Abstract: The second half of the 20th century has been marked by rapid advances of research methods in real problem solving, with rapid progress of the information technology and important structural and institutional changes that shaped a new landscape of the corporate and economic environment towards globalization of markets and trade. In that process the contribution that quantitative techniques can make to management decision making is significant.

Key words: quantitative techniques, models, analysis, decision.

            In the business world, and in fact, in practically every aspect of daily living, quantitative techniques are used to assist in decision making. In order to work effectively in a modern business organization, whether the organization is a private commercial company, a government agency, a state industry Of whatever, managers must be able to use quantitative techniques in a confident and reliable manner. Accountants make decisions based on the information relating to the financial state of organization. Economists make decision based on the information relating to the economic framework in which the organization operates. Marketing staff make decisions based on customer response to product and design.

            The quantitative methods contain two component parts, the quantitative and method, with asymmetrical attention to the quantitative term.
            Speaking about method, interest is focused upon the so- called Scientific Method. Science is the mastering of things of the real world, by knowledge about the truth. The term method drives to dialogue on methodology in science which is clouded, as the phrase scientific method is used in two different ways. The one is very general, as a process of improving understanding. Although vague, it is considered as a powerful definition, since it leaves room for criticizing dogmatic clinging to beliefs and prejudices, or appreciating careful and systematic reasoning about empirical evidence. The other is the traditional sense, and supports that there is a unique standard method, which is central to identity of the science. In effect, scientific progress requires many methods, so there is not a unique standard method, though taught as a straightforward testing hypotheses derived from theories in order to test those theories. The more acceptable definition of scientific method is a process by which scientists, collectively and over time, endeavour to construct an accurate (that is reliable, consistent and non-arbitrary) representation of the real world. The popular hypothetic-deductive standard method is excluding consideration of the process of discovery in science. Rather, research is defined as a penetrating process of learning and understanding the substance of actual things and facts, by use of different methods. The research process incorporates formulation of a research issue and construction of a conceptual framework, by using all available sources.
            The quantitative methods have a number of attributes, such as: they employ measurable data to reach comparable  and  useful  results,  assume alternative  plans  for achieving  objectives,  plan data, concerning observations collection, configuration and elaboration by statistical and econometric stochastic methods, check data reliability, choose appropriate sampling method, use carefully the
estimates of the parameters for forecasting and planning purposes, etc. since they derive from ex-post data concerning past.
            In an increasingly complex business environment managers have to grapple with a problems and issues which range from the relatively trivial to the strategic. In such an environment the quantitative techniques have an important role. It is obvious that life for any manager in any organization is becoming increasingly difficult and complex.
Organizations find them selves operating in an increasingly complex environment. Changes in government policy, privatization, increasing involvement of the European Union contribute to this complexity. At the same time, organizations face increasing competition from both home and abroad.
            Because of the increasing complexity of the business environment in which organizations have to function, the information needs of a manager become more complex and demanding also.
            The time available to a manager to asses, analyze and react to a problem or opportunity is much reduced. Managers and their supporting information systems need to take fast, and hope-fully appropriate, decisions.. Finally, to add to the problems, the consequences of taking wrong decisions become more serious and costly. Entering the wrong markets, producing the wrong products or providing inappropriate services will have major and big consequences for organizations. All of this implies that anything which can help the manager of an organization in facing up to this pressures and difficulties in the decision making process must be seriously considered.
            Quantitative techniques provide information about a situation or problem and a different way to examining that situation that may well help.
"Naturally such quantitative analysis will produce information that must be assessed and use in conjunction with other sources. Business problem are tackled from the quantitative perspective. The decisions that must be made lie at the centre of the process. These will be strongly influenced by the chosen organizations strategy with regard to its future direction, priorities and activities.

