improving the communication of accounting information throug

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Improving the communicationof accounting informationthrough cartoon graphics

Malcolm SmithMurdoch University, Perth, Australia, and

Richard TafflerCity University Business School, London, UK

IntroductionScant attention has been paid by accounting academics to the question ofimproving the communicative ability of financial statements and their decision-support role. Libby (1981, p. 101) identifies three available options for theimprovement of decision making:

(1) changing the content or presentation of the available information;(2) education of the decision maker; and (3) replacing the decision maker with a model.

This paper addresses the first of these options, in the context of improvementsin the presentation of accounting information.

Accounting data is essentially multivariate and its assessment depends onthe simultaneous effect of several variables in different spheres of activity.Complex tabular presentations do not facilitate an integration of the keyfeatures of the accounts and a segmented multi-column format may leave anindication of separate aspects of performance rather than an overallassessment. An alternative means of presentation might provide a clearer andmore efficient representation, complementing existing methods. Pictorialmethods, especially those able to represent several dimensions simultaneouslyin a form that may be perceived in terms of an overall impression (a Gestalt),may potentially be useful in this regard. De Sanctis and Jarvenpaa (1989)suggest that before graphical displays become more meaningful thantraditional numeric methods further studies need to demonstrate:

(1) the conditions under which graphs are effective;(2) how users might be trained to use graphs; and (3) how graphs might be altered to increase their power relative to

accounting data. The third of these criteria provides the focus of this paper.

Conventional pictorial methods are extremely limited in their application.Traditional graphs and charts work well in only two or three dimensions andquickly become over complicated when multivariate information is employed.

Accounting, Auditing &Accountability Journal,Vol. 9 No. 2, 1996, pp. 68-85. © MCB University Press, 0951-3574

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Working within three dimensions is extremely advantageous from acommunications point of view, but in many practical instances this is rarelypossible if more than a superficial overview is to be conveyed. Many alternativepictorial methods have been employed in an attempt to facilitate thecommunication of information – ranging from the familiar bar and pie chartsand pictograms to more obscure forms. The pie chart, bar chart and trendgraph as detailed by Beattie and Jones (1992), have become familiar andacceptable in the financial report as alternatives to the narrative and numericalform; schematic faces have yet to achieve such acceptability, perhaps because ofthe novelty of the approach and the emotive manner in which their accountingmessage is conveyed.

Alternative methods of presentation, notably those involving the use of afacial format, may seem a little strange to existing users, but the test of theirusefulness will be in the successful communication of financial messages. Whiledemanding attention, such figures should also be clear enough to makeinterpretation possible without a detailed explanation. The complexity andfamiliarity of faces makes them a special class of visual input which derivesfrom developmental changes in infants, whereby they learn quickly to respondto more differentiated forms. Schaffer (1971, p. 69), suggests that withincreasing age the overriding importance of the eyes as a source of recognitionand attraction is complemented by increasing attention to other facial features,facilitating the differentiation between various expressions. The similarreaction of infants to real faces, photographic representations and schematicline drawings, forms the basis of their reaction as adults to the messagesprovided by cartoon faces. The possibility exists that, with appropriateassignments, the facial format might be employed to communicate informationon the magnitude and change in a number of variables simultaneously withoutthe need for detailed explanation or education of users.

There has been limited study to date of the effectiveness of alternativemethods of presenting accounting information for financial decision purposes.Smith and Taffler (1984) recommend the further exploration of the use ofschematic faces to represent accounting information, following the success ofthis medium in displaying multivariate data in other task environments. Thispaper explores empirically the usefulness of the schematic face as acommunication device, in a particular decision context, compared with moreconventional presentation formats, focusing on the relative usefulness ofschematic faces, financial ratios and accounting statements as informationformats for decision making.

Literature reviewFinancial information is both complex and multidimensional and if a completepicture is to emerge, rather than a series of financial relationships, thenadditional graphical methods are required which will represent adequately themultivariate nature of financial data. Canadian Institute of CharteredAccountants CICA (1993, p. 122) suggests that the ability of multivariate

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graphics to portray data in an understandable form may result in theirproducing better decision making than corresponding tabular presentations.

