Broadly applicable approach, be it with a few ‘buts’
This is a summary of Chapter Five of The Systems Approach (TSA). It is part of a series of blogging posts, which will cover the whole of Churchman’s The Systems Approach (TSA), a rather well-known book he wrote in 1968, of which I am convinced that it hasn’t lost any of its relevance to the decision-making problems of the world today. You are advised to first read my summaries of the preface and chapters 1, 2, 3 and 4 since I will avoid repetition as much as possible. As usual, the paragraph numbers refer to the numbers in the concept map.
1. Input-output The input-output approach to systems is broadly applicable to systems in different sectors of the economy. ‘In’ go various types of resources (people, money ..) and out comes some kind of product or service. Like all other models the input-output model is not reality, but just provides a simplified representation of it. The idea is to provide a structure that can amplify human thought. This amplification by simplification does not add much as long as the entity is fairly simple and managers can handle it using experience, training and insight. But the input-output model becomes quite handy when things get more complicated and the input and output can be modeled mathematically to be used in computer programs for optimization purposes. In its mathematical form the input-output model is used especially by management scientists.
2. Examples … include: (a) the educational system of a country or a state (in the US), where the legislative body ‘inputs’ money and out come students with various kinds of degrees, high-school, college and graduate. In the process the input is transformed into buildings, teachers, administrators, books etc. The system creates some of its own potential in the form of teachers; (b) transportation, where money buys infrastructure and materials and out comes the transportation of people and goods from one place to another; and (c) an industrial firm, the input of which can be regarded as the initial investment of funds, and out of which come various kinds of products distributed to various consumers, as well as dividends returned to the investors.
3. Considerations The input-output model takes into account the same set of five considerations identified in chapter three. Churchman uses the simplified case of a manufacturing firm that makes 100 different kinds of furniture to illustrate the considerations: (a) measures of performance is the net profit expressed mathematically as weighted output minus cost subject to a set of constraint equations; (b) environment is the constraint on production technology, external capital, and market characteristics (demand); (c) resources are the internal capital and personnel; (d) components are the product lines, i.e. those subsystems that produce and market each product; and (e) management is the decision making on the amount of resources to make available to each component or product line. In most cases this will be optimized in such a way so as to maximize profit.
4. Mathematics Above is an example of a simple basic formula for calculating total net profit z, where xi represents the number of products of product line i, ai the profit per unit product of product line i, and bi the amount of fixed cost assigned to product line i. On the basis of this formula it seems as though the firm ought to carry on as much activity as it can, and especially activities associated with the most profitable products. At this point the two other critical items for consideration become important, the resources and the environment. The environment ´externally´ limits for instance the total amount of capital that the firm can pour into its products: the total amount of capital is ‘given’. The resources equally constrain the production capacity, but do so ´internally´ e.g. in the form of the skilled labor force available for producing some of the more profitable products. Another resource is the total budget allowed for the variable costs of the system, thus constraining the activities as a whole. These constraint relations can be expressed quite easily mathematically. Models of this type are often called linear programming models, because all of the relations are linear.
5. Modeling problems …. e.g.: (a) the distinction between resources and environment is not easy. Some managers can are sometimes accused of being too cautious, when they could for instance increase the amount of skilled labor time to increase profit by hiring additional people. This would require additional capital. The management scientist could extend the model to determine whether this would make sense. But how will that convince the investor? Should not then the model be extended to determine whether one investment is better than other opportunities for investment? If this is becoming way too complicated – which seems to be the case – should then the scientist not admit that his model is not looking at the system as a whole, but rather at a very limited system? (b) another modeling problem is that of the data to be used. The firm’s accountant will probably be willing to state how much it costs to make each product, but are these the right data given that much of the accountant´s work concerns taxation issue that may not be relevant to the profit side of the picture; (c) a further modeling problem is that of simple assumptions, e.g. of demand for the products to be fixed, irrespective of the price of the products, competition, and advertising. These simple assumptions are attractive because they ‘enable’ the separability of the system components, an ideal seldom realized.
6. Systemic problems …. include: (a) the fundamental limitation to any modeling of a system, because a system is always embedded in a larger system (embedding principle, see here); this principle also applies to ‘middle managers’ when ‘the company’ generates ideas that threaten their ‘systems’; (b) the true costs associated with any system always reflect the way in which the larger system behaves: management scientists often avoid the value problems of larger systems by letting a higher authority determine what measures of performance (e.g. net profit, students graduated) to apply for their limited systems; “in general, we can say that the larger the system becomes, the more the parts interact, the more difficult it is to understand environmental constraints, the more obscure becomes the problem of what resources should be made available, and deepest of all, the more difficult becomes the problem of the legitimate values of the system; (c) the role of the management scientist and the significance of his “systems approach” can be questioned, considering all the errors – irreversible errors sometimes – that it commits. Is it reasonable to reduce the manager to an ‘information processor’, thus ignoring his or her rich experience and judgment? Or are the “experienced leaders” the more suspect, considering the mess they made of things in cities, countries, and the world at large? And finally, is the management scientist not a kind of systems philosopher instead of a scientist, for believing in his approach.
Churchman, C. West (1968). The systems approach. New York: Delta. Worldcat.
‘The systems approach’ of Churchman is not available online, but some other books, reports and articles are. You may try for instance Churchman, C. W. (1968). Challenge to reason. McGraw-Hill New York. PDF. If you are looking for a more practical systems approach you may try Williams, B., & van ’t Hof, S. (2016). Wicked Solutions: a systems approach to complex problems (v. 1.03). [Lower Hutt]: Bob Williams. Amazon or partial preview.