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How managers decide to use planning models
32
Long Range
Planning
Vol. 13
April
1980
How Managers Decide to Use Planning Models Robert W. Blanning*
Recent published reports and surveys have shown that a growing number of corporations and government agencies are using decision models nor only for lower level scheduling and resource allocation but also for short-range and tong-range planning. Although the literature has described in some derail the types of models used and the ways in which they are used, limited attention has been paid to the ways in which managers decide whether or nor to use these models. This paper, which is based on a series of case studies, suggests that the decision to use planning models is made nor by performing a comprehensive cost benefit analysis, but by the use of a reference model--that is, an existing model, sometimes in a competitive organization, similar to the one being considered.
Introduction The past 10 years have seen widespread growth and development of corporate models in the U.S.‘*‘l and Britain.8 These models, which are typically deterministic simulations, calculate the financial and operational consequences of corporate decisions (especially investment and marketing decisions), and are used in strategic and tactical decision making. Since these models are used by senior managers and staff analysts, an important issue in their development is how these managers and analysts decide to initiate the development of a corporate planning model or to use an existing model. In reporting the results of the first survey of corporate models in the U.S., Gerschefski7 asked the question, ‘Why do some companies have models and not others?’ and responded ‘At this point it appears to be a matter of individual initiative. Models appear to exist in those companies where someone has heard about them and The more recent has proceeded to “sell” management’. survey by Naylor and Schauland” suggests that managers are beginning to take a more active interest in *The author is Assistant Professor of Decision Sciences, Wharton School, University of Pennsylvania 19174, U.S.A.
The
models in our corporate modelling : ‘The corporate survey enjoy a relatively high degree of political support on the part of management’. This is consistent with the observation of people concerned with management non-technical managers are information systems -that taking an active interest in the development of these systems and that this interest is an important determinant of their success.l *6- l 4 But this does not explain how managers make the decision to proceed. Although this issue has not yet been addressed in the literature on corporate modeling, it has been addressed in both the descriptive and normative literature on computer applications and manageof ment information systems .g The principal conclusion this literature is that a decision to proceed with a computer application should be made on an economic basis that takes into account the impact of the system on improved management decisions and of these decisions on organizational (usually economic) performance. Emery4 e5 presents a framework based on statistical decision theory for doing this, and the recent literature on information requirements analysis takes a similar approach. 12. l3 In addition, in their survey of corporate computer users, Taylor and Dean4 conclude, ‘Applications are planned and approved. . . on the same basis as other actions involving increased expenditures and investment-if not through return on investment analysis, at least on the basis ofjudgment of the value of improvements expected.’ This article presents a complementary view. It is argued that managers faced with the problem of estimating the benefits of a model not yet constructed encounter difficulties in estimating the impact of improved information on decisions and performance. Therefore, instead of thinking through the consequences of a proposed system on 0 priori grounds, they search for a reference model-that is, a model similar to the one being considered-and extrapolate from the observations of the reference model to evaluate the proposed model. The ways in which they do this are examined below.
How Managers Decide to Use Planning Models
The Case Studies In the summer of 1977, a project was initiated at The Wharton School to write case studies on planning models for use in a new course on this subject. The purpose of the cases and the course is to examine the relationships between modeling and MIS and to examine the ways in which a synthesis of these two technologies may be and are being used in short range and long range planning.* The cases are outlined below. The type of model, type of organization and purpose of model are given below: (1)A deterministic simulation used by a consumer services company for short-range logistical planning.
(2)A
Monte Carlo simulation used by a financial services company for long-range pension planning. (3)A simulation based on a data management system used by a consumer products company for financial and marketing planning.
(4 A
linear programming model used by a consumer products company for quarterly and yearly production and distribution planning.
(5)A
financial model consisting of simultaneous linear equations used by a common carrier for multi-year financial planning. (6) A linear programming model used by an oil company for multi-year financial planning.
33
legislation and regulation on corporate activities, and only a few of these appear in our sample. However, the cases that we were not able to write appear similar in terms of modeling technique and development decisions to the cases that we were able to write.
