Vol. 14, No. 4, December, 1967
Printed in U.S.A.
MANAGEMENT MISINFORMATION SYSTEMS*
Russell L. Ackoff
University of Pennsylvania
Five assumptions commonly made by designers of management information
systems are identified. It is argued that these are not justified in
many (if not most) cases and hence lead to major deficiencies in the resulting systems.
These assumptions are: (1) the critical deficiency under which most managers operate is
the lack of relevant information, (2) the manager needs the information he wants, (3) if a
manager has the information he needs his decision making will improve, (4) better
communication between managers improves organizational performance, and (5) a
manager does not have to understand how his information system works, only how to use
it. To overcome these assumptions and the deficiencies which result from them, a
management information system should be imbedded in a management control system. A
procedure for designing such a system is proposed and an example is give of the type of
control system which it produces.
The growing preoccupation of operations researchers and management scientists with
Management Information Systems (MIS’s) is apparent. In fact, for some of the design of such
systems has almost become synonymous with operations research or management science.
Enthusiasm for such systems is understandable: it involves the researchers in a romantic
relationship with the most glamorous instrument of our time, the computer. Such enthusiasm is
understandable but, nevertheless, some of the excesses to which it has led are not excusable.
Contrary to the impression produced by the growing literature, few computerized management
information systems have been put into operation. Of those I’ve seen that have been implemented,
most have not matched expectations and some have been outright failures. I believe that these
near- and far-misses could have been avoided if certain false (and usually implicit) assumptions on
which many such systems have been erected had not been made.
There seem to be five common and erroneous assumptions underlying the design of most
MIS’s, each of which I will consider. After doing so I will outline an MIS design procedure
which avoids these assumptions.
Give Them More
Most MIS’s are designed on the assumption that the critical deficiency under which most
managers operate is the lack of relevant informaiton. I do not denyy that most managers lack a
good deal of information that they should have, but I do deny that this is the most important
informational deficiency from which they suffer. It seems to me that they suffer more from an
over abundance of irrelevant information.
Received June 1967.
This is not a play on words. The consequences of changing the emphasis of an MIS
from supplying relevant information to eliminating irrelevant information is
considerable. If one is preoccupied with supplying relevant information, attention is
almost exclusively given to the generation, storage, and retrieval of information: hence
emphasis is placed on constructing data banks, coding indexing, updating files, access
languages, and so on. The ideal which has emerged from this orientation is an infinite
pool of data into which a manager can reach to pull out any information he wants. If,
on the other hand, one sees the manager’s information problem primarily, but not
exclusively, as one that arises out of an overabundance of irrelevant information, most
of which was not asked for, then the two most important functions of an information
system become filtration (or evaluation) and condensation. The literature on MIS’s
seldom refers to these functions let alone considers how to carry them out.
My expertise indicates that most managers receive much more data (if not
information) than they can possibly absorb even if they spend all of their time trying to
do so. Hence they already suffer from an information overload. They must spend a
great deal of time separating the relevant from the irrelevant and searching for the
kernels in the relevant documents. For example, I have found that I receive an average
of forty-three hours of unsolicited reading material each week. The solicited material
is usually half again this amount.
I have seen a daily stock status report that consists of approximately six hundred
pages of computer print-out. The report is circulated daily across managers’ desks.
I’ve also seen requests for major capital expenditures that come in book size, several of
which are distributed to managers each week. It is not uncommon for many managers
to receive an average of one journal a day or more. One could go on and on.
Unless the information overload to which managers are subjected is reduced, any
additional information made available by an MIS cannot be expected to be used
Even relevant documents have too much redundancy. Most documents can be
considerably condensed without loss of content. My point here is best made, perhaps,
by describing briefly an experiment that a few of my colleagues and I conducted on the
OR literature several years ago. By using a panel of well-known experts we identified
four OR articles that all members of the panel considered to be “above average,” and
four articles that were considered to be “below average.” The authors of the eight
articles were asked to prepare “objective” examinations (duration thirty minutes) plus
answers for graduate students who were to be assigned the articles for reading. (The
authors were not informed about the experiment.) Then several experienced writers
were asked to reduce each article to 2/3 and 1/3 of its original length only by
eliminating words. They also prepared a brief abstract of each article. Those who did
the condensing did not see the examinations to be given to the students.
