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6. Згуровский М.З., Панкратова Н.Д. Системный анализ: проблемы, методология, приложения. -Киев: Изд-во Наукова думка -2011. - 743 с.
7. Панкратова Н.Д. Тенденции и проблемы развития системного анализа как прикладной научной методологии //Сб. Научных трудов XXII Международной научно-практической конференции «Системный анализ в проектировании и управлении». (SAEC-2018). - анкт-Петербург, 22-24 мая, 2018. - С.28-44.
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УДК 303.732
Felix P. Tarasenko, D. Sc. (Information theory and Cybernetics), Prof.
A SURVEY OF METHODS OF SOLVING REAL-LIFE PROBLEMS
National Research Tomsk State University, Tomsk, Russia.
Abstract. Whatever people are doing, any of their purposeful activities (whether it is satisfying personal needs, or consumer service, social life, up to politics, high technologies, science and philosophy) is a trial of solving certain problem. Problems could be various: easy and difficult, small and large-scaled, simple or complex. And in practice we solve our problems with different levels of success. Desire to be always successful has led, during the last century, to appearance and development of practical section of systemology - Applied Systems Analysis, that generalizes positive and negative experience in solving problems, reveals causes of successes and failures. In this paper we present an attempt to give a survey of wide variety of methods of tackling different problems.
Keywords: Systems analysis, problem and problem situation, solutions of a problem, subjective and objective aspects in solving problems.
1. Asic notions
The basics of the systems view of the world were developed by many scientists and philosophers during the long history of our civilization; but as an entire doctrine in its complete form, it was presented for the first time by A. A. Bogdanov (Malinovsky) in his "Tectology" [1]. It was published in
Russia at the beginning of the 20th century, but for political reasons (Bogda-nov was a losing rival to Lenin for leadership in the Bolshevik party) it was suppressed and did not receive appropriate publicity.
The next wave of proclamations of the general view of the world was begun in the middle of the last century, shortly after WWII, by several outstanding systems thinkers and practitioners: Cybernetics by N. Wiener [2], General Systems Theory by W. R, Ashby [3] and L. Bertalanffy [4], The Art of Problem Solving by R.L. Ackoff [5], The Organizational Revolution by K. E. Boulding [6 ], The Non-Linear Dynamics (Synergetics) started by J. W. Forrester [7], I. Prigogine [8] and continued by many other outstanding authors, including Per Bak with his Science of Self-Organized Criticality [9]. Several attempts were made to generalize these ideas [10 - 13].
Gradually, it became clear that all these and related works formed an entire integral body of knowledge about the whole Nature and humanity as its part. This knowledge encompasses philosophy, methodology, theory, science, art, and practices of subjective (human) behavior. It was given a name of Sys-temology. And its phactical, technological part is Applied Systems Analysis.
Before discussing ways to solve problems, it is necessary to define the very concept of a problem. It is based on the fundamental concept of a problem situation [13].
A problem situation is some real set of circumstances, a state of things that someone is unhappy with, dissatisfied, and would like to change. This definition is illustrated in Fig. 1. Now we concretize the concept of the problem. The problem is the subjective negative attitude of the person to reality.
no problem
SITUA
TION
a problem
Fig. 1.
Let us pay attention to three points. First: our definition really fits any problem, regardless of its origin and nature. Thus, we began to describe 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 in what the emphasis is on: the "problem" situation highlights the objective component (reality), the "problem" - the subjective one (dissatisfaction). Third, there are no problems around us: the problem is a special state of the subject's psyche.
What does "to solve the problem" mean? From the definition it becomes clear that anything should be done for this, if only to reduce or completely remove the discontent of the subject. (In the following, such a subject will be called a "client", and the person helping in solving his problem will be called "systems analyst", or "facilitator").
2. Problem Solving Options
It turns out that there are a number of ways to solve problems. Which one or more of them to apply in a particular case, will be decided by those who are engaged in solving the problem, and tis depends on specific peculiarities of a problem situation considered. But now let us discuss what are all the possible options.
4-► • • , there is a problem
situation
Fig. 2.