The impact of graphical representation is an important attribute since aforceful picture must be produced which allows new stimuli from a complexdata set to be perceived while existing stimuli are being integrated.Psychologists, among them Yin (1969), Smith and Nielsen (1970), and Reed(1972), argue that the acquisition and organization of information withindimensions, by decision makers, is perceived as a Gestalt so that stimuli areprocessed in a holistic manner. In addition to providing a Gestalt, the familiarityof faces commands attention and triggers an emotional reaction whichenhances their overall impact in a way that other forms of graph do not.

Garner (1978), Homa et al. (1976) and Sergent (1984) provide empiricalsupport for the face being regarded as a spatial interrelationship of featurescapable of being perceived as a Gestalt, an issue central to the development ofthe schematic face in cognitive research. The familiarity of faces and their easeof recognition and description makes them superior to other pictorial forms ofrepresentation. Wilkinson (1982) demonstrates that face-based iconsoutperform alternative formats in the judgement of similarities. Haig (1984)demonstrates the incredible sensitivity of respondents to the smallest changesin facial features. Morton and Johnson (1989) note that faces are special morethan by virtue of their being visible parts of the human form since they cansignal their intentions. This is so even though there is no convincing evidencethat they are processed any differently from other objects among which werequire to discriminate.

Chernoff (1971) initiated the computer-based construction of schematic“faces” whose features can be made to vary in size and shape according to thevalue of the assigned variable[1]. The original form of portrait has beenadapted by Bruckner (1978) to provide greater variation and by Frith in Everitt(1978) and by Flury and Riedwyl (1981) to provide greater realism. Valentine(1986) views the human face as a series of vectors in multidimensional spacewith dimensions corresponding to significant features. Her study suggests thata matching of significant features with financial performance measures,provides the possibility of communicating multidimensional financialinformation in a simple, integrated and readily comprehensible form.

Three major contributions to the literature in this area (Moriarity, 1979;Smith and Taffler, 1984; Stock and Watson, 1984) have applied Chernoff ’smethods in a financial environment: Moriarity (1979), in the seminal study inthe area, working with financial statement data, examines the use ofmultidimensional graphics as a technique for describing the financial status ofthe firm. His innovative approach provides encouraging results which suggestthat unsupported faces provide an excellent framework for decision makingwhen produced as an alternative to information conveyed in more traditionalfashion. Moriarity examines the speed and accuracy with which respondentsclassify companies as failed or non-failed, without knowledge of prior


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probabilities, when presented with appropriate financial information inalternative formats.

Moriarity’s respondents found the changes most easily detected in the faces,which were classified faster and more accurately than either the raw accountingnumbers or derived ratios. His results suggest that our familiarity with facesmakes an interpretation of the portraits possible without a detailed knowledgeof the information used or the facial assignments employed. However,Moriarity’s sample included only ten respondents of any accountingsophistication, the remainder being first year accounting undergraduates, sothe strong relative performance with the faces may be attributable to ignoranceof accounting concepts. Moriarity makes no attempt to match the most salientfinancial and facial features nor to manipulate eyebrow slant in his schematicfaces, despite the psychological evidence suggesting their importance.

Stock and Watson (1984) take a similar approach but employ judgementally-determined bond ratings as their classification base in suggesting the potentialusefulness of schematic faces in situations where statistical models are weak.They demonstrate the relative usefulness of faces but their findings may reflectthe complexity of the task rather than the method of data presentation.

In addition, both of the above studies might be criticized for failing tocompare like with like, so that the superiority of presentation apparent from thefaces may actually represent superiority of information. Schematic faces areconstructed in a relative, not absolute manner, usually standardized relative toindustry means and standard deviations. However, Moriarity provides nostandard deviations for his financial ratios and Stock and Watson provideneither means nor standard deviations. No attempt is made to compare theperformance of users of varying levels of accounting sophistication.

Smith and Taffler (1984) in a UK environment illustrate how intertemporalperformance comparisons can be made using schematic faces together withtheir use in facilitating the distinction between failed and non-failed companiesin large datasets. They suggest that schematic faces may provide a clearerindication of financial status than is apparent from a company’s financial ratioprofile. However, their study does not show whether accounting data can beanalysed more quickly or more effectively in a facial format than whenrepresented by more conventional means. None of these studies adequatelyreflects contributions from the psychological literature relating to featureassignment and facial construction. These are addressed below with aconsideration of the features of the face, their interaction, and the use ofcaricatures.