The System Development
Decision
There were four ways in which the organizations outlined above made decisions to develop planning models. They are: (1) comparison with an ongoing system, (2) comparison with a related system, (3) initiation of a low-cost pilot project and (4) comparison with competitors’ behavior. The first method, comparison with an ongoing system, consisted of examining an existing manual or partially computerized decision support process and concluding that a limited computerization of the process would be desirable even if no model were constructed. For example, the corporate model for the common carrier (No. 5 in the examples of the previous section) was constructed after an executive concluded that the existing manual system for preparing pro forma financial statements was too time consuming, that automation of this process, even without the construction of a more sophisticated model, would be preferable to the existing practice, and that such a model, if it could be constructed,
(‘1 A
would provide an ‘additional consumer products company
(8)An
by
(9)An
agency
data management system in order to reconcile discrepancies in data sources before deciding to augment it with a financial simulation, and the government agency that constructed a system for energy planning (No. 9) had similar motivations.
Monte Carlo simulation and a statistical analysis program used by a government organization for personnel planning. interindustry economic model used government agency for economic analysis.
economic model used by a government for energy planning.
a
There is a slight bias in this sample with regard to the purposes of the models. A number of companies that we met with declined to allow us to write cases about their systems. Most of the reasons concerned: (1) the amount of time that company managers and analysts would have to spend providing us with information, (2) the reluctance of companies to release information that might be of use to their competitors and (3) the reluctance of companies to release information that might be seen by the government. The cases that we were not able to write for the first two reasons given above did not appear to differ from the ones we were able to write. However, the third reason introduced a bias, because the models that were rejected for this reason were the ones used to negotiate with government agencies about tax, regulatory and other matters, and the companies did not want the government agencies to know that they were using models for this purpose. Thus, it appears that a substantial number of planning models are used to determine the impact of government ‘The cases were written by four Research Assistants at Wharton under my supervision. They are: Ms. Jacinta A. Coleman, Mr. Charles Kutcher, Ms. Lisa J. Pearson, and Mr. Jeremy Reifsnyder. The case-writing effort was funded by a grant from IBM.
benefit. In addition, the (No. 3) implemented its
The second method, comparison with a related system, was used when the organization had already implemented a successful planning model in a related area and used that system as a reference point for evaluating the proposed model. For example, the logistical simulation for the consumer services company (No. l), the linear programming model for the consumer products company (No. 3), and the financial planning model for the oil company (No. 6) were each developed because people in the company had previously been successful in developing
planning
models.
The third method, initiation of a low-cost pilot project, was used when it was possible to implement the system or a significant subset of it at low cost and there was sufficient time to do so. (Some of the systems studied here were implemented under severe time pressures.) In this case the low cost was an important factor in the decision to proceed, because it made the benefits appear auite favorable in relation to the costs incurred bv the drganization. For example, the government agency that imnlemented a svstem for nersonnel ulannimz (No. 7) hid so in part because it Gas able to bbtain ; part of the system from another government agency. In addition, the government agency that developed an interindustry economic model to prepare economic
Long Range Planning Vol. 13
34
April 1980
impact statements (No. 8) did so not only because of the perceived benefits of the model but because it was able to obtain substantial financial support for an initial development effort from another government agency. Thr fourth method, comparison with competitors systems (or in the case of government agencies, comparison with systems developed by other agencies performing similar functions), was used by some organizations not because they wished to imitate their competitors, but because they considered their competitors’ behavior a useful reference point. For example, the financial services company that developed a Monte Carlo simulation for pension planning (No. 2) was motivated in part by the fact that several of its competitors were also developing such systems. In addition, the government agencies (No. 7, No. 8 and No. 9) were able to develop their systems with greater confidence because they had observed that other agencies with similar responsibilities were implementing similar systems. The four methods outlined above do not correspond closeiy with the literature referenced in the introduction to this paper. None of the organizations performed a formal cost/benefit analysis that contained quantitative estimates of the impact of improved information on management decisions and thence on performance. In many cases no formal proposal of any kind was prepared, and the formal reports that were prepared were usually used to communicate with external organizations (i.e. consultants hired to participate in the design or programming effort and outside agencies providing financial support). On the other hand, there was active management participation in the decision to develop the models, although in many cases the technical staffs were given substantial freedom once a decision to proceed had been made.
The Use of a Reference
I
I
Analysis
The decision process is a two-stage process: (1) the identification of an appropriate reference model and (2) the use of the reference model in deciding whether to proceed with the proposal (see Figure 1). There are four sources of a reference model, corresponding to the four methods identified above. They are: an existing manual effort which would be replaced with the proposed model (Method l), a planning model in the same organization that is similar to the one being proposed (Method 2), a low-cost pilot project (Method 3). and a planning model developed by another organization with similar responsibilities and problems (Method 4). Once an appropriate reference model (or possibly several such models) has been identified, its characteristics and usefulness are used to predict the usefulness of the proposed model. It is interesting to note that these results are consistent with the theory of disjointed incrementalism in public administ;ation,2* lo*l5 which states that managers in public sector organizations allocate resources (i.e. prepare budgets) by making incremental modifications to existing budgets, and with a few exceptions (new programs, programs that have become controversial, etc.) they confine their analytical efforts largely to an analysis of the increments, rather than perform a ‘ground-up’ or ‘zero-based’ cost/benefit analysis of all feasible budgetary decisions. This behavior is viewed as the result not of incompetent management, but of the intangibility and complexity of public-sector decision-making. This intangibility and complexity occurs also in the decision to develop planning models, with similar results.
