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TQM success efforts: use more quantitative or qualitative tools?

Introduction

Total quality management (TQM) is playing an important role in helping US companies become more competitive in the global market. Companies such as Xerox and Motorola have emerged as leaders in their industries as the result of implementing TQM (Bhalla and Wason, 1994). TQM is an approach to planning and implementing continuous organizational improvement. Its focus is on satisfying customers' desires, identifying problems, building commitment, and encouraging open decision making among workers (Sorensen and Weber, 1994).

The role of quality in the economic growth of a company is undoubtedly important. Total quality can be viewed as "conformance to requirements of customers, internal and external, by doing right things right, the first time every time." TQM is a customer-oriented approach which uses statistical tools and techniques, follows the plan-do-check-act scheme, implements the measures, and continues to improve procedures for smooth fulfilment of plans. One major component of TQM is the use of statistical tools such as flowcharting, Pareto analysis, cause-and-effect diagrams, and statistical process control in the decision-making process. These tools help abolish nonvalue-added activities in all functions. On the other hand, implementing TQM involves a change in managers' role: going from managers who direct, are competitive, rely on rules and organizational hierarchy, make separate decisions, view people as costs, and promote sameness, privacy, and passivity, to managers who lead, guide, co-operate, focus on the process, use informal networks, view people as assets, and encourage variety, flexibility, openness, sharing, risk taking, and involvement (Levinson and Ben-Jacob, 1996; Prasad and Dasaratha, 1991).

Since TQM's effective implementation relies on developing a business plan well established on major skills and providing value-added, customer-focused processes, it is interesting to examine any possible association of several variables that are used in TQM implementation in different industries such as hospitals, manufacturing, and service organizations.

A search of available literature on this issue did not reveal any studies testing the effectiveness of the tools as regards the success of TQM programmes. However, a number of articles have been written concerning the factors necessary for successful TQM programmes. Several authors (Braunstein, 1989; Caudron, 1993; Danne, 1992; Davies and Hinton, 1993; Doyle, 1992; Esler, 1992; Gilbert, 1992; Ginnodo and Wellins, 1993; Grayson, 1993; Kim and Johnson, 1994; Lengnick-Hall et al., 1993; Longenecker et al., 1993; Pascoe, 1992; "The Quality March," 1994) have stated that for TQM programs to be successful in any organization, factors such as management commitment, employee involvement, cultural change, ongoing training, communication, and commitment to quality must be implemented within the organization. Many US companies, such as L.L. Bean, General Motors, Universal Foods, and Hewlett Packard, are actively dealing with the issues of being on the mature and declining part of the success cycle as a result of losing market share to foreign markets. These companies are implementing TQM and are achieving success by implementing it correctly in their organizations, while at the same time keeping employees involved in this ongoing process (Braunstein, 1989; Caudron, 1993; Grayson, 1993; Rohan, 1990).

Heinrich (1994) pointed out that companies thus far have placed more emphasis on the qualitative aspects of TQM; however, companies will not fully realize the advantages of TQM unless the quantitative aspects of TQM are integrated into their operations. The role of TQM tools in TQM success has not been clearly concluded in the literature. The purpose of this study is to look at the tools that are widely used in TQM programmes and explore the relationship between the use of the tools and the successfulness of a TQM programme.

Methodology

The literature reports that TQM programmes are not always effective. Thus, what are the factors that contribute to the success or failure of TQM efforts? Specifically, this study is interested in the type of tools as a determinant of TQM success. This study looked at 15 frequently used TQM tools and classified them according to qualitative TQM tools and quantitative TQM tools. Qualitative tools consist mainly of subjective inputs, which often do not intend to measure something of a numerical nature. Quantitative tools, on the other hand, involve either the extension of historical data or the analysis of objective data, which usually avoid personal biases that sometimes contaminate qualitative tools. After carefully consulting with some experts in this area, the following classification is used:

Qualitative tools

1 flow charts; 2 cause-and-effect diagrams; 3 multi-voting; 4 affinity diagram; 5 process action teams; 6 brainstorming; 7 election grids; 8 task lists.

