Science in Management

Some Applications of Operational Research and Computer Science

C. S. Chedzey

• Publisher: Routledge
• Year: 2018
• eBook ISBN: 9781351257503
• Topic: Business
• Subtopic: Business General
• Index: Business

Originally published in 1970. Management consultants in the United Kingdom are often accused of cloaking their activities in secrecy. The confidential nature of consulting work often precludes the publication of case examples and it is only occasionally that press reports appear summarizing particular studies. Consulting firms, however, are in the unique position of gaining experience over the whole range of industry, commerce and government, and consequently have a full opportunity for spear-heading new developments and gathering technical know-how of wide value to managers.

Science in Management outlines the methods used by a consulting firm specializing in operational research and computer science and describes numerous case examples taken from a wide range of industries and from the public sector. These examples cover tactical problems, problems which overlap functional boundaries within a company and a few major projects of a strategic nature. The aim of the twenty contributors has been to explain in relatively simple terms, some of the more important techniques and to illustrate by practical examples, the wide scope of the management science approach at all problem levels.

The book will be helpful to all those seeking to apply science in management. It is written primarily for managers and those studying modern management methods, but parts of the book will be of interest to specialists as well.

PART I
Ideas and Means

In later parts of this book numerous case examples are described. This part of the book, together with Part II, is intended to provide sufficient background information to enable various examples discussed later to be more easily followed.

One objective in Part I has been to put operational research in general perspective by indicating its relationship and similarity of approach to other subjects, such as cybernetics, econometrics and systems engineering, which are also increasingly being applied to business problems.

Operational research workers continually use the word ‘model’, but its meaning in this context is not often explained to those managers interested in using the method and techniques of operational research. To overcome this obstacle, the concept of model-building is described as the central idea of the operational research approach and fundamental to the application of science to management problems. Models can simplify complex problems, increase the understanding of practical situations without disturbing the real-life conditions, and can help to predict, optimize and control. They, therefore, constitute a powerful method of attack on many management problems.

By way of preparation and introduction, a section has also been included indicating the importance of the computer as a mathematical machine for providing the means of applying scientific techniques in management, as distinct from its more restricted and current use for fast data processing and clerical purposes. Some of the later case examples illustrate the powerful advantages which can stem from this use of computers.

CHAPTER 1
The development of science in management

Science in management is by no means a new activity, and it would be difficult to establish any particular point in time when its use started. Perhaps the work of Taylor and Gilbreth¹ in the USA first focused attention on the wide scope for applying general scientific principles to management problems. It is of interest that this early work was much concerned with precision in measurement, and also stressed the importance of experiment, which were, of course, the first steps in the development of other sciences.

As a result of this work, the general movement known as ‘scientific management’ began. It was influenced very much by the general social and economic environment which existed at the time, and, in consequence, set itself rather limited goals and soon became somewhat discredited. Nevertheless, this movement paved the way for the development of ‘industrial engineering’, which gave the USA a formidable body of knowledge on which to organize their manufacturing industries with considerable success. In Europe, industrial engineering made much slower progress and was not taken up with much enthusiasm. Its ideas, however, gave birth to a number of consulting companies whose later development, particularly in the United Kingdom, was significant in producing a changed outlook.

The period immediately prior to World War II was essentially a time of consolidation, and perhaps no really new ideas emerged. In the United Kingdom the term ‘work study’ was coined to describe the activities of those using many of the concepts developed by the industrial engineers in the USA. Academic progress was being made in economics relating to the ‘theory of the firm’, but there seems to be little evidence of practical applications.

One particularly significant development, however, which occurred between the two world wars was the creation of the subject of econometrics. This is a boundary science in that it is based on both economic theory and mathematical statistics. Prior to this development, economic theories lacked sufficient quantification, so that when a number of factors were interacting it became difficult to make predictions. The later development of this subject was to have considerable similarity with the operational research approach.

World War II gave considerable impetus to the development of science in management. It not only accelerated the application of previous knowledge, but, more importantly, it fostered the creation of a number of new ideas. ‘Operational research’ as a name was first used in the military services in the United Kingdom and was quickly adopted by the military services in the USA where it was known as ‘operations research’. Also, ‘statistical quality control’ concepts were developed and applied with considerable success.

Even of greater significance for the longer-term future, Wiener and his colleagues were laying the foundations in the USA for a new science to be known as ‘cybernetics’.

Since the book is primarily concerned with operational research, we should pause here to consider the new ideas which developed during World War II under this name. There are at least three developments of significance.

First, scientists of varying backgrounds and disciplines were formed into teams to study specific problems in military strategy and tactics. This was quite a new feature and brought the scientist directly in contact with practical problems of decision-taking.

Secondly, in most of the studies undertaken, attention was paid to the chance factors involved, and probability theory was extensively employed. This also was a new feature, and it seems rather strange now that the importance of the statistical approach was not recognized earlier. The aim of much operational research work was to optimize under conditions of uncertainty.

