Topic 13
Organization of the development of solutions by the manager based on a systematic analysis of the current situation
1. Basic concepts and definitions of decision theory…………… 2
2. Factors that determine the effectiveness of decisions ……………..………… 9
3. Concepts, principles and paradigms for developing solutions …..………….. 16
4. Model of the problem situation …………………………………………….. 25
Literature …………………………………………………………………….. 33
St. Petersburg - 2012
Basic concepts and definitions of decision theory
Further, we will use the following basic concepts: control, decision maker, problem or task (controls), solution, goal (controls, activities), operation (cybernetic), alternative, active resources, result, model, conditions (decision development).
Please note that these basic concepts should be taken as terms only, and not as strict definitions. There are at least two reasons for this.
First, there are simply no rigorous definitions for some categories of decision theory (DMT). Secondly, any definition is always rather stagnant, and TPR is a dynamic, rapidly developing science that is constantly revising its conceptual and methodological apparatus. Therefore, there is no need to memorize those words by means of which we will interpret the meaning of the basic concepts, however, one must be deeply imbued with the thoughts and images that stand behind these words, and be able to interpret them.
Control. As already noted, the solution of the problem facing the decision maker is possible only by directing and using active resources to perform specific tasks or work. Nothing gets done on its own. People participating in the operation need to be told where, when, what and with what help, what are the requirements for the quality of the tasks or work performed, what are the allowable variations from the planned tasks and under what force majeure circumstances emergency measures should be taken, what are these measures, etc. All this is united by one concept - management. To manage is to direct someone or something towards an intended goal in order to achieve a desired result.
The main requirement for the quality of management is its continuity. The notion that everything will happen by itself is a mistaken idea - this is a dangerous delusion! It is akin to the notion that when driving a car, you can leave the steering wheel for a long time. Any business, like a car, without control can only move in one direction - down a slope. In addition to continuity, there are a number of other requirements for management, for example, the requirement for a certain freedom (“backlash”) in the actions of performers, the requirements for stability and flexibility (meaning that, if necessary, adjustments to a previously planned plan can be made with minimal losses), optimality, and some others. .
Solution. Usually the same problem can be solved in different ways. However, the quality of the outcome of the operation, that is, the value of its results, depends not only on the quality of active resources and the conditions for their use, but also on the quality of the way these resources are used under these conditions. In this regard, in this course, the word "solution" will most often be interpreted as the best way solution of the problem facing the decision maker, as the most preferable way to achieve the goal set by the decision maker. Consequently, the meaning of the word "solution" in our case will be somewhat different from the meaning that is attributed to it, for example, in mathematics, when one speaks of solving a mathematical problem.
In mathematics, the correct solution of a correctly posed problem is always the same, regardless of how and under what conditions this problem is solved. The mathematical solution is always objective. In contrast, the solution of the problem is subjective, since different decision makers can choose different ways of solving the problem that they like. And besides, the conditions for solving the problem leave a significant imprint on the decision maker's choice: the same decision maker in different conditions may prefer general case different way to fix the problem.
Target. A formalized description of the desired state, the achievement of which is identified in the mind of the decision maker with the solution of a problem or task. The goal is described in terms of the desired result.
Alternative. This is a conventional name for some of the possible (acceptable in accordance with the laws of nature and the preferences of the decision maker) ways to achieve the goal. Each individual alternative differs from other ways of solving the problem by the sequence and methods of using active resources, that is, by a specific set of instructions to whom, what, where, with what help and by what time. Active resources are all that can be used by the decision maker to solve the problem. We will always consider people, time, finances (money) and expendable materials available to the decision maker.
Result. Under the result, we mean a special form of describing the most important characteristics of the outcome of the operation for the decision maker. In the study of the operation, the degree of preference (or, conversely, not preference) of its results is presented in the most suitable scale for this: numerical, quantitative or qualitative. Let, for example, consider "victory" and "defeat" as the outcomes of a financial transaction. In this case, it will be possible to measure the results of the transaction, for example, either in the quantities of profits realized, shares and other securities purchased (quantitative scale), or in terms of the intensity of the outcome, for example, “big win”, “minor defeat”, “significant defeat” (qualitative scale), or in relation to the order of outcomes - the first victory, the second victory, the third victory (numerical scale). The type of scale is chosen depending on the purpose of measuring the results; this will be discussed in more detail later.
