Adoption of Strategic Total Quality Management Philosophies
Adoption of strategic total quality management philosophies Multi-criteria decision analysis model
Christian N. Madu, John Aheto and Chu-Hua Kuei
Lubin School of Business, Pace University, New York, USA
Dena Winokur
Marketing Department, Pace University, New York, USA
Introduction
In today’s competitive environment, quality is the key to an organization’s success and survival. To compete effectively, companies must embrace the principles of total quality management (TQM) and incorporate them into all of their activities. TQM calls for continuous improvement – a never-ending philosophy of change for the better. Thus, companies planning for their future survival should be flexible and willing to accept change as inevitable, and even desirable. This concept leads to the question of what role cost-accounting practices play in cost control and whether the traditional methods for controlling costs in a company hinder or support total quality efforts. Theoretically, it can be argued that traditional cost-accounting practices which utilize net present value (NPV), payback period, internal rate of return (IRR), and so on, may actually hinder the implementation of TQM. Influences of traditional cost-accounting practices on
TQM are described as follows:
• TQM relies heavily on process changes. Many companies have turned to the use of information technology in their pursuit of quality. One illustration is the increasing use of expert systems and artificial intelligence techniques which, when applied to a manufacturing setting, leads to significant improvements in quality. Another example is the use of flexible computer-integrated manufacturing systems to improve product quality and productivity.
Unfortunately, many organizations still concentrate on short-term goals and objectives which create a bias against new and more efficient technologies. In most goal-oriented businesses, automation has been found to be more effective over the long term than the use of direct labour. Yet, among service providers, when alternative technologies or manufacturing techniques are considered for selection and adoption, the overriding emphasis is still on short-term costs and returns.
International Journal of Quality
& Reliability Management,
Vol. 13 No. 3, 1996, pp. 57-72,
© MCB University Press,
0265-671X
Received 25 March 1994
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• Traditional cost accounting techniques focus on short-term rather than long-term goals and objectives. This emphasis on controlling costs without relating them to the long-term value additives of an attribute of any project may often lead to the elimination of those attributes whose effects may be in the long-term best interests of the organization. For example, quality improvement could be achieved by a manufacturer if the company is flexible and responds swiftly to changes in demand.
Time-based competitive management is so critical to the survival of industry today that it is difficult to provide quality services in its absence. In order to provide quality services, the manufacturer must adopt just-in-time management theory and develop a quality relationship with the company’s suppliers and vendors. In addition, it may be necessary to restructure the organization, thereby, retraining workers and adopting and managing new technologies. However, all these changes can be time-consuming and expensive.
If the manufacturer compares new technological processes with that of existing technology but does not have a good sense of the benefits of such new technology (such as improved corporate image, market expansion, responsiveness to market demands, and others that may not be as easily identifiable), it may never lead to the adoption of these new techniques. The company’s short-term focus on traditional cost control may, therefore, cause it to miss this important opportunity.
By focusing on long-term goals and objectives, the firm will be better able to: compete; provide quality services and products; develop a positive corporate image; respond in a timely manner to changes in the marketplace; and better control costs over the long term owing to the development of a more efficient production system which reduces wastes, reworks and scraps. More importantly, the firm’s survival is ensured, it expands its market share and becomes socially responsible by enriching the jobs of its workers. By expanding its job base, as its market share grows, it provides needed services to its customers, and effectively manages its limited resources.
• TQM is heavily embedded in the concept of continuous improvement.
This is a never ending process – a continual process of change. While change is inevitable, a firm employing TQM must learn to accept it and continue to work toward continuous improvement. However, this is not a simple process, as it may require structural, organizational, cultural and process transformation.
Yet the cost of these changes may not be seen as justifiable if viewed only from the short term. If a firm is surviving and making satisfactory profits, a status-quo mentality will tend to prevail. A long-term perspective must be taken, one that takes into account all the values of the quality imperatives administered by a firm before these changes could be effectively evaluated. Any attempt towards cost control must be coupled with an analysis of the long-term goals, objectives and vision of the firm.
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A thorough marketing audit of the firm must be conducted to determine its strengths, weaknesses, opportunities for future growth and threats to its survival. It is also important to understand how a firm is positioned in its industry in order to develop a more effective competitive strategy. Every organization must have a vision for the future and it should be able to answer the question: “Where do we want to be X number of years from now?” In the absence of such vision, the firm is bound to fail. Cost control is ineffective if it fails to reinforce the vision of the firm and justify why a costly investment in technology may be the key to the company’s survival in the future. An outward look should also be projected to benchmark the firm with leaders in other industries. Innovation is the key to success in a dynamic and rapidly changing environment. Product life cycles are much shorter in today’s environment and competition is much greater. The strategic importance of an investment is a crucial factor in the success of the company. For example,
Harris[1] notes that “the most obvious cost of not investing is lost opportunity. If you don’t make the investment, your competitors probably will, and in so doing will gain the early-mover advantages that you’ve passed up: early profits, superior access to customers, and valuable patents”.
Harris[1] further explains the strategic importance of investment from the viewpoint of competitors, employees, buyers, and suppliers. He notes that “the perceptual costs of not investing won’t flash red on your financial statements, nor will the lost opportunity costs. But they can wound your company as badly as money sunk in a bum investment”.
Clearly, traditional cost-accounting methods, principles, and practices tend to overemphasize quantitative factors, frequently at the expense of intangibles. These intangibles often have a direct impact on profitability.
The continuing role of traditional cost-accounting principles in decision making needs to be expanded to integrate less quantitative factors.
One method by which this can be accomplished is by combining traditional cost-accounting techniques such as NPV, IRR, with multicriteria decision-making models. Although several papers have presented similar concepts relating to the management of new technologies[2-5], TQM application/practice as the principal goal of a firm has not been explored.
Strategic planning process
The strategic planning process demands that a holistic view of technology selection be adopted, i.e. a determination must be made as to what will be the value additive of the new technology to the organization’s operations. The issue of “value” is very important since some value additives cannot be easily assessed by looking at the direct investment costs related to the new technology.
For example, strategic planning and implementation is effective only when commissioned and actively supported by top management.
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Top management has the power and the resources to direct effectively a team approach to solve organizational problems. It is top management’s responsibility to form an interdisciplinary team that will fully analyse organizational problems, review the company’s resources and limitations, its vision and mission, and appropriately define the strategies needed to achieve organizational goals. None of these can be achieved without top management’s commitment and support.
Strategic challenges
It is clear in today’s turbulent environment that an organization’s survival depends on its ability to satisfy customers’ wants and needs and to compete effectively in global markets. But, to compete effectively, the organization must respond to the dynamic changes that are taking place in its own internal environment. Obviously, the ability to meet these new challenges involves decisions as to the selection of new technology. Some of the challenges currently faced by industry include:
• Marketing of “green”, or environmentally safe, products. The environmental movement has become a global institution. Consumers are concerned about the possible negative impact that products or processes have on the environment. They do not want to be perceived as contributing to the problem and therefore, many will not patronize companies which they believe are producing environmentally unsafe products. Madu and Kuei[6,7] note that environmental quality has become a critical competitive element in business. Harrison[8] notes that the following trends will force organizations to become environmentally oriented – what he calls the AMP formula (Activists + Media +
Politicians), more litigation, an increase in penalties for corporate executives, investor activism and media scrutiny
Many of Japan’s industries have already realized the importance of this emerging trend and are spending heavily on research and development to produce environmentally safe technologies that will help them capture this growing market niche.
• Information systems technology is a critical area that cannot be ignored[9]. The world is getting smaller as a result of the spread of information technology. Communication barriers are being broken and strategic alliances are being formed across nations. The focus on global marketing and global competition cannot be achieved if information technology remains at a primitive level. In today’s market environment, timing is the key to competitiveness. Information has to be made available on a real-time basis whether it is on the assembly line floor or in a global setting.
• Computer-integrated systems – the advent of modern computer systems has contributed immensely to the swift introduction of new products into the marketplace. Simulated product designs and quality specifications
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can be evaluated and potential problems easily identified and corrected.
Test marketing can also be accomplished in a cost-efficient manner.
No longer do companies have to depend on the mass production system alone as a means of achieving economies of scale in production.
The advent of new computer integrated systems such as FMS, which can assist in producing orders for products requiting flexible designs, as specified by customers, can be accomplished at competitive prices.
