Accounting for the man-information interface in management information systems

OMEGA, The Int. Jl of Mgmt Sci., Vol. 1, No. 6, 1973

Accounting for the Man-Information Interface in Management Information Systems HERBERT MOSKOWITZ Purdue University

RICHARD O MASON University of California (Received April 1973; In revtsedform June 1973)

A primary cause for the failure of both formal and informal management information systems to live up to expectations stems from the designer's lack of awareness or improper conception of the interfaces existing between information and man, its user. This underscores the need for a better understanding of the relationship between man, psychologically and sociologically, and information. The results of several experiments performed in a simulated financial setting are presented as illustrations of human information processing tendencies in both individuals and committees. Design options to attenuate human foibles and limitations and to counterveil propensities to subvert systems are discussed. Areas for further research are suggested.

INTRODUCTION A s C H A L L E N G E S to traditional organizational structure continue in the form of new technology and new attitudes, increasing attention must be paid to the design and redesign of information and decision systems. Unfortunately, too few o f the design prescriptions are based on solid theory or empirical studies. This is at least in part attributed to our inadequate understanding of the psychological and sociological factors affecting man qua decision maker and his relationship with information. It seems necessary, then, to learn more about how people obtain, integrate, communicate, and act on information in concert with others in today's organizational settings. The research reported in this paper is concerned with the problem of h u m a n judgment and decision making as it relates to the design of management information and decision systems; in particular, with the processing of information that precedes and determines decision making activities. 679

Moskowitz, Mason--Accountingfor the Man-Information Interface Judgment is a primal cognitive activity that vitally affects the well-being and survival of all human beings. Decision making is more complex, involves far greater-reaching consequences, and is more risky than ever before in our history. Technology has empowered modern man to decide the destiny of huge population masses, even the entire Earth. Modern organizations have been affected as well, as they have become increasingly large and complex. Even the personal decisions that direct an individual's daily life have increased in complexity. The prime ingredient upon which decision making processes depend is information. And the difficulties attendant to decision making are principally blamed on the inadequacy of available information. Hence, our technological and managerial expertise have been mobilized to remedy this problem through a proliferation of technological and organizational devices to supply the decision maker with an abundance of data. The physician, for example, has access to sophisticated electronic monitors. Satellites via telemetry now relay masses of strategic and non-strategic data for military intelligence and human welfare. Computerized management information systems (MIS) efficiently provide more timely and complete information to the decision maker for the strategic and operating decisions that take place daily in the conduct of the enterprise. Groups, formed for judgmental and decision purposes (viz. committees, panels, councils, juries, boards, etc.) have become one of the most ubiquitous organizational instruments of our time, as a means of effecting information exchange and improving decision making. (Groups are also formed for other purposes, such as fact finding, representation of sectional interests, controlling individual power, soliciting organizational commitment, etc.) Even our personal decisions are no longer made without advice from others, as evidenced from the countless numbers of institutions and services created for the express purpose of expediting decision maker access to data from expert sources. We are indeed in an "information revolution" and have largely become a society of "symbol manipulators"? In the context of today's complex decision environment these developments, in general, are encouraging and praiseworthy. They must, however, be kept in perspective. There are numerous instances where the provision of more information has not resulted in improved decision making as, for example, many organizations with fully computerized MISs have unfortunately discovered, much to their chagrin. Ackoff [1] rightfully blames the failures of such systems on designers' ignorance of the needs and capabilities of the decision maker, the recipient and user of the information. This underscores the importance of examining more closely the relationship between man--psychologically and sociologically--and information. One aspect of this issue, which has received surprisingly little attention and has been apparently totally ignored in MIS design, concerns how man interprets and lit has been estimated that over 40 per cent of the Gross National Product is contributed by those involved in such tasks. This is increasing at an annual rate of 10 per cent [18]. 680