Model. Real world complex and varied. It takes a lot of creative effort and time to study or cognize it. At the same time, in order to develop solutions, it is often enough for a decision maker to know not everything in the object or phenomenon under study, but only the essential properties, features, patterns that are important for the solution. Problems. In order to save active resources, above all, time, simulation was invented. This is a special approach to the study of reality, when the decision maker discards excessively detailed details of the object or phenomenon being studied, leaving only its most significant features. It is only necessary to demand and make sure that such a simplification is not indiscriminate. It is important that based on the results and the study of the fragments of appearance, properties and relationships remaining after the simplification, it would be possible to draw the right conclusions for decision-making. Only in this case the modeling will be really useful. As a result, all real objects and phenomena essential for the development of solutions are replaced by compact, expressive and convenient for description, storage and other use of simplified images. Such simplified images are called models. Thus, the model retains all the important things that must be taken into account when developing solutions, however, the form of representation of the model is chosen such that the solution development process would be efficient. It should be borne in mind that modeling is carried out for different purposes. Here is a list of the most common modeling targets:
§ study some element of reality - didactic and research models;
§ work out some element of practical actions - training and game models;
§ to optimize any process, form or content of something - optimization models;
§ delegate authority to perform certain actions by other persons - preference models.
Each modeling goal can be associated with the most preferred form of building and presenting the model. For example, a model can be formed descriptively, that is, in words.
Such models are called verbal. The elements of reality and the connections between them can also be represented using symbols or signs. These are semiotic models. In addition, since childhood, everyone is familiar with physical copies of objects and objects - toys. And everyone in childhood played games: war, school, some profession, that is, they modeled behavior in reality. Each of us once drew something, expressing our thoughts about what we saw or heard. These graphic images are drawings, diagrams, maps of the area, etc. - also models, that is - simplified images of reality.
Each of these models has its own, well-defined set of properties. Verbal models have a high information capacity (remember at least the greatest work of Leo Tolstoy "War and Peace"), but they are difficult to use to transform information or solve computational and analytical problems. Semiotic models, depending on the specific form of using certain signs and symbols - diagrams, graphs, logic diagrams, mathematical equations and inequalities - are good, for example, for information and optimization problems, for representing them by means of computer science. Game models (political, economic, social and business games) occupy a special place. With the help of game models, it is convenient to study the mechanisms of behavioral uncertainty. When developing management decisions in economics, verbal and graphic forms of models are most often used. Mathematical and game models are used to increase the validity and evidence of decisions.
On the basis of a system analysis of the order of work of the head of an enterprise (firm) in the development of solutions, a graphical model of the management process has been developed. This model is shown in Figure 1.1.
Terms solution development. Each problem is always associated with a specific situation, a situation and a well-defined set of conditions. The problem is always solved within the existing state of affairs. Analyzing one or another way to achieve the goal, the decision maker must clearly understand the patterns that link the course and outcome of the operation with the decisions made. The totality of ideas about these regularities, of course, is perceived by decision makers in a simplified, model form. Some of the regularities can be fixed in a strictly formal form. For example, Newton's laws in mechanics describe in mathematical form the relationships in the chain "mass-force-acceleration".
Fig.1.1. Graphical model of the control process
In TPR, a model of regularities in a chain "decision-outcome" called the "mechanism of the situation." At the same time, it is believed that the model simplification of links in the specified chain does not in any way mean their rejection.
It means that of the whole variety of connections and regularities, only those that are of predominant importance, that is, those that make the most significant contribution to the formation of the result, are included in the model. For example, when evaluating time t fall of a body in the Earth's atmosphere from a height h it is necessary to take into account, strictly speaking, the influence of both the weight and the shape of the falling body, and atmospheric perturbations (wind), however, in a significant range of heights h we can assume that only the height as the leading factor determines the "mechanism of the situation." In this case, the relationship between h and t will be simplified unambiguous, namely: h = 0.5gt2.
In TPR, only two types of model relationships are considered in the “mechanism of the situation”: unambiguous and ambiguous.
Unambiguous connections give rise to a stable and well-defined relationship between the implemented solution and the outcome of its implementation. And as soon as the course of action is given, the outcome and the results associated with it immediately become quite certain (as in our example with the estimate of the time of falling from a given height). Such “mechanisms of the situation”, in which the expected outcome almost always occurs, and the probability of other (unexpected for the decision maker) outcomes is negligibly small, we will call non-risk situations, deterministic mechanisms of the situation or certainty conditions.
Such links between the method and the outcome of the operation (risk situations, or uncertainty conditions), within which, with repeated reproduction of the same alternative, different outcomes are possible. At the same time, the degree of possibility of the appearance of certain outcomes and results is quite commensurate (that is, some outcomes cannot be considered extremely unlikely compared to others).