Companies, therefore, do not have to depend on the mass production system alone as a means of achieving economies of scale in production.
These factors are just a few of the many reasons why simple quantitative approaches such as NPV, payback period, and ROI (return on investment) may not be appropriate to use in today’s dynamic environment. Clearly, these techniques emphasize the direct cost of a project and may not take into account the long-term benefits that accrue to a firm through the implementation of these new technologies.
Identifying strategic factors
The essence of a planning matrix is to build a critical list of factors that will help the firm strengthen its competitive position. This list often includes the organization’s key performance measures. While there are several ways of identifying these key factors, the authors choose to describe two of them.
Statistical analysis
Statistical analysis involves the analysis of industrial data to determine factors which may significantly impact a firm’s sales volume or predict how well the firm is doing in relation to its competitors. Through statistical analysis, it can be determined that the following factors are those that influence a firm’s performance and growth: case flow (CF); world-class manufacturing (WCM); earnings per share (EPS); employee satisfaction (ES); customer service (CS); innovation (I); and market share (MS).
This method is very objective and quite reliable and may involve human input through the use of survey questionnaires when adequate industrial data is not available.
Scoring models
Scoring models depend on the judgement and input of stakeholders.
Stakeholders are defined as members of groups who are directly or indirectly impacted by an organization’s performance. Scoring models are simple to use, but in order for the results to be valid, stakeholders must be knowledgeable about the problems facing the company and be able to make well thought-out, rational decisions about the several performance measures identified in the model. Frequently, this involves the scoring of a pair of factors in terms of their relative importance towards achieving the firm’s mission or goals.
While scoring models are easy to conceptualize, they are often biased and inconsistent. Once a bias is detected, the whole process becomes flawed and the decisions made based on the model, may not help the firm to achieve its goals.
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This, however, does not imply that qualitative decisions are a guaranteed outcome even when there is consistency among stakeholders. The chances of making quality decisions are enhanced only when the stakeholders are rational, in addition to consistent, in their judgements. Therefore, there must be a systematic way of identifying performance measures.
For the sake of brevity, the authors assume that a statistical analysis of a particular industry will yield the following factors: cash flow; world class manufacturing; earnings per share; employee satisfaction; customer service; innovation; and market share; which are determining factors for the success and growth of a firm in any industry. Actually, many of these factors have been identified by other researchers as key factors in measuring success in manufacturing firms[4,10].
Developing technological strategies
After a company identifies its key performance and growth measures, the firm evaluates potential technologies based on how they will help to achieve its desired level of performance. The organization asks itself critical strategic management questions, including the following: Where are we now? Where do we want to be? What are our strengths? What are our weaknesses? What new opportunities and challenges do we face? What threats and risks do we confront? What is our competition?
Obviously, the company must analyse its current situation thoroughly with a complete understanding of the strengths and limitations of its technological processes, before deciding to make any modifications or changes.
In answering these questions, business must adopt a new and forwardthinking attitude. For example, input from customers and workers must be taken into account and carefully reviewed and analysed before a new vision is forged by the firm. The firm’s major goal should be survival by remaining competitive in the marketplace. Obviously, this cannot be achieved if there is no customer base. Therefore, the needs and expectations of customers must be reasonably satisfied by the firm.
It is becoming increasingly clear that the implementation of new technology offers the best solution in order for firms to remain competitive. The demands of customers are becoming increasingly more difficult to satisfy and conventional manufacturing techniques may often prove to be wholly inadequate. For example, issues and concerns such as flexibility in, and quality of, product design; safety requirements; the environmental movement; reliability, and shorter lead times for the introduction of new products, are better achieved with the use of new technologies. Therefore, it comes as no surprise that most US executives believe that new technology is the most significant factor in improving their firms productivity and competitiveness
(IIE summary on productivity). Yet, it is not easy for an organization to select the appropriate technology in light of the many demands of its customers.
There are several competing technologies that an organization must select from, although technology selections are not necessarily mutually exclusive.
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Hottenstein[11] offers a list of eight factory (technology)-types of the 1980s and
1990s that may lead to competitiveness. This list is summarized below:
(1) Focused factory: narrow range of parts, products and/or processes.
Typically, no more than 300 employees. One, or at most, two competitive priorities. (2) Flexible factory: capable of producing variety of parts, models, or products without the premium costs usually associated with variety.
(3) Six-sigma factory: high quality of output where defects are measured in parts per million.
(4) Quick-response factory: capable of speed and agility in response to customer orders or changes in market direction.
(5) Innovative factory: capable of speed in getting new or improved products into production; sufficiently agile to handle product enhancements without significant process changes.
(6) Automated factory: capable of producing parts or products with little or no direct labour; programmable automation adds flexibility in switching quickly from one product to another.
(7) Extended factory: close, hand-to-hand relationships with customers and/or suppliers through direct communications links and/or liaison teams. (8) Smart factory: computer-integrated facility with expert systems capable of solving complex design, scheduling, and maintenance problems with little or no human intervention.
These factories all have their unique focus, tend to be specialized but lack a systemic and strategic view of the goals of the organization.
Madu and Kuei[6] offer a strategic total quality management (STQM) philosophy which examines and evaluates product quality based on the overall performance of the firm, i.e. the firm must meet the customers’ expectations of product quality and give value while also being environmentally safe; and the company must demonstrate that it is a socially responsible organization. Most firms have the same basic technology, yet some are more successful than others.
The authors conclude that if a firm wants to survive and remain competitive it must adopt the STQM philosophy. STQM applied to the factory of the future can be further broken down into component technologies.
In this article, from the list supplied by Hottenstein[11], the authors further expand on the theory of the six-sigma factory. Also, they examine the STQM factory and the traditional manufacturing practice referred to as the conventional factory. The key question is: how does a company identify the type of factory that must be adopted in order to enable it to achieve it’s desired level of performance? It is clear that due to the many factors involved in this decision and the high risk (including possible financial loss) of making the wrong decision, the varied options available to the firm must be fully articulated to the stakeholders before a decision is reached. Once this type of decision is made, it is not easily reversible and the consequences can be enormous.
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QFD matrix
Quality function deployment (QFD) is a planning tool that is customer-focused.
An organization’s mission and objectives are derived directly by looking at the attributes of customers. Identification of a customers’ attributes is not a simple task and it often involves conducting elaborate market surveys. Statistical tools such as factor analysis are frequently used to identify critical attributes of customers. Once these attributes are identified, QFD can be used to break down customers’ needs into specific corporate goals and tasks. This is done by listing corporate objectives that are needed to satisfy the consumer needs as identified by QFD.
Although the application of QFD has traditionally been strictly focused on redirecting organizational resources to satisfy customers’ needs, its being applied in this study in a slightly different context as a planning tool. Therefore, the intent is to assist a firm in selecting the factory-type that will help it best satisfy its customers’ needs. The firm has different needs and expectations that must be satisfied by adopting the right factory type.
For example some of the company’s needs and expectations are as follows: cash flow needs to be increased; implementation of a strategy of world-class manufacturing that will make the firm competitive; earnings per share must appreciate to maintain investor confidence; employee satisfaction is needed to increase the morale of the workplace and thereby, perhaps, improve quality and productivity; customer service must be flawless if revenue-share is to increase and the firm to remain in business; innovation both in marketing and technology is crucial in order for the company to survive and thrive in today’s environment; and market share should grow if the company is functioning properly and customers are satisfied with its products and service.
Clearly, some of these factors are interdependent. For example, market share cannot grow if customer satisfaction is not achieved. The crucial issue for a firm is to find the best manufacturing philosophy (factory type) that will help it to satisfy reasonably these critical factors. These multifaceted factors cannot be adequately analysed by any model that excludes human judgement, as they are not always purely quantitative. Often, they may involve a mixture of quantitative and qualitative factors thus requiring considerable human input.
Table I is a QFD matrix that compares these manufacturing philosophies to the attributes identified for the firm. The authors illustrate how QFD is actually implemented for this particular problem.
In QFD application, symbols are used to represent the interaction between any two items, for example, i and j. These symbols are defined as follows:
* strong relationship; # some relationship; + possible relationship.
Numerical values are also used to denote these relationships. They are 9, 3, and 1, respectively. Although the symbols used in QFD may be different, the numerical assignments and interpretations are the same.
