calculations, and whether any formal CoQ approach was used. The analysis provided a new insight into company practice, useful not only for academic research, but also for use by industry.

Managing cost of quality

543

TQM 18,5

544

Four companies were selected to participate in the research. The main objective of the selection was to identify the organizations with well established quality programs belonging to the different industrial sectors. Companies serving the same market could have been reluctant to share details concerning their quality practices with competition. This paper keeps the company names confidential and refers to them as company A, B, C and D. A benchmarking session took place at McGill University. The quality management programs running at the four companies were described by company representatives. The organizations utilized this occasion as an opportunity to obtain new information on the practices used at other companies and to mutually compare their experiences, efforts and successes. Summary of the benchmarking session This section summarizes the initiatives in the field of CoQ for the four participants. A comparative analysis of their quality strategies and final remarks follow. Company A Company A is a telecommunication company. It has very complex products, and therefore, the number of opportunities for defects per unit is very high (45,000 defect opportunities per assembly). However, company A’s customers expect zero defects. Quality initiatives, therefore, play an important role in the company’s product management. Company A’s model for CoQ measurement and calculation follow the P-A-F model, where CoQ ¼ (P þ A þ F(internal þ external) þ other costs)/cost of goods sold. Company A is well aware of formal CoQ methods and it has clearly determined its CoQ definitions. It knows exactly what are its conformance and non-conformance costs; however, it struggles to find out the shape of its CoQ curves, and hence, an optimum CoQ tactic. The search for an optimum CoQ is difficult because the business cycle changes often (every 2 years or less); product lines are released in phases, and component obsolescence and multiple engineering changes are quite common. Every change causes a new search for an optimum CoQ; moreover, different product lines require separate review, and variable volumes reduce optimization opportunities. Company A uses an activity-based management approach, which means that it uses activity-based costing (ABC) to determine cost categories. It maps financial categories into activity costs, and activities performed at cost centers are rolled up to aggregate quality costs and percentages. In this way, the company obtains exact information about every category: prevention costs, appraisal costs, as well as internal and external failure costs. An example of activity costs is given in Table I, and the resulting CoQ chart with cost of conformance (COC) and cost of non-conformance (CONC) indicated is shown in Figure 1. Company A uses other metrics for performance comparisons, such as “new versus mature product” or “part number based CoQ ratio.” CoQ is measured at individual test stages, which allows trend analysis and comparison using mature product as the benchmark for new product. Figure 2 shows the decreasing trend of CoQ for manufacturing operations. The graph shows a decrease for all CoQ components; however, it is failure costs which show the biggest reduction, about 40 percent over 18 months. The breakdown of CoQ and its cost values are measured quarterly.

Activity – primary

CoQ category

Product defects Change management Internal quality issues External quality issues DFX, NPI support Prototype support Product deliverables Manufacturing tools Quality reporting Other

Failure – internal Prevention Failure – internal Failure – external Prevention Prevention Appraisal Prevention Appraisal Cost of business Totals

Activity (percent) 8 12 17 9 4 6 22 6 10 6 100

Notes: DFX – design for excellence; NPI – new product introduction

Cost categories


Salaries Depreciation Suppliers Others

545

Table I. Example of activity costs in company A

Figure 1. CoQ chart for company A

Figure 2. CoQ in manufacturing operations for company A shown on a relative cost scale

TQM 18,5

546

Company A has been using their CoQ methodology successfully. The company declares savings in quality costs, has quality improvement in every part of their process, and achieves very aggressive improvement targets. Moreover, the end customer directly benefits from the in-house quality initiative. As a result, customer satisfaction is increasing. Company B Company B is a multinational microelectronics company, which dedicates a lot of effort to quality improvement. Their far-reaching and successful quality improvement program is the main axis of their quality initiatives. The program includes continuous improvement focused on process as well as extensive education and training on quality for all employees. Despite the fact that there is a great interest in reducing non-conformance cost, company B does not measure, report or chart CoQ. It does not use any formal CoQ model and does not try to optimize CoQ. Nevertheless, it does reduce cost due to poor quality through its continuous improvement activities. The company has a strong operations and process focus, where emphasis is put on process yield and cycle time improvement. It believes that a continuous quality improvement program focused on process will provide the opportunities for quality improvement and thus reduction in CoQ. Company C Company C is in the aerospace industry and emphasizes products with near zero defects. Company C describes its cost of poor quality model as an iceberg philosophy, where just a few categories for poor quality cost are measured and monitored. This is, however, just the tip of the iceberg, since most of the cost factors leading to poor quality are non-visible or completely hidden (and non-quantifiable). Company C has implemented a process that allows tracking of all non-quality events and associated root causes as well as corrective actions and lessons learned. It puts full attention into measuring the cost of poor quality. It has four main quality ratings, which measure non-conformities (scrap, rework, etc.), poor adherence to specifications (internal, external, customers’ suppliers’), number of defective parts in parts per million, and on-time delivery. Their cost of non-quality is systematically reduced through a corporate-wide initiative based on continuous improvement. It also uses a sophisticated IT system for tracking quality. Although company C has had success in improving the value of non-conforming quality costs, it does not use any CoQ model, and it does not include the CoQ among its calculation elements. Company D Company D is a manufacturer of home products. It has set its quality level at a fixed warranty rate, and it attempts to optimize its quality effort to achieve this target. At the time of the benchmarking session, the company did not measure CoQ; however, it was planning to do so and was building a CoQ model. The envisioned CoQ program was based on a P-A-F model. The strategy of company D was to directly attack failure costs in an attempt to drive them down, to invest in the right prevention activities to

bring about improvements, to reduce appraisal costs according to achieved results, and to continuously evaluate and redirect prevention efforts to gain further improvements.


