Before talking about the state of information systems, it might be useful to give a clear definition of what an information system is and even what a system is.

A system is a group of items that operate together to reach a common goal. This is the basic difference between a system and a union of individualities: the parts of a system work together toward a vision.

An information system (we will sometimes abbreviate it as IS) furthers this definition as a group of items that share information to reach a common objective. Strictly speaking, an IS is not necessarily made of software, even though most of what we will talk about in this book is about computerized information systems. And, even in the most sophisticated IS, there remains a non-neglectable part of information that is not software-contained. This is a situation that we will talk about, but for the main part of this book, we will put ourselves in the hypothesis of software-based information...

The precise definition of an information system, as interpreted in this book, has been given together with a brief history of its evolution. This history is not only very short but shows many recent evolutions, most of them radically different from the previous state of the art. This very rapid evolution is a sign that information systems design is not something that can be considered stabilized and completely understood.

There remains a large part of craftsmanship in the design and deployment of a software information system. Craftsmanship has its advantages: human attention to detail, custom-tailored functions, uniqueness, and more. It also has numerous drawbacks, such as high costs, difficulty in evolving in a controlled way, dependence on a few creators, and many others. These drawbacks outgrow the advantages in modern companies for which the information system has become the operational backbone.

Well-crafted information systems...

Engineering is about making things in a controlled way; information systems will not escape this much-awaited transition as their efficiency could be improved. To do so, we need indicators, measures, and a method to get the results on a given information system. Fortunately, there is a consensus on this in the field of expertise, as we will see now.

The measure of efficiency of a system

Since a system is a group of items working together toward a goal, as defined previously, measuring the efficiency of the whole means more than just knowing the efficiency measures of each item and summing them one way or another. It is often said that the value of a good information system is much more than the value of each of its moving parts and that the most positive effects come from their interactions.

A good way to measure the efficiency of an information system is to evaluate how much time and money it helps save on the functional processes it supports. However...

So far, things may been a bit theoretical. Most information systems are created without a defined plan and global, architected vision and this is reflected in the cost of maintenance – and thus the total cost of ownership – of the whole system. But what does this mean in practice? Is it that bad?

You may have heard expressions such as “spaghetti dish” or “data silos.” In the first case, the modules of the IS are so intertwined that it becomes impossible to touch a given part of the system without causing side effects on another one. In this case, evolution becomes complicated. The second expression is associated with modules of an IS that are so tightly separated from each other that they cannot share common data. This generally leads to duplicated data, loss of quality, and sometimes contradictory processes in the whole system. These are just a few examples of the designation of generic...

In this chapter, we discussed what an IS is and why, despite all the expertise and care that can be given by true craftsmanship in software design, the system that links all these applications together can present many issues, mainly in terms of maintenance costs and the ability to evolve in time and rise to the challenges of new business processes and requests for features. Many symptoms can alert us of the state of a given IS but they all boil down to one main reason: IT has not reached the state of a truly industrialized domain since it is still a very recent human activity compared to other actual industries.

In the next chapter, we will talk about how industrialization principles can be applied to software. This can be summed up in two actions: cutting down complexity and standardizing the interfaces.

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