Goldstein and Mackenberg (1966), Grant (1970), Laughery et al. (1971) andDe Soete and De Corte (1985) identify three main expressive areas of the facewhich link movements with particular emotions: the eyes, the eyebrows and themouth. They emphasize the importance of the eye and mouth regions, which aremore mobile than others and communicate more information, and the relativeinsignificance of the ears. Notably, Stock and Watson (1984) employ a featuredirection the opposite of that suggested by the psychological literature and

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accord the nose a prominent role in the assignment of financial variables tofacial features, despite the strong psychological evidence to the contrary.

McKelvie (1973) demonstrates that the perceived meaningfulness of the faceis at its greatest when both the eyebrows and mouth curvature vary from anaverage position, suggesting that the interaction of eyebrow slant and mouthcurvature provides an effective force in the communication of meaning in facialexpressions. The findings of these studies from the psychological domain areemployed in the facial constructions in this study.

Following Ryan and Schwartz (1956), Chernoff (1978) suggests thatexperience with caricatures and cartoons indicates that the need for realisticfaces on pictures is not great. Further supporting evidence is supplied byDiamond and Carey (1986), who find respondents to prefer schematic cartoonfaces to real faces in recognition exercises, and by Rhodes et al. (1987) who showthat facial caricatures are recognized more quickly than line drawings – resultsconsistent with a holistic theory of encoding. Benjamin and Pachella (1982)advise against making Chernoff faces more realistic, since the consequentintroduction of irrelevant information will cause perceptual problems. Theysuggest that respondents will be unable to ignore irrelevant features, even wheninstructed to do so, so that the number of features presented in the displayshould be equal to the number of variables whose values are to be mapped.

The suggestion is that where the facial portrait is required to communicate amessage the emphasis must be placed on the mobile features. These featurescan be varied efficiently with the Chernoff (1978) and Bruckner (1978)formulation to facilitate the interpretation of the overall portrait, so thatfinancial performance can be represented through appropriate assignment offinancial attributes to facial characteristics. Provided that due attention is paidto the combination of facial features, without overemphasis on dominantfeatures, it is possible that an integrative picture might emerge to give a clearindication of overall performance.

This study overcomes many of the deficiencies of its predecessors and makesoriginal contributions by incorporating relevant evidence from thepsychological literature, and by extending the experimental work to skilledusers. The complex issue of how financial variables are assigned to facialcharacteristics, however, remains an area for further study. No attempt is madehere to vary the feature assignment, rather a single assignment is employedthroughout; the most salient financial variables are assigned to those facialfeatures deemed by the literature to be the most important, in a manner entirelyconsistent with the psychological evidence.

Research methodThe task domain is the failed/non-failed company decision situation since thereis a wealth of literature demonstrating the strong degree of environmentalpredictability for accounting statement-based ratio information (e.g. Altman,1968; Taffler, 1982). A substantial literature, summarized by Foster (1986,p. 534), highlights the prediction of performance on the basis of trends supplied


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by financial ratios and accounting statements. The ease of processing facialprofiles suggests that they might provide a more efficient means of making thesame analysis. This paper suggests that the relative lack of predictability ofinformation presented in the form of schematic faces in existing studies may bedue to insufficient attention both to the appropriate assignment of variables tofacial components and the relevant psychological literature on feature saliency.

Accounting ratios suggested by Taffler and Sudarsanam (1980) are used torepresent the four key dimensions of accounting information[2]. These ratiosare assigned to facial features in order to provide Chernoff portraits of the typeshown in Figure 1. The aim is to produce faces which reflect the financialperformance of the company and which can be interpreted without the need fora detailed explanation of the variables employed or the feature assignments.

The schematic Chernoff faces employed here incorporate four variable features:mouth, eyes, eyebrows and nose. The ears remain constant throughout but thesize and shape of the face may change because of the size and position of thefacial features which it bounds. The precise location of each of the features isdetermined by the values of the assigned financial ratios relative to industrymeans and standard deviations. Thus, mouth (length, curvature and height)will be determined by a profit ratio; eye (separation, size and pupil direction)will be determined by financial gearing; eyebrow (angle and height) will bedetermined by liquidity, and nose (length and width) will be determined byworking capital position. Different assignments are possible, but this particularassignment ensures that three key financial performance measures (profit,gearing and liquidity) are assigned to the mobile features of the face.