There is a series of analyses that must take place in order to apply QFD effectively. These five steps are outlined below:
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(1) Assign numerical scores to the critical factors identified by the firm. The score assignment should be based on the relative importance of these factors in achieving the firm’s mission and goals.
(2) Evaluate these manufacturing philosophies or factories in terms of their strategic importance and assign a ratio scale to them. For example, the ratio scale of 5:3:1 used here, may imply a 5/9 probability of using STQM factory to achieve the strategic goals of the firm and a 1/9 probability of using the conventional factory to achieve the goals and mission of the firm. (3) Compute column total (CTj) scores as follows: where Pis are the scores assigned to the critical factors and Rjis are the interaction between the critical factors and the manufacturing philosophies. For example, for
(4) Compute an adjusted column total (ACTj) scores as
ACTj jCTj j i ij i n
= A = A P R
= å
1
STQM factory or CT1 = 9 ´ (2 + 4 + 2 + 2 + 6 + 4 + 1) = 189
CTj i ij i n
P R i n j m
; , , ,
, , ,
= = ¼
= ¼
= å
1
1 2
1 2
Strategic total quality management Six-sigma Conventional factory factory factory Row score
Cash flow * * * 2
World-class manufacturer * * # 4
Earnings per share * * # 2
Employee satisfaction * * + 2
Customer service * # + 6
Innovation * # + 4
Market share * + 1
CT 189 103 48
AJ 5 3 1
ACT 945 309 48
Rank 1 2 3
Notes:
Numerical value of symbols: * = 9; # = 3; + = 1; CT – Column totalJ = ·(RJ * InteractionIJ);
AJ – Strategic importance rating; ACT – Adjusted column totalJ = AJ * CTJ; I – Row index;
J – Column index
Table I.
QFD matrix for business planning
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where Aj is the ratio scale assigned to the manufacturing philosophies.
Therefore, ACT (STQM) = 5 ´ 189 = 945.
(5) Rank the manufacturing philosophies based on their Aj values. Notice that A1 > A2 > A3; so, this is the realized ranking obtained. This proves that the firm should adopt the STQM philosophy in order to achieve its mission and objectives. It is worth noting that the scores obtained here for both the critical factors and the manufacturing philosophies can be obtained systematically. The authors illustrate, later on in the paper, that there is an efficient technique to accomplish this.
Validation through benchmarking
Benchmarking, a method first popularized by Xerox, simply involves learning from the successful management practices of those firms that are leaders in their own industry. However, this does not require that the firm trying to gain this knowledge come from the same industry. For example, a firm specializing in the manufacture of electronics may gain valuable information from the operations of a courier service.
In Figure 1, benchmarking is used to position a firm among its competitors.
For illustration purposes, the hypothetical firm is called Firm C. Firm C is compared with Firms A and B, its major competitors. These firms are then compared based on the critical factors identified as those needed for success in one’s industry. A scale of 1 to 9 is used to rank the position of the firms based on their competitive ability for each of these critical success factors. That matrix is referred to as competitive benchmarking matrix. As Figure 1 illustrates, Firm B is definitely the most competitive among these three firms as it excels in all the critical success factors. With the exception of customer service, Firm C or Firm
A differ widely from Firm B. By summing up the column scores and obtaining the ratio scale for the three firms, the relative competitive positions of Firm A,
B, and C can be determined. This ratio scale is given as 0.148, 0.275 and 0.577, respectively. Although it is clear that Firm B is more competitive than Firm C and Firm C is more competitive than Firm A, other factors need to be evaluated in addition to the critical factors for industry success. For example, the manufacturing and/or management philosophies of the firms needs to be evaluated. The bottom matrix of Figure 1 shows that Firms B, C, and A are presently adopting STQM, six-sigma and conventional manufacturing philosophies. Applying benchmarking theory, it is obvious that the manufacturing practices of Firms C and A must be changed if they intend to be competitive. Changes in their manufacturing philosophies implies that these companies must adopt STQM philosophy. However, adopting this philosophy involves organizational changes such as: changes in organizational culture; work attitudes; management style; technology; and definition of quality. Yet, STQM philosophy is a broad concept that needs to be pragmatized, and therefore, further analysis is needed to break it down specifically into functional parts.
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This also becomes necessary in order to allocate appropriately the limited resources of the firm.
AHP application
To implement STQM philosophy effectively, mutually dependent technologies must be developed or transferred by the firm. The list of technologies that will support the aims of STQM are: environmentally safe technology; computeraided design/computer-aided manufacturing (CAD/CAM); electronic data interchange (EDI); executive information systems (EIS); expert systems (ES) and teleconferencing. There are various factors that influence how the firm should allocate its resources to each of these technologies in order to implement an STQM philosophy. Some of these factors include: relationships with stakeholders; ease of training and implementation of programmes; cost of introducing technology; enhancement of firm’s capabilities; and enhancement of the firm’s competitive position. The analytic hierarchy process (AHP) is used here to evaluate these factors and technologies.
AHP is a systematic procedure to generate priority indices for decision alternatives when multi-criteria are involved. AHP is based on hierarchy building as depicted in Figure 2. Level 1, which is the top hierarchy, deals with the goal of a project. Here, the interest is to develop STQM manufacturing philosophy. Level 2, which is the middle hierarchy, deals with the criteria – what factors will influence the achievement of STQM philosophy. Level 3 deals with decision alternatives – what technologies will enable the firm to develop STQM philosophy in light of the multi-criteria. What is apparently absent, is the fact that sub-goals and sub-criteria can also be integrated in Figure 2.
The AHP theory was developed by Saaty[12] and he, as well as others, have demonstrated the power and utility of AHP in several research studies[3,5,12].
Figure 1.
QFD matrix and benchmarking Cash flow
World-class manufacturer
Earnings per share
Employee satisfaction
Customer service
Innovation
Market share
AC
A
AC
AC
AA
CA
C
C
BBBB
CB
BB
Competitor A
Competitor B
Company C
1 2 3 4 5 6 7 8 9
Scale
Competitive benchmarking
STQM 6–S Con.
QFD
Matrix
B
C
A
STQM 6 CON.
Sigma
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AHP application is based on the use of ratio scale to assign stakeholders’ judgement to a pair of factors under comparison. This scale may be: 1 = equal importance; 3 = moderate importance; 5 = strong importance; 7 = very strong importance; 9 = extreme importance. The even numbers 2, 4, 6 and 8 are for compromise, and reciprocals show inverse comparisons. This method helps to generate priorities in the form of probabilities for these factors. Earlier in this paper, the use of scoring models was discussed; AHP is a more powerful model.
It is, in fact, the only known multi-criteria decision-making model that can measure consistency in a decision maker(s) judgement. This measure is very important since all quality decisions are consistent. AHP is easily implemented through the use of expert choice – a decision-support system program developed for AHP.
Through the use of expert choice to implement stakeholders weight assignments, the results presented in Table II, were obtained.
Figure 2.
Analytical hierarchy process for investment planning Goal: Adopt STQM philosophy
Ease of training and implementation Stakeholders ' relationships Cost of technology Enhancement of firm 's competitive position
Enhancement
of firm 's capabilities Expert systems Executive information systems
Electronic
data interchange Environmentally CAD/CAM safe technologies
Teleconferencing
Criteria decision alternatives Priority indices
Stakeholder’s relationships 0.290
Ease of training and implementation of programs 0.074
Cost of technology 0.082
Enhancement of firm’s capabilities 0.261
Enhancement of firm’s competitive position 0.292
Overall inconsistency index 0.02
Environmentally safe technology 0.255
Computer-aided design/Computer-aided manufacture 0.152
EDI 0.175
Executive information systems 0.166
Expert systems 0.092
Teleconferencing 0.161
Notes:
EDI= electronic data interchange; EIS = executive information systems; ES = expert systems
Table II.
Expert choice – investment planning
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Before proceeding to discuss this result, it should be noted that the overall inconsistency index is 0.02. This shows that stakeholders’ judgements are consistent. It is required that this value be less than 0.1.