A group of graduate students who had not previously read the articles were then
selected. Each one was given four articles randomly selected, each of which was in
one of its four versions: 100%, 67%, 33%, or abstract. Each version of each article
RUSSELL L. ACKOFF
MANAGEMENT MISINFORMATION SYSTEMS
was read by two students. All were given the same examinations. The average scores
on the examinations were then compared.
For the above-average articles there was no significant difference between average
test scores for the 100%, 67%, and 33% versions, but there was a significant decrease
in average test scores for those who had read only the abstract. For the below-average
articles there was no difference in average test scores among those who had read the
100%, 67%, and 33% versions, but there was a significant increase in average test
scores of those who had read only the abstract.
The sample used was obviously too small for general conclusions but the results
strongly indicate the extent to which even good writing can be condensed without loss
of information. I refrain from drawing the obvious conclusion about bad writing.
It seems clear that condensation as well as filtration, performed mechanically or
otherwise, should be an essential part of an MIS, and that such a system should be
capable of handling much, if not all, of the unsolicited as well as solicited information
that a manager receives.
The Manager Needs The Information That He Wants
Most MIS designers “determine” what information is needed by asking managers
what information they would like to have. This is based on the assumption that
managers know what information they need and want it.
For a manager to know what information he needs he must be aware of each type of
decision he should make (as well as does) and he must have an adequate model of
each. These conditions are seldom satisfied. Most managers have some conception of
at least some of the types of decisions they must make. Their conceptions, however,
are likely to be deficient in a very critical way, a way that follows from an important
principle of scientific economy: the less we understand a phenomenon, the more
variables we require to explain it. Hence, the manager who does not understand the
phenomenon he controls plays it “safe” and, with respect to information, wants
“everything.” The MIS designer, who has even less understanding of the relevant
phenomenon than the manager, tries to provide even more than everything. He thereby
increases what is already an overload of irrelevant information.
For example, market researchers in a major oil company once asked their marketing
managers what variables they thought were relevant in estimating the sales volume of
future service stations. Almost seventy variables were identified. The market
researchers added about half again this many variables and performed a large multiple
linear regression analysis of sales of existing stations against these variables and found
about thirty-five to be statistically significant. A forecasting equation was based on
this analysis. An OR team subsequently constructed a model based on only one of
these variable, traffic flow, which predicted sales better than the thirty-five variable
regression equation. The team went on to explain sales at service stations in terms of
the customers’ perception of the amount of time lost by stopping for service. The
relevance of all but a few of the variables used by the market researchers could be
explained by their effect on such perception.
The moral is simple: one cannot specify what information is required for decision making
until an explanatory model of the decision process and the system involved has been
constructed and tested. Information systems are subsystems of control systems. They cannot
be designed adequately without taking control in account.. Furthermore, whatever else
regression analyses can yield, they cannot yield understanding and explanation of phenomena.
They describe and, at best, predict.
Give a Manager the Information He Needs and His Decision
Making Will Improve
It is frequently assumed that if a manager is provided with the information he needs, he will
then have no problem in using it effectively. The history of OR stands to the contrary. For
example, give most managers an initial tableau of a typical “real” mathematical programming,
sequencing, or network problem and see how close they come to an optimal solution. If their
experience and judgement have any value they may not do badly, but they will seldom do very
well. In most management problems there are too many possibilities to expect experience,
judgement, or intuition to provide good guesses, even with perfect information.
Furthermore, when several probabilities are involved in a problem the unguided mind of
even a manager has difficulty in aggregating them in a valid way. We all know many simple
problems in probability in which untutored intuition usually does very badly (e.g., What are the
correct odds that 2 of 25 people select at random will have their birthdays on the same day of
the year?). For example, very few of the results obtained by queuing theory, when arrivals and
service are probabilistic, are obvious to managers; nor are the results of risk analysis where the
managers; own subjective estimates of probabilities are used.
The moral: it is necessary to determine how well managers can use needed information.
