The information revolution: Sub-optimization

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Sub-optimization

Each system controller will try to maximize the performance of his or her own system. For example, the data processing manager will want the latest, fastest and most powerful equipment so that his department can process its work as rapidly as possible. That way he gains the greatest kudos in the organization. The factory manager will have similar aims. After all, no one wants to appear to be doing a second-rate job.

The organization has limited resources, however, and if it gives the DP manager everything he wants then the factory manager may get very little. The organization will then be able to process its data very efficiently, but it won't do so well at producing goods. By maximizing his own perform­ance the DP manager is actually working to the detriment of the organization as a whole. The organization's limited resources have not been shared out in the best way, and the organization is unable to achieve optimum performance. This is called sub-optimization.

Top management obviously has to look at the outputs it expects from the organization as a whole, and decide how best to distribute its resources amongst the subsystems in

order to achieve those outputs. This is the principle of budgeting. Information processing obviously has an import­ ant role to play in the organization, but only top manage­ment can decide how much of its resources should be allocated to it.

The sub-optimization issue arises because the aims and the needs of one subsystem may conflict to some extent with those of another. To avoid sub-optimization it is necessary to bring subsystems that do conflict in this way together, placing them under a common superior.

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System boundaries

A system is said to be bounded by its inputs. These are, if you like, the 'interface' between it and its environment. When an information system is being designed, the first thing to decide is what its outputs should be, and what inputs are needed to produce these outputs. System bound­ aries are often movable: the system designer might wish to extend the boundaries of a system i.e. increase the number of outputs and therefore the number of inputs. (This will clearly reduce the boundaries of other systems by removing outputs and inputs from them.) Or he may wish to restrict the boundaries by breaking the system down into a number of subsystems, each with a more limited number of outputs and inputs.

When computers were first introduced into business in the 1960s the systems that they were designed to automate were very large. They had to be, as the computers them­ selves were large and expensive and could only be effectively used as a central resource for large-scale data processing activities such as accounting and stock control. Today, small inexpensive personal computers are taking over much of the business's information processing. Instead of being a cen­tralized facility, they are spread throughout the business, handling information on a departmental or sectional basis. Information systems therefore tend to be smaller and more informal - in other words, their boundaries are much more restricted.

The advantages of a large system include the fact that many users can share the same data, and that procedures are determined centrally and are consistent throughout the organization. The advantages of small systems include the fact that the users themselves can set up their own systems to meet their own requirements, rather than have someone else's ideas imposed on them, and systems can be much more flexible.

So when designing an information processing system, the first task is to define what its boundaries (i.e. its outputs and inputs) should be. Should it be restricted to serving a single section, or should it be much bigger, with outputs to several departments and correspondingly wide inputs?

Information has been called the life-blood of a business.

From it, all the transaction documents that the business needs to carry on its work are produced, as well as the performance reports that management needs to properly control the business. The design of the information process­ing systems are obviously of crucial importance, and can affect not only the efficiency and control of the entire organization, but also the way in which departments work.

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