Among the five criteria, enhancement of the firm’s competitive position and stakeholders relationships have priority indices of 0.292 and 0.290. These are the major criteria that will influence the choice of technology. Enhancement of the firm’s capabilities is a close third with a priority index of 0.261. The other two factors: ease of training and implementation of programs, and cost of technology, are not as influential in satisfying the goal of the firm which is to adopt STQM philosophy.
By focusing on these three main factors, it can be ascertained that
“environmentally safe” technology seems to be the overwhelming technology of choice for adoption when one looks at stakeholders relationships and takes into account the firm’s competitive position.
However, when looking at a firm’s capabilities, it is apparent that they are not well developed for “environmentally safe” technologies. Overall, however, the decision is made to focus more on environmentally safe technologies, then EDI,
EIS, teleconferencing, CAD/CAM and ES. Obviously, these results are derived by looking at the overall priority indices.
Linear programming application
It is clear that some of these technologies are interdependent. For example, environmentally safe technology may rely on CAD/CAM outputs for its inputs.
For instance, recyclable and biodegradable products may, in fact, be design outputs of CAD/CAM. Also, there is a considerable exchange of information and expertise between the different forms of technologies. An important element to capture is the actual flow of information, materials, and interaction between these technologies. These relationships, negate the reliance on using the priorities derived above through AHP in allocating limited resources to these technologies.
A flow matrix must, therefore, be established to show this dependent relationship between technologies. Such a flow matrix may, in an economic sense, be referred to as an input-output matrix.
Available economic statistics may be used to generate the input-output matrix. Otherwise, the Delphi method could be applied[2]. Suppose that in this example, the following input-output matrix is generated through the use of the
Delphi method:
A A A A A A
A
A
A
A
A
A
A
1 2 3 4 5 6
1
2
3
4
5
6
1 085 0 35 0 17 0 28 0 50 0 16
0 08 1 04 0 25 0 37 0 80 1 00
0 50 0 75 0 80 1 10 0 75 0 18
0 45 0 26 0 38 0 80 0 15 0 20
1 05 0 45 0 60 0 10 0 22
. . . . . .
. . . . . .
. . . . . .
. . . . . .
. . . . .
=
0 30
0 90 0 40 0 75 0 25 0 18 0 40
.
. . . . . . é ë êêêêêêêê ù û úúúúúúúú
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where A1 = environmentally safe technology; A2 = CAD/CAM; A3 = EDI;
A4 = EIS; A5 = ES and A6 = teleconferencing.
This matrix shows the degree to which there is interdependence between any of the pairs of technology (i, j) or within a particular technology. Note that in the previous application of AHP, priority indices were obtained and referred to as a vector (l):
To obtain a dependence vector (a), let A be a matrix of size n, i denotes the rows and j denotes the columns in A. aij represents the cells in matrix A. Then, dependence vector (at) can be expressed as:
For example,
With a obtained, the firm’s limited resources can now be allocated. Suppose that the firm has $100 million to invest on all these technologies. For illustration purposes, this is called R and the following requirements Ri (in millions of dollars) are demanded by the technologies as shown in Table III.
We notice that the total requirement of $107 million exceeds the allocated funds of $100 million. Let Wbe a vector that represents the decision variables in a1 = l1 [l1A11 + l2 A12 + l3 A13 + l4 A14 + l5 A15 + l 6 A16 ]
= 0.255 [ 0.255(1.085 ) + 0.152(0.35 ) + 0.175(0.17 ) + 0.166(0.28 )
+ 0.092(0.50 ) + 0.161(0.16 )]
= 0.1219.
So,
a =
0.122
0.079
0.116
0.066
0.048
0.088 é ë êêêêêêêêêê ù û úúúúúúúúúú
.
ai = l i lj aij j =1 nå "i . l .
.
.
.
.
.
= . é ë êêêêêêêê ù û úúúúúúúú
0 255
0 152
0 175
0 166
0 092
0 161
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linear programming. In other words, it will represent the allocations made to the different technologies. Therefore, the objective is to:
This LP problem is easily solved by using a “greedy” heuristic search algorithm. This is implemented by going through the a-vector to find the weights of each technology type. The one with the highest weight gets the first priority. It is assigned all its demands if there are enough resources to meet its demand. Thus, for example, environmentally safe technology with a weight of
0.122 will get its full requirement of $10 million. Move now to teleconferencing and see if there are enough funds to allocate the $10 million it demands. The balance now is $53 million. The next to consider is CAD/CAM which demands
$25 million, therefore, it too gets its full requirement. With $28 million left ElS is next and it demands $20 million, so, it also gets its full requirement. A total of
$8 million is now left and ES is the only unallocated technology. It demands $15 million but due to the unavailability of funds, it receives only the $8 million available. Notice that with this approach, those technologies with higher interdependent relationships will get the highest priorities in the allocation plan. It is also possible that in some cases, some technologies or projects may not be allocated any funds. Suppose for example, that any of the higher priority technologies such as CAD/CAM had demanded $8 million more than originally allocated; ES could not be allocated any funds.
Conclusions
In this paper, the authors discuss the problems of traditional cost-accounting principles and how they influence the adoption of total quality management
(TQM). Clearly, in order to achieve TQM, process transformation must take
Maximize a TW such that
W
R
R
W i i i 0
1
£ £ å = .
Technology Resource requirement
Ai Ri
A1 27
A2 25
A3 10
A4 20
A5 15
A6 10
Total 107
Table III.
Requirement of technologies IJQRM
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In this paper, strategic variables have been identified and analysed using quality function deployment and the analytic hierarchy process. The paper has also demonstrated how resource allocation decisions can be made through the application of linear programming.
The systematic and holistic procedure developed by the authors views the environment of a company as dynamic and ever-changing and takes into account the fact that organizational decision making often involves human inputs and is done as a reaction to competitors’ actions. Therefore, direct cost is not the only factor that influences technology decisions. Traditional costaccounting techniques seem unable to deal with this fact. A competitive benchmarking matrix has been used to show how a firm can assess its competitive position, react to it and move in the right direction without solely weighing the investment costs of technology.
References
1. Harris, T.G., “Fad-surfers, risk-dodgers, and beloved companies”, Harvard Business
Review, January-February 1993, pp. 7-9.
2. Madu, C.N., Kuei, C.H. and Madu, A.N., “Establishing priorities for the information technology industry in Taiwan – a Delphi approach”, Long Range Planning, Vol. 24 No. 5,
1991, pp. 105-18.
3. Madu, C.N. and Georgantzas, N.C., “Strategic thrust of manufacturing automation decisions: a conceptual framework”, IIE Transaction, Vol. 23 No. 2, 1991, pp. 138-48.
4. Krinsky, I. and Miltenburg, J., “Alternate method for the justification of advanced manufacturing technologies”, International Journal of Production Research, Vol. 29 No. 5,
1991, pp. 997-1015.
5. Madu, C.N., “A quality confidence procedure for GDSS application in multi-criteria decision-making”, IIE Transactions, (forthcoming).
6. Madu, C.N. and Kuei, C.H., “Strategic total quality management”, in Madu, C.N. (Ed.),
Management of New Technologies for Global Competitiveness, Quorum Books, Westport,
CT, 1993.
7. Madu, C.N. and Kuei, C.H., “Introducing strategic quality management”, Long Range
Planning, Vol. 26 No. 6, 1993, pp. 121-31.
8. Harrison, E.B., Going Green: How to Communicate Your Company’s Environmental
Commitment, Business One, Irwin, Homewood, IL, 1993.
9. Madu, C.N. and Kuei, C.H., “Strategies for global competitiveness”, in Madu, C.N. (Ed.),
Management of New Technologies for Global Competitiveness, Quorum Books, Westport,
CT, 1993.
10. Eccles, R. and Pyburn, P.J., “Creating a comprehensive system to measure performance”,
Management Accounting, October 1991, pp. 41-4.
11. Hottenstein, M., Production and Operation Management, Doctoral Consortium of 1991,
Academy of Management.
12. Saaty, T.L., The Analytic Hierarchy Process, McGraw-Hill, New York, NY, 1980.
References: CT, 1993. 8. Harrison, E.B., Going Green: How to Communicate Your Company’s Environmental Commitment, Business One, Irwin, Homewood, IL, 1993. CT, 1993. 12. Saaty, T.L., The Analytic Hierarchy Process, McGraw-Hill, New York, NY, 1980.