Moriarity (1979), Stock and Watson (1984) and Smith and Taffler (1984) alluse this type of schematic face structure to contrast “healthy” and “distressed”companies. An impression of a healthy, profitable and secure company iscreated by a smiling face and large eyes, while a company in financial distresshas a worried frown, down-turned mouth and small eyes. The overall messagecreated for the latter would be one of the empty, washed-out face of animpoverished enterprise.

Figure 1.A template for failure

classification:alternative outcomes

from the assignment offinancial variables tofacial characteristics

Distressed Neutral Healthy

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The clarity with which the foregoing figures convey their financialmessages, in the absence of a detailed narrative explanation, provides theimpetus for an analysis of the relative explanatory power of alternativepresentation formats.

The feature assignment illustrates the way in which a visual impression ofthe personality of each company can be created which may even allow somespeculation as to its corporate identity and attributes[3]. The financial ratios aremapped precisely onto the facial features so that their positions correspondprecisely relative to industry averages.

For each financial ratio calculated, the industry means and standarddeviations corresponding to that time period are used to convert the ratio into anumerical form expressed as “number of standard deviations above/below theindustry mean”.

For example, suppose that the manufacturing Company XYZ has aprofitability ratio (PBIT/TA) of 0.238, where the industry mean and standarddeviation for that sector in that particular year are respectively 0.07 and 0.12.Relative to the rest of the sector Company XYZ’s profitability is, therefore, 1.4standard deviations above the mean

The mean position for the neutral face and the total range of lengths and anglesfeasible in the facial caricature allow the development of means and standarddeviations for each facial feature. Financial ratios are mapped onto theirassigned facial characteristic in terms of the number of standard deviationsfrom the mean so that a precise correspondence of number to position isachieved. If profitability is mapped onto the mouth, say, then both the lengthand curvature of the mouth will be determined by the profit ratio. In the case ofCompany XYZ, above, both the length and the curvature will be 1.4 standarddeviations above their mean position, resulting in the display of a modest smile.

Use of industry relatives means that it is possible for an improved financialratio in absolute terms to coincide with a deterioration of facial message if theratio improvement is lower than that for the industry as a whole. The implicituse of industry statistics in constructing the facial portrait potentially improvesthe processing of financial messages over that with financial ratios, even whenthe industry statistics are made available to users.

Consequent on the results of earlier studies, together with the incorporationof advances in the psychological literature, two issues arise for furtherconsideration:

(1) facial profiles might be processed significantly more quickly than eitherfinancial ratios or accounting statements;

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(2) the classification decisions made using the facial profiles might be moreaccurate than those made with either financial ratios or accountingstatements.

Together, these issues prompt a discussion of the resultant improvement indecision performance from the use of schematic faces, measured in terms of“efficiency” and “effectiveness”. With respect to the format of presentation, themost efficient form of presentation is defined by Bertin (1983) as that whichminimizes the effort, measured by time, which is expended to interpret therelevant aspects of the information set and provide a satisfactory answer to thegiven question. Effectiveness is defined by Lusk (1979), in this context, as theform of presentation which makes it easiest to generate the most accurateanswer to a given set of questions.

An experiment is, therefore, conducted to examine the facility of respondentsof varying accounting sophistication with accounting information presented inalternative formats. Their processing time and the number of errors ofclassification that they make generate measures of the efficiency andeffectiveness of the alternative formats.

Although several previous studies (e.g. De Sanctis, 1984; Remus, 1984) havecompared graphical and tabular data presentation formats, few have usedschematic faces. Mackay and Villarreal (1987) recognize that Chernoff displayscapture multivariate data holistically, in a mnemonic way,unique amonggraphical presentations, making comparisons with other presentation formspotentially difficult. Their study fails to identify any superiority of Chernofffaces over tabular data in financial decisions, but they do not distinguishbetween Type I and Type II errors. Altman et al. (1977) suggest a relativemisclassification cost weighting of 40:1 in favour of Type I errors, relative toType II errors, suggesting that a processing format is required which minimizesopportunities to misclassify failed companies.