When, because of the complexity of the decision process, they can’t use it well, they should be
provided with either decision rules or performance feed-back so that they can identify and
learn from their mistakes. More on this point later.
More communication Means Better Performance
One characteristic of most MIS’s which I have seen is that they provide managers with
better current information about what other managers and their departments and divisions are
doing. Underlying this provision is the belief that better interdepartmental communication
enables managers to coordinate their decisions more effectively and hence improves the
organization’s overall performance. Not only is this not necessarily so, but it seldom is so.
One would hardly expect two competing companies to become more cooperative because the
information each acquires about the other is improved. This analogy is not as far fetched as
one might first suppose. For example, consider the following very much simplified version of
a situation I once ran into. The simplification of the case does not affect any of its essential
RUSSELL L. ACKOFF
A department store has two “line” operations: buying and selling. Each function is
performed by a separate department. The Purchasing Department primarily controls one
variable: how much of each item is bought. The Merchandising Department controls the price
at which it is sold. Typically, the measure of performance applied to the Purchasing
Department was the turnover rate of inventory. The measure applied to the Merchandising
Department was gross sales; this department sought to maximize the number of items sold
times their price.
Now by examining a single item let us consider what happens in this system. The
merchandising manager, using his knowledge of competition and consumption, set a price
which he judged would maximize gross sales. In doing so he utilized price-demand curves for
each type of item. For each price the curves show the expected sales and values on an upper
and lower confidence band as well. (See Figure 1.) When instructing the Purchasing
Department how many items to make available, the merchandising manager quite naturally
used the value on the upper confidence curve. This minimized the chances of his running short
which, if it occurred, would hurt his performance. It also maximized the chances of being
over-stocked but this was not his concern, only the purchasing manager’s. Say, therefore, that
the merchandising manager initially selected price P1 and requested that amount Q1 be made
available by the Purchasing Department.
In this company the purchasing manager also had access to the price-demand curves. He
knew the merchandising manager always ordered optimistically.
MANAGEMENT MISINFORMATION SYSTEMS
Therefore, using the same curve he read over from Q1 to the upper limit and down to the expected
value from which he obtained Q2, the quantity he actually intended to make available. He did not
intend to pay for the merchandising manager’s optimism. If merchandising ran out of stock, it
was not his worry. Now the merchandising manager was informed about what the purchasing
manager had done so he adjusted his price to P2. The purchasing manager in turn was told that the
merchandising manager had made this readjustment so he planned to make only Q2 available. If
this process – made possible only by perfect communication between departments – had been
allowed to continue, nothing would have been bought and nothing would have been sold. This
outcome was avoided by prohibiting communication between the two departments and forcing
each to guess what the other was doing.
I have obviously caricatured the situation in order to make the point clear: when organizational
units have inappropriate measures of performance which put them in conflict with each other, as is
often the case, communication between them may hurt organizational performance, not help it.
Organizational structure and performance measurement must be taken into account before opening
the flood gates and permitting the free flow of information between parts of the organization. (A
more rigorous discussion of organizational structure and the relationship of communication to it
can be found in. .)
A Manager Does Not Have to Understand How an Information System
Works, Only How to Use It
Most MIS designers seek to make their systems as innocuous and unobtrusive as possible to
managers lest they become frightened. The designers try to provide managers with very easy
access to the system and assure them that they need to know nothing more about it. The designers
usually succeed in keeping managers ignorant in this regard. This leaves managers unable to
evaluate the MIS as a whole. It often makes them afraid to even try to do so lest they display their
ignorance publicly. In failing to evaluate their MIS, managers delegate much of the control of the
organization to the systems designers and operators who may have many virtues, but managerial
competence is seldom among them.
Let me cite a case in point. A Chairman of a Board of a medium-size company asked for help
on the following problem. One of his larger (decentralized) divisions had installed a computerized
production-inventory control and manufacturing-manager information system about a year earlier.
It had acquired about $2,000,000 worth of equipment to do so. The Board Chairman had just
received a request from the Division for permission to replace the original equipment with newly
announced equipment which would cost several times the original amount. An extensive “justifi-
cation” for so doing was provided with the request. The Chairman wanted to know whether the
request was really justified. He admitted to complete incompetence in this connection.