They are naturally divided into three groups: 1) to influence the subject in order to reduce his dissatisfaction, - without changing reality; 2) to change the reality so that the dissatisfaction of the subject is weakened; 3) to arrange a most proper combination of both possibilities (see Fig .2). Consider each of the groups.
3. Ways to influence on the subject
There are three possibilities to change the attitude of the subject to reality for the better, without changing reality itself.
First of all, what is the subject dissatisfied with? With what he knows about the situation. But he does not know everything! And among the things that he does not know, information of a positive nature may well be. If you let it know to the subject, then his dissatisfaction will decrease.
There are many examples of this, but the case deserves special attention when this option is carried out in the form of subject educating, teaching, training. In this case, the cause of dissatisfaction is precisely the lack of information, and getting it during training leads to a solution to the problem. Interestingly, when familiarizing with several American firms practicing systems analysis, it was found that about 90% of the problems of their clients were solved namely through training, retraining and advanced training of the client's company personnel. This illustrates the fact that if you want to change
realityi change yourself first. Or rather, it is a sequence of subjective aspect of a problem.
It is worth mentioning another peculiarity of this method of solving problems. Additional information provided to the client must necessarily be positive, but not obligatory true. There are cases when the problem is resolved with the help of false information. Everyone can remember an episode from his life when he was telling a lie. And if you admit to yourself why the deception was preferred to truth, it turns out that with the help of lies in those conditions it was possible much easier and faster to reach the goal than with the help of truth. This is not an excuse, and certainly not propaganda of a lie, but only a statement of the fact that there would be no lie if it were not useful. In all languages there are such concepts as "lie for salvation": "white lie", "holy lie" in social life; plus, disinformation of an enemy in war, fake news in politics, mimicry among animals, insects, and even plants ...
Another option for manipulating information is sorting out the useful truth from harmful one, or preparing an effective mixture of truth and lies (see Fig. 3). For example, one Dutch poultry farm managed to significantly increase the productivity of meat production by setting chickens eye lenses with a darkened top. The fact that the chickens there is a hierarchy: the larger is the bird's crest, the higher it is in the hierarchy. And during feeding, "senior" drive away "junior" from the trough. Lenses do not allow a bird to see who has what crest; disputes have ceased, the food, being stopped "dosed", has dramatically (by about 20%) increased the growth of all birds.
submit a quantity
situation
of information
Fig. 3.
The next possibility to solve the problem without changing the reality is to change the perception of this reality by the subject. Since the evaluation of the subjects of their relationship with the environment is a mental phenomenon, then there is the possibility of influencing on the psyche of the subject in the right direction. Forms of influence can be different: mental (hypnosis, suggestion, propaganda, advertising, etc.); physical (effects of various fields -acoustic, electric, magnetic); chemical (psychotropic drugs, narcotics, alcohol). See Fig.4.
information
situa
psychi-
physical
chemical
Fig. 4.
Let us emphasize that we do not evaluate what is good and what is bad; we merely state that there are actual opportunities.
The third possibility to solve the problem without changing the problem situation itself is based on the fact that the problem arose as a result of the interaction of the subject with the situation. Therefore, sometimes the problem can be solved by interrupting this interaction (see Fig.5).
information quantity
, I è\ information
situa H—H * ; R-
v / appreciation
interraption of
information
moving to another situation
rest (break, leave,...) elimination
Fig. 5.
Here, too, there is a whole range of options: from pleasant ones to the problem carrier (promotion, assignment to study or vacation), using more or less neutral (transfer to another department, rotation), to painful ones (dismissal, etc.) and even to the extremely cruel, condemned, but, unfortunately, still existing ("There is a person - there is a problem, there is no person - there is no problem").
4. Intervention in reality
Let us now turn to the second group of possibilities for solving the problem — by intervening in the problem situation itself. Naturally, the intervention should change the situation in such a way that the client's discontent decreases or disappears altogether. However, at the same time we have to face a very significant circumstance, which, in fact, gave impetus to the detailed development of the technology of applied system analysis. However, at the same time we have to face a very significant circumstance, which, in fact, stimulates the detailed development of the technology of applied system
analysis. The fact is that in a real (problematic for our client) situation, not only our problem carrier is involved, but also many other actors who assess this situation from their own positions. For them, it may not be a problem, or their problems differ from the client's problem (Fig. 6).