While the simplicity of the facial technique is a positive feature incommunicating financial information, especially to the less sophisticated ofusers of accounting information, it can be a barrier preventing its widespreaduse. It has to be demonstrated that, apart from the novelty of approach, thismethod can improve on the quality of decisions made using traditionalmethods. To test the hypothesis that facial profiles might provide an efficientmeans of representing financial variables, an experiment is devised to test thereactions of respondents to financial information expressed in alternativeforms:

• accounting statements; • financial ratios derived from these statements; and • “faces” constructed by the application of financial ratios to particular

facial features. The experiment is conducted with three different groups of skilled users and agroup of naïve[4] users to represent users of all levels of sophistication:

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accounting academics from the Universities of Leeds, Lancaster andBirmingham, accounting practitioners from Big 6 companies and MBA financemajors from City University, London. Together they provide a sample size of121 sophisticated users, comprising 52 accounting academics, 23 practitionersand 46 postgraduate students. The skilled users, though not all practitioners,employ accounting information and financial statement data regularly, andhave an extensive knowledge of accounting terminology and format.Comparisons with naïve users, unfamiliar with accounting information, provedunworkable at the pilot stage of the study causing them to be excluded from thesample. These relatively unsophisticated users responded well to the schematicfaces but for them the faces were the only accounting medium to convey anymeaning.

A systematic sample of 20 listed UK manufacturing companies is chosen toprovide a majority that are still trading and a minority of failures, together withexamples of companies across the whole range of processing difficulty. Arandom sample of a company database is not employed since it would beunlikely to give many (if any) failures. A 14:6 (i.e. 70 per cent:30 per cent) splitbetween non-failed and failed companies in the sample is adopted because itconforms closely with the percentage split at the time between healthy anddistressed companies in the population, based on their computed Z-scores. Thisdivision avoids an even distribution of companies while providing enoughvariety in the sample to illustrate the performance range. Companies withfinancial year ends between 1974 and 1980 are chosen to reflect the clearlyhealthy/clearly failed extremes while including several marginal andpotentially more difficult cases. At no time are the respondents made aware ofthe 14:6 division[5]. Accounting statements and financial ratios are preparedand faces constructed for each of the 20 companies over five-year periods and arandom numbering system used to separate the statements/ratios/facesinformation bases.

Respondents are familiarized with the use of schematic faces during a20-minute briefing session immediately prior to the conduct of the experiment.The briefing addresses:

• accounting information as a complex multivariate dataset; • alternative graphical means for displaying data; • focus on the schematic face and its computer-based construction; and• advantages and disadvantages for potential applications of such faces in

the financial environment Prior to the experiment respondents are issued with sample information sheetsto illustrate the manner in which the statements and ratios will be depicted andwith an illustration of the assignment of ratios to features in the facialrepresentations.

Each respondent is then issued with three separate sets of materials andasked to make failed/healthy decisions for each of the 20 cases, together with an


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indication of the total time spent in processing the materials. Each set ofmaterials comprises financial information over a five-year period presented in adifferent medium. For failed companies the fifth year is the last prior to failure.On completion of the first decision task, respondents are asked to repeat theexercise successively with 20 sets of company financial ratios and schematicfaces respectively. They are informed that the companies are different in eachinstance[6].

Processing orders are varied so that all six possible orderings of statements-ratios-faces, statements-faces-ratios, etc., are employed. Test materials areordered randomly for distribution among the three user groups in order todetermine any impact that order of processing might have on the accuracy andspeed of classification. A common single assignment of financial ratios to facialfeatures is used throughout[7]. On completion of the experiment respondentsare informed of the identity of the companies and their financial status. Mackayand Villarreal (1987) express concern over individual differences in cueresponsiveness in the use of schematic faces. They note that content validitymight be lowered because of the comic appearance of the faces, and that femalesappear to be more responsive to facial displays than males, both factors havinga potential impact on the quality of the resulting decisions. Although desirable,the testing of gender effects is not possible with this sample. Only three of theentire sample of 121 are female, all being MBA students. We might speculatetherefore that the subsequent results might even understate the impact ofschematic faces.

