quality costs- a critique of some economic cost of quality models_plunkett and dale 1988
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Quality costs: a critique of some 'economic cost ofquality' modelsJ. J. Plunkett a; B. G. Dale aa Department of Management Sciences, UMIST, Manchester, U.K
Online Publication Date: 01 November 1988
To cite this Article: Plunkett, J. J. and Dale, B. G. (1988) 'Quality costs: a critique ofsome 'economic cost of quality' models', International Journal of ProductionResearch, 26:11, 1713 — 1726
To link to this article: DOI: 10.1080/00207548808947986URL: http://dx.doi.org/10.1080/00207548808947986
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INT. J. PROD. RES., 1988, VOL. 26, NO. I I, 1713-1726
Quality costs: a critique of some 'economic cost of quality' models
J. J. PLUNKETTt and B. G. DALEt
Whilecarrying out a study of the collection and useof quality-relatedcosts inmanufacturingindustry the authors found in the literature many notional modelspurporting to indicate the relationships between the major categories of qualitycosts, and a few sets of real data. Despite being based on common principles,there are wide differences betweensome of the models, and between the modelsand real data. The paper categorizes and discusses the models in the light of theresearch experience. It is concluded that many of the models are inaccurate andmisleading, and serious doubts are cast on the concept of an optimum qualitylevel corresponding to a minimumpoint on the total quality-cost curve.
l. Introduction
In the course of a two-year study of the collection and use of quality-relatedcosts in manufacturing industry (Plunkett 1986) it became apparent that the costsand economics of many quality-related activities, including investment in preventionand appraisal activities, are not known (Plunkett and Dale 1986). It is perhapssurprising therefore to find published in the literature a number of diagrammaticrepresentations of quality-costs models which purport to show relationshipsbetween the major quality-cost categories. Many discussions of quality costs in theliterature feature such a model, but many quality-management practitioners aredoubtful about the representations and feel that they can be misleading.
The general suppositions underlying all these notional models are that investment in prevention and appraisal activities will bring handsome rewards fromreduced failure costs, and that further investment in prevention activities will showprofits from reduced appraisal costs. However, despite these common principlesthere are wide differences between some of the models. This paper discusses thevarious notional models and their implications and, in the light of our research,compares them with data from the literature.
2. A classification of quality-cost models
For the purpose of this discussion, models of quality-cost relationships publishedin the literature can be conveniently arranged into the following five groups.
Group A. Notional diagrams used in standard textbooks to indicate the principles of reducing failure and appraisal costs by increasing expenditure on prevention activities. Typical diagrams taken from Kirkpatrick (1970), Robertson (1971),Caplen (1972), and Besterfield (1979) are shown in Fig. 1.
Group B. Diagrams based on actual data published by Krzikowski (1963), Kohl(1976), Campanella and Corcoran (1983), Huckett (1985), and Hagan (1986). Theseare shown in Fig. 2.
Received June 1987.t Department of ManagementSciences. UMIST, Manchester, U.K.
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1714 J. J. Plunkett and B. G. Dale
BESTERFIELD 1979 CAPlEN 1972
TOTAL DIRECT OPERATNO< QUALITY COSTS nD"".'" j
PREvENTI()lIj "NOAPPRAISAL COSTS
'oo':-v-"'-----------==--v:PRODUCT DEFECT LEVEL- '"
DECREASING
Reproduced by permission of Prentice-Hall Inc. Reproduced by permission of Century Hutchison Ltd.
INCREASINGQUALITYOF COf\FORMANCE
KIRKPATRICK 1970INCREASINGCOST
r ~,~au""",co,,MINIMUM : PREVENTION
TOTAL COST FAILURE
LL.-==:2::~~~HIGH'.R """'c;';;oo;;;o,.......---,=~
QUALITY lEVEL
--QUALlTV CONTROl COSTa(PREVENTION COSTS)
ROBERTSON 1971
Reproduced with permission of Pitman Publishing Ltd.
Figure I. Group A.
Group C. Models from Lockyer (1985) and from the trammg literature of a.Ieading automotive manufacturer, company A (Anon. 1985), both of which appearto be based on experience, are grouped with a model constructed from data takenfrom an illustrative case developed by Veen (1974). They are shown in Fig. 3.
Group D. Notional diagrams all showing similar characteristics and taken frompublications devoted specifically to quality costs, i.e. BS 6143 (1981), Urwick Group(1981), and Harrington (1976). These are shown in Fig. 4.