Quantitative tools

1 Shewart cycle (PDCA); 2 control charts; 3 scatter diagrams; 4 Pareto charts; 5 sampling; 6 run charts; 7 histograms.

One interesting question the survey intended to answer is whether or not TQM programmes are more successful in organizations when their approach to TQM is based on the use of quantitative tools rather than solely on the use of qualitative tools. To provide a possible answer to the question, a questionnaire was developed and mailed to 1,484 managers who were in charge of quality programmes in a four-state area (Louisiana, Texas, Arkansas, Mississippi). An example of the questionnaire is presented in the Appendix. The mailing list was obtained from professional organization membership lists and through consultant contacts (quality consultants for a local hospital).

Results

Descriptive statistics

The response rate of the survey totalled 365 returned surveys, or 25 per cent. Table I shows the breakdown in frequency and percentage of the usable responses received from the mail-out of the questionnaire.

Of the returned questionnaires, 34, or 9 per cent, had not implemented TQM. These responses were omitted from the sample. Manufacturing represents, by far, the largest number of responses at 184, or 56 per cent; hospitals at 92, or 28 per cent; and service organizations at 55, or 17 per cent. Implementation of TQM, as shown in Table II, is at high levels, suggesting that TQM is very popular at this time. Hospitals have a very high implementation rate due to new, 1994 accreditation standards. Because of these new standards, many hospitals are new to some aspects of TQM. This is reflected in the success rate of hospitals as mentioned later in the paper. The questionnaire used three measures as indicators of a successful TQM programme:

* customer research;

* improved product;

* respondent assessment of success.

Since TQM is a customer-focused approach, one effective measure of a successful TQM programme is to understand how a company is delivering to customers what they need, want, expect, and are willing to pay for. Conducting customer research is one way to gain feedback from customers. Improved product is a measure of a process producing quality products. Flaws in a process lead to customer complaints, duplication of effort, and costly rework. A successful TQM programme should be one producing all productive work. Respondent assessment of success is more related to employee involvement, one of the three distinct subsystems. It is important to involve all employees in quality-related activities to ensure that continuous improvement can be carried out in a process. These three measures of indicators of a successful TQM programme were used for three distinct TQM subsystems - customer focus, continuous improvement, and employee improvement.
Table I

TQM research: total sample

Type of organization     Frequency     Relative

Manufacturing               184         0.556
Service                      55         0.166
Hospital                     92         0.278
Total usable                331         1.00




Total responses to these indicators reveal 34 per cent have positive customer research, 38 per cent partially positive, 1 per cent not positive, and 27 per cent are not doing customer research. Improvement in product saw more positive results with 57 per cent indicating improved product quality, 39 per cent partial improvement, and 4 per cent saying no improvement. The last measure of success revealed that 45 per cent of the respondents indicated that their TQM programme is successful, while 50 per cent say it is partially successful and 5 per cent say it is not successful. Table III summarizes the three indicators and Tables IV-VI show TQM performance by type of organization.
Table II

Implementation of TQM

Type of organization    Fully    Per cent    Partially    Per cent

Manufacturing            116        63          68           37
Service                   36        65          19           35
Hospital                  55        60          35           38
Total                    202        56         121           33




[TABULAR DATA FOR TABLE III OMITTED]

[TABULAR DATA FOR TABLE IV OMITTED]
Table V

Product has improved

                            Yes         Partially          No
Type of organization     (per cent)     (per cent)     (per cent)

Manufacturing                63             31              5
Service                      51             44              4
Hospital                     42             48              3




[TABULAR DATA FOR TABLE VI OMITTED]

An interesting finding is that there is a high percentage of organizations that are not engaged in customer research (see Table IV). Manufacturing firms have the highest proportion of lack of customer research, hospitals the second highest, and service organizations the lowest. This finding is significant because of the fact that TQM's basic philosophy is determining the needs of the customer and meeting those expectations.

In all three indicators of success, manufacturing firms show the greatest level of success while service organizations are the second most successful, and hospitals are the least successful. Furthermore, the tables reveal that hospitals have the highest occurrence of being partially successful, service organizations the second highest, and manufacturing firms are the least partially successful. All three sectors show similar occurrences of TQM being an unsuccessful experience (see Table VI) and also reveal a low occurrence of abandonment of TQM by all organizations.

Table VII summarizes the entire sample by the observed mean and percentage of time the qualitative/quantitative tool is used. The least often used tools are affinity diagrams and selection grids. These two tools are used for the purpose of problem identification and solution planning. The reason that these two tools are not used as much may be the fact that several other tools are more popular and are designed for the same identical purpose. Some examples of the more popular tools are control charts, flow charts, brainstorming, and Pareto analysis. All of the tools fit into four categories, which are:

* problem identification;

* solution planning;

* evaluating indicators;

* data analysis.