The most expressive model of the "mechanism of the situation" with a multi-valued relationship between the alternative and the outcome is random mechanism occurrence of insured events. Even if the same insurer insures several identical objects, two outcomes are possible: insured event” or “non-occurrence of an insured event”. And if the number of insurance objects is connected with the occurrence of an insured event, then the result is several possible values of the paid insurance amount of insurance objects. This is a typical mechanism of stochastic (random) uncertainty, and interaction with competitors is behavioral.
But there are more difficult situations. For example, there may be no data on the probabilities of certain outcomes, although it is known that random factors are the main ones in the operation. Or it may turn out that there is no data on possible alternatives for the behavior of other subjects involved in the decision maker operation, although it is known that these persons will take some actions to achieve the goals. Finally, the nature of the phenomena and events occurring in the operation may simply be unclear or unknown. The "mechanisms" of all such situations will be referred to the class of naturally uncertain. The list of concepts used in the TPR is not limited to this presentation. As the material is presented in the appropriate places, important concepts will be introduced there, such as a problem situation, the effectiveness of a solution, an expert, a criterion, preferences, best solution and etc.
In this textbook, we will use and adhere to the meaning of the following basic concepts: management, decision maker, problem or task (management), decision, goal (management, activity), operation (cybernetic), alternative, active resources, result, model, conditions (solution development ).
Please note that these basic concepts should be taken as terms only, and not as strict definitions.
There are at least two reasons for this.
First, there are simply no strict definitions for some categories of TPR. Secondly, any definition is always rather stagnant, and TPR is a dynamic, rapidly developing science that is constantly revising its conceptual and methodological apparatus. Consequently, there is no need to memorize those words by means of which we will interpret the meaning of the basic concepts, however, one must be deeply imbued with the thoughts and images that stand behind these words, be able to interpret them.
For methodological reasons, when describing the basic concepts, we will highlight in italics those terms for which interpretations have already been given or the meaning of which will be necessarily explained further, in a place convenient for presenting the material in the textbook.
Control. As already noted, the solution of the problem facing the decision maker is possible only by directing and using active resources to perform specific tasks or work. Nothing gets done on its own. People participating in the operation need to be told where, when, what and with what help, what are the requirements for the quality of the tasks or work performed, what are the allowable variations from the planned tasks and under what force majeure circumstances emergency measures should be taken, what these measures are and other All this is united by one concept "management". To manage is to direct someone or something towards an intended goal in order to achieve a desired result.
The main requirement for the quality of management is its continuity. The notion that everything will happen by itself is a mistaken idea - this is a dangerous delusion! It is akin to the notion that when driving a car, you can leave the steering wheel for a long time. Any business, like a car, without control can only move in one direction - down a slope! In addition to continuity, there are a number of other requirements for management, for example, the requirement for a certain freedom ("backlash") in the actions of performers, the requirement for stability and flexibility (meaning that, if necessary, adjustments to a previously planned plan can be made with minimal losses), optimality, and some others. .
Solution. Usually the same problem can be solved in different ways. However, the quality of the outcome of an operation, i.e., the value of its results, depends not only on the quality of active resources and the conditions for their use, but also on the quality of the way these resources are used under these conditions. In this regard, in this textbook, the word "solution" will most often be interpreted as the best way to solve the problem facing the decision maker, as the most preferable way to achieve the goal intended by the decision maker. Consequently, the meaning of the word "solution" in our case will be somewhat different from the meaning that is attributed to it, for example, in mathematics, when one speaks of solving a mathematical problem.
In mathematics, the correct solution of a correctly posed problem is always the same, regardless of who solves this problem and under what conditions.
The mathematical solution is always objective. In contrast, the solution to the problem is subjective, since different decision makers can choose different methods of solving the problem that they like. And besides, the conditions for solving the problem leave a significant imprint on the decision maker's choice: the same decision maker in different conditions may prefer, in the general case, an unequal way to solve the problem.
Target. A formalized description of the desired state, the achievement of which is identified in the mind of the decision maker with the solution of a problem or task. The goal is described in terms of the desired result.
Alternative. This is a conventional name for some of the possible (acceptable in accordance with the laws of nature and the preferences of the decision maker) ways to achieve the goal. Each individual alternative differs from other ways of solving the problem by the sequence and methods of using active resources, that is, by a specific set of instructions to whom, what, where, with the help of what and by what time.
Active resources are all that can be used by the decision maker to solve the problem. We will always consider the main active resources to be people, time, finances (money) and consumables available to decision makers.