A meeting was arranged at the Division at which I was subjected to an extended and detailed
briefing. The system was large but relatively simple. At the heart of it was a reorder point for
each item and a maximum allowable stock level. Reorder quantities took lead-time as well as the
allowable maximum into account. The computer kept track of stock, ordered items when required
and generated numerous reports on both the state of the system it controlled and its own “actions.”
When the briefing was over I was asked if I had any questions. I did. First I asked if, when the
system had been installed, there had been many parts whose stock level exceeded the maximum
amount possible under the new system. I was told there were many. I asked for a list of about
thirty and for some graph paper. Both were provided. With the help of the system designer and
volumes of old daily reports I began to plot the stock level of the first listed item over time. When
this item reached the maximum “allowable”: stock level it had been reordered. The system
designer was surprised and said that by sheer “luck” I had found one of the few errors made by the
system. Continued plotting showed that because of repeated premature reordering the item had
never gone much below the maximum stock level. Clearly the program was confusing the
maximum allowable stock level and the reorder point. This turned out to be the case in more than
half of the items on the list.
Next I asked if they had many paired parts, ones that were only used with each other; for
example, matched nuts and bolts. They had many. A list was produced and we began checking
the previous day’s withdrawals. For more than half of the pairs the differences in the numbers
recorded as withdrawn were very large. No explanation was provided.
Before the day was out it was possible to show by some quick and dirty calculations that the
new computerized system was costing the company almost $150,00 per month more than the hand
system which it had replaced, most this is excess inventories.
The recommendation was that the system be redesigned as quickly as possible and that the new
equipment not be authorized for the time being.
The questions asked of the system had been obvious and simple ones. Managers should have
been able to ask them but – and this is the point – they felt themselves incompetent to do so. They
would not have allowed a handoperated system to get so far out of their control.
No MIS should ever be installed unless the managers for whom it is intended are trained to
evaluate and hence control it rather than be controlled by it.
A Suggested Procedure for Designing an MIS
The erroneous assumptions I have tried to reveal in the preceding discussion can, I believe, be
avoided by an appropriate design procedure. One is briefly outlined here.
1. Analysis of The Decision System
Each (or at least each important) type of managerial decision required by the organization
under study should be identified and the relationships between them should be determined and
flow-charted. Note that this is not necessarily the same thing as determining what decisions
are made. For example, in one company I found that make-or-buy decisions concerning parts
were made only at the time when a part was introduced into stock and was never subsequently
reviewed. For some items this decision had gone unreviewed for as many as twenty years.
Obviously, such decisions should be made more often; in some cases, every time an order is
placed in order to take account of current shop loading, underused shifts, delivery times from
suppliers, and so on.
Decision-flow analyses are usually self-justifying. They often reveal important decisions
that are being made by default( e.g., the make-buy decision referred to above), and they
disclose interdependent decisions that are being made independently. Decision-flow charts
frequently suggest changes in managerial responsibility, organizational structure, and measure
of performance which can correct the types of deficiencies cited.
Decision analyses can be conducted with varying degrees of detail, that is, they may be
anywhere from coarse to fine grained. How much detail one should become involved with
depends on the amount of time and resources that are available for the analysis. Although
practical considerations frequently restrict initial analyses to a particular organizational
function, it is preferable to perform a coarse analysis of all of an organization’s managerial
functions rather than a fine analysis of one or a subset of functions. It is easier to introduce
finer information into an integrated information system than it is to combine fine subsystems
into one integrated system.
2. An Analysis of Information Requirements:
Managerial decisions can be classified into three types:
(a) Decisions for which adequate models are available or can be constructed and from which
optimal (or near optimal) solutions can be derived. In such cases the decision process
itself should be incorporated into the information system thereby converting it (at least
partially) to a control system. A decision model identifies what information is required
and hence what information is relevant.