Christian N. Madu, John Aheto and Chu-Hua Kuei
Lubin School of Business, Pace University, New York, USA
Dena Winokur
Marketing Department, Pace University, New York, USA
Introduction
In today’s competitive environment, quality is the key to an organization’s success and survival. To compete effectively, companies must embrace the principles of total quality management (TQM) and incorporate them into all of their activities. TQM calls for continuous improvement – a never-ending philosophy of change for the better. Thus, companies planning for their future survival should be flexible and willing to accept change as inevitable, and even desirable. This concept leads to the question of what role cost-accounting practices play in cost control and whether the traditional methods for controlling costs in a company hinder or support total quality efforts. Theoretically, it can be argued that traditional cost-accounting practices which utilize net present value (NPV), payback period, internal rate of return (IRR), and so on, may actually hinder the implementation of TQM. Influences of traditional cost-accounting practices on
TQM are described as follows:
• TQM relies heavily on process changes. Many companies have turned to the use of information technology in their pursuit of quality. One illustration is the increasing use of expert systems and artificial intelligence techniques which, when applied to a manufacturing setting, leads to significant improvements in quality. Another example is the use of flexible computer-integrated manufacturing systems to improve product quality and productivity.
Unfortunately, many organizations still concentrate on short-term goals and objectives which create a bias against new and more efficient technologies. In most goal-oriented businesses, automation has been found to be more effective over the long term than the use of direct labour. Yet, among service providers, when alternative technologies or manufacturing techniques are considered for selection and adoption, the overriding emphasis is still on short-term costs and returns.
International Journal of Quality
& Reliability Management,
Vol. 13 No. 3, 1996, pp. 57-72,
© MCB University Press,
0265-671X
Received 25 March 1994
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• Traditional cost accounting techniques focus on short-term rather than long-term goals and objectives. This emphasis on controlling costs without relating them to the long-term value additives of an attribute of any project may often lead to the elimination of those attributes whose effects may be in the long-term best interests of the organization. For example, quality improvement could be achieved by a manufacturer if the company is flexible and responds swiftly to changes in demand.
Time-based competitive management is so critical to the survival of industry today that it is difficult to provide quality services in its absence. In order to provide quality services, the manufacturer must adopt just-in-time management theory and develop a quality relationship with the company’s suppliers and vendors. In addition, it may be necessary to restructure the organization, thereby, retraining workers and adopting and managing new technologies. However, all these changes can be time-consuming and expensive.
If the manufacturer compares new technological processes with that of existing technology but does not have a good sense of the benefits of such new technology (such as improved corporate image, market expansion, responsiveness to market demands, and others that may not be as easily identifiable), it may never lead to the adoption of these new techniques. The company’s short-term focus on traditional cost control may, therefore, cause it to miss this important opportunity.
By focusing on long-term goals and objectives, the firm will be better able to: compete; provide quality services and products; develop a positive corporate image; respond in a timely manner to changes in the marketplace; and better control costs over the long term owing to the development of a more efficient production system which reduces wastes, reworks and scraps. More importantly, the firm’s survival is ensured, it expands its market share and becomes socially responsible by enriching the jobs of its workers. By expanding its job base, as its market share grows, it provides needed services to its customers, and effectively manages its limited resources.
• TQM is heavily embedded in the concept of continuous improvement.
This is a never ending process – a continual process of change. While change is inevitable, a firm employing TQM must learn to accept it and continue to work toward continuous improvement. However, this is not a simple process, as it may require structural, organizational, cultural and process transformation.
Yet the cost of these changes may not be seen as justifiable if viewed only from the short term. If a firm is surviving and making satisfactory profits, a status-quo mentality will tend to prevail. A long-term perspective must be taken, one that takes into account all the values of the quality imperatives administered by a firm before these changes could be effectively evaluated. Any attempt towards cost control must be coupled with an analysis of the long-term goals, objectives and vision of the firm.
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A thorough marketing audit of the firm must be conducted to determine its strengths, weaknesses, opportunities for future growth and threats to its survival. It is also important to understand how a firm is positioned in its industry in order to develop a more effective competitive strategy. Every organization must have a vision for the future and it should be able to answer the question: “Where do we want to be X number of years from now?” In the absence of such vision, the firm is bound to fail. Cost control is ineffective if it fails to reinforce the vision of the firm and justify why a costly investment in technology may be the key to the company’s survival in the future. An outward look should also be projected to benchmark the firm with leaders in other industries. Innovation is the key to success in a dynamic and rapidly changing environment. Product life cycles are much shorter in today’s environment and competition is much greater. The strategic importance of an investment is a crucial factor in the success of the company. For example,
Harris[1] notes that “the most obvious cost of not investing is lost opportunity. If you don’t make the investment, your competitors probably will, and in so doing will gain the early-mover advantages that you’ve passed up: early profits, superior access to customers, and valuable patents”.
Harris[1] further explains the strategic importance of investment from the viewpoint of competitors, employees, buyers, and suppliers. He notes that “the perceptual costs of not investing won’t flash red on your financial statements, nor will the lost opportunity costs. But they can wound your company as badly as money sunk in a bum investment”.
Clearly, traditional cost-accounting methods, principles, and practices tend to overemphasize quantitative factors, frequently at the expense of intangibles. These intangibles often have a direct impact on profitability.
The continuing role of traditional cost-accounting principles in decision making needs to be expanded to integrate less quantitative factors.
One method by which this can be accomplished is by combining traditional cost-accounting techniques such as NPV, IRR, with multicriteria decision-making models. Although several papers have presented similar concepts relating to the management of new technologies[2-5], TQM application/practice as the principal goal of a firm has not been explored.
Strategic planning process
The strategic planning process demands that a holistic view of technology selection be adopted, i.e. a determination must be made as to what will be the value additive of the new technology to the organization’s operations. The issue of “value” is very important since some value additives cannot be easily assessed by looking at the direct investment costs related to the new technology.
For example, strategic planning and implementation is effective only when commissioned and actively supported by top management.
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Top management has the power and the resources to direct effectively a team approach to solve organizational problems. It is top management’s responsibility to form an interdisciplinary team that will fully analyse organizational problems, review the company’s resources and limitations, its vision and mission, and appropriately define the strategies needed to achieve organizational goals. None of these can be achieved without top management’s commitment and support.
Strategic challenges
It is clear in today’s turbulent environment that an organization’s survival depends on its ability to satisfy customers’ wants and needs and to compete effectively in global markets. But, to compete effectively, the organization must respond to the dynamic changes that are taking place in its own internal environment. Obviously, the ability to meet these new challenges involves decisions as to the selection of new technology. Some of the challenges currently faced by industry include:
• Marketing of “green”, or environmentally safe, products. The environmental movement has become a global institution. Consumers are concerned about the possible negative impact that products or processes have on the environment. They do not want to be perceived as contributing to the problem and therefore, many will not patronize companies which they believe are producing environmentally unsafe products. Madu and Kuei[6,7] note that environmental quality has become a critical competitive element in business. Harrison[8] notes that the following trends will force organizations to become environmentally oriented – what he calls the AMP formula (Activists + Media +
Politicians), more litigation, an increase in penalties for corporate executives, investor activism and media scrutiny
Many of Japan’s industries have already realized the importance of this emerging trend and are spending heavily on research and development to produce environmentally safe technologies that will help them capture this growing market niche.
• Information systems technology is a critical area that cannot be ignored[9]. The world is getting smaller as a result of the spread of information technology. Communication barriers are being broken and strategic alliances are being formed across nations. The focus on global marketing and global competition cannot be achieved if information technology remains at a primitive level. In today’s market environment, timing is the key to competitiveness. Information has to be made available on a real-time basis whether it is on the assembly line floor or in a global setting.
• Computer-integrated systems – the advent of modern computer systems has contributed immensely to the swift introduction of new products into the marketplace. Simulated product designs and quality specifications
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can be evaluated and potential problems easily identified and corrected.
Test marketing can also be accomplished in a cost-efficient manner.
No longer do companies have to depend on the mass production system alone as a means of achieving economies of scale in production.
The advent of new computer integrated systems such as FMS, which can assist in producing orders for products requiting flexible designs, as specified by customers, can be accomplished at competitive prices.
Companies, therefore, do not have to depend on the mass production system alone as a means of achieving economies of scale in production.
