Introduction: How Appeared the Systems Analysis

Perhaps everyone will agree that any human activity, regardless of its professional nature, aims to solve problems constantly and consistently arising before us. The problems are small- and large-scale, relatively easy and difficult, very different, and requiring the use of scientific and practical information and knowledge of various fields.

It is striking that some people more often successfully solve problems, while others experience difficulties and even failures. The natural desire for success prompts us to find out how the actions of successful and unsuccessful people differ. There is a need to accumulate and generalize the experience of solving problems, both positive and negative, in order to not repeat the wrong actions and use successful techniques in the future.

There are always specialists who seek to meet the public need: the study of the experience of problem-solving has also begun. However, what happened could be called a “historical misunderstanding”. To solve any problem, it is necessary to use knowledge, often deeply professional, and a set of necessary professions for each problem is both specific and unique. This created a lasting impression that although everyone has problems, the problems of a doctor are very different from the problems of an engineer; the problems of a natural scientist are not the same as the problems of a manager; and so on. The specifics of the problems came to the fore. Therefore, the accumulation and generalization of experience in problem-solving began within each profession separately. In each specialty, such sections appeared, and in most professions, they took shape as entire disciplines. First, the military and then economists came up w'ith “operations research”; physicians with “general human pathology” and “the art of diagnosis”; engineers with “system engineering” and “methods of engineering creativity”; social scientists with “political science”, “futurology”, and “conflict-ology”; and administrators with “systems approach” and “governance”; this list is not exhaustive.

In the 50s-60s of the last century, in the wake of the boom of cybernetics and systems sciences (now it is not possible to determine who first said “a”), appeared the idea to compare problem-solving methods in different professions. At first glance it appeared strange, but on a second glance, it appeared to be a natural phenomenon. Yes, to solve a specific problem you need special, sometimes very deep professional knowledge, specific to the problem. But if you pay attention not to the substantive specificity of the problem but to the technology of tackling with it, and to the sequence of actions and precautions, it turns out that the probability of success increases if you follow the same advice, regardless of the nature of the problem.

From this arose the idea of proposing a certain universal algorithm of actions for solving problems, suitable for use in any profession. This idea does not seem fantastic if we take into account that we all live in the same world, obey the same general laws of the universe, and only interact with it from different sides. This universal systemic approach was gradually realized by all, although some professionals still put a distinct professional meaning in their term “system analysis”, describing the problems of their specialty.

For several decades, the idea of developing a commonly used problem-solving methodology led to the creation of a special technology, which we began to call Applied Systems Analysis (as opposed to concrete “system analyses”). This area of knowledge has already become a profession: systems analysts are trained in a number of universities around the world; there are dozens of companies taking orders to solve any problem from any customer; in Vienna, Austria, the International Institute for Applied Systems Analysis is working on global and international problems; and many higher education institutions include a course of applied systems analysis in the curricula of various faculties, both physical and mathematical, as well as natural sciences and humanities.

The technology of applied systems analysis can be compared with a locksmith’s suitcase containing a set of tools and accessories that the locksmith uses when fixing the latest problem. In addition to the tools themselves, the locksmith uses the knowledge that must be applied in a certain sequence. Similarly, to use the technology of applied systems analysis, it is necessary to understand and accept its methodology, as well as to acquire a systemic view of the surrounding reality. Therefore, the entire course consists of two parts: (1) systems thinking: the methodology (philosophy and theory) of applied systems analysis; and (2) systems practice (design thinking): the technology of applied system analysis.

In the first part of this book, four basic concepts are presented on which the entire structure of this discipline is based: (1) the concept of a problem (how we evaluate the perceived reality), (2) the concept of a system (how reality is arranged), (3) the concept of a model (how we cognize reality), and (4) the concept of governance or control (how we change reality). They are sufficient for a logical, reasonable presentation and a conscious use of systems analysis technology, which is presented in the second part.

An important feature of applied systems analysis is to take into account the differences between the problems intentionally formalized, “hard” (up to the construction of quantitative mathematical models) and poorly structured, “soft”, qualitative problems, set out in terms of spoken or descriptive professional language. Accordingly, different “hard” and “soft” methodologies are used in systems analysis. At the same time, the methods of gradual development, promoting our description of the problem from its “soft” appearance to the most “hard” option available in the given conditions, are developed.

Applied systems analysis differs from other sciences in a number of peculiar features.

First, it focuses not on finding general laws of nature, but on tackling a particular problem with its unique peculiarities.

Second, solving a real-life problem may require knowledge from several different professions; hence, applied systems analysis has a universal, interdisciplinary, over and above disciplinary character.

Third, the debate about the extent to which applied systems analysis can be considered as a science has ended with the understanding that a fusion of science, art, and craft is needed to solve real-life problems. The proportions between them are specific to each problem.

Fourth, systems analysis is performed not by the system analyst, but by the participants of the problem situation. The analyst knows the technology, that is, which questions and in what order to ask, and the answers to them are known only to the people involved in the situation. Hence, the product of the systems analysis (a decision to the problem) is developed not by a professional specialist (facilitator), but by a team of participants of the situation (stakeholders) under the unobtrusive guidance of the analyst.

Questions and Tasks

  • 1. Why has the accumulation and generalization of experience in solving problems started (and continues) within each individual profession?
  • 2. Why, despite the huge variety of problems, the technology (set of techniques) to solve them is almost the same in case of success and differs in case of failure?
  • 3. Can you formulate the main differences between the applied systems analysis of traditional sciences?
  • 4. Why can applied systems analysis be called a supradisciplinary and interdisciplinary field of activity, both in theoretical and in practical spheres?

I. Systems Thinking: Four Basic Concepts of Applied Systems Analysis

The Problem and Methods of Its Solution

Before discussing ways to solve problems, it is necessary to define the very concept of a problem. It is based on the original concept of a problem situation.

A problem situation is a real set of circumstances, a state of things, that someone is unhappy with, dissatisfied with, and would like to change.

This definition is illustrated in Figure 1.1. Now we concretize the concept of the problem.

The problem is the subjective negative attitude of the person to reality.

Let us pay attention to three points.

First, our definition fits any problem, regardless of its origin. Thus, we began to fulfill the promise to build a universal method of dealing with problems.

Second, in terms of the problem and the problem situation, two aspects are inextricably linked: objective (the presence of a real situation) and subjective (a negative assessment of reality by the subject). The difference between these concepts lies in what the emphasis is on: the “problem situation” highlights the objective component (reality), and the “problem” highlights the subjective one (dissatisfaction).

Third, there are no problems around us: the problem is a special state of the subject’s psyche.

What does “solve the problem” mean? According to the definition, it is clear that anything should be done for this if only to reduce or completely remove the discontent of the subject. In the future, such a subject will be called a “client”, and the person helping in solving the subject’s problem will be called “systems analyst” or “facilitator”.

Problem-Solving Options

There are a number of ways to solve problems. Which one or what of them to apply in a particular case is decided by those who are engaged in solving the problem. But now let us discuss the possible options.

Work on performance review — need to add acknowledgments, do global role profiles

FIGURE 1.1 Work on performance review — need to add acknowledgments, do global role profiles.

Reason of a problem may lie either in the subject, object, or both

FIGURE 1.2 Reason of a problem may lie either in the subject, object, or both.

They are naturally divided into three groups: (1) to influence the subject to reduce his/her dissatisfaction, without changing the reality; (2) to change the reality so that the dissatisfaction of the subject is weakened; and (3) to arrange a proper combination of both possibilities (see Figure 1.2). Let us consider each of the groups.

 
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