Discussion Table II shows a comparison of the quality initiatives and CoQ effort carried out by the four companies. The following discussion is focused on the relation between the quality strategies and the industrial sectors, on the kinds of CoQ models used, on the satisfaction with company efforts, the results stemming from the quality costing programs, and the recommendations by the authors of this paper.

547

Quality strategies The business environment, which is the industry sector and product line, dictates the strategy adopted by the companies to assure achievement of the required level of quality. Companies A, B and C all work in high-tech industries that require very high levels of quality, and therefore, they all have quite elaborate quality and productivity improvement systems with the objective to achieve zero or near zero defects. Company D, which serves home product markets, uses a fixed rate of return through its warranty policy as its quality limit. The company, however, does have a continuous improvement program. Quality costs Table II suggests that company A is the only one that in fact measures both kinds of quality costs, conformance and non-conformance. This allows the company to search for the right balance between the amount spent on quality and the resulting benefits. Companies B and C both regard reducing non-conformance cost as a high priority, and therefore, they exert substantial efforts in measuring and monitoring failures and other non-conformances. At the same time, they use elaborate, systematic quality improvement programs in order to reach a zero defect quality level. The direction of these initiatives is consistent with the industry quality environment, which tolerates absolutely no defect, no matter what the cost is. Conformance costs are consequently given much less attention in the quality management programs and measuring them together with the CONC is, therefore, disregarded. The situation for company D is, however, quite different. Even though the company also does not measure conformance costs, the nature of its own quality strategy suggests that it would benefit greatly if it started doing so. Identification and measurement of both kinds of the quality costs would certainly improve the quality policy that company D follows. The policy has a determined rate of return as its quality Industry Company sector A B C D

Telecom Electronics Aerospace Home products

Quality strategy

Quality costs

Formal CoQ model

Quality efforts

Program satisfaction

Zero defect Zero defect Zero defect Percentage of allowable defects

CONC þ COC CONC CONC CONC

P-A-F þ ABC None None None

Intensive Intensive Intensive Moderate

High High High Moderate

Notes: COC, cost of conformance; CONC, cost of non-conformance; P-A-F, traditional model including: prevention þ appraisal þ failure costs; and ABC, activity-based costing

Table II. Comparison of quality initiatives of four companies

TQM 18,5

548

limit. Being able to find an appropriate tradeoff between conformance and non-conformance costs would help company D determine an optimal level of effort towards achieving quality. Formal CoQ methods Literature (Porter and Rayner, 1992; Schiffauerova and Thomson, 2006) suggests that, if quality costs are measured by companies, then the classical P-A-F model is the one most frequently used in practice. Even within the limited sample of four companies, P-A-F was the only model encountered. Company A is currently calculating its quality costs according to the traditional categorization of prevention, appraisal and failure costs. Moreover, company D claims that it is planning to utilize this model in the near future as well. The results of this research, therefore, confirm other researchers’ findings on the frequency of the use of the P-A-F method in industry. Focus by companies on the classical P-A-F methodology is not surprising; however, there are several other alternatives available for monitoring CoQ. Other quality costing methods, such as Crosby’s model or process cost model, are being used with success (Schiffauerova and Thomson, 2006). Every company has to choose an appropriate CoQ method that suits its needs and its situation best. For a detailed checklist of the issues to be considered when deciding on a CoQ approach, Dale and Plunkett (1995). ABC is considered to be more compatible with quality cost measurement systems than traditional accounting. Although most CoQ measurement methods are activity/process oriented, traditional cost accounting establishes cost accounts by the categories of expenses instead of activities. Thus, many CoQ elements need to be estimated or collected by other methods. There is no consensus method on how to allocate overheads to CoQ elements and no adequate method to trace quality costs to their sources (Tsai, 1998). The use of ABC for a CoQ calculation is, therefore, an appealing alternative, and company A is benefiting from this powerful combination. The employment of a CoQ approach together with ABC enables company A to obtain exact information about every CoQ category: prevention costs, appraisal costs as well as internal and external failure costs. Companies B and C do not utilize any formal quality costing system. This is in agreement with the common suggestion that the CoQ approach is not fully appreciated by organizations and the practical use of formal quality costing in industry is quite rare. Satisfaction with quality efforts The quality initiatives of companies A, B, and C are very elaborate and the amount of effort is intensive. Whether they use a formal CoQ method or they solely aim at a reduction in the cost of poor quality, the companies obtain excellent results from their quality programs. All three companies mentioned a high satisfaction with their quality efforts during the benchmarking session. Judging by the success of company A with its CoQ program, we suggest that companies B and C would benefit from measuring CoQ, and that they would be surprised if they knew their real quality costs. These companies should select an appropriate CoQ model that suits the company’s situation and implement the quality costing methodology in order to improve the efficiency of their quality initiatives. Monitoring quality costs would allow them to better identify target areas for cost reduction and quality improvement. Moreover, sufficient savings should occur to justify CoQ measurement expenses.