Fig. 6.
Any change in the situation as a result of our intervention in it will be noticed and evaluated by all its participants, and not necessarily it will be approved by all.
A fundamentally important question arises: how should one proceed in connection with this circumstance?
To answer this question, let us turn to the fundamental, cardinal difference between the object and the subject. The subject, being simultaneously a physical object, exists in a real physical environment and, like any other object, is subject to the effects of this environment. Unlike the object, the subject is not only subordinate to natural laws, but also endowed with the ability to evaluate its interactions with the environment: he may or may not like something. This is where the individuality of the subject is laid. For now, we emphasize that the assessments are purely individual, subjective; there can be no objective assessments. As a result, the same reality is evaluated by different subjects differently.
The following advice may be useful in this regard:
Whenever any evaluative word is heard in your presence (good - bad,
useful - harmful, right - wrong, etc.), be alert and ask the question:
"In what sense ? "
The essence of the advice is that there are no evaluations objective. Evaluations are always subjective, and if you want to understand the true meaning of what has been said by others, you need to find out what criteria
the evaluator applies; different subjects may evaluate the same thing differently.
Let us now return to our question of how to act, solving the client's problem if there are other participants in the situation with inevitably different interests. Answer: we must act correctly. The word "correct" is an evaluative one, hence the question arises of what is meant by this.
5. Three types of ideologies
The correct behavior is considered to be the maximum consistent with the ideology adopted by the subject. It is ideology that determines what is bad and what is good, what is right and what is wrong - for the person.
It turns out that ideologies may be different. The choice of each "own" ideology is a complex result of personal choice, the impact of education, culture and circumstances. Ideologists cite a large number of arguments in favor of their own ideology, discussing its many differences from other teachings. However, you can point out one feature that helps to distinguish between ideologies. This is the definition of what attitude to other subjects is correct.
Although many various gradations between ideologies can be introduced (like between numerous political parties in some countries), the essential differences in attitude to others can be made between the three types of ideologies. And each of them leads to different approaches to solving the reallife problem.
The first type of ideology is called conditionally "the principle of the priority of the main person". In our case (Fig. 6, field 1), this principle leads to an intervention that is pleasing to the client, no matter of the opinions of other participants. Some of them may like it, some - not, but it must be implemented by all means. There are real-life examples of the implementation of such an ideology: dictatorship, monarchy, autocracy, unity of command, hierarchical organization, egoism, self-esteem, etc. You can even explicitly admit that in some circumstances, such an ideology gives the greatest chance for success (army, war, emergency, need to concentrate efforts of many people on a single common purpose, etc.).
It is necessary, however, to keep in mind that a number of features are inherent in the implementation of this ideology, which will inevitably have to be taken into account. First, the implementation of such an approach to solving the problem of the number-one-person will surely cause discontent of a certain part of the other participants in the situation, which will prompt them to respond. Hence, those who accepted this ideology should have the power to suppress the discontented and the willingness to use this force.
The second ideology can be called the "group priority principleAc-cording to it, among the participants of the situation, besides the client, there
are other subjects no less important and valuable than the client (in Fig. 6 -field 2).
Therefore, now the intervention should be carried out taking into account the interests of all "ours". This, on the one hand, complicates the design of the intervention, but on the other, it opens up the possibility of using the resources of not only the client, but also the rest of our group. There are many examples of real practice of this ideology: racism, nationalism, fascism, communism, capitalism, - any group activity, including political party, trade union, sports, etc.). We emphasize that here we do not set the task to assess such ideology: for those who accepted it, it is the only correct one, for opponents it is unacceptable. However, it is worth noting some of the inherent features of this ideology, which are latently embedded in it and in appropriate conditions may manifest themselves negatively. First of all, this is a double morality: by dividing everyone into "us" and "them", "ours" and "alien", it allows them to be treated differently. In the class policy variant, "not ours" are generally regarded as enemies, which leads to aggressiveness and build-up of power structures. Different groups resolve this contradiction in different ways, stories are known for successful and tragic variants.