Model
Although the four methods identified above appear quite distinct, they share a common property, which I will call the use of a reference model. In each case, the persons or groups of persons making the decision to r 1 Manual
proceed did so by comparing a proposed model with an existing model (a reference model), and they evaluated the proposal by observing the advantages and disadvantages of the reference model and extrapolating to the proposed one. They did not perform a cost/benefit analysis ‘from the ground up’, but focused their analytical efforts on the examination of the differences.
Conclusion:
Cost/Benefit
Analysis
These results suggest a new direction for thinking about the application of cost/benefit analysis to the evaluation
1
1
t--A I
I
I Identification
Reference
Selected Reference Model(s)
I
1 Analysis of ’
Planning
Model *
Proposed Planning Model
I
Figure 1. The use of a reference system
Decision to Proceed
How Managers Decide to Use Planning Models of planning models. Specifically, they suggest that such an analysis be based on a reference model. It is this author’s observation that many managers feel that their most useful models could never have been justified in advance by a cost/benefit analysis, because not enough was known about the process being modeled to anticipate the benefits (or even in some cases the eventual uses) of these models. As one manager told us about a very successful model he was using, ‘If we had had to justify this with a cost/benefit analysis, we would never have gone ahead with it’. An explicit understanding of how managers decide to proceed with the development effort for a planning model may help to clarify this process and to make it more productive.
References Steven L. Alter, How effective managers use information ci,systems, Harvard Business Review, 54 (6). 97-104, November-December
(5)
James C. Emery, Cost/benefit analysis of information systems, in System Analysis Techniques, ed. by J. Daniel Couger and Robert W. Knapp, pp. 395-425, Wiley, New York (1974).
(6)
John T. Garrity, Top management and computer profits, Harvard Business Review, 41 (4). 6-8, 10, 12, 172, 174. July-August (1963).
(7)
George W. Gerschevski, Corporate models-the state of the art, Management Science 16 (6). pp. 8-303-8-312, February (1970).
(8)
Peter H. Grinyer and Jeff Wooller, Computer models for corporate planning, Long Range Planning, 6 (I), 14-25, Februan/ (1975).
(9)
John Leslie King and Edward L. Schrems, Cost-benefit analysis in information systems development and operation, Computing Surveys, 10 (1). 19-34, March (1978).
(10)
Charles E. Lindblom, Public Administration (1959).
(11)
Thomas H. Naylor and Horst Schauland, Corporate simulation models: a survey, Long Range Planning, 9 (2). 94-100, April (1976).
(12)
William M. Taggart, Jr. and Marvin 0. Tharp, Dimensions of information requirements analysis, Data Base, 7 (1). 5-13, Summer (1975).
(13)
William M. Taggart, Jr. and Marvin 0. Tharp, A survey of information requirements analysis techniques, Computing Surveys, 9 (4). 273-290, December (1977).
(14)
James W. Taylor and Neal J. Dean, Managing to manage the computer, Harverd Business Review. 44 (5), 98-110. September-October (1966).
(15)
Aaron Wildavski and Arthur Hammann, Comprehensiveversus incremental budgeting in the department of agriculture, Administrative Science Quarterly, 10 (3) 321-346, December (1965).
(1976).
(2) David Braybrook and Charles E. Lindblom, A Strategy of Decision: Policv Evaluation as a Social Process, The Free Press, MacMillan, New York (1963). (3)
(4)
Gary W. Dickson and Richard F. Powers, MIS project management: myths, opinions and reality, in lnformation Systems Administration, by F. Warren McFarlan, Richard L. Nolan and David P. Norton, pp. 401-412, Holt, Rinehart and Winston, New York (1973). James C. Emery, Chapter 4: Economics of information, in Organizational Planning and Control Systems: Theory and Technology, pp. 66-107, MacMillan, New York (1969).