ResultsOutcomes measuring the “efficiency” and “effectiveness” of the alternativeprocessing media are detailed in Table I for both the complete sample of 121respondents and each of the separate user groups. An analysis of these resultshighlights two differences, each statistically significant at the 5 per cent level:

(1) The proportion of failed cases misclassified is very much higher thanthat of the non-failed cases. This is a potentially important feature of the

Mean percentage of classification errorsType I Type II Classification time

(Healthy when failed) (Failed when healthy) (Minutes)Accounts Ratios Faces Accounts Ratios Faces Accounts Ratios Faces

Accountants(n = 23) 29.0 31.2 5.1 15.8 29.5 20.8 12.9 11.6 4.0Academics(n = 52) 34.0 38.8 15.4 12.8 16.6 13.2 11.2 7.6 3.8MBA students(n = 46) 31.2 30.4 9.0 16.0 17.9 16.3 11.4 8.0 4.1Total 32.0 34.2 11.0 14.6 19.5 15.8 11.6 8.5 4.0

Table I.Mean error classification

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results neglected by earlier studies, if, as suspected, the “missed failure”is a relatively more important misclassification.

(2) The time spent processing the facial profiles is less than half that spenton either accounting statements or financial profiles.

Paired-case t-tests are employed to compare the decision-making performanceof individual respondents for each of the means of presentation. For each of the121 respondents the t-statistics generated are shown in Table II together withthe corresponding level of statistical significance.

The faces produce significantly fewer Type I errors, than either theaccounting statements or the financial ratios. The faces produce significantlyfewer Type II errors than the ratios, but not the statements. The high rates ofmisclassification with financial ratios are consistent with the findings ofMoriarity (1979) who attribute it to a lack of understanding of what the ratiosreally represent.

Table III shows the corresponding differences for processing times,demonstrating that the faces are processed significantly more quickly thaneither the accounting statements or financial ratios. The facial profiles therefore

Processing timeRatios Faces

Accounting statements 6.5 18.1(0.000) (0.000)

Financial ratios 13.0(0.000)

Note: The levels of statistical significance are in parentheses

Table III.t-statistics for processing time differences

Financial ratios Schematic facesType I Type II Type I Type II

Accounting statementsType I 0.9 9.1

(0.358) (0.000)Type II 4.0 1.1

(0.000) (0.277)Financial ratiosType I 10.6

(0.000)Type II 2.8

(0.006)Note: The levels of statistical significance are in parentheses

Table II.t-statistics for error differences


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generate decisions at least as good, and often better, than using other sources,and much more quickly.

An analysis of the error classification of Table I demonstrates the extent towhich performance differences are attributable to the accounting sophisticationof the subjects and the processing order of materials. Tables IV and V reveal theF-statistics, and corresponding levels of significance, resulting from an ANOVArelating error incidence and processing time to the status of subjects andprocessing time.

Table IV shows that order of processing does not significantly influence theincidence of error for any of the alternative media. The level of accountingsophistication does impact on classification errors, with the accountingpractitioners making significantly more Type II errors using the financial ratios

Accounting Order ofsophistication processing

Accounting statementsType I 0.7 1.1

(0.506) (0.354)Type II 2.4 1.8

(0.100) (0.123)Financial ratiosType I 2.3 0.9

(0.101) (0.469)Type II 6.5 0.4

(0.002) (0.821)Schematic facesType I 5.8 1.4

(0.004) (0.214)Type II 5.4 1.2

(0.006) (0.314)Note: The levels of statistical significance are in parentheses

Table IV.F-statistics for Type I/II

errors

Accounting Order ofsophistication processing

Accounting statements 1.3 0.4(0.283) (0.798)

Financial ratios 7.7 6.2(0.001) (0.002)

Schematic faces 0.7 2.7(0.492) (0.023)

Note: The levels of statistical significance are in parentheses

Table V.F-statistics for

processing times

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and the accounting academics making significantly more Type I and Type IIerrors with the schematic faces.

Observed error patterns help to explain the manner of informationprocessing and the decision-making strategies employed. A simultaneousconsideration of profitability, short-term debt and balance sheet strength issufficient to avoid errors of classification for each of the alternative processingformats[8].

We may speculate on decision-making strategies employed by reference tothe error patterns generated by respondents. A naïve processing strategy,applied systematically, of designating companies as “failed” based on anegative profit before tax figure, generates a familiar error pattern comprisingthree Type I errors and two Type II errors. This pattern of Type I errors arisesin 18 per cent of accounting statement misclassifications (and 13 per cent offinancial ratio misclassifications); this pattern of Type II errors arises in 27 percent of accounting statement misclassificaitons (and 19 per cent of financialratio misclassifications).