(b) Decisions for which adequate models can be constructed but from which optimal solutions
cannot be extracted. Here some kind of heuristic or search procedure should be provided
even if it consists of no more than computerized trial and error. A simulation of the model
will, as a minimum, permit comparison of proposed alternative solutions. Here too the
model specifies what information is required.
(c) Decisions for which adequate models cannot be constructed. Research is required here to
determine what information is relevant. If decision making cannot be delayed for the
completion of such research or the decision’s effect is not large enough to justify the cost
of research, then judgement must be used to “guess” what information is relevant. It may
be possible to make explicit the implicit model used by the decision maker and treat it as a
model of type (b).
In each of these three types of situations it is necessary to provide feedback by comparing
actual decision outcomes with those predicted by the model or decision maker. Each
decision that is made, along with its predicted outcome, should be essential input to a
management control system. I shall return to this point below.
Aggregation of Decisions
Decisions with the same or largely overlapping informational requirements should be
grouped together as a single manager’s task. This will reduce the information a manager
requires to do his job and is likely to increase his understanding of it. This may require a
reorganization of the system. Even if such a reorganization cannot be implemented
completely what can be done is likely to improve performance significantly and reduce
the information loaded on managers.
Design Of Information Processing
Now the procedure for collecting, storing, retrieving, and treating information can be
designed. Since there is a voluminous literature on this subject I shall leave it at this
except for one point. Such a system must not only be able to answer questions addressed
to it; it should also be able to answer questions that have not been asked by reporting any
deviations from expectations. An extensive exception-reporting system is required.
Design Of Control Of The Control System
It must be assumed that the system that is being designed will be deficient in many and
significant ways. Therefore it is necessary to identify the ways in which it may be
deficient, to design procedures for detecting its deficiencies, and for correcting the system
so as to remove or reduce them. Hence the system should be designed to be flexible and
adaptive. This is little more than a platitude, but it has a not-so-obvious implication. No
completely computerized system can be as flexible and adaptive as can a man-machine
system. This is illustrated by a concluding example of a system that is being developed
and is partially in operation. (See Figure 2.)
The company involved has its market divided into approximately two hundred marketing
areas. A model for each has been constructed as is “in” the computer. On the basis of
competitive intelligence supplied to the service marketing manager by marketing
researchers and information specialists he and his staff make policy decisions for each
area each month. Their tentative decisions are fed into the computer which yields a
forecast of expected performance. Changes are mare until the expectations match what is
desired. In this way they arrive at “final” decisions. At the end of the month the computer
compares the actual performance of each area with what was predicted. If a deviation
exceeds what could be expected by chance, the company’s OR Group then seeks the
reason for the deviation, performing as much research as is required to find it. If the cause
is found to be permanent the computerized model is adjusted appropriately. The result is
an adaptive man-machine system whose precision and generality is continuously
increasing with use.
Finally it should be noted that in carrying out the design steps enumerated above, three
groups should collaborate: information systems specialists, operations researchers, and
managers. The participation of managers in the design of a system that is to serve them,
assures their ability to evaluate its performance by comparing its output with what was
predicted. Managers who are not willing to invest some of their time in this process are
not likely to use a management control system well, and their system, in turn, is likely to
1. Sengupta, S.S., and Ackoff, R.L., “Systems Theory from an Operations Research Point
of View,” IEEE Transactions on Systems Science and Cybernetics, Vol. 1 (Nov.
1965), pp. 9-13.
Vol. 15, No. 4, December 1968
Printed in U.S.A.
Management Misinformation Systems – Another Perspective
An identification and critical examination of the assumptions made by designers of management
information systems is particularly timely. Russell L. Ackoff attempted to do just that in his article,
“Management Misinformation Systems.” (Management Science, December 1967). He identified five
common assumptions underlying management information systems design and proposed that these
assumptions are unwarranted in many (if not most) cases and lead to major deficiencies in the resulting
systems. The purpose of this letter is to examine briefly these assumptions (given in italics) and the
supporting illustrations presented in the Ackoff article.