Omega, VoL 1, No. 6 integrates the information he receives. Typically, once the information reaches the decision maker, he is left to his own devices, in much the same manner that has been relied upon since antiquity, best expressed as "a kind of gut feeling". The focus of this paper is on the individual and collective processes that humans qua decision makers employ to assimilate discrete items of probablistic information. Although there was little research in this area prior to 1960, since then much has been done, and the annual volume has been increasing exponentially, stimulated by the growing awareness of the problem's significance and the aid of the omnipresent computer. An excellent summary of this research is found in Slovic and Lichtenstein [25]. Much of the recent work has been accomplished within the "Bayesian" school by "behavioral decision theorists". The modem impetus for what we are calling the Bayesian paradigm is rooted in the work of von Neumann and Morganstern [29] who revived interest in maximization of expected utility as a core tenet of rational decision making, and to Savage [22], whose Foundations of Statistics fused the concepts of utility and subjective probability into an axiomatized theory of decision making under uncertainty. Little of the research results, however, have been applied to organizational problems (one exception is Driver and Streufert [4]). This can be primarily attributed to psychologists' preoccupation with developing theories of human behavior and their laxity in getting their findings to bear on urgent, practical problems. Their work has thus been confined to the experimental laboratory where they employ tasks that have little if any relevance to real world decision problems. For example, most Bayesian experiments use some variant of the familiar book-bag and poker-chip paradigm to study human information processing behavior. Would people behave similarly in more meaningful situational settings remains an important empirical question. Things have, however, begun to change; partly because funding agencies have been clamoring for more relevance, and because formal planning and decision models which require subjective probability inputs are being introduced into management practice (e.g. in planning and controlling research and development (R&D) projects [27], capital budgeting [10]). Consequently specialists from many disciplines have begun to focus on the integration process itself. Their efforts center around three broad questions: (1) What is the decision maker doing with the information available to him? (2) What should he be doing with it ? (3) How can this knowledge be used in practical applications ? The first question is psychological and sociological, that of understanding how man uses information and how this behavior is affected by others around him. The second and third are normative, pragmatic questions and involve an attempt to make information processing and decision making more effective and efficient. It is in this spirit and in the hope of (1) providing a perspective for further empirical work useful to MIS design and (2) engendering managerial awareness 681

Moskowitz, Mason--Accountingfor the Man-Information Interface of the interfaces existing between men and information, that we report the results of some experiments which examined the processes by which individuals and groups integrated information into a judgment or decision. What particularly distinguished these experiments from other Bayesian information processing studies was the more realistic nature of the task and focus on both the individual and group as the decision making unit. The problem setting was one familiar to financial institutions: the decision whether to grant a personal loan to a prospective borrower. The decision making unit was a loan lending committee, normally used for such types of decisions in practice. The experiments reported below addressed several questions concerning the nature and sources of conservatism in human information processing behavior, i.e. 2

(1) Does conservatism exist when individuals and groups process information in a simulated business decision setting ? (2) For both individuals and groups, to what extent is conservatism affected by the order of presentation of and the degree of informativeness of the data ? (3) Might conservatism be partially explained by one's risk taking tendency, or second order probabilities (i.e. probabilities concerning the numerical value or credibility of the direct first order probabilities regarding the hypothesis) ? The paper proceeds as follows. The Bayesian Model, as pertains to these experiments, is first discussed briefly. Next is described the general research methodology and task. The experiments and their results follow. The final section is reserved for a discussion of the practical implications.

THE BAYESIAN MODEL The Bayesian approach is thoroughly embedded within the framework of decision theory. Its basic tenets are that opinions should be expressed in terms of subjective probabilities, and that the optimal revision of such opinions, in the light of relevant new information, should be accomplished via Bayes' Theorem, the normative model. It specifies certain internally consistent relationships among probabilistic opinions and serves to prescribe, in this sense, how men should think. More spedfically, Bayes' Theorem spedfies the revision of the probability of hypothesis H as a result of information provided by the occurrence of datum D. The revision of probabilities involving two hypotheses, H and H', which is zConservatism denotes that upon receipt of new information, humans revise their posterior probability estimates in the same direction as Bayes' Theorem, but the revision is typically too small; i.e. humans act as if the data are less informative than they truly are. Much of Bayesian research has been motivated by a desire to discover the determinants of conservatism.

