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.
INTRODUCTION
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
IMPORTANCE OF QUANTITATIVE METHODS FOR MANAGERS
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
QUANTITATIVE MODELS
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 BE EXPLICIT ABOUT OBJECTIVES
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.