And now - the good news: applied systems analysis adheres to the third ideology (see Fig. 6 - field 3). It can be called "the principle of priority of all and each". It is based on two postulates:
- there are no identical subjects, they are all different;
- despite the differences, all subjects are possessing equal rights and have equal social value.
It follows that it is wrong, immoral to solve the problems of some at the expense of others. Correct, moral is recognized only the improving intervention. Improving intervention is a change in a problem situation that is positively evaluated by at least one of its participants and non-negatively by all others. Naturally, our client should be among those who positively assess the proposed intervention.
In connection with the above, applied systems analysis can be called the theory and practice of design and implementation of improving interventions. And since this does not give rise to new discontent among any of the participants in the situation, another definition of applied system analysis can be formulated as a technique for solving real-life problems without creating new problems.
An inventor, developer, disseminator, advocate, and successful practitioner of improving intervention in practices of solving problems was Russell L. Ackoff. His findings and achievements became one of the most significant developments in management of the 21st century (see, for instance, his book "Idealized Design" [14].
6. Is improving intervention feasible?
The experience shows that when the definition of improving interventions in the audience is announced, there necessarily found skeptics (and the older the audience are, the more of them), who consider what has been said to be a beautiful, but unattainable goal. There are many reasons for skepticism. Let's discuss the main ones.
• "It is impossible to make everyone feel good". This is a substitution of the thesis: improving intervention is not when "everyone is good", but when no one is worse, and this is not the same thing.
• "Experience shows that no solution to any complex problem is possible without creating new problems". In reality, it often happens. But this is only a consequence of the fact that the systems technology was not realized properly. Obvious examples of this are the anti-alcohol campaigns conducted in USA in the beginning of XX century, and in the end of it during the Soviets era in USSR. Both attempts failed, producing many new problems. The negative experience of solving problems is not connected with the impossibility of solving them successfully, but with non-compliance with the requirements of their systemic solution (fight with symptoms, not with reasons, or not taking into account some essential ties with environment).
• " Very often failures in solving problems are due to lack of resources and mistakes in decision-making". Therefore, it is important to consider improving intervention as an ideal to be pursued, even if it turns out to be not fully achievable. "Improving intervention is often difficult to find, but rarely impossible" (R. L. Ackoff). Applied systems analysis proposes a method of moving toward a goal, although the practice of this movement may come up against a lack of information, making mistakes, insufficient resources, and a shortage of time. It is important to move in the right direction as far as possible.
Perhaps the most serious reason for doubting the feasibility of improving interventions is the contradictory interests of the participants in the problem situation, sometimes reaching the point of conflict. How can you make an improvement intervention when someone is dissatisfied with the very fact that others are better? Or when everyone seeks to prove and assert their rightness, and their positions are different or even incompatible?
There are several possibilities to move towards improved intervention even in such conditions (see below). And actually in the systems analysis it is offered to refuse clarification "who is right?", and move on to the search, the creation of "common agreement", preferring common peace and efficiency ("consensus") before their rightness [14].
7. Four types of improving interventions
Returning to the ways of solving problems, it is interesting to consider the classification proposed by R. Ackoff [15]. He noted that despite the enormous diversity, the dissimilarity of problems, there are only four ways to solve them.
7.1. ABSOLUTION.
This term in the colloquial English denotes the actions of a priest who forgives sins to parishioners: he listens to confession and does nothing. In the professional language of systems analysis, this term denotes non-interference. Please note: this does not make anyone worse. But preference should be given to non-interference only if any proposed interventions lead to worse results. Examples: actions of a doctor in case of difficulty of diagnosis (placebo), behavior of a sapper when an explosive device is found unknown to him, recommended non-interference in the family problem of your friends.
7.2. RESOLUTION
R. Ackoff proposed to designate with this term such a type of intervention, in which the problem is solved partially, not in the full scale, but in an acceptable way. There are several possibilities to do this.