35
The science of ‘muddling through’, Review, XIX (2). 79-100, Spring
Long Range
Planning
Vol. 13
April
1980
How Managers Decide to Use Planning Models Robert W. Blanning*
Recent published reports and surveys have shown that a growing number of corporations and government agencies are using decision models nor only for lower level scheduling and resource allocation but also for short-range and tong-range planning. Although the literature has described in some derail the types of models used and the ways in which they are used, limited attention has been paid to the ways in which managers decide whether or nor to use these models. This paper, which is based on a series of case studies, suggests that the decision to use planning models is made nor by performing a comprehensive cost benefit analysis, but by the use of a reference model--that is, an existing model, sometimes in a competitive organization, similar to the one being considered.
Introduction The past 10 years have seen widespread growth and development of corporate models in the U.S.‘*‘l and Britain.8 These models, which are typically deterministic simulations, calculate the financial and operational consequences of corporate decisions (especially investment and marketing decisions), and are used in strategic and tactical decision making. Since these models are used by senior managers and staff analysts, an important issue in their development is how these managers and analysts decide to initiate the development of a corporate planning model or to use an existing model. In reporting the results of the first survey of corporate models in the U.S., Gerschefski7 asked the question, ‘Why do some companies have models and not others?’ and responded ‘At this point it appears to be a matter of individual initiative. Models appear to exist in those companies where someone has heard about them and The more recent has proceeded to “sell” management’. survey by Naylor and Schauland” suggests that managers are beginning to take a more active interest in *The author is Assistant Professor of Decision Sciences, Wharton School, University of Pennsylvania 19174, U.S.A.
The
models in our corporate modelling : ‘The corporate survey enjoy a relatively high degree of political support on the part of management’. This is consistent with the observation of people concerned with management non-technical managers are information systems -that taking an active interest in the development of these systems and that this interest is an important determinant of their success.l *6- l 4 But this does not explain how managers make the decision to proceed. Although this issue has not yet been addressed in the literature on corporate modeling, it has been addressed in both the descriptive and normative literature on computer applications and manageof ment information systems .g The principal conclusion this literature is that a decision to proceed with a computer application should be made on an economic basis that takes into account the impact of the system on improved management decisions and of these decisions on organizational (usually economic) performance. Emery4 e5 presents a framework based on statistical decision theory for doing this, and the recent literature on information requirements analysis takes a similar approach. 12. l3 In addition, in their survey of corporate computer users, Taylor and Dean4 conclude, ‘Applications are planned and approved. . . on the same basis as other actions involving increased expenditures and investment-if not through return on investment analysis, at least on the basis ofjudgment of the value of improvements expected.’ This article presents a complementary view. It is argued that managers faced with the problem of estimating the benefits of a model not yet constructed encounter difficulties in estimating the impact of improved information on decisions and performance. Therefore, instead of thinking through the consequences of a proposed system on 0 priori grounds, they search for a reference model-that is, a model similar to the one being considered-and extrapolate from the observations of the reference model to evaluate the proposed model. The ways in which they do this are examined below.
How Managers Decide to Use Planning Models
The Case Studies In the summer of 1977, a project was initiated at The Wharton School to write case studies on planning models for use in a new course on this subject. The purpose of the cases and the course is to examine the relationships between modeling and MIS and to examine the ways in which a synthesis of these two technologies may be and are being used in short range and long range planning.* The cases are outlined below. The type of model, type of organization and purpose of model are given below: (1)A deterministic simulation used by a consumer services company for short-range logistical planning.
(2)A
Monte Carlo simulation used by a financial services company for long-range pension planning. (3)A simulation based on a data management system used by a consumer products company for financial and marketing planning.
(4 A
linear programming model used by a consumer products company for quarterly and yearly production and distribution planning.
(5)A
financial model consisting of simultaneous linear equations used by a common carrier for multi-year financial planning. (6) A linear programming model used by an oil company for multi-year financial planning.
33
legislation and regulation on corporate activities, and only a few of these appear in our sample. However, the cases that we were not able to write appear similar in terms of modeling technique and development decisions to the cases that we were able to write.