            The transformation of data into information, also called information analysis, was supported by management information system processes. Adequate models help develop quantitative techniques in a business context. Models are simplified depictions of reality and often take the form of an equation or set of equations that describe some economic setting. In economic theory models are deterministic.
Models come in a variety of forms in business: they are not just quantitative. A scale model might be constructed of a new office development, a financial model may be developed to asses the impact of budget changes on product/service delivery; the marketing department may develop a model in terms of assessing customer response to product changes.
            However, any model, no matter what its form or purpose, has one distinctive feature: it is an attempt to represent a situation in a simplified form. Which model will be adequate depends on purpose of investigation and analysis.
Many operational problems and decision making have been based on research that deals with application of model or quantitative techniques.        There are fundamentally four reasons why quantitative techniques are used by managers:

            Models force managers to identify and record the types of decisions (decision variables) that influence objectives.
            Models force managers to identify and record pertinent interactions and trade-off between decision variables. Models force managers to record constraints (limitations) on the values that variables may in quantitative decision-making problems, different kinds of formal mathematical and other types of models have been implemented.
            All organizations in business use many quantitative methodologies, including network analysis, forecasting (regression, path analysis, and time series), cost-benefit analysis, optimization (linear programming, assignment, and transportation), sensitivity analysis, significance testing, simulation, benchmarking, and total quality management.
            Moreover, decision support systems and computers based on this programmed techniques are increasingly being used for enhancing organizations capabilities. Recently, there have been relatively rapid advances in the use of large amounts of data and in the development of new techniques for their analysis.
In some cases decision makers faced with complex problems cannot find, and perhaps should not-seek, the best possible solutions. Qualitative analysis is based primarily on the managers judgment and experience; it includes managers conceptual and interpersonal ability to understand that behavioral techniques help to solve problems. Qualitative analysis is considered more as an art than a science. If the manager has had little experience with no routine problems, or if a problem is sufficiently complex, then a quantitative analysis might be a very important consideration for the managers final decision-making.
            Quantitative  analysis concentrates on  the  facts, data,  or quantitative  aspects associated  with problems. A managers educational and technical knowledge of quantitative procedures help to
enhance the decision-making process. The manager who is knowledgeable in quantitative decision-making procedures is .in a much better position to compare and evaluate the qualitative and quantitative sources of information, or ultimately, to combine alternatives to make the best possible decisions.
            At present, seat-of-the-pants, reactive managerial styles are already on the wane, and increased emphasis is being placed on "scientific" analysis and planning. Up-to-date experience is still invaluable, but it must be used with greater discipline. Analysis is now more rigorous, and computers permit more alternatives to be analyzed in greater depth. But, most important, formal planning is being used as a basis for action, not merely for pro forma exercises. On a higher and more conceptual level, quantitative analysis is facilitating communication where it never existed before. When a problem has been stated quantitatively, one can often see that it is structurally similar to other problems (perhaps from completely different areas) which, on the surface, appear to be quite different.  And once a common structure has been  identified,   insights and predictions can be transferred   from   one   situation   to   another;   the   quantitative   approach   can   actually   foster communication.
            Thus it is not necessary-or even desirable-for modern managers to be skilled practitioners of quantitative analysis. But they frequently lack even the ability to recognize the right tool or data when they sec them, let alone the ability to focus on the basic structure of a problem rather than its situational uniqueness.
            Yet they must be able to do so if they arc to do more than generate elegant nonsense. Managers must learn what the various tools are designed to do and what the limits of their capabilities are. They must be able to understand what staff specialists are attempting to achieve by a particular analysts and to discuss the appropriateness of alternative procedures sensibly (which also requires the development of additional vocabulary).
            They must fully understand the variables a model will and will not consider and be able to evaluate whether the relationships among the variables are sensible. Managers cannot use an analytical tool wisely unless they fully comprehend the underlying assumptions, what the analysis achieves, what compromises the model makes with reality, and how its conclusions are to be adapted to changing circumstances and intangible considerations. All of this requires a more thorough knowledge of operations than of mathematics.
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