The first is to use insufficient resources to completely solve the problem, in order to mitigate discontent, having solved this problem partially. A good example of this is some increase in wages, pensions and scholarships to public sector employees against the background of galloping inflation; allocation of limited resources by draw, by turns or equally.
The second possibility is to try to return to the state when there was no problem: determine what caused the problem and eliminate this cause; find the culprit and punish him. This (alas, common) solution is incomplete, partial, outdated: any event in the world is the result of many reasons, and the elimination of one of them is certainly not complete. Another example of such an approach is to repeat the action that has previously been successful in a similar case. But this is due to the risk of insufficient similarity of circumstances, which can lead to unexpected results.
7.3. SOLUTION
In the professional language of systems analysis, this word is a term denoting the best intervention under given conditions. The relevant scientific term "optimal" has already entered the spoken language and public consciousness, so it is important to understand and apply it correctly. Optimal means the best under the given constraints. For all the seeming simplicity of this definition, it requires explanation.
First, what does "the best" mean? The same objects can be ordered in different ways, depending on what quality to consider. The criterion that evaluates this quality allows you to find the best (against this quality) alterna-
tive. There is not a trivial question at all: how to choose the best option if the alternatives are compared not by one but by a combination of several criteria? It's important for us that before talking about optimality, it is necessary to specify, determine by which criterion (or criteria) the compared options will be ordered, i.e. in what sense we will use the term "best".
However, this is not enough for optimality. The second, no less important, integral part of the concept of optimality is the dependence of the result of choice on specific constraints in this situation. Under the same quality criteria, the choice from the same set of alternatives under different constraints will generally be different. Therefore, only those alternatives that satisfy the imposed restrictions make sense to compare with each other according to the chosen quality criterion: the best alternative in the sense of the criterion that does not meet the restriction cannot be implemented.
The desire to do everything as best as possible is so natural for people that it is not surprising how quickly the abstract mathematical concept of op-timality has moved from science into business, governance, and even in everyday life. Although the widespread popularity of the idea of optimality, apparently, is a consequence of the great fashion for cybernetics in the 1950s -1980s, a few people, except specialists, drew attention to the warning of N. Wiener, the cybernetics father, about the need for careful use of this concept.
The fact is that intervention in a problematic situation is based on the information we have about the situation. And the degree of knowledge of our situation may be different. There are well-structured problems that allow the construction of quantitative mathematical models; for example, many engineering and scientific problems (such problems are called "hard", - hard problems). But many of the problems of real life are described in languages far from mathematics, - from everyday problems described in spoken language, to professional ones, which are engaged, for example, many humanitarians and naturalists (such problems are called "fuzzy", "soft", — soft problems). Naturally, these differences are also taken into account in a number of details of the problem-solving technology, which makes it possible to speak of "hard" and "soft" technologies of applied systems analysis.
The difference between "hard" and "soft" methodologies of system analysis can be emphasized once again on the example of optimality. Both optimality components (criteria and constraints) are sensitive to this difference. The very requirement that the quality criteria and limitations are expressed quantitatively already means that the situation under consideration is so well studied that it allows the construction of its mathematical description. And the optimization problem is a formal mathematical problem, quite adequate to the problems of the" hard " type (and the course of optimization
methods is one of the largest and most ingenious mathematical subjects at the university).
But already within the framework of formal mathematical models, the "fragility" of optimal solutions was revealed: often even with small deviations from the assumptions in the formulation of the problem, the quality of its solution can change very dramatically. So consideration of the problems of stability (robustness) of solutions is an important section of the theory of optimization.
In the transition to "soft" problems the situation is much more complicated. And it's not just that for such problems it's harder (if at all possible) to find quantitative measures for criteria and constraints. The main thing is that the "softness" of the problem is a consequence of its little knowledge; in particular, there is no possibility to list all the important limitations, and this, as we have seen, radically affects the quality of choice. Hence, the optimality in this case should be considered an unattainable ideal, which is still worth striving for. And optimization attempts should be considered only as an element of the trial and error method.