The System Development
Decision
There were four ways in which the organizations outlined above made decisions to develop planning models. They are: (1) comparison with an ongoing system, (2) comparison with a related system, (3) initiation of a low-cost pilot project and (4) comparison with competitors’ behavior. The first method, comparison with an ongoing system, consisted of examining an existing manual or partially computerized decision support process and concluding that a limited computerization of the process would be desirable even if no model were constructed. For example, the corporate model for the common carrier (No. 5 in the examples of the previous section) was constructed after an executive concluded that the existing manual system for preparing pro forma financial statements was too time consuming, that automation of this process, even without the construction of a more sophisticated model, would be preferable to the existing practice, and that such a model, if it could be constructed,
(‘1 A
would provide an ‘additional consumer products company
(8)An
by
(9)An
agency
data management system in order to reconcile discrepancies in data sources before deciding to augment it with a financial simulation, and the government agency that constructed a system for energy planning (No. 9) had similar motivations.
Monte Carlo simulation and a statistical analysis program used by a government organization for personnel planning. interindustry economic model used government agency for economic analysis.
economic model used by a government for energy planning.
a
There is a slight bias in this sample with regard to the purposes of the models. A number of companies that we met with declined to allow us to write cases about their systems. Most of the reasons concerned: (1) the amount of time that company managers and analysts would have to spend providing us with information, (2) the reluctance of companies to release information that might be of use to their competitors and (3) the reluctance of companies to release information that might be seen by the government. The cases that we were not able to write for the first two reasons given above did not appear to differ from the ones we were able to write. However, the third reason introduced a bias, because the models that were rejected for this reason were the ones used to negotiate with government agencies about tax, regulatory and other matters, and the companies did not want the government agencies to know that they were using models for this purpose. Thus, it appears that a substantial number of planning models are used to determine the impact of government ‘The cases were written by four Research Assistants at Wharton under my supervision. They are: Ms. Jacinta A. Coleman, Mr. Charles Kutcher, Ms. Lisa J. Pearson, and Mr. Jeremy Reifsnyder. The case-writing effort was funded by a grant from IBM.
benefit. In addition, the (No. 3) implemented its
The second method, comparison with a related system, was used when the organization had already implemented a successful planning model in a related area and used that system as a reference point for evaluating the proposed model. For example, the logistical simulation for the consumer services company (No. l), the linear programming model for the consumer products company (No. 3), and the financial planning model for the oil company (No. 6) were each developed because people in the company had previously been successful in developing
planning
models.
The third method, initiation of a low-cost pilot project, was used when it was possible to implement the system or a significant subset of it at low cost and there was sufficient time to do so. (Some of the systems studied here were implemented under severe time pressures.) In this case the low cost was an important factor in the decision to proceed, because it made the benefits appear auite favorable in relation to the costs incurred bv the drganization. For example, the government agency that imnlemented a svstem for nersonnel ulannimz (No. 7) hid so in part because it Gas able to bbtain ; part of the system from another government agency. In addition, the government agency that developed an interindustry economic model to prepare economic
Long Range Planning Vol. 13
34
April 1980
impact statements (No. 8) did so not only because of the perceived benefits of the model but because it was able to obtain substantial financial support for an initial development effort from another government agency. Thr fourth method, comparison with competitors systems (or in the case of government agencies, comparison with systems developed by other agencies performing similar functions), was used by some organizations not because they wished to imitate their competitors, but because they considered their competitors’ behavior a useful reference point. For example, the financial services company that developed a Monte Carlo simulation for pension planning (No. 2) was motivated in part by the fact that several of its competitors were also developing such systems. In addition, the government agencies (No. 7, No. 8 and No. 9) were able to develop their systems with greater confidence because they had observed that other agencies with similar responsibilities were implementing similar systems. The four methods outlined above do not correspond closeiy with the literature referenced in the introduction to this paper. None of the organizations performed a formal cost/benefit analysis that contained quantitative estimates of the impact of improved information on management decisions and thence on performance. In many cases no formal proposal of any kind was prepared, and the formal reports that were prepared were usually used to communicate with external organizations (i.e. consultants hired to participate in the design or programming effort and outside agencies providing financial support). On the other hand, there was active management participation in the decision to develop the models, although in many cases the technical staffs were given substantial freedom once a decision to proceed had been made.
The Use of a Reference
I
I
Analysis
The decision process is a two-stage process: (1) the identification of an appropriate reference model and (2) the use of the reference model in deciding whether to proceed with the proposal (see Figure 1). There are four sources of a reference model, corresponding to the four methods identified above. They are: an existing manual effort which would be replaced with the proposed model (Method l), a planning model in the same organization that is similar to the one being proposed (Method 2), a low-cost pilot project (Method 3). and a planning model developed by another organization with similar responsibilities and problems (Method 4). Once an appropriate reference model (or possibly several such models) has been identified, its characteristics and usefulness are used to predict the usefulness of the proposed model. It is interesting to note that these results are consistent with the theory of disjointed incrementalism in public administ;ation,2* lo*l5 which states that managers in public sector organizations allocate resources (i.e. prepare budgets) by making incremental modifications to existing budgets, and with a few exceptions (new programs, programs that have become controversial, etc.) they confine their analytical efforts largely to an analysis of the increments, rather than perform a ‘ground-up’ or ‘zero-based’ cost/benefit analysis of all feasible budgetary decisions. This behavior is viewed as the result not of incompetent management, but of the intangibility and complexity of public-sector decision-making. This intangibility and complexity occurs also in the decision to develop planning models, with similar results.