Thirdly—and this is probably the most important new idea which emerged from this war-time activity—came the concept of model-building. The building of models or theories to represent reality is, of course, the method used in all sciences. This approach enables predictions to be made of what will happen under certain circumstances. The recognition that this approach could also be used in man-made problem areas, as distinct from its use in the natural sciences, was the most important step arising from the new activity of operational research. This, coupled with the recognition of the importance of statistics, is the basic reason for the immediate success of war-time operational research and also, of course, for the great scope of its later application to problems in industry and commerce.

At this point it is interesting to compare the two war-time developments of operational research and cybernetics. The Greek word from which ‘cybernetics’ is derived means ‘steersman’, and it is the science of control and communication. As a name it was first used in 1947¹ but its ideas were being formulated much earlier, for by 1942 many of the basic concepts existed in outline. The starting-point was probably the realization that those areas that lay on the boundaries between the established sciences offered an important growth potential for science.

Initially in operational research, models were constructed to represent the behaviour of some particular problem situation. It was soon found, however, that single models could be constructed which could represent many different practical situations and that problems could be divided into classes. In other words, although superficially particular problems appeared to be quite different from each other, they were essentially the same when described in mathematical terms. This was an important step, since once a problem could be classified a body of knowledge was often available to aid its solution.

Cybernetics is based on much the same idea in that the systems or models which are developed are applicable not only to biology, psychiatry and other natural sciences, but also to man-made problem areas, such as economics, social science and business problems. The fact that exact correspondence can be established between each branch of science enables each branch to benefit from advances elsewhere.

A further similarity between cybernetics and operational research is that both subjects employ probability theory quite extensively. From this brief discussion it will probably be recognized that operational research can be considered to be the application of part of the science of cybernetics, and it is likely that, as time passes, operational research scientists will employ the concepts of cybernetics to an increasing extent, particularly when considering large-scale, complex situations. There are many different views among specialists, however, on the relationship between operational research and cybernetics.

After World War II, operational research was applied extensively to industrial and commercial problems, both in the USA and in the United Kingdom. Considerable progress has been made, both in the success of practical applications and in the theoretical development of basic models.

The post-war development of the subject of econometrics also parallels in many ways the type of thinking employed in operational research and cybernetics.¹ The construction of econometric models and its use of probability concepts perhaps justify its description as a sister subject to operational research. As a subject, of course, it exists in its own right, and is likely to make important contributions to the solving of national economic problems. Its close similarity to operational research has led many economists trained in its methods to work in operational research teams. In the past economists have tended to observe and describe events in industry, whereas today they are playing an increasingly practical part in devising solutions to actual problems facing companies and industries.

Another subject having a close similarity with operational research is systems engineering. The origin of this name is perhaps not so easily identified as that of operational research, with its war-time associations, but it seems to have evolved from the early school of scientific management. As a name, it is currently used quite extensively in North America, although not very much in Europe. The concept of model-building and the seeking of optimum solutions to problems really form the basis of the subject, but there is also considerable emphasis on establishing systems that will perform automatically with the least human participation, and on the provision of practical hardware for the implementation of solutions.

It is evident, therefore, that very similar ideas and approaches have emerged almost independently in recent years from different background disciplines—econometrics from economists, systems engineering from engineers and operational research from scientists. Each of these subjects seems not only to be closely related to each other, but also to represent different practical applications of the more general science of cybernetics.

Operational research makes extensive use of mathematics and statistics, but this is because these subjects are essentially the language of science. A common fallacy is to regard operational research as a form of ‘business mathematics’, whereas its aim, in fact, is to use any science or technology which can assist in solving the problems which it faces. To the scientist it is the only sensible way of tackling problems, but to the business-man trained in the commercial tradition with its emphasis on hunch and the largely intuitive assessment of money-making projects, its novel feature is the use of statistical theory, mathematics, experimental method and the sheer elaborateness of investigation.

Operational research, together with the social sciences, bridges the gap between the scientific world, largely centred on the universities, and the managerial world. There is an analogy between engineering’s use of science for commercial and social ends, and the operational researcher’s use of science for determining commercial strategy and the deployment of resources.

The commercial world differs from the scientific world in that for business it is generally impossible to avoid selecting a course of action, even if theoretical understanding is incomplete. This difference, together with social factors, has been responsible for the gap between science and commerce. For a long time, the snobbery of much of the scientific world towards commerce has been equalled by the snobbery of much of the commercial world towards what was considered to be ‘long-haired’ impracticability. Fortunately, in more recent years there has been a growing appreciation of the contribution that science can make to management decisions, and the scientist has had many opportunities to learn from practical experience about the nature of the business world.

A further and most important factor which has helped to bring this about has been the development of the compute...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgements
• Foreword
• General Scheme of the Book
• List of Contributors
• Part I Ideas and Means
• Part II Methods and Models
• Part III First-level applications tactical projects ‘problems galore’
• Part IV Second-level applications integrating activities
• Part V Third-level applications strategic studies
• Index