Tables VIII-X show how often TQM tools are used by successful, partially successful, and unsuccessful organizations. It is apparent, from a review of these tables, that organizations which are successful use quantitative tools more than organizations which are not as successful. The variance becomes greater for organizations that are not as successful. The only exception seems to be the qualitative tool of brainstorming, which is the most often used tool of the three sectors (manufacturing, service, and hospitals). A major quantitative tool is the control chart, which is used to identify special and common causes. Successful organizations use this tool 68 per cent of the time.
Table VII

TQM research: total sample

Qualitative         Time used     Quantitative         Time used
tools               (per cent)    tools                (per cent)

Flow chart              60        Control chart            58

Cause-and-effect
diagram                 43        Scatter diagrams         35

Multi-voting            35        Pareto charts            63

Affinity diagram        15        Sampling                 68

Brainstorming           75        Run chart                53

Selection grids         13        Histograms               58

Task list               58
Table VIII

Stated TQM successful

                              Proportion used
TQM tool                         (per cent)       Quantitative tool

Brainstorming                        80                 no
Sampling                             73                 yes
Pareto chart                         70                 yes
Control chart                        68                 yes
Histogram                            65                 yes
Flow chart                           65                 no
Run chart                            63                 yes
Task list                            60                 no
Cause-and-effect diagram             50                 no
Scatter diagram                      43                 yes
Multi-voting                         35                 no
Affinity diagram                     18                 no
Selection grid                       18                 no
Table IX

Partially successful

                              Proportion used
TQM tool                         (per cent)       quantitative tool

Brainstorming                        73                 no
Sampling                             65                 yes
Flow chart                           58                 no
Pareto chart                         58                 yes
Task list                            55                 no
Histogram                            53                 yes
Control chart                        50                 yes
Run chart                            48                 yes
Cause-and-effect diagram             40                 no
Multi-voting                         35                 no
Scatter diagram                      30                 yes
Affinity diagram                     15                 no
Selection grid                       13                 no




Statistical analysis

The statistical analysis consisted of a computation of the Spearman-rank correlation, hypothesis test, and logistic regression. The Spearman-rank correlation was used to compare the qualitative and quantitative TQM tools. This was done to determine whether a significant difference exists between the two populations of tool usage. The results of this computation revealed a correlation coefficient of -0.65714. This coefficient suggests that there is a strong negative correlation between the two groups of tools showing that as the use of one group increases, the use of the other one decreases. The following hypothesis was formulated and tested:

H1: The use of qualitative tools is not related to the use of quantitative tools.
Table X

Stated unsuccessful

                              Proportion used
TQM tool                         (per cent)       Quantitative tool

Brainstorming                        68                  no
Sampling                             50                  yes
Pareto chart                         45                  yes
Task list                            43                  no
Control chart                        43                  yes
Histogram                            40                  yes
Row chart                            38                  no
Cause-and-effect diagram             33                  no
Scatter diagram                      23                  yes
Multi-voting                         23                  no
Run chart                            20                  yes
Affinity diagram                      5                  no
Selection grid                        0                  no




At a significant level of 0.05, the null hypothesis is rejected. Thus, the hypothesis-testing result confirms that there is a strong correlation between the two groups of tools as indicated by the Spearman-rank correlation analysis.

Logistic regression was conducted to determine if the qualitative and/or quantitative tools explain the variation of the dependent variable. Several choices of a dependent variable were used including: the question concerning whether the respondent considered their TQM programme to be successful; the question of receiving positive customer research; and whether the product had improved. The logistic regression model expresses the dependent variable in binary terms of either "1" or "0". In this analysis, the "1" is unsuccessful, and the "0" is successful in each of the three categories in the table. Each of the dependent variables included both successful and unsuccessful responses. The purpose of using the logistic regression was to learn whether the qualitative or quantitative variables explained a variation in the dependent variables. Table XI is a summary of the independent variables' p-values obtained from the regression.
Table XI

Logistic regression - independent variables' p-values

                                                 Positive
                        Stated       Improved    customer
TQM tools             successful     product     research