Group E. Notional models which are similar in principle to the others but whichdiffer in an important detail (i.e. the position of the optimum cost in the qualityspectrum). They are taken from Juran (1974), Veen (1974), Thoday (1976), and Campanella and Corcoran (1983). They are shown in Fig. 5.
Even a cursory examination of the groups reveals some notable differences, themost striking of which is the dissimilarity between the notional models (Figs I, 4and 5) and those based on actual data (Fig. 2). The remaining group, group C(Fig. 3), bears closer resemblance to the data plotted in Fig. 2 than to any othergroup. Another striking feature is the way in which some of the notional modelsconveniently, and in some cases inexplicably, combine major quality-cost categories.Lastly there is the diversity of measures of quality used as abscissae in indicating therelationships between the major quality-cost categories.
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Quality costs 1715
2.1. Group A
The models shown in Fig. I are a selection of notional models taken from textbooks, where they were clearly intended only to convey the idea that there can be atrade-off between prevention and appraisal costs and failure costs (though as Cox1979 rightly points out, such trade-offs are not always allowable). It is not intendedhere to analyse these models in detail, but it is worth noting Caplen's (1972) combination of failure and appraisal costs vs Besterfield's (1979) preference for combining prevention and appraisal costs in indicating the principle.
It is also interesting to note that in three of the four models the minimum costcoincides with an approximately equal division of costs between failure andprevention/appraisal costs, which is in broad agreement with Caplen's (1972) criterion for the determination of inspection levels. However, in the remaining modelCaplen (1972) shows prevention costs alone to be equal to combined failure andappraisal costs. The latter situation is far removed from any real situation found inour research or elsewhere in the literature.
The combination of cost categories in these ways can seem logical, but it isdependent upon one's objective. If, for example, the objective is to reduce failurecosts, there may be little point in distinguishing between prevention and appraisalcosts. If, on the other hand, the objective is to reduce failure and/or appraisal costs,then maybe it is not important to separate them. The research experience was thatquality managers are constantly looking for preventive measures which will reduceappraisal and/or prevention costs, but this does not justify combining them. It is ourview that each cost category should be plotted separately. It is worth noting alsothat these notional models do not distinguish between internal and external failurecosts.
2.2. Group B
The data plotted in Fig. 2 were the only published data found which could beused to check the notional models. They are also useful, because cost-consciouscompanies are always keen to learn by how much their quality costs might bereduced by improved management of quality.
It will be noticed immediately that all the data are plotted against a linear timebase rather than against some measure of quality performance. While it is reasonable to suppose that the cost reductions were accompanied by improvements inquality, the time/quality relationships, or their effects on the costs diagrams, are notknown. Indeed, it is unlikely that the cost or quality profiles between inception of acost-reduction programme and post-warranty pay-off will be linear with time.Ideally, costs should be plotted against measures of quality performance.
Krzikowski's (1963) data show the relative proportions of the constituent costcategories. In the original paper the total quality costs are also expressed as percentages (6,4-4,4%) of some undefined cost. From the text it appears that they arepercentages of manufacturing cost. A feature of the data is the relatively high proportion of appraisal costs (60-75%) and low failure costs (12-20%) by comparisonwith typical figures of 30% and 65% respectively from more recent literature. Theslight upturn in total costs in the last year is explained in the text of the paper asbeing entirely owing to a one-off additional cost for training inspectors.
Kohl's (1976) data are closer to what is regarded as typical by many quality-costcommentators, and suggests that fairly modest increases in prevention and appraisal
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1716 J. J. Plunkett and B. G. Dale
KRZIKOWSKI 1963
11158 '951 111118 1I1S9 11180 11161 Hie:! 1967 HI68 19611 1970 Hll1 1I~72 '1173 11174
PREVENTION COST
CAMPANELLA AND CORCORAN 1983
11180 11181 '98:2 11183 I~
~~NOUAL'TY COST
"PPR"ISALC~
JFMAIolJJASOJIIDJ FM"MJJ"SOND
1(177 1978
© American Society for Quality Control.Reprinted by permission.
S"~ ,~ .~ , ~OT".. aUAlITYCOST
~r!4.,
HAGAN 1986
r------------:=I'OO
"IJ
Reproduced by Courtesy of Marcel Dekker Inc.