The frequency of this pattern of errors suggests a myopic profit focus, to theextent that neither balance sheet information nor industry data receiveappropriate emphasis.This single-variable fixation apparently extends to theschematic faces, where the most common misclassification pattern (of threeType II errors, but no Type I errors) is consistent with a strategy of designatingas failed those companies displaying a down-turned mouth. Thismisclassification pattern is observed in 26 per cent of error profiles, but theextent of error is apparently less serious because the schematic facesautomatically incorporate industry averages where a down-turned mouth isassociated not with negative profits, but profitability levels less than theindustry average. Poor performers (potential Type I errors) are, therefore,identified and the overprediction of failure (Type II error) becomes the dominantform of error.

Overall, 69 per cent of errors on the accounting statements, 57 per cent oferrors on ratios and 77 per cent of errors on the faces are consistent with a focuson the profit variable alone. This processing pattern is apparently particularlyprevalent among the accounting academics, resulting in a disproportionatenumber of both Type I and Type II errors. The integration of balance sheetinformation on the accounting statements and ratios, corresponding to theincorporation of upper-face features on the schematic faces, allows a rapidreduction in the number of misclassifications.

Table V shows that the processing time due to the financial ratio analysis isinfluenced by both levels of accounting sophistication and processing order.The accountants take a significantly longer time to process the financial ratiosthan either of the other groups, consistent with the unfamiliarity argumentscited above. The processing time for the ratios is significantly shorter whenthey are considered last of the three datasets. The reduction in elapsedprocessing time when being processed last is common to all three informationmedia, but is significantly more marked in the case of the financial ratios.


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Discussion and further researchThere has been limited study to date of the effectiveness of alternative methodsof presenting accounting information for financial decision purposes. Thispaper explores empirically the usefulness of the schematic face as acommunication device, in a particular decision context, compared with moreconventional presentation formats. The paper addresses the relative usefulnessof schematic faces, financial ratios and accounting statements as informationformats for decision making, demonstrating that schematic faces provide analternative means of presentation which might provide a clear and efficientrepresentation, complementing existing methods. In this respect the paperprovides substantial support for the findings of Moriarity (1979) but in amanner which produces results far more reliable than those of Moriarity orStock and Watson (1984). The Moriarity study has the potential for biasedoutcomes favouring faces attributable to accounting ignorance, associated withthe inclusion of too few experimental subjects of any accounting sophistication.Both of the above studies use arbitrary author-driven selections of featureassignments which make no reference to the relevant psychological evidence onthe saliency and mobility of facial features. Neither study includes means andstandard deviations for the financial ratio information provided, running therisk of producing results attributable to superior information and not superiorpresentation, given that the schematic faces implicitly incorporate thesestatistics. This present study overcomes all of these deficiencies associated withearlier research in this area.

Evidence is provided that schematic faces are processed more quickly thaneither of the more traditional methods of information presentation, with no lossof accuracy, by users of varying levels of accounting sophistication. Repeatedmisclassifications are consistent with overemphasis on the profit figure. Wherethe facial profiles produce misclassifications not apparent with the otherprocessing media, this is consistent with undue emphasis on the mouth as afacial characteristic. Subject feedback on their response to the use of facialcaricatures, relative to more conventional information forms, is most revealing.Very little use is apparently made of mean and standard deviation informationwhen provided, so that the superiority of the face may be at least partlyattributable to the way in which it “forces” subjects to employ this additionalinformation. The precise assignment of the financial variables to facial featurestoo, appears to be relatively unimportant once subjects are familiar with theformat. This is reassuring since the message conveyed by the face is so clearthat the opportunities for manipulation might lead us to call for accountingstandards which control the assignment of variables to features. Smith et al.(1993) suggest that the feature assignment is of much less importance toprocessing in practice than the methodology employed. Evidence fromsubsequent trials conducted by the authors is consistent with De Sanctis andJarvenpaa (1989) who suggest the presence of a learning curve in the use ofgraphical information in the accounting profession. Casual observationsuggests that with practice users of schematic faces will develop a holistic

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perspective and reduce the overemphasis accorded the mouth, with thepotential for further improved decision making.