These factors are just a few of the many reasons why simple quantitative approaches such as NPV, payback period, and ROI (return on investment) may not be appropriate to use in today’s dynamic environment. Clearly, these techniques emphasize the direct cost of a project and may not take into account the long-term benefits that accrue to a firm through the implementation of these new technologies.
Identifying strategic factors
The essence of a planning matrix is to build a critical list of factors that will help the firm strengthen its competitive position. This list often includes the organization’s key performance measures. While there are several ways of identifying these key factors, the authors choose to describe two of them.
Statistical analysis
Statistical analysis involves the analysis of industrial data to determine factors which may significantly impact a firm’s sales volume or predict how well the firm is doing in relation to its competitors. Through statistical analysis, it can be determined that the following factors are those that influence a firm’s performance and growth: case flow (CF); world-class manufacturing (WCM); earnings per share (EPS); employee satisfaction (ES); customer service (CS); innovation (I); and market share (MS).
This method is very objective and quite reliable and may involve human input through the use of survey questionnaires when adequate industrial data is not available.
Scoring models
Scoring models depend on the judgement and input of stakeholders.
Stakeholders are defined as members of groups who are directly or indirectly impacted by an organization’s performance. Scoring models are simple to use, but in order for the results to be valid, stakeholders must be knowledgeable about the problems facing the company and be able to make well thought-out, rational decisions about the several performance measures identified in the model. Frequently, this involves the scoring of a pair of factors in terms of their relative importance towards achieving the firm’s mission or goals.
While scoring models are easy to conceptualize, they are often biased and inconsistent. Once a bias is detected, the whole process becomes flawed and the decisions made based on the model, may not help the firm to achieve its goals.
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This, however, does not imply that qualitative decisions are a guaranteed outcome even when there is consistency among stakeholders. The chances of making quality decisions are enhanced only when the stakeholders are rational, in addition to consistent, in their judgements. Therefore, there must be a systematic way of identifying performance measures.
For the sake of brevity, the authors assume that a statistical analysis of a particular industry will yield the following factors: cash flow; world class manufacturing; earnings per share; employee satisfaction; customer service; innovation; and market share; which are determining factors for the success and growth of a firm in any industry. Actually, many of these factors have been identified by other researchers as key factors in measuring success in manufacturing firms[4,10].
Developing technological strategies
After a company identifies its key performance and growth measures, the firm evaluates potential technologies based on how they will help to achieve its desired level of performance. The organization asks itself critical strategic management questions, including the following: Where are we now? Where do we want to be? What are our strengths? What are our weaknesses? What new opportunities and challenges do we face? What threats and risks do we confront? What is our competition?
Obviously, the company must analyse its current situation thoroughly with a complete understanding of the strengths and limitations of its technological processes, before deciding to make any modifications or changes.
In answering these questions, business must adopt a new and forwardthinking attitude. For example, input from customers and workers must be taken into account and carefully reviewed and analysed before a new vision is forged by the firm. The firm’s major goal should be survival by remaining competitive in the marketplace. Obviously, this cannot be achieved if there is no customer base. Therefore, the needs and expectations of customers must be reasonably satisfied by the firm.
It is becoming increasingly clear that the implementation of new technology offers the best solution in order for firms to remain competitive. The demands of customers are becoming increasingly more difficult to satisfy and conventional manufacturing techniques may often prove to be wholly inadequate. For example, issues and concerns such as flexibility in, and quality of, product design; safety requirements; the environmental movement; reliability, and shorter lead times for the introduction of new products, are better achieved with the use of new technologies. Therefore, it comes as no surprise that most US executives believe that new technology is the most significant factor in improving their firms productivity and competitiveness
(IIE summary on productivity). Yet, it is not easy for an organization to select the appropriate technology in light of the many demands of its customers.
There are several competing technologies that an organization must select from, although technology selections are not necessarily mutually exclusive.
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Hottenstein[11] offers a list of eight factory (technology)-types of the 1980s and
1990s that may lead to competitiveness. This list is summarized below:
(1) Focused factory: narrow range of parts, products and/or processes.
Typically, no more than 300 employees. One, or at most, two competitive priorities. (2) Flexible factory: capable of producing variety of parts, models, or products without the premium costs usually associated with variety.
(3) Six-sigma factory: high quality of output where defects are measured in parts per million.
(4) Quick-response factory: capable of speed and agility in response to customer orders or changes in market direction.
(5) Innovative factory: capable of speed in getting new or improved products into production; sufficiently agile to handle product enhancements without significant process changes.
(6) Automated factory: capable of producing parts or products with little or no direct labour; programmable automation adds flexibility in switching quickly from one product to another.
(7) Extended factory: close, hand-to-hand relationships with customers and/or suppliers through direct communications links and/or liaison teams. (8) Smart factory: computer-integrated facility with expert systems capable of solving complex design, scheduling, and maintenance problems with little or no human intervention.
These factories all have their unique focus, tend to be specialized but lack a systemic and strategic view of the goals of the organization.
Madu and Kuei[6] offer a strategic total quality management (STQM) philosophy which examines and evaluates product quality based on the overall performance of the firm, i.e. the firm must meet the customers’ expectations of product quality and give value while also being environmentally safe; and the company must demonstrate that it is a socially responsible organization. Most firms have the same basic technology, yet some are more successful than others.
The authors conclude that if a firm wants to survive and remain competitive it must adopt the STQM philosophy. STQM applied to the factory of the future can be further broken down into component technologies.
In this article, from the list supplied by Hottenstein[11], the authors further expand on the theory of the six-sigma factory. Also, they examine the STQM factory and the traditional manufacturing practice referred to as the conventional factory. The key question is: how does a company identify the type of factory that must be adopted in order to enable it to achieve it’s desired level of performance? It is clear that due to the many factors involved in this decision and the high risk (including possible financial loss) of making the wrong decision, the varied options available to the firm must be fully articulated to the stakeholders before a decision is reached. Once this type of decision is made, it is not easily reversible and the consequences can be enormous.
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QFD matrix
Quality function deployment (QFD) is a planning tool that is customer-focused.
An organization’s mission and objectives are derived directly by looking at the attributes of customers. Identification of a customers’ attributes is not a simple task and it often involves conducting elaborate market surveys. Statistical tools such as factor analysis are frequently used to identify critical attributes of customers. Once these attributes are identified, QFD can be used to break down customers’ needs into specific corporate goals and tasks. This is done by listing corporate objectives that are needed to satisfy the consumer needs as identified by QFD.
Although the application of QFD has traditionally been strictly focused on redirecting organizational resources to satisfy customers’ needs, its being applied in this study in a slightly different context as a planning tool. Therefore, the intent is to assist a firm in selecting the factory-type that will help it best satisfy its customers’ needs. The firm has different needs and expectations that must be satisfied by adopting the right factory type.
For example some of the company’s needs and expectations are as follows: cash flow needs to be increased; implementation of a strategy of world-class manufacturing that will make the firm competitive; earnings per share must appreciate to maintain investor confidence; employee satisfaction is needed to increase the morale of the workplace and thereby, perhaps, improve quality and productivity; customer service must be flawless if revenue-share is to increase and the firm to remain in business; innovation both in marketing and technology is crucial in order for the company to survive and thrive in today’s environment; and market share should grow if the company is functioning properly and customers are satisfied with its products and service.
Clearly, some of these factors are interdependent. For example, market share cannot grow if customer satisfaction is not achieved. The crucial issue for a firm is to find the best manufacturing philosophy (factory type) that will help it to satisfy reasonably these critical factors. These multifaceted factors cannot be adequately analysed by any model that excludes human judgement, as they are not always purely quantitative. Often, they may involve a mixture of quantitative and qualitative factors thus requiring considerable human input.
Table I is a QFD matrix that compares these manufacturing philosophies to the attributes identified for the firm. The authors illustrate how QFD is actually implemented for this particular problem.
In QFD application, symbols are used to represent the interaction between any two items, for example, i and j. These symbols are defined as follows:
* strong relationship; # some relationship; + possible relationship.
Numerical values are also used to denote these relationships. They are 9, 3, and 1, respectively. Although the symbols used in QFD may be different, the numerical assignments and interpretations are the same.
