Knowledge that Transforms

The scientists who have suggested improvements of the techniques of managerial analysis and decision making through the application of the “scientific method” have called attention to a worthwhile and important goal. Their proposals are bound to initiate a process of self-analysis and re-appraisal of the current methodical foundations of managerial policies. But the challenge in itself—even if made in a very determined manner—is no proof of its correctness and adequacy though this seems to be the opinion of some of the challengers. In order to arrive at a final conclusion it is essential to determine whether the scientific method is as applicable and valuable in the managerial field as it has proven to be in the physical sciences. The basic assumptions and procedures of the scientific method must be examined as a prerequisite for such a determination. No comprehensive analysis of such a broad problem is possible within the scope of this paper. The presentation will have to be restricted to a few characteristic examples to indicate the fundamental trends. Much more work will have to be done as a preliminary for reaching results which may be widely accepted. The principal purpose is to encourage such work.

In this paper we study the question of determining an Ss inventory policy in the presence of delivery time being a random variable. Otherwise the usual conditions of the problem are retained (demand is considered a random variable, etc.). We will use the basic work of Whitin (Whitin, Thomson M. 1953. The Theory of Inventory Management. Princeton University Press, Princeton.), as a starting point, and develop our analysis as an extension of his exposition (where delivery time is taken as being constant). It will be our purpose to derive formulas for the determination of the order size and of the reordering point.

The Institute of Management Sciences (TIMS) was formally organized on December 1, 1953. Sixty-three charter members adopted the constitution and by-laws of the society and confirmed the objectives of the Institute: “To identify, extend, and unify scientific knowledge that contributes to the understanding and practice of management.” Of the charter members, approximately one-third are academic people and about two-thirds represent industry and business. All were united in their belief in scientific foundation for the field of management.

In the economic systems of most industrial countries the bulk of the sales made by business concerns of any significant size is in the form of credit sales. In large retail outlets such as department stores, credit sales become even more important and the number of accounts receivable becomes exceedingly large. Under such conditions the proper credit policy to be followed becomes a management problem of the first magnitude. In addition to the proper credit policy it is necessary for management to determine the proper reserve for uncollectibles. One of the traditional methods of generating information on these questions has been the aging of the accounts receivable. It is precisely on management problems of this kind, where good information about large masses of data must be derived, that modern statistical sampling techniques can play an important role. When the data for decision-making purposes are the result of a statistical sample, management has an objective measure of the quality of the data on which the decision may be made. The specific objective of this paper is to demonstrate the usefulness of statistical sampling in the aging of receivables for the purpose of setting the allowance for uncollectibles.

The present study has essentially been conceived as a part of a larger study in the field of operations research. Its purpose resides in the scientific detection of the best and economically optimal strategy to be used in prospecting for metal deposits in the Sahara. The purpose of mining exploration is to discover workable deposits, and to acquire certain information on the natural wealth. This, of course, will involve certain costs. With zero expenditure there is zero information. But the cost of complete information would be inconceivable. Between these two extremes there is an optimum which we propose to seek. Obviously, the determination of such optimum is impossible unless a certain attitude towards risk is adopted. Such determination will also be conditional on at least an approximate knowledge of the probability distributions involved in the problem. The present study aims at the analysis of the second aspect, and attempts to evaluate the economic prospects of mining exploration in the Sahara, from the point of view of statistical distributions of both the number of deposits and their value.

This paper describes how linear programming procedures have been used at North Carolina State College to determine optimal combinations of products for farm firms and to specify the quantities of capital that farmers would find it profitable to invest. It shows how the introduction of risk considerations may alter drastically programs which are obtained for certain situations. The usefulness of the technique in evaluating soil conservation practices, farm leasing arrangements and related problems is pointed out.

Our principal object is to examine the industrial arena in which the psychologist is active. A short excursion is taken into the fields of aptitude testing and the psychological evaluation of industrial engineering techniques. However, the major portion of our treatment is reserved for the human relations area.

It is common for matrices in industrial applications of linear programming to have a large proportion of zero coefficients. While every item (raw material, intermediate material, end item, equipment item) in, say, a petroleum refinery may be indirectly related to every other, any particular process uses few of these. Thus the matrix describing petroleum technology has a small percentage of non-zeros. If spacial or temporal distinctions are introduced into the model the percentage of non-zeros generally falls further. The present paper discusses a form of inverse which is especially convenient to obtain and use for matrices with a high percentage of zeros. The application of this form of inverse in linear programming is also discussed.

We have all become increasingly aware of the postwar trend towards automation, which is an advanced form of mechanization. Mechanization's purpose is to relieve man of certain duties using human energy for power; automation's purpose is to relieve him of certain mental tasks and the related physical tasks necessary for their expression. Most of us sense that electronic computers, which are themselves examples of automation, will play an important role in the mechanization of control processes of the routine type. We note again that linear programming makes it possible to mechanize part of the higher order controls. It appears likely that as this mechanization becomes more accepted, it will be linked more and more to tighter production control. In a word, automation may become super-automation.

Does it seem feasible to attempt acceleration of the development of basic knowledge about organizations by utilizing the methodological advances which have occurred in the study of small groups? Specifically, how might the small group laboratory procedures of the social psychologist and sociologist be adapted to the study of organizations? Someday it may be possible to characterize social collectivities on a “meaningful set of orthogonal (independent) dimensions;” then “the definition of group and the discrimination of group from no-group [will] become arbitrary matters of convenience.” (1) In the meantime, it still seems fruitful to distinguish “small groups” from “organizations,” so that the extension of the methodologies from one area to the other is done with a modicum of circumspection. Groups are more or less stable configurations of persons in interaction. “Interaction” refers to the interlocking of the reactions of individuals to each other as stimulus objects.