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Management Information System

by Aadesh Jain
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Aadesh Jain
Aadesh Jain
MANAGEMENT INFORMATION SYSTEMS Stephen B. Harsh Department of Agricultural Economics Michigan State University harsh@msu.edu INTRODUCTION Management information systems encompass a broad and complex topic. To make this topic more manageable, boundaries will be defined. First, because of the vast number of activities relating to management information systems, a total review is not possible. Those discussed here is only a partial sampling of activities, reflecting the author's viewpoint of the more common and interesting developments. Likewise where there were multiple effects in a similar area of development, only selected ones will be used to illustrate concepts. This is not to imply one effort is more important than another. Also, the main focus of this paper will be on information systems for use at the farm level and to some lesser extent systems used to support researchers addressing farm level problems (e.g., simulation or optimization models, geographic information systems, etc.) and those used to support agribusiness firms that supply goods and services to agricultural producers and the supply chain beyond the production phase. Secondly, there are several frameworks that can be used to define and describe management information systems. More than one will be used to discuss important concepts. Because more than one is used, it indicates the difficult of capturing the key concepts of what is a management information system. Indeed, what is viewed as an effective and useful management information system is one environment may not be of use or value in another. Lastly, the historical perspective of management information systems cannot be ignored. This perspective gives a sense of how these systems have evolved, been refined and adapted as new technologies have emerged, and how changing economic conditions and other factors have influenced the use of information systems. Before discussing management information systems, some time-tested concepts should be reviewed. Davis offers a commonly used concept in his distinction between data and information. Davis defines data as raw facts, figures, objects, etc. Information is used to make decisions. To transform data into information, processing is needed and it must be done while considering the context of a decision. We are often awash in data but lacking good information. However, the success achieved in supplying information to decision makers is highly variable. Barabba, expands this concept by also adding inference, knowledge and wisdom in his modification of Haechel's hierarchy which places wisdom at the highest level and data at the lowest. As one moves up the hierarchy, the value is increased and volume decreased. Thus, as one acquires knowledge and wisdom the decision making process is refined. Management information systems attempt to address all levels of Haechel's hierarchy as well as converting 1
data into information for the decision maker. As both Barabba and Haechel argue, however, just supplying more data and information may actually be making the decision making process more difficult. Emphasis should be placed on increasing the value of information by moving up Haechel's hierarchy. Another important concept from Davis and Olsen is the value if information. They note that “in general, the value of information is the value of the change in decision behavior caused by the information, less the cost of the information.” This statement implies that information is normally not a free good. Furthermore, if it does not change decisions to the better, it may have no value. Many assume that investing in a “better” management information system is a sound economic decision. Since it is possible that the better system may not change decisions or the cost of implementing the better system is high to the actual realized benefits, it could be a bad investment. Also, since before the investment is made, it is hard to predict the benefits and costs of the better system, the investment should be viewed as one with risk associated with it. Another approach for describing information systems is that proposed by Harsh and colleagues. They define information as one of four types and all these types are important component of a management information system. Furthermore, the various types build upon and interact with each other. A common starting level is Descriptive information. (See Figure 1). This 1 Figure 1 – Types of Information 2
information portrays the “what is” condition of a business, and it describes the state of the business at a specified point in time. Descriptive information is very important to the business manager, because without it, many problems would not be identified. Descriptive information includes a variety of types of information including financial results, production records, test results, product marketing, and maintenance records. Descriptive information can also be used as inputs to secure other needed types of information. For example, “what is” information is needed for supplying restraints in analyzing farm adjustment alternatives. It can also be used to identify problems other than the “what is” condition. Descriptive information is necessary but not completely sufficient in identifying and addressing farm management problems. The second type of information is diagnostic information, This information portrays this “what is wrong” condition, where “what is wrong” is measured as the disparity between “what is” and “what ought to be.” This assessment of how things are versus how they should be (a fact-value conflict) is probably our most common management problem. Diagnostic information has two major uses. It can first be used to define problems that develop in the business. Are production levels too low? Is the rate earned on investment too low? These types of question cannot be answered with descriptive information alone (such as with financial and production records). A manager may often be well supplied with facts about his business, yet be unable to recognize this type of problem. The manager must provide norms or standards which, when compared with the facts for a particular business, will reveal an area of concern. Once a problem has been identified, a manager may choose an appropriate course of action for dealing with the problem (including doing nothing). Corrective measures may be taken so as to better achieve the manager’s goals. Several pitfalls are involved for managers in obtaining diagnostic information. Adequate, reliable, descriptive information must be available along with appropriate norms or standards for particular business situations. Information is inadequate for problem solving if it does not fully describe both “what is” and “what ought to be.” As description is concerned with “what is” and diagnostics with ”what is wrong,” prediction is concerned with “what if...?” Predictive information is generated from an analysis of possible future events and is exceedingly valuable with “desirable” outcomes. With predictive information, one either defines problems or avoids problems in advance. Prediction also assists in analysis. When a problem is recognized, a manager will analyze the situation and specify at least one alternative (including doing nothing) to deal with it. Predictive information is needed by managers to reduce the risk and uncertainty concerning technology, prices, climate, institutions, and human relationships affecting the business. Such information is vital in formulating production plans and examining related financial impacts. Predictive information takes many forms. What are the expected prices next year? What yields are anticipated? How much capital will be required to upgrade production technologies? What would be the difference in expected returns in switching from a livestock farm to a cropping farm? Management has long used various budgeting techniques, simulation models, and other tools to evaluate expected changes in the business. 3
Without detracting from the importance of problem identification and analysis in management, the crux of management tasks is decision making. For every problem a manager faces, there is a “right” course of action. However, the rightness of a decision can seldom, if ever, be measured in absolute terms. The choice is conditionally right, depending upon a farm manager’s knowledge, assumptions, and conditions he wishes to impose on the decision. Prescriptive information is directed toward answering the “what should be done” question. Provision of this information requires the utilization of the predictive information. Predictive information by itself is not adequate for decision making. An evaluation of the predicted outcomes together with the goals and values of the manger provides that basis for making a decision. For example, suppose that a manager is considering a new changing marketing alternative. The new alternative being considered has higher “predicted” returns but also has higher risks and requires more management monitoring. The decision as to whether to change plans depends upon the managers evaluation of the worth of additional income versus the commitment of additional time and higher risk. Thus, the goals and values of a farm manager will ultimately enter into any decision. HISTORICAL PERSPECTIVE The importance of management information systems to improve decision making has long been understood by farm management economists. Financial and production records have long been used by these economists as an instrument to measure and evaluate the success of a farm business. However, when computer technology became more widely available in the late 1950s and early 1960s, there was an increased enthusiasm for information systems to enhance management decision processes. At an IBM hosted conference, Ackerman, a respected farm management economist, stated that: “The advances that have taken place in calculating equipment and methods make it possible to determine the relationship between ultimate yields, time of harvest and climatic conditions during the growing season. Relationship between the perspective and actual yields and changing prices can be established. With such information at hand the farmer should be in a position to make a decision on his prediction with a high degree of certainty at mid-season regarding his yield and income at harvest time.” This statement, made in 1963, reflects the optimism that prevailed with respect to information systems. Even though there was much enthusiasm related to these early systems they basically concentrated on accounting activities and production records. Examples include the TelFarm electronic accounting system at Michigan State University and DHIA for dairy operations. These early systems relieved on large mainframe computers with the data being sent to a central processing center and the reports send back to the cooperating businesses. To put these early efforts into a management information system framework, the one proposed by Alder (House,ed.) is useful. (See Figure 2). They would be defined as data oriented systems with 4

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