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VIII. INFORMATION MANAGEMENT AND DECISION SUPPORT SYSTEMS
Effective budgeting and fiscal management requires relevant information--incremental knowledge that reduces the degree of uncertainty in a particular problem situation.
INFORMATION MANAGEMENT SYSTEMS
An information management system (IMS) provides a process by which pertinent information is organized and communicated in a timely fashion to resolve organizational problems.
IMS, DBMS, and Computers
Information management systems make use of the computer's capacity to store and retrieve vast amounts of data and are composed of data bases and the software packages (computer programs) required to manage them.
Data Base Management Systems should include: (a) high-level, interactive query language facilities; (b) interactive financial modeling packages that permit "what if" calculations to be made; (c) support for modeling and simulation; (d) a statistical analysis package; (e) word-processing software; and (f) customized software related to specialized management needs.
The Relational Model
In 1969, E. F. Codd proposed a universal foundation for database systems, based on the mathematics of relations and first-order predicate logic. 
o Codd's relational model covers the three primary aspects that any DBMS must address--structure, integrity, and manipulation.
o Relational DBMS present databases to the user as collections of tables which must obey a certain discipline.
Data manipulation by relational DBMS consists of a well-defined, complete set of mathematical operations.
o Tables are dynamically maintained by the system and can use information about the database (e.g., statistics) to optimize the logical operations.
o Structured Query Language or SQL is the concrete expression of the relational model which has gained industry acceptance
Centralized Data Processing Centers
The design of an effective IMS often can be inhibited by undue preoccupation with how data will be processed and with the characteristics of processing hardware and software.
Many early wrong notions about data processing can be dispelled by first deciding what kind of information is needed, how soon, how much, and how often. As Kennevan suggests, an IMS is:
an organized method of providing past, present, and projection information relating to internal operations and external intelligence. It supports the planning, control and operational functions of an organization by furnishing information in the proper time frame to assist in the decision-making process. 
DESIGNING AN INFORMATION MANAGEMENT SYSTEM
The design of an IMS should begin with an identification of the important types of decisions required by the organization.
Decision flow analyses often identify areas in which changes should be made in: (a) management responsibilities, (b) organizational structure, and/or (c) measures of performance.
Such analyses often reveal that important decisions are being made by default--for example, where past decisions are still binding, even though they no longer are applicable to current problems and procedures.
Ackoff has suggested that organizational decisions can be grouped into three types:
(1) Decisions for which adequate models exist or can be developed and from which optimal solutions can be derived;
(2) Decisions for which models can be constructed, but from which optimal solutions cannot be readily extracted; and
(3) Decisions for which adequate models cannot be constructed. 
Problem Definition and Classification
The first step in solving a problem is to state it--the more a problem can be extended through the examination of timely information, the greater the promise of finding a successful solution.
A distinction should be made among four different types of problem sets.
(1) Generic events, of which the specific occurrence is only a symptom, require adaptive decisions, that is, decisions which may require considerable reconstruction of programmed details before they are applicable to a given problem situation.
(2) Nonrecurrent generic problems are unique to a given organization, but have confronted many other organizations in the past--some general decisions rules exist, and decision makers can turn to the experience of others for these guidelines.
(3) Unique situation--the event itself may be unique or the circumstances in which the event has occurred may be unique.
(4) Early manifestation of a new generic problem.
The relationship among these four categories can be described in terms of (1) the availability of rules and principles (information) for dealing with such problems and (2) the frequency of encounter of these situation.
Information management systems can provide safeguards against incomplete definitions by providing mechanisms to reject such definitions when they fail to encompass the observed facts regarding the problem.
An excellent solution to an apparent problem will not work in practice, because it is the solution to a problem that does not exist in fact.
An IMS for Management Planning and Control
Three specific data areas provide inputs for the formulations of strategic decision:
(1) Environmental intelligence--data about the broader environment of which the organization is a part, including assessments of client/citizen needs;
(2) Autointelligence--data about the component elements of the particular organization, including an evaluation of its resources and capacity to respond to client needs; and
(3) Historic data--bring together and analyze the lessons of past experience.
Memory banks of the organization store data, to be retrieved when particular decision situations arise or when an assessment of goals and objectives is appropriate.
Basic analyses can be carried out using various modeling programs, and the results can be stored in the data base for reference and updating.
Diagnosis of trends can be aided by modeling and simulation programs, statistical analysis packages, and programs such as network analysis.
Through forecasting, probable happenings are outlined by assuming the continuance of existing trends into hypothetical futures.
Alternatives can be formulated and analyzed through the storage/query capabilities of the DBMS.
Policy and resource recommendations combine the results of previous decisions and program actions.
Tactical and technical innovations can be tested using various "what if" scenarios.
Resource management plans translate the overall intent of strategic plans into more specific programs and activities.