1. The critical deficiency under which most managers operate is the lack of relevant information.
Ackoff contends that managers suffer more from an over abundance of irrelevant information than they do
from lack of relevant information. This is followed by the suggestion that information be filtered
(evaluated) and condensed to reduce the information overload to which managers are subjected. In the face
of seemingly endless pages of computer print-outs, book-size requests for capital expenditures and other
forms that consume unnecessary hours of managers’ time, suggestions leading to filtered and/or condensed
information are likely to be greeted with enthusiasm. This does however raise another important issue:
what are the useful limits to filtration and condensation?
Just as processing leading to information overload is not in the best interests of the organization,
indiscriminate filtration and “over-condensation” can likewise lead to non-salutary results. For example,
consider the case of major capital investment proposals originating from various divisions of a company.
Assume that book-size capital expenditure proposals are now condensed for headquarters to a single listing
of proposed projects (with brief descriptions) and ranked according to some criterion function such as
internal rate of return. The headquarters group has two basic options available: (1) accept the divisional
estimates; or (2) make a subjective adjustment to compensate for estimated divisional bias. Neither of these
alternatives is very comforting since there is no compelling basis for choice except perhaps assessing past
behavior which may be neither instructive nor relevant. Here then is clearly a case “over-condensation”
since the report received by headquarters cannot be used to make an intelligent appraisal of the proposals
competing for scarce resources since information about the uncertainty underlying key market and cost
variables is not available. “Over-condensation” can occur even if risk analysis techniques are actually
employed in a company.
In brief, the undesirable state of “over-condensation” is reached when the decision maker no longer has a
sound basis for judging the validity of transmitted information.
Filtration has potential as an effective adjustment in the face of information overload. The key question
is: where in the system should “filtration decisions” be made? If these decisions were initiated largely at
the lower levels of the organization one might question the limited perspective underlying the decisions.
1Filtration decisions made at the highest level of the organization, however, offer little or no relief from
information overload. The relevant strategy then is a function of the confidence that executives have in the
filtration decisions made by managers at lower levels.
To illustrate this in the context of the capital expenditure analysis example, consider the set of projects
enumerated by the divisions for review by the headquarters group. This set consists only of those projects
proposed for adoption and excludes projects rejected at the divisional level. Hence, the information
presented to headquarters was indeed filtered. If there are no serious conflicts between the way divisions
and headquarters perceive organizational objectives and their attitudes toward risk are identical, then the
filtered list of projects is in all probability justified. In the overwhelming majority of cases where the ideal
headquarters-divisional relationship does not exist, it would seem to be more appropriate to ask divisions to
enumerate their total set of project opportunities with “accept” or “reject” recommendation for each. (Even
in this situation divisional managers would undoubtedly filter certain projects, but the potential for filtering
In summary, while managers can often make reasonable adjustments to compensate for information
overload, overfiltration and condensation tend to accentuate the biases of lower-level managers and provide
the executive decision maker with an inadequate basis for making necessary adjustments. The relevant
information for managers is somewhere on the continuum between over-filtration and –condensation, and
information overload. I contend that the basic assumption that “the critical deficiency under which most
managers operate is the lack of relevant information” remains unchallenged.
2. The manager needs the information that he wants. Ackoff argues that the conditions for a manager to
know what information he needs are rarely satisfied. The principal problem here is that the decision
maker’s own conception of an appropriate decision model to fit a specific situation is generally not well
developed. I would fully subscribe to Ackoff’s subsequent plea for an active collaboration among
information systems specialists, operations researchers, and managers in the various stages of systems
design as the best available strategy for overcoming this deficiency.
The respective roles of the operations researcher-information specialist and manager can be illustrated in
the context of the service station problem presented by Ackoff. I would envision the main thrust of the
manager’s responsibility to be, first, to recognize occasions for making decisions and, then, to frame
appropriate questions in light of the decisions to be made. The manager in the major oil company, for
example, finds it necessary to make decisions concerning locations of future service stations. An
appropriate criterion may be sales or profit maximization subject to certain technological and management-
imposed constraints. The manager clearly wants information about future sales potential for alternative
service-station locations. And the manager needs the information that he wants.