Figure 2. Group B.
expenditure can produce dramatic reductions in failure costs in the beginning, butthat a point is reached such that, if the prevention and appraisal expenditures arenot increased further, there is no further significant reduction in failure costs. TheBS 6143 (1981) arid Thoday (1976) models (Figs. 4 and 5 respectively) appear tosupport this view by indicating a continuing reduction in failure costs whilst increasing prevention and appraisal costs. Mortiboy's (1985) explanation of these relationships is that in the early stages of a quality-cost reduction programme qualitymanagers tackle problems themselves, improving quality and reducing failure costsat little or no extra cost to the company. The quality manager is then fully occupiedtrying to maintain the higher level of quality attained, with the same level ofresources, leaving him no time to tackle further problems. Hence there is no further
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Quality costs 1717
improvement without taking on extra resources, which subsequently increases thejoint prevention and appraisal expenditure. A similar situation arises when qualityimprovement groups are set up to tackle quality problems. Improvement continuesonly while the group activity is sustained and, in the words of Juran, 'managementhold the gains'.
Huckett's (1985) published data are limited to total quality costs expressed as apercentage of manufacturing cost. However, it is evident from the text (and from thefact that the company, Rank Xerox at Micheldean, were joint winners of the 1984British Quality Award for quality assurance throughout the production process)that the company achieved very high standards of quality conformance but theirtotal quality costs are continuing to fall, suggesting that if indeed there is anoptimum cost it occurs close to perfection. (It is perhaps pertinent to note hereSekiya's (1985) assertion that, whilst it is possible to set optimal quality levels, thosecompanies that set as their goal the attainment of the very finest quality will win inthe end.) Interesting cost items included in Huckett's quality costs are 'exceedingrequirements-work performed for which there is no need' and 'lost opportunitieslost business due to failure to meet customer requirements'. If these refer directly totheir standard products it is reasonable to include them, but otherwise 'work forwhich there is no need' may be a matter of subjective judgement, debatable, andperhaps more a matter of efficiency than quality.
Campanella and Corcoran's (1983) data corroborate the impressions gainedfrom other real data, and from research experience, that, in particular, making significant reductions in total quality costs has been a slow process brought aboutmainly by modest increases in prevention costs. An interesting feature of the data isthat reductions in appraisal costs contributed nearly as much to the reduction intotal quality costs as did the reduction in failure ('unquality') costs. The potential forlarge savings to be made by reducing appraisal costs is a popular theme among thequality fraternity, and indeed Richardson (1983) and Kohl (1976) have claimed thatsubstantial savings were achieved by this means.
Hagan's (1986) data, gathered over 11 years, broadly corroborate Kohl's (1976)data in that appraisal and prevention costs are maintained at a sensibly constantproportion of sales income whilst failure costs are continually reduced. It indicatesalso a transfer of expenditure from appraisal to prevention in the early years, evenin the face of falling sales revenue. It then appears that the company featured byHagan felt they had the right balance between these two quality-cost categories andmaintained them at a constant proportion of their increasing sales revenue for 4 or5 years. Their judgement in this appears to be vindicated by the continuing declinein failure cost and total costs of quality. The value of sales increased dramaticallyover the last few years and there is a suspicion that, as drawn, the fall in the rate ofquality improvement (as indicated by the change in the rate of fall of Failure costs) isaccompanied by a slight relative increase in appraisal expenditure compared withprevention expenditure, but this is not certain. It would be interesting to knowwhether, in this case, the dramatic increase in sales income in the tenth year wasowing to increased output, or to monetary inflation and changes in exchange rates.
2.3. Group C
The models from Lockyer (1983), company A (Anon. 1985), and one based onillustrative data taken from Veen (1974), have been grouped together in Fig. 3 andshown in their original forms because they have much in common. Firstly, they bear
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1718 J. J. Plunkett and B. G. Dale
PROCESS CAPABiliTY INCREASING
Reproduced by permission of Pitman Publishing Ltd.
eo
.~c
§ s
a
I II IVUNCERTA~TY A\\oo'~ENI'lG ENlIGHTENMmT WISDOM
DEVelOPMENT STAGES
\~" POSSiBlESAVINGS FROMA"BASIC'QUALITY COSTSYSTEM
UNBALANCED BASIC B"SlC COMPREHENSIVESITUATION INSPECTION CONTROL OU"LITY CONTRO\.
DEVELOPMENT STAGES
'0
~n COMPANY A 1985-.~ REPLOTTED
c......j.
"'.1>
'"DEVELOPMENT STAGES
Figure 3. Group C.
a greater resemblance in shape and proportion to the actual data curves shown inFig. 2 than to the notional models shown in Figs. I, 4 and 5, although none of thethree is claimed to be based on actual data. Secondly, the style of presentation of allthree leads to some ambiguity because it is not entirely clear whether or not thecurves are of cumulative costs. Thirdly, the diagram derived from Veen's illustrativedata (1974) and the model advanced by company A (Anon. 1985) are strikinglysimilar, despite differences in labelling and magnitude of costs.