7.4. DISSOLUTION
This term denotes an intervention, ending in complete extinction of the problem and non-appearance of new problems. It would seem, what could be better than optimal? The essential difference between the third and fourth methods is that "optimal" is the best under given conditions, and the "dissolution" considers the restrictions and conditions not as firmly fixed, but as subject to change or cancellation, in order to find new, previously unacceptable options, among which may be much more effective than previously optimal.
An important option to "dissolve" the problem is to prevent it, taking measures to ensure that it does not appear. Here, the change of the system is made not after the appearance of the problem in order to solve it, but before that - in order to prevent it.
A vivid analogy is the change in the fire protection system. In the past, this system mainly consisted of fire fighters, brave, exotically dressed, rushing down the street in their cars with flashing lights and sirens to fight fire, heroically save the lives of people and their property. In the current system, the majority of employees are fire inspectors. They without light and sound effects regularly check the buildings under their jurisdiction in order to prevent fires. They prescribe improving changes of objects and processes, reducing the likelihood of fire and possible damage from them. And this activity is no less - if not more! - important than extinguishing fires.
And in this way, in far-sighted organizations, special employees are introduced into the staff, whose duty is to conduct preventive inspection of all components of the organization, early detection of dangerous situations and
trends. Sometimes such employees are called "internal auditors", "thinking engineers", "inspectors", etc. So far this function is implemented only in the form of an internal audit. A gape in organizations is the absence of persons responsible for the implementation of preventive improving intervention. This responsibility is assigned to managers who are already loaded with the management of the current activities of their unit.
R. Ackoff gave a vivid example of applying all four methods to solving one real problem.
A problem has arisen in a bus company in a large city: after the introduction of performance premiums for high quality, conflicts between drivers and conductors began. The fact is that the quality of the work of drivers was assessed by the accuracy of the observance of the timetable, and conductors -by how well they serve the passengers. During rush-hours, the conductors delayed the sending signal (they had to check not only the ticket availability but also the correct payment depending on the distance, and the incoming ones to sell the tickets, each to his destination station), and this adversely affected the drivers surcharge.
At first, the company's management ignored the problem (ABSOLUTION), expecting that everything would settle down by itself. But the problem continued to escalate, the trade unions were involved in the conflict. Then the leadership tried to return to the old system of payment (RESOLUTION), but both trade unions protested, as this would mean the abolition of surcharges. Then the management suggested to the trade unions to agree on the division of the surcharge fund (SOLUTION), but they did not want to cooperate with each other.
The problem was DISSOLUTED by a visiting systems analyst who discovered that during rush-hours the number of buses on the line (regulated during the day) was greater than the number of stops. At these hours, the conductors began to be removed from the buses and assigned to each stops. They were selling tickets before the bus arrived, they had time to check the tickets for those leaving and began to send a departure signal in time. At the end of the rush hour, the conductors returned to the buses, and the extra buses were removed from the line. In addition, the company took a smaller number of conductors.
This interesting example should not give the impression that the four types of solutions are arranged in order of absolute preference: in this case, "dissolving" (removal the restriction "conductors must always work in the bus") turned out to be the best of them, but in other problems any other can be the best.
Moreover, the preference for a particular type of intervention depends on the mental orientation of the manager. R. Akoff proposed [15] to distin-
guish four types of managers engaged in planning, decision-making, and implementing decisions:
1. Reactive management is dissatisfied with the current situation and where everything is going; prefers what was in the past; management efforts are aimed at returning to the previous state by eliminating the causes of the changes. The preferred type of problem solving is resolution, the methods used are past experience, common sense, qualitative assessments, the choice of a "good enough", "acceptable" solution. An example of a satisfactory application of such an approach is the clinical practice of healing, but even then there are fatal failures. In management, such an approach is associated with authoritarian management, planning from the top down, aimed at solving separate problems, eliminating the undesirable without considering its connection with the other components of the situation (which often leads to the appearance of even more undesirable).
2. Iinactive (passive) management - is satisfied with the present, wants neither a return to the past, nor future changes; impedes changes, appreciates stability; believes that if nothing is done, then nothing will happen, and that is good; that it is necessary to act only when there is a threat, a crisis. At the same time, unlike reactivists who are trying to eliminate the causes, inactivists are engaged in the suppression of symptoms ("crisis management"). The preferred type of problem solving is "absolution", ignoring or denying the problem, the hope that it will disappear or be solved by itself.