682

Omega, Vol. 1, No. 6 relevant to the experiment discussed may be written as p(H [ D) -- p(H' [ D) = [p(D I H) -- p(D I H ' ) ] . [p(H) -- p(H')], or more simply, nl = Lr~0. The p(H) is revised to p(H ] D) due to the occurrence of D. The r~0 and L"~1 denote the odds in favour of H over H ' prior and posterior to the occurrence of D respectively. L refers to the likelihood ratio [L : p(D ] H) + p(D I H')] and is a measure of the diagnosticity (or informativeness)of D where diagnosticity refers to the amount of revision from r~0 to ~1. A more detailed explanation of the Bayesian paradigm can be found in [25] and appropriate references cited therein. More specifics on the model as related to these experiments are found in [19]. The primary data analysis in most Bayesian probability revision experiments (as well as in our experiments) compares subjects' probability revisions upon receipt of each datum with those of Bayes' theorem. To supplement direct comparisons of Bayesian probabilities and subjective estimates Peterson, Schneider, and Miller [21] introduced a measure of the degree to which performance is optimal, called the accuracy ratio. A subject's or group's accuracy ratio with respect to, say, X is defined as logLxa log Lx where L~ is the log likelihood ratio inferred from the subjects' probability estimates and log Lx is the optimal (Bayesian) log likelihood ratio. The conversion to log likelihood ratios is made because the optimal responses then become linear with the amount of evidence favoring one hypothesis over the other. The accuracy ratio is 1.0 when subjective revision equals Bayesian revision and decreases below 1.0 as the subject becomes more conservative. 3

RESEARCH METHOD The experimental instrument used in this research involves the evaluation of applicants for personal loans by a bank lending officer. With the exception of its summary form and the particular numerical values used, the data items are the same as those available to many bank lending officers. This instrument was chosen as the experimental task for a variety of reasons: (1) Loan decisions in banks and financial institutions are frequently made by lending committees or subcommittees [15]. (2) A Bayesian solution to the problem can be calculated thus providing an objective standard by which to compare human vs optimal probability assessments. (3) The task is meaningful to subjects. 3The AR, however, can sometimes obscure the process at work. For example, if subjects do not give very different estimates for different data, the Bayesian denominator does all the work, resulting in what appears to be a conservative Bayesian process where there may be no "process" at all. To preclude the possibility of such misinterpretations, subjects' raw revised probability responses must also be examined. 683

Moskowitz, Mason--Accounting for the Man-Information Interface The task, consequently, possesses a variety of properties which makes it well suited for systematically investigating human information processing behavior, while also providing a high degree of subject interest and involvement.

Task The intent was to make the task as representative of the real decision making situation as possible. In considering a loan application one of the critical judgments that a lending officer makes is his assessment of the likelihood that the applicant will either default or be delinquent. Lending officers arrive at this judgment on the basis of the data that they receive about the applicant. Some of this data comes from the loan application form itself, some comes from the bank's internal records and some comes from outside sources such as reference and credit data services. Discussions with lending officers and observation of the methods used in various banks indicate that different banks and different lending officers each develop their own approach or "style" for sifting through and evaluating these data. The experience of banks varies however. Some find external sources such as the credit data services to be quite informative as to the likelihood of default or delinquency; others rely more on their own credit scoring techniques or on indications from past history with the applicant. The real task according to several lending officers is to "collect the relevant data, weight it and to arrive at a conclusion". In an effort to aid lending officers in making this judgment several banks' management science departments have analyzed the various data sources and have estimated the probability that an applicant might default or be delinquent given certain data patterns. Since we are interested in improving the generalizability of our results to real information systems and decision-making situations our experiment attempted to replicate these actual conditions as closely as appropriate experimental design procedures would permit. In the experiment each subject assumed the role of a bank loan officer or member of a loan committee who was to assess the probability that a loan applicant requesting a $5000, unsecured, vacation loan would become delinquent in his payments during the coming year [i.e. H = hypothesis "applicant will be delinquent", subject estimated P(H)]. In addition to background information obtained from the loan application, data on the applicant from three conditionally independent, binary, symmetric information sources were sequentially presented to the loan officer, which, although fictionalized, provided objective (relative frequency) conditional probabilities [e.g. P(Dx [ H)] based on actual historical studies of bank files. 4 These were (1) the bank's own internal records, (2) a credit scoring system based on the borrower's attributes, and (3) a credit data service which provided retail credit information. The conditional pro+The information sources were developed from discussions with officials from several financial institutions and were based on independent sources they used in evaluating loan applicants. 684