Result. Under the result, we mean a special form of describing the most important characteristics of the outcome of the operation for the decision maker. In the study of the operation, the degree of preference (or, conversely, non-preference) of its results is presented in the most suitable scale for this: numerical, quantitative or qualitative. Let, for example, consider "victory" and "defeat" as the outcomes of a financial transaction. In this case, it will be possible to measure the results of the transaction, for example, either in terms of the amounts of profits realized, shares and other securities purchased (quantitative scale), or in terms of the intensity of the manifestation of the outcome, for example, “big win”, “minor defeat”, “significant defeat " (qualitative scale), or in relation to the order of outcomes - the first victory, the second victory, the third victory (numerical scale). The type of scale is chosen depending on the purpose of measuring the results; this will be discussed in more detail later. Model. The real world is complex and varied. It takes a lot of creative effort and time to study or cognize it. At the same time, in order to develop solutions, it is often enough for a decision maker to know not everything in the object or phenomenon being studied, but only the essential properties, features, patterns that are important for solving the problem. In order to save active resources, especially time, modeling was invented. This is a special approach to the study of reality, when the decision maker discards excessively detailed details of the object or phenomenon being studied, leaving only its most significant features. It is only necessary to demand and make sure that such a simplification is not indiscriminate. It is important that, based on the results of studying the fragments of appearance, fragments of properties and relationships remaining after simplification, it would be possible to draw the right conclusions for decision-making; Only in this case the modeling will be really useful. As a result, all real objects and phenomena essential for the development of solutions are replaced by simplified images that are compact, expressive and convenient for description, storage and other use. Such simplified images are called models. Thus, the model retains all the important things that must be taken into account when developing solutions, but the form of the model representation is chosen so that the solution development process would be effective. It should be borne in mind that modeling is carried out for different purposes. Here is a list of the most common modeling targets:
to study some element of reality - didactic and research models;
work out some element of practical actions - training and game models;
optimize any process, form or content of something - optimization models;
delegate authority to perform certain actions by other persons - preference models.
Each modeling goal can be assigned the most preferred form of constructing the II representation of the model. For example, a model can be formed descriptively, i.e. in words. Such models are called verbal. The elements of reality and the connections between them can also be represented using symbols or signs. These are semiotic models. In addition, since childhood, everyone is familiar with physical copies of objects and objects - toys. And everyone in childhood played games: war, school, some profession, i.e., simulated behavior in reality. Each of us once drew something, expressing our thoughts about what we saw or heard. These graphic images - drawings, diagrams, maps of the area, etc. - are all also models, that is, simplified images of reality.
Each of these models has its own, well-defined set of properties. Verbal models have a high information capacity (remember at least the greatest work of Leo Tolstoy "War and Peace"), but they are difficult to use to transform information or solve computational and analytical problems. Semiotic models, depending on the specific form of using certain signs and symbols - diagrams, graphs, logic diagrams, mathematical equations and inequalities - are good, for example, for information and optimization problems, for representing them by means of computer technology. Game models (political, economic, social and business games) occupy a special place. With the help of game models, it is convenient to study the mechanisms of behavioral uncertainty. When developing managerial decisions in the economy, verbal and graphic forms of models are most often used. Mathematical and game models are used to increase the validity and evidence of decisions.
On the basis of a system analysis of the order of work of the head of an enterprise (firm) in the development of solutions, a graphical model of the management process has been developed. This model is shown in fig. 1.1.2.
Rice. 1.1.2. Graphical model of the control process
Conditions for the development of solutions. Each problem is always associated with a specific situation, a situation and a well-defined set of conditions. The problem is always solved within the existing state of affairs. Analyzing one or another way to achieve the goal, the decision maker must clearly understand the patterns that link the course and outcome of the operation with the decisions made. The totality of ideas about these regularities, of course, is perceived by decision makers in a simplified, model form. Some of the regularities can be fixed in a strictly formal form. For example, Newton's laws in mechanics describe in mathematical form the relationships in the "mass-force-acceleration" chain.
In TPR, the model of regularities in the chain "decision - outcome" is called the "mechanism of the situation." At the same time, it is believed that the model simplification of the links in the specified chain does not in any way mean their rejection. This means that out of the whole variety of connections and regularities, only those that are of predominant importance, that is, those that make the most significant contribution to the formation of the result, are included in the model. For example, when estimating the time t of the fall of a body in the Earth’s atmosphere from a height h, one must, strictly speaking, take into account the influence of both the weight and shape of the falling body, and atmospheric perturbations (wind), however, in a significant range of values of the height h, we can assume that only the height is the leading factor determines the "mechanism of the situation". In this case, the connection between hut will be simply unambiguous, namely: h = 0.5e r2.
In TPR, only two types of model relationships are considered in the "mechanism of the situation": unambiguous and ambiguous.