3. Preactive (preventive) management is convinced that the future will be better than the past and the present, therefore, it is trying to accelerate changes and use the opportunities associated with them. Forecasting the future, the ability to learn and adapt to changes in the environment, planning and creating changes becomes important. The preferred type of problem solving is "solution", finding the optimal solution, i.e. the best in given conditions. Technologies are mainly quantitative - methods of optimization, operations research, mathematical (more often - linear) programming, risk analysis, balance of expenses and income, etc.
4. Interactive management not only does not want to return to the past and the perception of the present, but also to accept the impending future. It is sure that the future can be created by the efforts aimed at it. The preferred type of solution is dissolution, the implementation of changes in the system and/or its environment, leading to the disappearance of the problem. The technology of this is idealized design.
8. More about applied system analysis
This chapter has two objectives: to specify the concept of the problem and methods of solving it, and, moreover, to give a general idea of the applied
systems analysis itself. The first goal may be considered achieved (to the extent we need now). To achieve the second goal, two more features of applied systems analysis should be discussed, which have not yet been mentioned.
Consider the typical sequence of actions in time during the system analysis (Fig.7).
Operations Research
r-->
Building of Study of Realistation Prognosis model model of decision
\ ( V V \
........ II I I I I I j I I I I I I I ll 111 I I I ^
0 Problem Model Decision End
Fig. 7.
At the moment "Problem", the client turns to the system analyst with his problem, which he could not solve on his own. After signing a contract that imposes a number of obligations on both sides, work begins in accordance with the technology
After a series of operations, there comes a moment "Model", when we get a sufficiently adequate model of the problem situation. Now comes the period of playing on the model of the results of certain interventions. At the end of this period, a (usually multi-criteria) selection of the most appropriate option "Decision" is made. From the decision to its implementation - the path is not easy, also requiring a fairly strict adherence to technology (in modern language this period is called management). With diligence and luck, we can reach the End point when the problem is solved.
Now, let's pay attention to two more features of applied systems analysis.
The first follows from the fact that there was an O moment in the past (Fig. 7), when there was no problem at all. And if the client then turned to a systems analyst, one could to subject analyzing the course of the future and predicting the appearance of a problem while maintaining the firm's style and tactics. But it would also be possible to design an intervention that would prevent the occurrence of the problem. This is reflected in a slightly humorous saying: "The best systems analysis is one that does not come true". Therefore, the forecasting technique is included in the arsenal of applied system analysis. So far this function is realized in organizations only in the form of internal audit. It is a fact, however, that clients most often turn to analysts after their own attempts to solve an already urgent problem fail.
The second, very important, fundamental feature of applied system analysis is indicated in Fig.7 coverage of the scope of analysis beyond the
t
limit "End" of the problem. It allows you to discuss the question: what will happen after the problem is solved? Of course, the former client will again have some problem. Not as a result of the solution of the previous one, if we tried to implement an improving intervention (in principle, not creating new problems), but in case of unavoidable changes in the environment and in the system itself. And what, go back to the consulting firm? This will not be necessary due to the specific feature of the systems analysis.
The matter of fact is that the problem solving process cannot be performed only by the system analyst (facilitator, consultant) alone. To build a model of a problem situation, information is needed that is possessed only by its participants themselves. Therefore, a mandatory element of the technology is their involvement in the process of working on a problem. The facilitator knows what questions, in what form, in what sequence to ask, to build an adequate model of the situation on the basis of the information received, and only the participants in the situation can answer these questions. Moreover, it is they, and not the facilitator, who will have to implement the developed intervention.
As a result, the process of system analysis will be performed by the employees of the client's company themselves. And doing some work on their own efforts is the most effective form of training them for this activity. Thus, in applied system analysis, it turns out to be a naturally built-in, integral part of training in system analysis itself. As a result, the need to re-apply to a consulting firm is significantly weakened.
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