Examination of the models in this group raises a number of interesting points.For example, Lockyer's diagram straightaway draws attention to the problem ofdefinitions of quality and what expenditures to include among quality costs. Mostcontributors to the literature on the topic do not bother to define their terms.Lockyer, however, defines failure costs in his model as 'correction costs', therebyperhaps omitting scrap, warranty and other failure costs. He also uses 'Total qualityassurance costs for quality acceptable to customer' and suggests that the relationships he indicates are only true for one customer-perceived quality level. WhilstLockyer's concepts may be more difficult to grasp he at least defines his terms, andthe use of process capability has advantages over undefined measures of quality.However, the way the model is labelled in the original reference suggests that the
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Quality costs 1719
costs are plotted cumulatively, but it is evident from the text that they are in theusual non-cumulative form. If one keeps in mind the narrow view taken of failurecosts in this case (i.e. correction costs only), the uncertainty of the relationshipbetween degree of quality and process capability (which is usually taken to mean theability to meet a given specification), and its limitation to 'one customer-perceivedquality level', it would be unwise to claim that valid comparisons can be made withother models. Nevertheless, the failure, appraisal and prevention curves are ofsimilar form and relationship as in the models based on real data though the total, ifdrawn, would pass through a minimum, and correspond with Lockyer's ideasexpressed in the accompanying text:
Where the manufacturing capability is low for a quality acceptable to the customer, the total quality assurance costs are high, the failure costs predominating.As the manufacturing ability improves (usually by increasing appraisal andespecially-prevention costs), the failure costs drop very steeply. When the manufacturing capability is "matched" to the customer's quality requirements, thetotal quality assurance costs will be at a minimum.
Veen's illustrative data first came to the writers' notice, plotted in the formshown in Fig. 3, in a private communication. In his original paper, Veen publishesthe model shown in Fig. 5 and uses other data in an ingenious presentation aboutbalancing various kinds of quality costs. Veen does not plot these other datagraphically. They have been picked up and presented (with acknowledgement), inthe form shown in Fig. 3, by a contributor to a BSI technical committee. The presentation is included here to illustrate how readily seemingly substantive models canbe created and given credibility by taking data from reputable sources and usingthem for purposes for which they were not intended. Worse still, the presentation ofthe contrived model is ambiguous and misleading. The presentation is ambiguousbecause the labelling of the curves is inconsistent with the label indicating 14% ofturnover as possible savings. If it is assumed that the curves are absolute costcurves, and the costs of each of the major cost categories are summed at each development stage, quality costs are 32, 43, 39 and 26% respectively. These figurescannot be manipulated to give rise to a 14% saving as indicated on the diagram.(Moreover, it is misleading to suggest that, in the general case, quality costs may besuch a high proportion of turnover.) Hence it is clear that the top curve must be atotal-costs curve and that the magnitude of the cost categories at each stage isrepresented by the distance between adjacent curves.
Company A's diagram (taken from their supplier training course notes) plotsquality costs as a percentage of sales vs Crosby's (1979) four stages of quality management. The similarity to the diagram based on Veen's illustrative data has alreadybeen pointed out. It should be noted also that the total quality costs indicated ateach management stage approximate closely to those indicated by Crosby (1979).
It is clear from the shading and labelling of this model that the costs are plottedcumulatively and therefore it is not directly comparable with most other models,hence it has been re-plotted in the more usual non-cumulative form (Fig. 3). Thereplotted model has a number of interesting features. The first is that in progressingfrom 'Uncertainty' to 'Awakening' a modest increase in appraisal expenditure produces a substantial reduction in total quality costs, which is attractive to the supplier, and a dramatic transfer of the remaining failure costs from the external-failurecategory to the internal-failure category, which suits the purchaser's objectives very
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1720 J. J. Plunkett and B. G. Dale
well. Further development of a company's quality management system sees a transfer of expenditure (and emphasis) from appraisal to prevention activities, accompanied by substantial reductions in internal failure, external failure and total costs. It isinteresting also to note that, as drawn in the diagram, the reduction in externalfailure costs is 25% greater than the reduction in total costs, whilst the internalfailure costs are approximately doubled. The message company A is giving to itssuppliers is therefore very clear-quality costs should be in-house.