Omega, Vol. 1, No. 6 babilities were presented in the form of statements, such as "The records show that among those people who have never been delinquent 90 per cent obtained a score of less than 75 points. Mr. Jones' score is 60 points". The conditional probability matrix for each information source is depicted in Table 1. TABLE 1. INFORMATIVENESSOF INFORMATIONSOURCES Hypothesis

H (delinquent) H' (not delinquent) Likelihoodratio

Data item X X"

0.20 0.80 1[4

Data item Y Y"

0.80 0-20 4

0.10 0.90 1/9

0.90 0.10 9

Data item Z Z"

0.30 0-70 3/7

0.70 0.30 7/3

With each item of new data received from the information sources the individual or committee indicated on a 99 position scale the likelihood that the borrower would be delinquent in paying back his loan within one year. Prior to the information processing task a reduced version of Kogan and Wallach's [13] Choice Dilemmas Questionnaire (CDQ) was administered to determine the risk-taking propensity of the individuals and groups. At the completion of the processing task the subjects reviewed the information sources and evaluated the credibility of the data provided by each source on a 10 point scale. The accuracy ratio was used as the basic criterion for evaluating subjects' probability responses. The experimental instrument was employed in two sets of experiments, the first dealing with individual behavior (Experiment I), the second with group behavior (Experiment II). The experiments, results, and discussion are individually summarized below.

Experiment I The purpose of this experiment was to determine the effect of degree of informativeness and order of presentation on individual information processing behavior. A second objective was to determine whether individual's risk attitudes and trustworthiness of the information sources influenced their behavior. The experimental design was as follows. From the three information sources in Table 1 eight data group combinations can be enumerated, and from each group there exist six orders of presentation, totalling 48 data group sequences. In that it was infeasible to test all data group sequences a 3 × 3 latin-square design was formulated by randomly selecting X', Y, and Z' as the data items for presentation (Experiment IA) and its counterpart was formulated by using X, Y', Z (Experiment IB). This led to the following complementary latin-square design (Table 2). After reading the situational scenario the subject recorded his prior probability that the borrower would be delinquent on the scale provided. Then depending upon his experimental group, he received the first item of information 685

Moskowitz, Mason--Accounting for the Man-Information Interface TABLE 2. LATIN-SQUAREEXPERIMENTALDESIGN Experiment I Group

A-1 A-2 A-3

Order of presentation 1 2 3

X' Y Z'

Z" X" Y

Experiment II Group

Y Z' X'

B-1 B-2 B-3

Order of presentation 1 2 3

X Y' Z

Z X Y'