Quantitative

Control chart           0.993         0.228       0.800
Scatter diagram         0.626         0.765       0.702
Pareto chart            0.879         0.961       0.821
Sampling                0.511         0.089       0.145
Run chart               0.020         0.072       0.202
Histogram               0.516         0.969       0.371

Qualitative

Flow chart              0.004         0.010       0.200
Cause and effect        0.990         0.546       0.122
Multi-voting            0.494         0.779       0.620
Affinitive diagram      0.692         0.752       0.178
Brainstorming           0.843         0.840       0.971
Selection grid          0.985         0.985       0.985
Task list               0.360         0.554       0.044




The overall p-values for each of the regression runs are listed as follows:

Stated successful

qualitative tool -0.0004 quantitative tools -0.0044

Improved product

qualitative tools -0.0079 quantitative tools -0.0009

Customer research

qualitative tools -0.0002 quantitative tools -0.0556

Below is a listing of the percentage of the variables correctly classified:

Stated successful

qualitative tools -89.51 quantitative tools -90.60

Improved product

qualitative tools -92.13 quantitative tools -92.82

Customer research

qualitative tools -99.05 quantitative tools -96.12

Both of the overall p-values and the percentages correctly classified indicate that the regression model significantly explains the variation in the dependent variables.

Conclusions

The sample of the population that was the focus of the study (Louisiana, Texas, Arkansas, Mississippi) suggests that the TQM management philosophy is very popular in this region of the United States. This finding is consistent with current literature, reporting that TQM is not only popular in the United States but also internationally.

The TQM programme success rate of 51 per cent for manufacturing, 40 per cent for services, and 34 per cent for hospitals is surprising. The researchers expected the success rate to be much higher. The statistics gathered from the research show that many organizations are partially successful. This fact was not expected by the researchers. Also not expected was the low proportion of organizations using the PDCA cycle since it is well recognized to be an important framework of TQM. Additional research to discover the reasons, structure, and their effectiveness is an interesting source of further research. Another interesting topic to explore in the future is the correlation of time since TQM is implemented to the success of the programme. This could have positive implications for the large number of partially successful responses received.

Analysis of the data reveals that quantitative and qualitative tools do affect the success of a TQM programme. It is quite apparent from Tables VIII-X that quantitative tools are used more by organizations that are more successful. Also, as an organization moves from being partially successful to unsuccessful in the study, quantitative tools became less used. One explanation for this finding is that the use of quantitative tools requires some degree of employee training, and the real driver is training. Employee involvement and training have been discussed in the literature as a key element to make TQM work (Lengnick-Hall et al., 1993). Hence, one may conclude that the success of a TQM programme is driven by training the workforce on a variety of issues, one of which is use of the tools.

It was revealed in the Spearman-rank correlation that quantitative and qualitative tools are negatively correlated. This suggests that organizations use more of one group of tools at the expense of the other group. Tables VIII-X support this finding. The hypothesis test also proved there was a significant relationship between the two populations. The final test of logistic regression further proved the relationship of the two groups of tools and the success of TQM.

References

Bhalla, S.K. and Wason, S.K. (1994), "Managing the technological process", Quality Progress, January, pp. 81-5.

Braunstein, D. (1989), "Recapturing the spirit", Journal for Quality and Participation, September, pp. 48-53.

Caudron, S. (1993), "Change keeps TQM programs thriving", Personnel Journal, October, pp. 104-7.

Danne, D.J. (1992), Total Quality Management in Industry and Its Implications for Secondary Education (Education Restructuring), Pepperdine University, p. 249.

Davies, K. and Hinton, P. (1993), "Managing quality in local government and the health service", Public Money and Management, January-March, pp. 51-4.

Doyle, K. (1992), "Who's killing total quality?", Incentive, August, pp. 12-19.

Esler, B. (1992), "Teamwork key to SPC success", Graphic Arts Monthly, May, pp. 78-82.

Gilbert, J.D. (1992), "TQM flops - a chance to learn from the mistakes of others", National Productivity Review, Autumn, pp. 491-9.

Ginnodo, B. and Wellins, R.S. (1992-93), "Research shows that TQM is alive and well", Tapping the Network Journal, Winter, pp. 2-5.

Grayson, C. (1993), An Exploratory Study of the Relative Impact of Organizational Contextual Factors on Individual Decisions to Buy-In and Maintain Commitment to an OrganizationWide Total Quality Management Effort (Employee Satisfaction, Recognition), California School of Professional Psychology, p. 247.