However, the most interesting feature of the model is .the shape of the total costcurve. It is interesting in two respects. Firstly, it does not pass through a minimum.This causes one to conjecture whether this is because, in company A's experience,quality costs do not (or should not) pass through a minimum, or whether they donot wish to give their suppliers the idea that there is an optimum level of quality(which may be some way away from perfection, and which would conflict withcompany A's operating policy of never-ending improvement). Clearly it is in themanufacturer's interests to get their suppliers to pursue perfection. Secondly, theshape of the total-costs curve is similar to Huckett's (Fig. 2) total quality-costscurve, which is based on actual data. Also, the form of the curves in the convertedmodel is not dissimilar to those produced from Kohl's data (Fig. 2).
The use of Crosby's (1979) stages of development of quality management asabscissa complicates analysis and comparisons of the model because the relationship between quality achieved and the state of development of a company's qualitymanagement is not known. Whilst it is recognized that the model is only notional, itdoes appear that the company's ideas of a quality-cost model are closer to the truththan many others.
It is worth noting here that a realistic diagram based on Crosby's stages ofdevelopment can only be constructed after the stage of 'wisdom' had been reached,i.e. with hindsight. This is because measurement of quality costs is among thequality-management techniques being developed. Crosby suggests that attempts tocollect quality costs in the early stages of development will identify only about onesixth of them. Thus the diagram purports to represent actual costs, as opposed tomeasurable costs, at each stage of development.
2.4. Group D
The models shown in Fig. 4 are similar in many ways to the models in Fig. I.However, they have been segregated for discussion because they appear in publications devoted specifically to quality costs, and hence might be expected to reflectaccurately the relationships between the major cost categories and the cost savingsto be expected from investment in prevention or appraisal activities. In addition,two of the models-BS 6143 (1981) and Urwick Group (1981)-are widely publicized,and carry the authority and prestige that attaches to publications of the BSI and toa leading firm of management consultants.
The quality-costs model published in BS 6143 confuses and misleads. It does soby failing to separate prevention and appraisal costs, thereby suggesting thatreduction of failure costs by increasing the combined expenditure on prevention andappraisal is the prime strategy for reducing quality costs. In fact, reduction ofappraisal costs by increasing preventive measures may be a reasonable and worthwhile alternative to reducing failure costs. Indeed, in some cases it is the easiest andquickest way to achieve substantial reductions in quality costs. However, expendi-
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Quality costs
BS 6143 1981
1721
.,~,
~I~I0 1.'0'~I~,
TOTAL COSTS II,,I
II,
MEASURE OF QUALIfY(QUALITY LEVE;L)
.~s
HARRINGTON 1976
f:S:ISI C"~l~O"A81.E OVA",,, cos's
rz.z.a TOTAL' .... ""E CO"S
PRODUCT DEFECT lEVEL
Reproduced by permission of theBritish Standards Institute
Reprinted by permission from QUALlTY,a Hitchcock Publication
.§
URWICK GROUP 1981FALlflE COSTS
, B85% 10'l1.
URWICK GROUP 1981with data
WOf'lSE_ QVALITY _BE;T1E~ WORSE_ QuALITY _BElTER
Reproduced by permission of the UrwickManagement Centre/Price Walerhous~
Figure 4, Group D.
ture on appraisal, above a certain threshold level, tends to move costs from externalto 'internal failure categories, and savings derive mainly from detecting faults sooner.(It seems curious that in view of the strength of inspection activities in industry, andrecently, the attention paid to sampling plans and techniques, the overall economicsof appraisal activities are not discussed in depth in the quality-cost literature.)
The model misleads by suggesting:
(i) that huge reductions can be achieved at little cost;
(ii) that the economic balance occurs at a point where 70% of the total qualitycosts are failure costs (corresponding closely to the quality-cost distributionlabelled 'typical' in the text of the Standard); and
(iii) that the optimum quality measure lies approximately two-thirds of the wayacross the quality-level range. (This point may be countered by arguing thatthe quality range represented is only the high end of the range, but thiswould not be consistent with the way prevention and appraisal costs arerepresented in the diagram.)
The Urwick Group's (1981) model in their booklet Quality Costs-A Key toSurvival is even more confusing and misleading. In their (praiseworthy) attempts topromote expenditure on prevention, they separate out prevention costs, butinexplicably combine appraisal and failure costs in their model (Fig. 4). (Note: there
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1722 J. J. Plunkett and B. G. Dale
is some ambiguity about the latter because a point on the 'Appraisal/Failure Costs'line is labelled 'Halving failure costs'.) Like the model from BS 6143, it suggests verysubstantial returns on investment in prevention, and that the optimum may lie sometwo-thirds of the way across the quality spectrum. However, it differs in the respectthat optimum quality in this model coincides with a point where prevention costsare about equal to the combined appraisal/failure costs. (There may be instances ofsuch quality-cost distributions, but none has been met with in our research.) It isinteresting to note, however, that their 'balanced costs' position does not coincidewith the minimum total cost, but has a 70: 30 split between appraisal/failure costsand prevention costs, corresponding exactly to the BS 6143 split between failure andprevention/appraisal costs.