Y" Z X

(e.g. G r o u p A1 received X ' initially). H e was given 5 m i n to consider the i n f o r m a t i o n , t o re-evaluate his previous estimate, a n d to m a r k his revised p r o b a b i l i t y on a new scale. H e t h e n received the second item o f i n f o r m a t i o n (e.g. Z ' ) with the s a m e instructions a n d finally he received the t h i r d item (e.g. Y). O n e h u n d r e d a n d t w e n t y u p p e r division u n d e r g r a d u a t e business a d m i n i s t r a tion students at San F e r n a n d o Valley State College were " h i r e d " as b a n k l o a n m a n a g e r s a n d were r a n d o m l y assigned into each o f the e x p e r i m e n t a l groups. Results. T a b l e 3 shows the cell a n d m a r g i n a l effects in terms o f m e a n accuracy r a t i o s for each o f the m a i n factors c o n t r o l l e d for: A = informativeness o f item (i.e. m a g n i t u d e o f Bayesian l i k e l i h o o d ratio), B = o r d e r o f presentation, a n d C = g r o u p assignment. A n analysis o f variance ( A N O V A ) using a 3 × 3 l a t i n - s q u a r e design with no r e p e a t e d measures [31, pp. 524--529] was p e r f o r m e d o n the data. T h e results s h o w e d b o t h a significant d a t a item effect ( E x p e r i m e n t I A : F = 8"5; d f = 2, 1 7 1 ; p < 0.005; E x p e r i m e n t I B : F = 18.55; d f = 2, 171; p < 0.005), a n d a significant o r d e r effect ( E x p e r i m e n t I A : F ---- 3-39; d f = 2, 171 ; p < 0.05; E x p e r i m e n t I B : F ---- 3.20; d f = 2 , 1 7 1 ; p < 0.05). TABLE 3. MAIN EFFECTS Experiment I A Effect items Z'(70%) X'(80%) Y (90%) B Marginals

1

B Effect order 2

3

1.04 C3 0.94 C1 0.70 C2 0.89

0.82 C1 1.02 Cz 0.41 Ca 0.75

0.94 C2 0.55 C3 0.33 Cx 0.61

I

B Effect order 2

3

1"62 C3 0.83 C1 0.59 C2 1"10

0"75 C1 0.89 C2 0.45 C3 0"70

1"25 C2 0.61 C3 0.26 C~ 0.71

C Effect group Numer of A Marginals assignment subjects 0.93 0.84 0.48 0-75

Ct = 0.70 Cz = 0-88 C3 = 0.67

nl = 20 n2 ~-20 n3 = 20 n = 60 Total observations = 180

Experiment II A Effect items Z X Y' B Marginals

686

C Effect group Number of A Marginals assignment subjects 1"20 0.77 0.44 0.81

C1 = 0-61 Cz = 0.91 C3 = 0.90

nl ---=20 nz ~ 20 n3 = 20 n ---- 60 Total observations = 180

Omega, Vol. 1, No. 6 ANOVA assumes the effects of the three different fixed factors are additive, that errors are normally distributed with homogeneous variance. In order to determine whether the conclusions were materially affected by these assumptions the Kolmognrov-Smirnov non-parametric two-sample test was applied to the data [24, pp. 127-136]. Both ANOVA and Kolmogorov-Smirnov tests indicated that order of presentation affected the subject's accuracy ratios such that items received first were less conservative (viz. primacy effect), and that accuracy ratios varied inversely with the degree of informativeness as measured by the Bayesian likelihood ratio. 5 Neither the CDQ nor trustworthiness scores showed any relationship with the accuracy ratios and thus appeared to have no significant effect on information processing behavior. Discussion. One purpose of this experiment was to investigate the existence and nature of conservatism in a business setting. A major concern was the question of whether the conservatism phenomenon, repeatedly confirmed in the book-bag and poker-chip experiments in the psychological laboratory, extended to more realistic inference-drawing situations. Our results confirmed and extended these findings (although students were used as subjects and not actual bank officers). As in psychological studies, conservatism was affected by the informativeness of data, i.e. greater conservatism was observed with more informative data. The finding of a primacy effect also agreed with psychological experiments investigating sequential use of probabilistic information when such sequences contained data which both supported and refuted the hypothesis in question [25]. Hence, these effects appear to have considerable generality. The absence of any relationship between risk attitudes and information processing behavior could suggest that the subject's beliefs (viz. subjective probabilities) and tastes (viz. utilities) were independent. Such behavior would be consistent with Savage's "independence of beliefs on rewards" postulate which characterizes "rational man" [22]. However, this must be interpreted cautiously on two counts. First, the CDQ has become an increasingly questionable measure of risk-taking propensity [3]. Second, the majority of evidence in the psychological literature argues against the existence of risk-taking propensity as a generalized characteristic of people [26]. A person's previous learning experiences in specific risk-taking settings seem much more important than his general personality characteristics. The fact that both sequence of presentation and degree of data informativeness affect a decision maker's probability estimates and consequently can affect the nature and appropriateness of the decisions taken, indicate the importance of accounting for these factors in the design, implementation, and operation of both formal and informal MISs. and