The impact of the use of caricatures on the behaviour of subjects can haveboth positive and negative effects, with the potential to influence decisionmaking. The novelty value of schematic faces generates interest and makes themfun to work with; however, the trend in the use of graphics and other visuals inthe annual report, as reported by Beattie and Jones (1992) has not extended tothe use of schematic faces. The message conveyed by the faces may be just tooclear for this purpose, effectively preventing their successful obfuscation byfirms wishing to disguise poor performance. Interestingly in this context,consulting conducted by the authors to display company schematic faces at theAGM to convey corporate performance, was discontinued once the faces ofcompetitors were clearly superior to those of the client company! On the negativeside, the faces may be perceived as trivial and not credible, with the potential forlowering the content validity of the experiment. One potential subject (amongthe group of accounting academics approached here) refused to take part in theexperiment on these grounds. By demonstrating the potential for improveddecision making utilizing new technologies even the most reluctant ofparticipants cannot help but be impressed; in this case a group of accountants ofa largely conservative demeanour make demonstrably more accurate decisions,much more quickly, through a medium that they had previously not confronted.

The results presented here demonstrate the usefulness of schematic faces as adecision tool in the financial environment, with the potential to have a significantimpact on the work of bankers, asset managers and financial analysts. Byproviding a speedy, accurate method of processing information, particularly forextreme cases, the schematic faces may free up management time for the moredetailed analysis of complex situations. These might feasibly include theperformance of investment managers, being appraised simultaneously on anumber of different dimensions of activity, the communication of divisional ordepartmental performance based on non-financial achievement, or therepresentation of companies by different aspects of their stock marketperformance. All of these examples would move away from the failed/non-failedcontext, the last away from the good/bad distinction, by searching instead forpatterns of performance that might yield a balanced portfolio.

Future research must also pay more attention to the differences betweenindividual subjects. Mackay and Villarreal (1987) hypothesize that mental state,cultural group, personality and psychological factors may be interveningvariables worthy of investigation. Sobol and Klein (1989) echo these concerns,demonstrating empirically that the efficiency and effectiveness of graphicaldisplays is dependent on the cognitive style of the respondents. They suggestthat persons with a cognitive style suited to thinking, rather than feeling, havemore success with less traditional graphic forms, though their study did notextend to a study of schematic faces. These factors should be taken into accountin future studies in this area.


graphics

83

Notes1. The computer code employed to construct Bruckner’s version of the Chernoff face is

detailed in Wang (1978, pp. 115-20).2. The four ratios are:

These four variables represent the same four dimensions (profitability, working capital,gearing and liquidity) as employed by Taffler (1982) in his Z-score model. The fourvariables above are preferred to his model variables (PBT/CL, CA/TL, CL/TA, NCI) on thegrounds of user familiarity.

3. This visual representation of performance, based on accounting numbers, complementsthe idea of “corporate personality” developed in a numerical sense by Sorter et al. (1966).

4. The naïve users comprised a group of 30 first-year undergraduate business students whohad yet to undertake an accounting course.

5. Previous studies (e.g. Houghton, 1984) show that respondents tend to assume anapproximately equal division of failed and healthy companies. Where specific priorprobabilities are indicated (e.g. Libby, 1975) respondents may fail to treat each case on itsindividual merits, preferring to rank cases on a best-to-worst basis and then group on thebasis of the given failure base rate.

6. Sample test materials used in the experiment are available from the first author.7. This is a complex and potentially significant issue. Further empirical work is currently

being undertaken to resolve the specification of an optimum assignment of financialvariables to facial characteristics. Results to date, from Smith et al. (1993), suggest that it isthe adoption of schematic facial profiles which is important to communication, rather thanany particular feature assignment methodology.

8. The total sample of 20 cases is classified correctly through the adoption of an appropriatelinear discriminant model. A simple decision strategy based on a unit-weighted linearcombination of three of the four financial ratios generates one Type II error:

A combination of down-turned mouth, small eyes and perplexed eyebrows similarlycorrectly identify all of the failed companies from the schematic faces.

PBIT

TA

TL

NW

QA

CL < 0.– +

•

•

•

•

Profitability by Profit before interest and tax

Total assets

PBIT

TA;

Working capital position by Working capital

Net capital employed

WC

NCE;

Financial leverage by Total liabilities

Net worth

TL

NW ; and

Liquidity by Quick assets

Current liabilities

QA

CL

AAAJ9,2

84

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