The aim of the paper is to use computer simulation models of an entire industry's distribution channel as instruments of theory development. The major phenomena to be explained center around recent developments in distribution systems, resulting from advancing technology in the logistics of distribution as well as in communications between the various levels of the channel. Dynamic instabilities and various adaptive response patterns are found to be explainable more immediately by the hierarchical nature of the feedback-control relationships prevailing between various levels of the distribution channel than by environmental changes reflected in demand patterns.
The model is designed to aid a decision maker who is considering the expansion of existing facilities or building a new plant for old or new products. The model conditionally expands the facilities if the ratio of manufacturing capacity to potential customer demand is at the point the decision maker believes new facilities are required.
In this presentation, we have tried to see the usual applications of operations research in the marketing field. This field is in quick evolution. Among the most promising uses, we can cite: - the decision theory applied to operations with technical and commercial risks which escape from probability laws - the integrated systems of control and predictive planning in advertising and marketing fields that will probably give a new statute to test markets - investigation of the exposure concept (advertising and commercial) and the notion of response curve of a market versus exposures (consumers - advertising, sales promotion) (retailers - agents visits) - the behaviour studies of households in the consumer panels by statistical observations which will permit to simulate the market attitudes in relation with the launching strategy of the products. Those scientific approaches will be developed if the marketing executives are trained to take the best of a better organisation.
We understood this work essentially as an automatisation of the actual way of making budgets in a great international company. But the huge size of the model prevents a real back and forth movement of information between central management and decentralised units (feedback effects).
This model is purely a financial one. To give the inputs the different departments of the company must have their own models. The advantage of the corporate financial model is to make the different departments aware of the necessity of computing the inputs and to make the lack of information appear.
The factors entering into the financial planning of a large corporation are manifestly intricate, and even in the few instances in which the long term objectives are unambiguously defined it is rarely easy to see how these can be attained. In some cases it is by no means obvious what the objectives should be, but it is hoped that at the corporate level our model could be used to examine the financial implications of alternative decisions and thereby assist in the setting of targets. The development of on-line computer facilities at a reasonable cost allows programs (such as ours) to perform in conversational mode with the user taking decisions during the run. The usefulness of any completely automatic simulation model is limited by the difficulties of quantifying the company's objectives. These are best summed up in somewhat vague financial and socio-political terms. The model has little to offer in the latter field, but when operated by skilled top management should have a significant contribution to make to the former. It would, for instance, be difficult to construct an algebraic formula which draws attention to the possibility of being taken over, but a financial expert using the model would be able to detect the danger signals from the business ratios, balance sheet and profit and loss account items printed out. This would, in turn, help him to isolate the investment decisions that led to this situation.
There is a limit to what one should expect from concept testing even under the best of circumstances. Often it is difficult to develop a product that will live up to the promise of the concept, or to develop a presentation of a concept that will do justice to the product. Even if product and concept match exactly, there are too many other variables operating in the marketplace to expect concept testing to predict accurately all the time. Despite these limitations concept testing does appear to work and companies are generally pleased with their test programs. What is needed is much more methodological research to develop and test alternative techniques. At present, there is scarcely any objective evidence in support of one concept testing method over another. I lean toward tests which use finished presentations of concept statements and simulate purchase behaviour to some degree. When the evidence is in, I am confident we shall find that these techniques are the most predictive.
In the realm of simulation techniques one must consider a certain number of objectives, fields of application, and methods. The principal objectives of such games are, to give individual attention to the formation of future decision-makers, to increase their awareness of problems, to prepare management for the task of formulating policies and assessing their effectiveness, and to give them experience in series-decision-making, where later decisions depend upon the effect of earlier decisions. My researches departed from the realisation that no one had ever made a real business game that is, a game where commercial activity itself is simulated.