5"Primacy" denotes that one gives more credence to data received earlier in a sequence than to data received later. "Recency" denotes the reverse concept. 687

Moskowitz, Mason--Accountingfor the Man-Information Interface Experiment II I n this experiment, we were interested in determining whether interacting consensus groups (the m o s t c o m m o n f o r m o f g r o u p decision making procedure) behaved differently f r o m individuals under the same conditions as in the previous experiment. I n that it was infeasible to replicate all the conditions tested in Experiment I, due to limitations on subject availability, only part B was performed (Table 2). Subject availability considerations also affected g r o u p size which was limited to three members. Support for a g r o u p size o f three derives f r o m a HarvardBusiness Review survey [6] which reported that executives preferred odd n u m b e r e d committee groups with an ideal size o f 5, and next most preferred size o f 3, and G o l d m a n [9] w h o f o u n d that 3-person groups were m o s t efficient in a variety o f problem-solving tasks. The procedure followed was similar to that in Experiment I. G r o u p s were instructed to reach a consensus for each response. A l t h o u g h no time limit was specified discussion groups generally t o o k no longer than 5 rain for each decision. Individuals' responses were also obtained prior to g r o u p discussion. All groups succeeded in achieving consensus, and the nature o f the discussions indicated that participants were highly involved in the experimental tasks. One hundred and seventeen upper division undergraduate industrial management students at Purdue University served as b a n k officers. The individual a n d small group behavioral laboratories o f the Behavioral Science Laboratories at the K r a n n e r t School were used to conduct the experiments. Results. Table 4 shows the cell and marginal effects in terms o f mean accuracy

TABLE 4. MEAN ACCURACY RATIOS BY DATA ITEM, ORDER, ASSIGNMENT AND GROUP

D1 Nominal groups A Data items effect z x y' B Marginals

1

B Order effect 2

1"82 (72 0.72 C1 0.57 C3 1.03

1"14 C1 0"73 Ca 0"47 (72 0.78

3

C Group assignment Number of A Marginals effect groups

1"14 Ca 1"36 C1 = 0"73 nt = 13 0.69 C2 0.71 Cz = 0"99 nz = 13 0.33 Ca 0"45 Ca = 0"79 na = 13 0.72 0.84 n = 39 Number of subjects (39 × 3) = 117 Total group observations (39 × 3) = 117

D 2 Interacting groups A Data items effect z x y' B Marginals

1

B Order effect 2

1.47 C2 0-63 C1 0'38 Cs 0'83

1,00 Ct 0,75 C3 0,46 C2 0.74

3

C Group assignment Number of A Marginals eqect groups

1.13 (73 1.21 C1 = 0.63 nx = 13 0.82 (72 0.72 C2 = 0"92 n2 = 13 0.25 Ct 0.36 C a - 0.75 n 3 = 13 0.73 0"77 n = 39 Number of subjects (39 × 3) = 117 Total group observations (39 × 3) = 117 688

Omega, VoL 1, No. 6 ratios for each of the main factors controlled for: A = informativeness of data item (i.e. magnitude of Bayesian likelihood ratio), B = order of presentation, and C = group assignment. 6 ANOVA employing both 3 × 3 × 2 and 3 × 3 latin-square designs [31, pp. 524-532] were performed to analyze the data. The results of the 3 × 3 designs (which treated both nominal and interacting groups separately) showed a significant data item effect (nominal groups: F = 1044; df = 2, 108; p = 0 . 0 0 ; interacting groups: F = 46-07; df -----2, 108; p = 0.00), a significant order effect (primacy) for nominal groups (F = 131 "67; df = 2, 108;p = 0.00), but no order effect for interacting groups (F = 0.85; dr= 2, 108; p = not significan0. Treating nominal and interacting groups in concert, namely as a third factor using the 3 × 3 × 2 design, revealed a significant group effect (p < 0.02). That is, interacting groups were more conservative in their accuracy ratios than nominal groups. The non-parametric Wilcoxon matched-pairs signed-ranks test [24, pp. 75-83] and the Kolmogorov-Smirnov two-sample test were also applied to the data and corroborated the ANOVA results. Nominal groups I0 ~

