Knowledge that Transforms

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.

Report of the second national meeting of the Institute of Management Sciences, held on October 20–21, 1955, in New York City. This report presents —A. General Session —B. Papers on Accounting —C. Selected Topics —D. Automation and Computation —E. New Techniques and Ideas —F. Transportation —G. Forecasting and Planning —H. Behavioral Sciences —I. Addresses

As interest grows rapidly in industry on the potentialities of mathematical programming techniques, it appears worthwhile to have a paper devoted to some of the more promising developments which may speed up the transition from interest to use. Three topics have been selected (in three sections that follow) which have recently come into prominence: uncertainty, combinatorial problems, and large scale systems. The reader will find in the course of their discussions that a survey—though perhaps not a systematic survey—has been made of current techniques in the linear programming field.

It is shown that a number of fundamental optimal routing and design problems for communication networks consisting of facilities for transmission, switching, relaying, etc., may be treated in a straightforward, computationally feasible manner by linear programming methods. These methods provide a general system approach for resolving the complex interactions among system capacities, users' demands, and economic factors. Various aspects of implementation and generalizations are discussed.

The 1955 Conference on Business Statistics (Held in Philadelphia, June 9 and 10, 1955, sponsored by the Wharton School of the University of Pennsylvania, and by the American Statistical Association. The panel on linear programming was organised by M. M. Flood.) included a two-day panel discussion on “The Current Uses of Linear Programming in American Business.” The participants in the panel represented a wide enough segment of those who have been active in linear programming to permit brief coverage of a major portion of the active applications. Consequently, this report attempts to summarize the “state of the art” on the basis of that conference (The report is based in part on a verbal summary at the close of the panel discussions by a committee which consisted of A. Orden, L. Wheaton Smith, Jr., and H. H. Cauvet.).

An application of linear decision rules to production and employment scheduling was described in the last issue of this journal [Holt, C. C., F. Modigliani, H. A. Simon. 1955. A linear decision rule for production and employment scheduling. Management Sci. (October).]. The hypothetical performance of these rules represented a significant improvement over the actual company performance as measured by independent cost estimates and other managerial measures of efficiency. The quadratic cost function which was used should be applicable to production and employment scheduling decisions in many other situations. Also the general approach of approximating decision criteria with quadratic functions and obtaining linear decision rules can usefully be extended to many decision problems. In the present paper we will demonstrate (a) how optimal (i.e., minimum expected cost) decision rules may be derived for a quadratic cost function involving inventory, overtime, and employment costs, and (b) how the numerical coefficients of the rules may be computed for any set of cost parameters.

Theory and fact are just two sides of the same coin; but the two sides of a coin are different, and this difference will continue to characterize the development of management science. I hope that the future issues of the journal will more and more emphasize the problems of measurement and data-determination, just as they have emphasized “theoretical” formulations in the past. I take the diversity of point of view as a sign of a healthy organism. I see too that as this diversity shapes itself into a more unified attack, the objectives of TIMS and its peculiar role in intellectual and management activity will become clear.

In this paper we study the question which inventory policy is optimal in the presence of long delivery lags under otherwise simple conditions. The data on which the solution depends are the average demand per day (say), the carrying cost per unit and day, the fixed and per unit costs of ordering, the penalty per day of shortage, and the delivery lag. It will be shown that under certain conditions, mentioned presently, the optimal inventory policy is of the following simple type: order a fixed amount whenever the level of stock plus outstanding orders reaches a certain level. Formulas for the determination of the order size and of the reordering point will be derived.

How will electronics and scientific analysis change management planning and control? Five years ago this question held no interest for businessmen. Computers were used only for high speed calculation. There was none of the equipment needed for rapid input, and printed output, for rapid sorting, and for access to large volumes of storage. Five years ago a few scientists suspected that their new methods might be applied to business problems, but the change from the logistics of war to the planning and control of business proved more difficult than they had hoped. Now, five years later, the rush is on.

The interest in capital equipment analysis that has been evident in the business literature of the past five years is the product of numerous social, economic, and business developments of the postwar period. No conclusive listing of these developments can be attempted here. However, four should be mentioned which are of particular importance in this search for a more systematic method for discovering, evaluating, and selecting investment opportunities. These are: (1) the high level of capital outlays (in absolute terms); (2) the growth in the size of business firms; (3) the delegation of responsibility for initiating recommendations from top management to the profit center, which has been part of the general movement toward decentralization; and (4) the growing use of “scientific management” in the operations of the business firm.