There is a series of analyses that must take place in order to apply QFD effectively. These five steps are outlined below:
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(1) Assign numerical scores to the critical factors identified by the firm. The score assignment should be based on the relative importance of these factors in achieving the firm’s mission and goals.
(2) Evaluate these manufacturing philosophies or factories in terms of their strategic importance and assign a ratio scale to them. For example, the ratio scale of 5:3:1 used here, may imply a 5/9 probability of using STQM factory to achieve the strategic goals of the firm and a 1/9 probability of using the conventional factory to achieve the goals and mission of the firm. (3) Compute column total (CTj) scores as follows: where Pis are the scores assigned to the critical factors and Rjis are the interaction between the critical factors and the manufacturing philosophies. For example, for
(4) Compute an adjusted column total (ACTj) scores as
ACTj jCTj j i ij i n
= A = A P R
= å
1
STQM factory or CT1 = 9 ´ (2 + 4 + 2 + 2 + 6 + 4 + 1) = 189
CTj i ij i n
P R i n j m
; , , ,
, , ,
= = ¼
= ¼
= å
1
1 2
1 2
Strategic total quality management Six-sigma Conventional factory factory factory Row score
Cash flow * * * 2
World-class manufacturer * * # 4
Earnings per share * * # 2
Employee satisfaction * * + 2
Customer service * # + 6
Innovation * # + 4
Market share * + 1
CT 189 103 48
AJ 5 3 1
ACT 945 309 48
Rank 1 2 3
Notes:
Numerical value of symbols: * = 9; # = 3; + = 1; CT – Column totalJ = ·(RJ * InteractionIJ);
AJ – Strategic importance rating; ACT – Adjusted column totalJ = AJ * CTJ; I – Row index;
J – Column index
Table I.
QFD matrix for business planning
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where Aj is the ratio scale assigned to the manufacturing philosophies.
Therefore, ACT (STQM) = 5 ´ 189 = 945.
(5) Rank the manufacturing philosophies based on their Aj values. Notice that A1 > A2 > A3; so, this is the realized ranking obtained. This proves that the firm should adopt the STQM philosophy in order to achieve its mission and objectives. It is worth noting that the scores obtained here for both the critical factors and the manufacturing philosophies can be obtained systematically. The authors illustrate, later on in the paper, that there is an efficient technique to accomplish this.
Validation through benchmarking
Benchmarking, a method first popularized by Xerox, simply involves learning from the successful management practices of those firms that are leaders in their own industry. However, this does not require that the firm trying to gain this knowledge come from the same industry. For example, a firm specializing in the manufacture of electronics may gain valuable information from the operations of a courier service.
In Figure 1, benchmarking is used to position a firm among its competitors.
For illustration purposes, the hypothetical firm is called Firm C. Firm C is compared with Firms A and B, its major competitors. These firms are then compared based on the critical factors identified as those needed for success in one’s industry. A scale of 1 to 9 is used to rank the position of the firms based on their competitive ability for each of these critical success factors. That matrix is referred to as competitive benchmarking matrix. As Figure 1 illustrates, Firm B is definitely the most competitive among these three firms as it excels in all the critical success factors. With the exception of customer service, Firm C or Firm
A differ widely from Firm B. By summing up the column scores and obtaining the ratio scale for the three firms, the relative competitive positions of Firm A,
B, and C can be determined. This ratio scale is given as 0.148, 0.275 and 0.577, respectively. Although it is clear that Firm B is more competitive than Firm C and Firm C is more competitive than Firm A, other factors need to be evaluated in addition to the critical factors for industry success. For example, the manufacturing and/or management philosophies of the firms needs to be evaluated. The bottom matrix of Figure 1 shows that Firms B, C, and A are presently adopting STQM, six-sigma and conventional manufacturing philosophies. Applying benchmarking theory, it is obvious that the manufacturing practices of Firms C and A must be changed if they intend to be competitive. Changes in their manufacturing philosophies implies that these companies must adopt STQM philosophy. However, adopting this philosophy involves organizational changes such as: changes in organizational culture; work attitudes; management style; technology; and definition of quality. Yet, STQM philosophy is a broad concept that needs to be pragmatized, and therefore, further analysis is needed to break it down specifically into functional parts.
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This also becomes necessary in order to allocate appropriately the limited resources of the firm.
AHP application
To implement STQM philosophy effectively, mutually dependent technologies must be developed or transferred by the firm. The list of technologies that will support the aims of STQM are: environmentally safe technology; computeraided design/computer-aided manufacturing (CAD/CAM); electronic data interchange (EDI); executive information systems (EIS); expert systems (ES) and teleconferencing. There are various factors that influence how the firm should allocate its resources to each of these technologies in order to implement an STQM philosophy. Some of these factors include: relationships with stakeholders; ease of training and implementation of programmes; cost of introducing technology; enhancement of firm’s capabilities; and enhancement of the firm’s competitive position. The analytic hierarchy process (AHP) is used here to evaluate these factors and technologies.
AHP is a systematic procedure to generate priority indices for decision alternatives when multi-criteria are involved. AHP is based on hierarchy building as depicted in Figure 2. Level 1, which is the top hierarchy, deals with the goal of a project. Here, the interest is to develop STQM manufacturing philosophy. Level 2, which is the middle hierarchy, deals with the criteria – what factors will influence the achievement of STQM philosophy. Level 3 deals with decision alternatives – what technologies will enable the firm to develop STQM philosophy in light of the multi-criteria. What is apparently absent, is the fact that sub-goals and sub-criteria can also be integrated in Figure 2.
The AHP theory was developed by Saaty[12] and he, as well as others, have demonstrated the power and utility of AHP in several research studies[3,5,12].
Figure 1.
QFD matrix and benchmarking Cash flow
World-class manufacturer
Earnings per share
Employee satisfaction
Customer service
Innovation
Market share
AC
A
AC
AC
AA
CA
C
C
BBBB
CB
BB
Competitor A
Competitor B
Company C
1 2 3 4 5 6 7 8 9
Scale
Competitive benchmarking
STQM 6–S Con.
QFD
Matrix
B
C
A
STQM 6 CON.
Sigma
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AHP application is based on the use of ratio scale to assign stakeholders’ judgement to a pair of factors under comparison. This scale may be: 1 = equal importance; 3 = moderate importance; 5 = strong importance; 7 = very strong importance; 9 = extreme importance. The even numbers 2, 4, 6 and 8 are for compromise, and reciprocals show inverse comparisons. This method helps to generate priorities in the form of probabilities for these factors. Earlier in this paper, the use of scoring models was discussed; AHP is a more powerful model.
It is, in fact, the only known multi-criteria decision-making model that can measure consistency in a decision maker(s) judgement. This measure is very important since all quality decisions are consistent. AHP is easily implemented through the use of expert choice – a decision-support system program developed for AHP.
Through the use of expert choice to implement stakeholders weight assignments, the results presented in Table II, were obtained.
Figure 2.
Analytical hierarchy process for investment planning Goal: Adopt STQM philosophy
Ease of training and implementation Stakeholders ' relationships Cost of technology Enhancement of firm 's competitive position
Enhancement
of firm 's capabilities Expert systems Executive information systems
Electronic
data interchange Environmentally CAD/CAM safe technologies
Teleconferencing
Criteria decision alternatives Priority indices
Stakeholder’s relationships 0.290
Ease of training and implementation of programs 0.074
Cost of technology 0.082
Enhancement of firm’s capabilities 0.261
Enhancement of firm’s competitive position 0.292
Overall inconsistency index 0.02
Environmentally safe technology 0.255
Computer-aided design/Computer-aided manufacture 0.152
EDI 0.175
Executive information systems 0.166
Expert systems 0.092
Teleconferencing 0.161
Notes:
EDI= electronic data interchange; EIS = executive information systems; ES = expert systems
Table II.
Expert choice – investment planning
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Before proceeding to discuss this result, it should be noted that the overall inconsistency index is 0.02. This shows that stakeholders’ judgements are consistent. It is required that this value be less than 0.1.
Among the five criteria, enhancement of the firm’s competitive position and stakeholders relationships have priority indices of 0.292 and 0.290. These are the major criteria that will influence the choice of technology. Enhancement of the firm’s capabilities is a close third with a priority index of 0.261. The other two factors: ease of training and implementation of programs, and cost of technology, are not as influential in satisfying the goal of the firm which is to adopt STQM philosophy.