In the same booklet the Urwick Group publishes quality-cost data from atypical sample of clients as in Table I. These data have been superimposed byPlunkett (1986) on to a version of their quality-costs model by converting absolutecosts to percentages, with interesting results (Fig. 4). It will be seen that all of theirtypical sample of clients are well to the left of the optimum, suggesting rather poorquality performance. It is difficult to accept that seven typical companies from sucha diverse range of industries all have mediocre standards of quality performance.(Standards of quality performance in this context means performance with respectto costs. It does not necessarily mean that the companies market mediocre-qualityproducts. So far as their customers are concerned they may manufacture excellentproducts. What is implicit in quality-cost models is that improved quality andquality-cost performances accrue from increased expenditure on prevention activities. It does not follow that when prevention expenditure is relatively low, outgoingproduct quality is poor.) Hence one is led to suspect the model and/or the data maybe inaccurate. Closer examination of the data shows the failure costs to be 66-94%(average 85%) of total costs, which seems high by comparison with other publisheddata. It may be that the Urwick Group's methods of calculating failure costs tend tomaximize them (e.g. by valuing scrap at sales value). Consultants often maximizecosts they are trying to reduce, thereby maximizing claimed savings. If these failurecosts are deflated so that they average 70% (i.e. close to the generally acceptedaverage) the effect is only to move the average from A to B (Fig. 4), i.e. still well tothe left of the 'balanced costs' and optimum costs positions, thereby suggesting thatthe greater inaccuracy lies in the model.
Annual quality costsNo. of
Industry employees Failure Appraisal Prevention Total
Footwear 750 1,100,000 175,000 25,000 1,300,000Board manufacturing 500 800,000 40,000 10,000 850,000Building systems 750 120,000 50,000 10,000 180,000Foundry A 200 350,000 50,000 15,000 415,000Foundry B 300 500,000 50,000 30,000 580,000Mechanical handling 300 500,000 30,000 5,000 535,000
equipmentGlass manufacturing 150 200,000 20,000 10,000 230,000
Overall percentage 87·5 10 2·5 100of total
Table 1.
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Quality costs 1723
JURAN 1980
QPnl>Uo4POINT
CAMPANELLA & CORCORAN 1983'0
\O.~OTAL CXl
00 r T
LOSS OUE TOomen",(FALlJlE COST)
~•§ _~~~~_~~_~~T
'0
00
QUALITY OF CONFORMANCE
COST OF APPRAISALPLUS PREVENTION
100'110DEFECTIVE
Reproduced by permission of theMcGraw-Hill Book Company
THODAY 1976
© American Society/or Quality Control.Reprinted by permission
VEEN 1974
DEGREE OF' PERFECTION ...HCREASl'la QUALITY _ Pert.cllo"
Reproduced by permission 0/theInstitute of Quality Assuraru:e
Reproduced by permissionofthe EOQC
Figure 5. Group E.
2.5. Group E
Although the models in Fig. 5 have broadly similar characteristics to the modelsin Figs 1 and 4 in that they indicate the possibility of balancing the different types ofquality costs at some optimum level, they differ in two important details: (i) the rateof change of cost with quality is much greater; and (iii the optima are positionedmuch closer to perfection.
Campanella and Corcoran's (1983) diagram is so similar to Juran's version thatit must surely have been taken from the earlier publications of either Juran (1974) orJuran and Gryna (1980). Although it is clear that the models are only notional,effects are clearly exaggerated, as indicated for example by the idea of costs increasing to infinity, which of course they cannot. It also seems curious that a modelsuggesting such a pronounced and precise optimum should appear alongside realdata (Campanella and Corcoran 1983-Fig. 2) which exhibit no such characteristic.
It is clear from the text of Veen's (1974) paper that his model is the result ofexperience and some careful thought. It is interesting to note his view that the ratesof reduction in both appraisal and failure costs can be maintained constant almostto the point of product perfection-but only by a rapid increase in preventionexpenditure. The position on the scale of quality at which this occurs (98% ofperfection) endorses the views implied (but not quantified) in the other models inthis group. It is interesting also to note Veen's implied view that the optimum maybe attained with a constant and relatively low level of expenditure on prevention
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activities. A useful point paraphrased from the text of Veen's paper is that, in thecase of a market which inclines towards consistently higher quality demands, it maybe advantageous to operate to the right of the minimum cost. This means payingrelatively greater attention to prevention. In this wayan organization is always onestep ahead of developments and can think about tomorrow's problems instead ofhaving to devote all its energy to today's problems.