While the task of enumerating relevant variables for forecasting equations should be conducted jointly by
the operations researcher and manager, in most situations it would be reasonable to expect that model choice
and refinements are largely the domain of the operations researcher. The choice of a statistical forecasting
model in this case or any model in the more general case calls for the exercise of careful judgment on the
part of the operations researcher. Problem type, relative importance of the problem, time available before
decision must be made, and expected degree of utilization of model results by decision makers all qualify as
strategic considerations in choosing among alternative models. Finally, the information specialist should
present the results to the manager in an easily understood form, without resorting to either information
overload or over-condensation.
3. If a manager has the information he needs his decision making will improve. Ackoff points out that
because of the complexity of the decision process, managers oftentimes cannot use information well. To
support this contention, Ackoff suggests that most managers furnished with an initial tableau of a typical
mathematical programming, sequencing, or network problem are unlikely to come close to an optimal
solution. While one certainly would not want to argue with the validity of this proposition, its relevance to
the main argument must be questioned. Specifically, I would submit that to furnish a manger with an initial
tableau is to furnish him with data, not information. (The distinction is explained by Adrian M. McDonough
in his book, Information Economics and Management Systems: “The term ‘data’ is used here to represent
messages that can be available to the individual but which have not as yet been evaluated for their worth in a
specific situation… ‘Information’ is used here as the label for evaluated data in a specific situation … a
given message may remain constant in content and yet, under this approach change from data to information
when it is put to use in making a decision”) The fact that managers cannot easily convert data to
information underlies the very need and justification for developing management decision models. If
managers could independently iterate from an initial to final tableau, the simplex and other related
algorithms would become redundant and unnecessary. In the Ackoff case, the manager is not provided
information until the results appearing in the final tableau are communicated to him. At that juncture we
can only hope that his decision making will improve.
In brief then, Ackoff’s illustration fails to invalidate the assumption that if a manager has the information
he needs his decision making will improve, because the decision maker was not provided with the
information he needed. Perhaps, a more interesting and significant question to ask is: to what extent does
the information the manager really needs (e.g., final tableaus) improve decision making?
4. Better communication between managers improves organizational performance. It is true that better
communication between managers does not necessarily improve organizational performance. Ackoff’s
example involving a purchasing and a merchandising department in a department store illustrates this point.
I believe it is important to emphasize, however, that the origin of the problem described does not lie in the
communication, but instead in the conflicting measures of performance used to judge the two departments.
Ackoff thus has properly established that interdepartmental communication among departments with
conflicting measures of performance may not only be of doubtful value, but may actually work counter to
the best interests of the organization as a whole. However, the proposition that well-conceived
interdepartmental communication enables managers to coordinate their decisions more effectively when
appropriate, nonconflicting measures of performance are present was not invalidated.
5. A manager does not have to understand how an information system works, only how to use it.
Ackoff’s challenge to the notion that a manager need not understand how an information system works, only
how to use it, is particularly significant. It is difficult to debate the merits of this assumption without a more
detailed agreement concerning the degree of understanding Ackoff would require of managers. The best
available evidence of intent can be gleaned from the case study presented.
A computerized production and inventory control system was discovered to be costing the company almost
$150,000 per month more than the former manual system. Most of this was attributed to excess inventories.
Apparently, a major cause of unreasonable inventory accumulations was a program error which confused
the maximum allowable stock level and the reorder point. To suggest that the manager understand the
information system to a point where he would detect the programming error seems neither reasonable in an
organizational plan nor an economical use of the manager’s time. Indeed, to argue for understanding and
analysis by managers at this level of detail is legitimate cause for cries of “information overload.” A more
constructive approach would suggest that a manager should have developed techniques and guidelines using
exception reporting for discovering a situation where an “improved” system costs $150,000 more than its
unglamorous predecessor. Perhaps, even more importantly the manager would be well advised to develop a
more reliable system for hiring better system designers.
While I agree with Ackoff that “no management information system should ever be installed unless the
managers for whom it is intended are trained to evaluate and hence control it rather than be controlled by it,”
my agreement is within the context explained above. To insist upon detailed systems design knowledge by
managers as a prerequisite for new management information systems is tantamount to calling for an
information system moratorium or at minimum a significant reduction in research and progress in the field.
Graduate School of Business