Model
Although the four methods identified above appear quite distinct, they share a common property, which I will call the use of a reference model. In each case, the persons or groups of persons making the decision to r 1 Manual
proceed did so by comparing a proposed model with an existing model (a reference model), and they evaluated the proposal by observing the advantages and disadvantages of the reference model and extrapolating to the proposed one. They did not perform a cost/benefit analysis ‘from the ground up’, but focused their analytical efforts on the examination of the differences.
Conclusion:
Cost/Benefit
Analysis
These results suggest a new direction for thinking about the application of cost/benefit analysis to the evaluation
1
1
t--A I
I
I Identification
Reference
Selected Reference Model(s)
I
1 Analysis of ’
Planning
Model *
Proposed Planning Model
I
Figure 1. The use of a reference system
Decision to Proceed
How Managers Decide to Use Planning Models of planning models. Specifically, they suggest that such an analysis be based on a reference model. It is this author’s observation that many managers feel that their most useful models could never have been justified in advance by a cost/benefit analysis, because not enough was known about the process being modeled to anticipate the benefits (or even in some cases the eventual uses) of these models. As one manager told us about a very successful model he was using, ‘If we had had to justify this with a cost/benefit analysis, we would never have gone ahead with it’. An explicit understanding of how managers decide to proceed with the development effort for a planning model may help to clarify this process and to make it more productive.
References Steven L. Alter, How effective managers use information ci,systems, Harvard Business Review, 54 (6). 97-104, November-December
(5)
James C. Emery, Cost/benefit analysis of information systems, in System Analysis Techniques, ed. by J. Daniel Couger and Robert W. Knapp, pp. 395-425, Wiley, New York (1974).
(6)
John T. Garrity, Top management and computer profits, Harvard Business Review, 41 (4). 6-8, 10, 12, 172, 174. July-August (1963).
(7)
George W. Gerschevski, Corporate models-the state of the art, Management Science 16 (6). pp. 8-303-8-312, February (1970).
(8)
Peter H. Grinyer and Jeff Wooller, Computer models for corporate planning, Long Range Planning, 6 (I), 14-25, Februan/ (1975).
(9)
John Leslie King and Edward L. Schrems, Cost-benefit analysis in information systems development and operation, Computing Surveys, 10 (1). 19-34, March (1978).
(10)
Charles E. Lindblom, Public Administration (1959).
(11)
Thomas H. Naylor and Horst Schauland, Corporate simulation models: a survey, Long Range Planning, 9 (2). 94-100, April (1976).
(12)
William M. Taggart, Jr. and Marvin 0. Tharp, Dimensions of information requirements analysis, Data Base, 7 (1). 5-13, Summer (1975).
(13)
William M. Taggart, Jr. and Marvin 0. Tharp, A survey of information requirements analysis techniques, Computing Surveys, 9 (4). 273-290, December (1977).
(14)
James W. Taylor and Neal J. Dean, Managing to manage the computer, Harverd Business Review. 44 (5), 98-110. September-October (1966).
(15)
Aaron Wildavski and Arthur Hammann, Comprehensiveversus incremental budgeting in the department of agriculture, Administrative Science Quarterly, 10 (3) 321-346, December (1965).
(1976).
(2) David Braybrook and Charles E. Lindblom, A Strategy of Decision: Policv Evaluation as a Social Process, The Free Press, MacMillan, New York (1963). (3)
(4)
Gary W. Dickson and Richard F. Powers, MIS project management: myths, opinions and reality, in lnformation Systems Administration, by F. Warren McFarlan, Richard L. Nolan and David P. Norton, pp. 401-412, Holt, Rinehart and Winston, New York (1973). James C. Emery, Chapter 4: Economics of information, in Organizational Planning and Control Systems: Theory and Technology, pp. 66-107, MacMillan, New York (1969).
35
The science of ‘muddling through’, Review, XIX (2). 79-100, Spring