By focusing on these three main factors, it can be ascertained that
“environmentally safe” technology seems to be the overwhelming technology of choice for adoption when one looks at stakeholders relationships and takes into account the firm’s competitive position.
However, when looking at a firm’s capabilities, it is apparent that they are not well developed for “environmentally safe” technologies. Overall, however, the decision is made to focus more on environmentally safe technologies, then EDI,
EIS, teleconferencing, CAD/CAM and ES. Obviously, these results are derived by looking at the overall priority indices.
Linear programming application
It is clear that some of these technologies are interdependent. For example, environmentally safe technology may rely on CAD/CAM outputs for its inputs.
For instance, recyclable and biodegradable products may, in fact, be design outputs of CAD/CAM. Also, there is a considerable exchange of information and expertise between the different forms of technologies. An important element to capture is the actual flow of information, materials, and interaction between these technologies. These relationships, negate the reliance on using the priorities derived above through AHP in allocating limited resources to these technologies.
A flow matrix must, therefore, be established to show this dependent relationship between technologies. Such a flow matrix may, in an economic sense, be referred to as an input-output matrix.
Available economic statistics may be used to generate the input-output matrix. Otherwise, the Delphi method could be applied[2]. Suppose that in this example, the following input-output matrix is generated through the use of the
Delphi method:
A A A A A A
A
A
A
A
A
A
A
1 2 3 4 5 6
1
2
3
4
5
6
1 085 0 35 0 17 0 28 0 50 0 16
0 08 1 04 0 25 0 37 0 80 1 00
0 50 0 75 0 80 1 10 0 75 0 18
0 45 0 26 0 38 0 80 0 15 0 20
1 05 0 45 0 60 0 10 0 22
. . . . . .
. . . . . .
. . . . . .
. . . . . .
. . . . .
=
0 30
0 90 0 40 0 75 0 25 0 18 0 40
.
. . . . . . é ë êêêêêêêê ù û úúúúúúúú
IJQRM
13,3
70
where A1 = environmentally safe technology; A2 = CAD/CAM; A3 = EDI;
A4 = EIS; A5 = ES and A6 = teleconferencing.
This matrix shows the degree to which there is interdependence between any of the pairs of technology (i, j) or within a particular technology. Note that in the previous application of AHP, priority indices were obtained and referred to as a vector (l):
To obtain a dependence vector (a), let A be a matrix of size n, i denotes the rows and j denotes the columns in A. aij represents the cells in matrix A. Then, dependence vector (at) can be expressed as:
For example,
With a obtained, the firm’s limited resources can now be allocated. Suppose that the firm has $100 million to invest on all these technologies. For illustration purposes, this is called R and the following requirements Ri (in millions of dollars) are demanded by the technologies as shown in Table III.
We notice that the total requirement of $107 million exceeds the allocated funds of $100 million. Let Wbe a vector that represents the decision variables in a1 = l1 [l1A11 + l2 A12 + l3 A13 + l4 A14 + l5 A15 + l 6 A16 ]
= 0.255 [ 0.255(1.085 ) + 0.152(0.35 ) + 0.175(0.17 ) + 0.166(0.28 )
+ 0.092(0.50 ) + 0.161(0.16 )]
= 0.1219.
So,
a =
0.122
0.079
0.116
0.066
0.048
0.088 é ë êêêêêêêêêê ù û úúúúúúúúúú
.
ai = l i lj aij j =1 nå "i . l .
.
.
.
.
.
= . é ë êêêêêêêê ù û úúúúúúúú
0 255
0 152
0 175
0 166
0 092
0 161
Decision
analysis model for TQM
71
linear programming. In other words, it will represent the allocations made to the different technologies. Therefore, the objective is to:
This LP problem is easily solved by using a “greedy” heuristic search algorithm. This is implemented by going through the a-vector to find the weights of each technology type. The one with the highest weight gets the first priority. It is assigned all its demands if there are enough resources to meet its demand. Thus, for example, environmentally safe technology with a weight of
0.122 will get its full requirement of $10 million. Move now to teleconferencing and see if there are enough funds to allocate the $10 million it demands. The balance now is $53 million. The next to consider is CAD/CAM which demands
$25 million, therefore, it too gets its full requirement. With $28 million left ElS is next and it demands $20 million, so, it also gets its full requirement. A total of
$8 million is now left and ES is the only unallocated technology. It demands $15 million but due to the unavailability of funds, it receives only the $8 million available. Notice that with this approach, those technologies with higher interdependent relationships will get the highest priorities in the allocation plan. It is also possible that in some cases, some technologies or projects may not be allocated any funds. Suppose for example, that any of the higher priority technologies such as CAD/CAM had demanded $8 million more than originally allocated; ES could not be allocated any funds.
Conclusions
In this paper, the authors discuss the problems of traditional cost-accounting principles and how they influence the adoption of total quality management
(TQM). Clearly, in order to achieve TQM, process transformation must take
Maximize a TW such that
W
R
R
W i i i 0
1
£ £ å = .
Technology Resource requirement
Ai Ri
A1 27
A2 25
A3 10
A4 20
A5 15
A6 10
Total 107
Table III.
Requirement of technologies IJQRM
13,3
72 place. Appropriate new technology that is supportive of the practices of TQM must be adopted. Making the right decision about the choice of new technologies involves the careful analysis of several strategic variables.
In this paper, strategic variables have been identified and analysed using quality function deployment and the analytic hierarchy process. The paper has also demonstrated how resource allocation decisions can be made through the application of linear programming.
The systematic and holistic procedure developed by the authors views the environment of a company as dynamic and ever-changing and takes into account the fact that organizational decision making often involves human inputs and is done as a reaction to competitors’ actions. Therefore, direct cost is not the only factor that influences technology decisions. Traditional costaccounting techniques seem unable to deal with this fact. A competitive benchmarking matrix has been used to show how a firm can assess its competitive position, react to it and move in the right direction without solely weighing the investment costs of technology.
References
1. Harris, T.G., “Fad-surfers, risk-dodgers, and beloved companies”, Harvard Business
Review, January-February 1993, pp. 7-9.
2. Madu, C.N., Kuei, C.H. and Madu, A.N., “Establishing priorities for the information technology industry in Taiwan – a Delphi approach”, Long Range Planning, Vol. 24 No. 5,
1991, pp. 105-18.
3. Madu, C.N. and Georgantzas, N.C., “Strategic thrust of manufacturing automation decisions: a conceptual framework”, IIE Transaction, Vol. 23 No. 2, 1991, pp. 138-48.
4. Krinsky, I. and Miltenburg, J., “Alternate method for the justification of advanced manufacturing technologies”, International Journal of Production Research, Vol. 29 No. 5,
1991, pp. 997-1015.
5. Madu, C.N., “A quality confidence procedure for GDSS application in multi-criteria decision-making”, IIE Transactions, (forthcoming).
6. Madu, C.N. and Kuei, C.H., “Strategic total quality management”, in Madu, C.N. (Ed.),
Management of New Technologies for Global Competitiveness, Quorum Books, Westport,
CT, 1993.
7. Madu, C.N. and Kuei, C.H., “Introducing strategic quality management”, Long Range
Planning, Vol. 26 No. 6, 1993, pp. 121-31.
8. Harrison, E.B., Going Green: How to Communicate Your Company’s Environmental
Commitment, Business One, Irwin, Homewood, IL, 1993.
9. Madu, C.N. and Kuei, C.H., “Strategies for global competitiveness”, in Madu, C.N. (Ed.),
Management of New Technologies for Global Competitiveness, Quorum Books, Westport,
CT, 1993.
10. Eccles, R. and Pyburn, P.J., “Creating a comprehensive system to measure performance”,
Management Accounting, October 1991, pp. 41-4.
11. Hottenstein, M., Production and Operation Management, Doctoral Consortium of 1991,
Academy of Management.
12. Saaty, T.L., The Analytic Hierarchy Process, McGraw-Hill, New York, NY, 1980.
References: CT, 1993. 8. Harrison, E.B., Going Green: How to Communicate Your Company’s Environmental Commitment, Business One, Irwin, Homewood, IL, 1993. CT, 1993. 12. Saaty, T.L., The Analytic Hierarchy Process, McGraw-Hill, New York, NY, 1980.
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