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Thus, two new significant findings emerged: (1) Although significant primacy effects existed for individuals (or, for nominal groups--statistical constructs of individual responses) these were vitiated in interacting groups. (2) Interacting groups were more conservative in their information processing behavior. Discussion. The fact that the group judgments were more conservative than its individual members' is of theoretical and practical interest. Just as an impressive array of empirical studies have focused on understanding group ~To compensate for the group biases inherent in previous comparisons of individual and group performances, nominal groups were formed by averaging the individual accuracy ratios of the group's three members [16]. 689

Moskowitz, Mason--Accounting for the Man-Information Interface Ini'eroct"ing groups i

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risk-taking, i.e. in demonstrating the existence of a risky shift and the reasons or mechanisms explaining its presence (see [1 I], [14] and [17] for summaries), similarly more studies of group information processing behavior should be performed to understand the determinants of increased conservatism between individuals and groups. From a decision-making viewpoint, if groups generally do process information more conservatively and should this bias be of sufficient magnitude to over-ride any risky shift attributed to group attitudes, this would tend to confirm and explain Whyte's [30] and others' observations of more conservative decision making in actual committees. Turning to our second finding, the vitiation of any order effects in the group raises an interesting conjecture. Namely, that communication among group members generates new information which concomitantly acts to attenuate the weights attached to earlier received information, thus functioning to vitiate primacy effects. These results and other interpretations, of course, should be treated cautiously until further empirical evidence emerges across a broader spectrum of experimental conditions. They also raise several new and important questions. To cite one, consider the aggregation process used in this experiment---consensus. In the average "real world" conference, however, decisions are made by majority rule--"the equitable or democratic thing to do". This focuses on the important empirical question concerning the relationship between the use of various amalgamation decision rules such as unanimity, majority, etc. and judgmental performance and group satisfaction. This issue takes on great practical significance in the light of current societal forces at work whose common impulse is to democratize institutions at every level [8]. Let us now shift our attention to the normative, operational implications of this line of inquiry for managers and MIS specialists. 690

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PRACTICAL IMPLICATIONS The experiments described provide further documentation of man's difficulties, both individually and collectively, in processing probabilistic information. Unfortunately, there is abundant evidence indicating that these difficulties persist when the subject leaves the artificial confines of the laboratory and resumes the task of using familiar sources of information to make decisions that are important to himself and to others. Examples have been found in business, military, governmental policy, design of scientific instruments, management of R&D [2, pp. 717-722] as well as in our natural resources. Man left solely to his intuition is not enough, as he is limited in his ability to master all the information in complex situations nor does he always behave as logic and reason tell him he should. Hence, managers and information system specialists must identify and account for such human deficiences in designing the MIS. What are the options open? One option is to incorporate counter-biases to offset various kinds of suboptimal behavior, or eliminate the conditions which create them. Consider, for example, the prospect of attenuating bias created by order of presentation. The designer, to some extent, can control the timeliness with which data is presented to the decision maker. For instance, he can analyze the delay time patterns (i.e. elapsed time from original sensing of data to its presentation to the decision maker) to determine any bias that would cause one kind of data to be systematically presented before another and to analyze forms and reporting structures for any obvious sequence biases. Here attempts could be made to synchronize data delay patterns and to reorganize forms and reports. A second alternative is to automate the information aggregation process, where technically and economically appropriate, similar to the computerprogrammed mathematical decision models of the operations researcher and management scientist which have been applied to the repetitive types of decisions of middle management (e.g. inventory, congestion, scheduling, etc.). Two approaches (viz. Bayesian and regression) have been proposed. The notion of an automated Bayesian probabilistic information processing (PIP) system is not new. It was first introduced by Edwards [7] because of his concern about the optimal use of information in military and business settings. Use of regression models developed from managers' past behavior has also received considerable scrutiny by both management scientists and psychologists. Recent research [25, pp. 716-721] has shown that such systems hold promise for improving information processing and decision making in organizations. Such systems, for example, have already been proposed for medicine, probation decision making, and production scheduling; applications to weather forecasting, jurisprudence, and business situations seem imminent. The overwhelming preponderance of day-to-day decisions, however, are and will continue to be made by the majority of business managers via the intuitive 691