Thoday's (1976) model (which is also reproduced by Chisholm 1982), incorporates the view that total quality cost has two main components, the cost of achieving quality and the cost of failure to achieve quality. He calls these internal andexternal quality costs respectively. By Thoday's definitions internal quality costs aremade up of prevention and appraisal costs, whilst external quality costs compriseexternal failure costs. Thus his cost groupings correspond with those of the BS 6143model. (Thoday's external failure costs contain elements which some practitionersmay not readily accept as external failure costs or even as quality costs, e.g. preventive maintenance on products; loss of goodwill, including loss of customers andadditional sales promotion necessary if quality level is too low; and national workshops.)
However, Thoday's model is also interesting in two other respects. Firstly, itpostulates the notion of minimum levels of costs, which increase rapidly as oneapproaches or departs from perfection. Hence the optimum cost occurs near thehigh end of the quality spectrum, not two-thirds of the way across as in the BS 6143and Urwick Group models. The second feature is that Thoday claims that therapidly rising costs follow exponential curves. (Chisholm 1982 states: 'It can beshown that the cost of achieving quality increases as an exponential curve as qualityapproaches perfection. The cost of failure similarly increases exponentially asquality deviates from perfection' and cites Thoday 1976 as his source. In the writers'view the curves are not 'shown' to be exponential; they are only claimed to be so.]When the 'internal' and 'external' costs are added together the resulting total costgoes through a minimum value. It is but a small step from the concept of aminimum cost to the notion of optimal quality as presented in BS 6143, and theUrwick Group notional quality models. The notional models of Veen, Lockyer, andthe automotive manufacturing company (Fig. 3), and the data of Campanella andCorcoran, Kohl, and Huckett (Fig. 2), do not appear to support the idea that thecurves are exponential, or that there is an optimum level of quality corresponding tominimum quality costs. Krzikowski's data alone show a slight upturn in total costsat a high level of quality for reasons which have been explained.
3. Concluding remarks
Although quality-cost models have been taken from a number of sources andgrouped and compared with each other to bring into question the validity of thepopular notional models, the legitimacy of doing so may itself be questioned. Forexample, although all the models (with the exception of Lockyer-Fig. 3) use absolute cost or a simple variation of it as the ordinate, abscissae range from measures ofquality dimensioned only at their extremes to undimensioned process capability,arbitrary quality-management development stages, or time. It is clear also from thecontributions of Huckett (1985) and Thoday (1976) that different authors mayinclude among their quality costs items which other practitioners would not readilyaccept as being quality costs. In addition, combining different categories of failurecosts, and prevention with appraisal costs, as in most notional models, or combin-
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ing appraisal and failure costs, as in the Urwick Group model (Fig. 4), obscures therelationships between categories of activity and between their associated costs. Itmay also be argued that the diagrammatic representations are only notional and areintended only to illustrate principles. Nevertheless, it is felt that the comparisonsand criticisms made are valid and that even notional models should reflect, so far asis possible, the existing state of knowledge. It is important to get it right, not just toprovide a predictive tool but also because it can have a strong bearing on thequality philosophy of a company. Indeed, the authors believe that the notion ofoptimum quality levels has seriously inhibited the development of total quality management in companies.
It may be, of course, that hard evidence is available to support the notion thatquality-cost curves are exponential and give rise to cost minima, but the authorshave not found it. It would be unfortunate if the notion of an optimum quality cost,given such prominence and wide publicity, was based on speculation.
Some of the models imply nonsensically extravagant returns on investment inprevention and/or appraisal. Indeed, it is noticeable that whenever investment inprevention expenditure is discussed there is an implicit expectation of a large returnon the investment. While recognizing that companies are in business to make profit,and that there may be competition for limited resources, the paybacks expected (andsometimes proffered) from investment in quality seem unusually high, and since highreturns are usually associated with high risk, one wonders whether, as a generalrule, the benefits from investment in prevention are seen in business circles as beingproblematical.