The budget process provides important managerial feedback in terms of evaluations of prior program decisions and actions.
Feedforward information emerges from the various projections and forecasts required by financial analysis and budgeting processes.
Management control activities draw on the memory banks of the organization in search for programmed decisions--decisions that have worked successfully in the past.
Resource evaluations include information regarding the current fiscal status of the organization (accounting data), as well as the overall response capacity of other organizational resources (systems readiness).
Programming techniques can be used to further detail responsibilities for carrying out operations and the resources required by these operations.
Performance evaluations draws data from the broader environment regarding the efficiency and effectiveness with which client needs are met, problems are solved, opportunities are realized.
Systems readiness defines the response capacity of the organization in the short-, mid-, and long-range futures and examines if sufficient flexibility exists to meet a wide range of possible competitive actions.
Feedback must be obtained on the output of the organization in terms of quality (effectiveness), quantity (efficiency of service levels), cost, and so on.
Resource evaluations (inputs) provide feedback at the early stages of program implementation.
Summary and exception reports generated by the IMS may become part of higher-level reviews and evaluations and, in turn, may lead to adaptations or innovations of goals and objectives.
Feedforward anticipates lags in feedback systems by monitoring inputs and predicting their effects on output variables.
DECISION-SUPPORT SYSTEMS (DSS)
Decision-support systems encompass more powerful and more user-friendly capabilities for data retrieval, database management, modeling, and graphics.
According to the proponents of DSS, the ultimate mission of the computer should be to interact effectively with management so as to influence decisions on a day-to-day basis.
Since management problems often are relatively short-lived, traditional methods of building relatively large management information systems to deal with such problems may result in the delivery of "too much, too late."
Certain basic conditions must be met if a DSS is to have the desired impact on the decision-making process of an organization:
(a) the right problems must be addressed; (b) the right people must participate in the development of the decision support system; (c) the right tools must be used; and (d) the process must evolve as decision situations and technology change. 
The DSS should be demand-driven rather than supply-generated--the demand for decision support must come from top-level management rather than being "force-fed" on the basis of available data.
A DSS should be capable of continual evolution, often in unanticipated ways as problems evolve.
The DSS should be provided as a relatively stable product since users do not want to have to learn new commands every few weeks in order to access the system.
Fundamental objective of a DSS is to enhance the attributes of good decision-making and not to devalue them by substituting quantity of data for quality of information.
IMPLEMENTATION OF AN INFORMATION MANAGEMENT SYSTEM
Implementation of an information management system can be a traumatic experience.
o New patterns of communications will emerge, and new and presumably better information will be available to assist in carrying out decision-making and administrative responsibilities.
o The need for changes organizational changes may be uncovered which may be even more unsettling than the procedural changes necessary to implement the system. .
Commitment of Top Management
Anthony and Herzlinger have suggested that "the driving force behind a new system must come from top management, . . . it is unlikely that a majority of operating managers will voluntarily embrace a new system in advance of its installation, let alone be enthusiastic advocates of it." 
Installation of a new information system involves pressure, persuasion, and compromise in proper proportions as is the case with any important political action. 
Operating managers will be more likely to support the system if they are convinced that it will benefit them in carrying out their assigned responsibilities.
The best way to "pass the word" is to have managers teach managers.
Demonstrated success in one area often can lead to more general acceptance of the system throughout the organization.
Even with the best IMS, data must still be analyzed and interpreted by managers--although the system can provide certain decision parameters, it cannot make decisions.
The fundamental objectives of an IMS/DSS is to reduce management costs as a percentage of total organizational costs and to satisfy the "increasingly voracious appetite for decision-influencing management information. . . ." 
Without careful design and implementation an IMS can become a resource-demanding devil--an organizational black hole that can absorb considerable energy with little apparent payoff.
 E. F. Codd, "A Relational Model of Data for Large Shared Data Banks," Communications of the ACM, June 1970.
 Walter J. Kennevan, "Management Information Systems," in Management of Information Handling Systems, edited by Paul W. Howerton (Roselle Park, N.J.: Hayden Book Company, 1974).
 Russell L. Ackoff, "Management Misinformation Systems," Management Science (Application Series) 14 (December 1967), reprinted in Donald H. Sanders and Stanley J. Birkin, Computers and Management in a Changing Society (New York: McGraw-Hill, 1980), p. 44.
 Martin Lasden, "Computer-Aided Decision-Making," Computer Decisions, 14:11 (November, 1982), 157
 Robert N. Anthony and Regina Herzlinger, Management Control in Non-Profit Organizations (Homewood, Ill.: Richard D. Irwin, 1975), p. 316.
 Ibid., p. 323.
 Robert C. Heterick, "Administrative Support Services," Cause/Effect 4 (November 1981), p. 29.