Heinrich, G. (1994), "Integrating TQM with statistical and other quantitative techniques", National Productivity Review, Spring, pp. 287-95.

Kim, P.S. and Johnson, D.D. (1994), "Implementing total quality management in the health care industry", Health Care Supervisor March, pp. 51-7.

Lengnick-Hall, M.L., Heinrich, G. and Middleton, E. (1993), "Employee involvement makes TQM work", Personnel Journal, October, p. 108.

Levinson, H.J. and Ben-Jacob, J. (1996), "Managing quality improvement on a development pilot line", Quality Management Journal, Vol. 3 No. 2, pp. 16-35.

Longenecker, C.O. and Scazzero, J.A. (1993), "Total quality management from theory to practice: a case study", International Journal of Quality and Reliability Management, pp. 24-31.

Pascoe, L.B. (1992), A Study of the Importance of Key Components of Total Quality Management Programs in American Manufacturing Firms (Quality Management, Management Commitment, Customer Orientation, Employee Involvement), United States International University, p. 156.

Prasad, A. and Dasaratha, (1991), "Economic rationale of total quality process", ASQC Quality Congress Transactions-Milwaukee, pp. 369-74.

"The quality march (Part 3)" (1994), Hospitals and Health Networks, January, pp. 45-8.

Rohan, T. M. (1990), "New crisis in quality", Industry Week, October, pp. 11-14.

Sorensen, P. and Weber. D. (1994), "Organizational cultural and TQM implementation", Training and Development, April, pp. 69-71.

Appendix

Please complete the following questionnaire. We will be happy to share with you the results of the study if you desire... simply include your card or mailing address. After completing the questionnaire, please tape closed so that the business reply side is visible, and return as soon as possible.

1. What is your position in the organization?

CEO Vice-President Quality Manager Other

2. What is the number of employees in your organization?

1-100 101-200 201-300 301-400 401-500 501-600 More than 600

3. What sector is your business?

Private Governmental

4. Please indicate the classification of your organization.

Manufacturing Service Hospital

5. Has TQM, CQI, or an equivalent programme been implemented in your organization?

Yes Partially No

NOTE: If your answer to Question 5 is "No", please stop and mail the questionnaire back.

6. Circle the number of years it took your quality programme to be fully implemented.

Less than 1 1 2 3 4 5 Continuing

7. Does your customer research show that TQM/CQI has been successful?

Yes Partially No Not doing customer research

8. Has TQM/CQI improved the quality of your product or service?

Yes Partially No

9. Do you feel your TQM/CQI programme has been successful?

Yes Partially No

10. Using the scale below, circle the number that corresponds with your measurement of the extent to which your organization is using TQM/CQI tools.
                            Never                   Always
Tools                       use                     use

Flow charts                 1     2     3     4     5
Cause-and-effect diagrams   1     2     3     4     5
Multi-voting                1     2     3     4     5
Affinity diagrams           1     2     3     4     5
Process action teams        1     2     3     4     5
Brainstorming               1     2     3     4     5
Election grids              1     2     3     4     5
Task lists                  1     2     3     4     5
Shewart cycle (PDCA)        1     2     3     4     5
Control charts              1     2     3     4     5
Scatter diagrams            1     2     3     4     5
Pareto charts               1     2     3     4     5
Sampling                    1     2     3     4     5
Run charts                  1     2     3     4     5
Histograms                  1     2     3     4     5




11. How many months of initial training was used to implement your TQM/CQI programme?

1-2 3-4 5-6 Over 6 No training

12. Has your organization abandoned a TQM/CQI effort?

Yes

Larry Scheuermann

Professor of Quantitative Methods at the University of Southwestern Louisiana, Lafayette, Louisiana, USA

Zhiwei Zhu

Associate Professor in the Business Systems, Analysis and Technology Department at the University of Southwestern Louisiana, Lafayette, Louisiana, USA

Sandra B. Scheuermann

Instructor of Accounting at the University of Southwestern Louisiana, Lafayette, Louisiana, USA
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Title Annotation:total quality management
Author:Scheuermann, Larry; Zhu, Zhiwei; Scheuermann, Sandra B.
Publication:Industrial Management & Data Systems
Date:Jul 1, 1997
Words:3726
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