The view that many of the widely publicized quality-economics models are inaccurate, and may even be of the wrong form, is widely supported by quality managers. Everyone would like to have a valid model which they could use to assesstheir present situation and predict the effects of changes. So far as is known thereare insufficient data available to construct such a model, though there should beenough collective experience available to make a reasonable' hypothesis as to theshape and the relative proportions of the constituent costs in the diagram. Forexample, there are reasonably good grounds for believing that optimum quality, if itexists, is near to the highest attainable standard of quality. The model should takeaccount of the fact thai investments in prevention through capital or resources ofteninvolve relatively large stepwise increases. It should also reflect the often considerable time lag to be expected between investment in prevention and/or appraisal andreduction in failure costs, and especially warranty costs.
Acknowledgments
The financial support of the Science and Engineering Research Council, throughtheir research contract GR/C33475 which led to the production of this paper, isgratefully acknowledged.
The authors also wish to thank the publishers of the models shown for permission to reproduce them in this paper.
ReferencesANON., 1985, Statistical Process Control Course Notes (Company A).BESTERFIELD, D. H., 1979, Quality Control (EnglewoodCliffs, New Jersey: Prentice-HalI).BS 6143,1981, Guide to the Determination and Use of Quality Related Costs (London: British
Standards Institution).CAMPANELLA, J., and CORCORAN, F. J., 1983, Principles of quality costs. Quality Progress, 16,
No.4, 16-21.
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800-801.CROSBY, P. B., 1979, Quality is Free (New York: McGraw-Hili).HAGAN, 1. T., 1986, Quality Management Handbook (eds. Walsh, Wurster & Kimber), (New
York: Marcel Dekker).HARRINGTON, J. H., 1976, Quality costs-the whole and its parts-part 1. Quality (Illinois), 15,
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Quality and Reliability, 2, No.2, 5-14.JURAN, J. M. (ed.), 1974, Quality Control Handbook (New York: McGraw-Hili).JURAN,1. M., and GRYNA, F. M., 1980, Quality Planning and Analysis (New York: McGraw-
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ceedings of the 7th EOQC Conference, Copenhagen, pp. 129-145.LOCKYER, K. G., 1983, Production Management (London: Pitman).MORTIBOYS, R. J., 1985 (Consultant to the National Quality Campaign}--private communica
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turing industry. Ph.D. Thesis, UMIST, UK.PLUNKETT, J. J., and DALE, B. G., 1986, Quality costs: the economics of some engineering
practices. Chartered Mechanical Engineer, 33, No. 11,33-35.RICHARDSON, D. W., 1983, Cost benefits of quality control-a practical example from
industry. BSI News, October 14-15.ROBERTSON, A. G., 1971, Quality Control and Reliability (London: Pitman).SEKIYA, S., 1985, Quality control at Toyota Motor Corporation. Productivity Digest, 4, No.2,
68-87.THODAY, W. R., 1976, The equation of quality and profit. Quality Assurance 2, No.2, 48-52.URWICK GROUP, 1981, Quality Costs-a Key to Survival (Urwick Group pamphlet).VEEN, B., 1974, Quality costs. Quality (EOQC publication), No.2, pp. 55-59.
Tandis qu'ils effectuaient une etude de la collection et de I'utilisation desrapports cout-qualite dans les industries de fabrication, lea auteurs ont decouvertdans la documentation de nombreux modeles notionnels pretendant indiquer lesrelations entre les principales categories de couts de qualite et quelques ensembles de donnees reelles, Malgre Ie fait qu'ils soient fondes sur des principlescomrnuns, iI existe d'importantes differences entre certains des modeles et entreles modeles et les donnees reelles, L'article categorise et examine les modeles a lalumiere de l'experience de la recherche. II en conclut que beaucoup de modelessont incorrects et trompeurs et mettent serieusement en doute Ie concept d'unniveau de qualite optimale correspondant a un point minimum sur la courbetotale du rapport cout-qualite.
Bei einer Untersuchung der Erfassung und Verwendung von qualitatsabhangigen Kosten fanden die Verfasser in der Literatur zwar viele abstrakteModelle, die Anspruch darauf erheben, die Beziehungen zwischen den hauptsachlichen Qualitatskostenkategorien aufzuzeigen, aber nur wenige echte Daten.Obwohl die Modelle auf den g1eichen Grundsatzen basieren, bestehen merklicheUnterschiede sowohl zwischen einigen der Modelle als auch zwischen den Modellen und den wirklichen Daten. Diese Abhandlung kategorisiert und besprichtdie Modelle aus der Sicht der bei der Untersuchung gemachten Erfahrungen.Wir kommen zu dem Ergebnis, daf viele der Modelle ungenau und irrefiihrendsind, und ziehen die Vorstellung einer optimalen Qualitatsstufe, der einMinimum auf der Giitegesamtkostenkurve entspricht, ernstlich in Zweifel.