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Moskowitz, Mason--Accounting for the Man-Information Interface and syllogistic process of deductive reasoning, in contrast with the computerbased management science decision models. What can the MIS architect do to improve man's ability to be logical and optimal? He can perhaps make his greatest contribution here, by incorporating into his design a flexible and adaptable control system having the following two crucially important properties (1) a reward system for good probability assessors and (2) a feedback system to foster learning through experience to develop good probability assessors. This need becomes crystal clear when one reflects on the financial consequences of inaccurate estimations of uncertainty and the numerous instances of probability slanting experienced in practice (primarily caused by control systems which reward managers for underestimates or overestimates). Such biases have been reported in R & D activities [27], in applying project management and control models such as PERT, 7 in maintenance activities [12], and in capital budgeting [33] to cite just a few examples. Yet there is little evidence to indicate any appropriate efforts to encourage estimation improvement; indeed, the reverse seems true. To meet this need scoring rules (viz. payoff functions), designed to compel individuals to articulate their true beliefs, have been developed and tested in several probability assessment tasks, and appear to have potential value in real world applications. An excellent discussion of these methods and their application in practice is found in Winkler [32]. Ebert [5] further demonstrates their use in an R&D context. McKell and Moskowitz [20] have proposed a normative model, incorporating scoring rules, which attempts to integrate both the forecasting and control functions in an MIS environment.

SUMMARY We have briefly considered some of the important options available to the MIS designer in dealing with man's inability to optimally use information. In evaluating these options the beleagured designer shoulders an immense responsibility which he cannot handle alone. He must seek expert advice. Just as he has recently begun to collaborate with management scientists and managers (the information users), he must also seek advice from the behavioral decision theorist. This might appear, at first glance, heretical, but recall the actions of many organizations a few years back to hire resident industrial psychologists trained in human factors to design the replacement of knobs, levers, gauges, etc. Certainly MIS design is more difficult and at least as important. This growing need for management and behavioral scientist to collectively attempt to integrate human and non-human processes in organizations has also been emphasized recently by Schein [23]. Let us conclude by indicating some general directions research should be taking. First, we need to learn more about the relationship between man and 7See EYRINGHB (1963) Evaluation of Planning Models for Research and Development Projects. DBA Dissertation, Graduate School of Business, Harvard University. 692

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information, both psychologically and sociologically. For example, how does man's social environment and cultural background affect his probability judgments? Are groups more effective than individuals as information processing and decision making entities ? What is the optimal group or committee format [28] ? What is the effect of the procedure for amalgamating group members' opinions (i.e. social choice function) on group judgmental and decision making performance; the effect of data complexity, format of data presentation, how data are worded, information structure of the organization, etc. Some of these topics have scarcely been touched, yet are vitally important in the context of real organizations. From the standpoint of learning, how can we best train (formally or experientially through feedback) managers to become optimal information processors ? Psychologists have paid little attention to this question, as their motives have been traditionally theoretical rather than practical. Most importantly, we need application oriented research to provide the missing link between social scientists and policy makers. This is beginning to happen. The need to develop such linkages between normative and descriptive behavior and the actual practice of management information systems design and operation must be emphasized. It is hoped that studies such as this through both making the designer (information specialist) and user (manager) more aware of the types of behavior actually found and the alternative design opportunities can contribute to that end.

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