Company D has a continuous improvement program that brings it moderate results and is already looking to improve it by implementing a CoQ strategy. As mentioned above, the implementation of a suitable CoQ method would secure reduced costs and improved quality benefits for company D.


Summary Even though quality is nowadays considered to be a critical success factor for achieving competitiveness, the CoQ approach is not fully appreciated by organizations, and only a minority of them use formal quality costing methods. The four companies that participated in the benchmarking session with McGill University on CoQ have systematic quality initiatives, and have been successful in improving quality and reducing the CONC. However, the only company that measures CoQ and uses a formalized CoQ model is company A. Company D is at the point of starting to use this quality measurement tool as well; however, it is at the beginning of this path. On the other hand, company B and company C focus their quality efforts solely on continuous quality improvement. They measure, monitor and work mostly with the CONC, and do not formally include COC in their analysis. It was recommended that companies B, C and D set up a suitable formal quality costing system compatible with the needs and the situation of each company. For companies B and C this program will mainly facilitate identification of the target areas for quality improvement and cost reduction in quality effort. For company D it would also help balance its quality costs and establish an optimal level of effort towards achieving quality. CoQ programs should be part of any quality management program. The methodology is not complex and is well documented. CoQ programs provide a good method for identification and measurement of quality costs, and thus allow targeted action for reducing CoQ. Further education on the practical level is needed for managers to understand better the CoQ concept in order to appreciate fully the benefits of the approach, to increase their ability to implement a CoQ measurement system and to save money.

549

References Crosby, P.B. (1979), Quality is Free, McGraw-Hill, New York, NY. Dale, B.G. and Plunkett, J.J. (1995), Quality Costing, 2nd ed., Chapman and Hall, London. Dale, B.G. and Plunkett, J.J. (1999), Quality Costing, 3rd ed., Gower Press, Aldershot. Feigenbaum, A.V. (1956), “Total quality control”, Harvard Business Review, p. 34. Hesford, M.G. and Dale, B.G. (1991), “Quality costing at British aerospace dynamics”, Proceedings of the Institution of Mechanical Engineers, Vol. 205, G5, p. 53. Juran, J.M. (1951), Quality Control Handbook, 1st ed., McGraw-Hill, New York, NY. Marsh, J. (1989), “Process modeling for quality improvement”, Proceedings of the Second International Conference on Total Quality Management, p. 111. Plunkett, J.J. and Dale, B.G. (1987), “A review of the literature on quality-related costs”, International Journal of Quality & Reliability Management, Vol. 4 No. 1, p. 40. Porter, L.J. and Rayner, P. (1992), “Quality costing for total quality management”, International Journal of Production Economics, Vol. 27, p. 69.

TQM 18,5

550

Purgslove, A.B. and Dale, B.G. (1996), “The influence of management information and quality management systems on the development of quality costing”, Total Quality Management, Vol. 7 No. 4, p. 421. Robison, J. (1997), “Integrate quality cost concepts into team problem-solving efforts”, Quality Progress, March, p. 25. Ross, D.T. (1977), “Structured analysis (SA): a language for communicating ideas”, IEEE Transactions on Software Engineering, Vol. SE-3 No. 1, p. 16. Schiffauerova, A. and Thomson, V. (2006), “A review of research on cost of quality models and best practices”, International Journal of Quality & Reliability Management, Vol. 23 No. 6. Tsai, W.H. (1998), “Quality cost measurement under activity-based costing”, International Journal of Quality & Reliability Management, Vol. 15 No. 7, p. 719. Whitehall, F.B. (1986), “Review of problems with a quality cost system”, International Journal of Quality & Reliability Management, Vol. 3 No. 3, p. 43. Williams, A.R.T., van der Wiele, A. and Dale, B.G. (1999), “Quality costing: a management review”, International Journal of Management Reviews, Vol. 1 No. 4, p. 441. About the authors Andrea Schiffauerova is studying the structures of innovative networks, knowledge flows and the performance of the firms within industrial clusters for her PhD. She has also participated in projects in cost of quality, technical information transfer, risk management, quality function deployment and engineering change. Andrea Schiffauerova is the corresponding author and can be contacted at: andrea.schiffauerova@polymtl.ca Vince Thomson is a Werner Graupe Professor of Manufacturing Automation. He has been involved in manufacturing and information technology related research for the past 25 years at McGill University and the National Research Council (Canada). His research has ranged from shop floor control and production scheduling to the present interest in real-time control and process management in manufacturing. His process management research has focused on new product introduction, concurrent engineering and manufacturing support in terms of coordination, metrics, and process principles. E-mail: vince.thomson@mcgill.ca