Unambiguous connections give rise to a stable and well-defined relationship between the implemented solution and the outcome of its implementation. And as soon as the course of action is given, the outcome and the results associated with it immediately become quite definite (as in our example with the estimate of the time of falling from a given height). Such "mechanisms of the situation", in which the expected outcome almost always occurs, and the probability of other (unexpected for the decision maker) outcomes is negligibly small, we will call non-risk situations, determined by the mechanisms of the situation, or certainty conditions.
Such links between the method and the outcome of the operation (risk situations, or conditions of uncertainty) are considered to be multivalued, within which, when the same alternative is repeatedly reproduced, different outcomes may appear. At the same time, the degree of possibility of the appearance of certain outcomes and results is quite commensurate (that is, some outcomes cannot be considered extremely unlikely compared to others).
The most expressive model of the "mechanism of the situation" with a multi-valued relationship between the alternative and the outcome is a random mechanism for the occurrence of insured events. Even if the same insurer insures several identical objects, two outcomes are possible: "the occurrence of an insured event" or "the non-occurrence of an insured event". And if the number of insurance objects is connected with the occurrence of an insured event, then the result is several possible values of the paid insurance amount of insurance objects. This is a typical mechanism of stochastic (random) uncertainty, and interaction with competitors is behavioral.
But there are also more difficult situations. For example, there may be no data on the probabilities of certain outcomes, although it is known that random factors are the main ones in the operation. Or it may turn out that there is no data on possible alternatives for the behavior of other entities involved in the LIR operation, although it is known that these individuals will take some actions to achieve their own goals. Finally, the nature of the phenomena and events occurring in the operation may simply not be clear or known. "Mechanisms" of all such situations will be referred to the class of naturally uncertain.
The list of concepts used in the TPR is not limited to this presentation. As the material is presented, such important concepts as the problem situation, the effectiveness of the solution, the expert, the criterion, preferences, the best solution, etc. will be introduced in the appropriate places.
Decision theory
Decision theory- a field of study involving the concepts and methods of mathematics, statistics, economics, management and psychology in order to study the patterns of people's choice of ways to solve various kinds of problems, as well as ways to find the most profitable possible solutions.
Decision making is a process of rational or irrational choice of alternatives, aimed at achieving a conscious result. Distinguish normative theory, which describes rational process decision making and descriptive theory describing the practice of decision making.
Alternative selection process
The rational choice of alternatives consists of the following steps:
- situational analysis;
- Problem identification and goal setting;
- Search for the necessary information;
- Formation of alternatives;
- Formation of criteria for evaluating alternatives;
- Conducting an assessment;
- Choosing the best alternative;
- Implementation (execution);
- Development of criteria (indicators) for monitoring;
- Performance monitoring;
- Evaluation of the result.
The irrational choice of alternatives includes all the same components, but in such a "compressed" form that tracing cause-and-effect relationships becomes impossible.
Ergodicity problem
In order to make "rigorous" statistically reliable forecasts for the future, you need to get a sample of future data. Since this is impossible, many experts assume that samples from past and current, for example, market indicators are equivalent to a sample from the future. In other words, if you take this point of view, it turns out that the predicted indicators are only statistical shadows of past and current market signals. This approach reduces the analyst's job to figuring out how market participants receive and process market signals. Without the stability of the series, it is impossible to draw reasonable conclusions. But this does not mean at all that the series should be stable in everything. For example, it can have stable variances and completely non-stationary means - in this case, we will draw conclusions only about the variance, otherwise, only about the mean. Resilience can also be more exotic. The search for stability in series is one of the tasks of statistics.
If decision makers believe that the process is not stationary (stable), and therefore ergodic, and even if they believe that the probability distribution functions of investment expectations can still be calculated, then these functions are “susceptible to sudden (that is, unpredictable) changes” and the system is essentially unpredictable.
Decision making under uncertainty
Uncertainty conditions are considered to be a situation where the results of the decisions being made are unknown. Uncertainty is divided into stochastic (there is information about the probability distribution over a set of outcomes), behavioral (there is information about the impact on the results of the behavior of the participants), natural (there is information only about possible outcomes and no information about the relationship between decisions and outcomes) and a priori (there is no information and about possible outcomes). The task of substantiating decisions under conditions of uncertainty of all types, except a priori, is reduced to narrowing the initial set of alternatives based on the information available to the decision maker (DM). The quality of recommendations for decision-making under conditions of stochastic uncertainty is enhanced by taking into account such characteristics of the decision maker's personality as the attitude to one's own gains and losses, and the propensity to take risks. Justification of decisions under conditions of a priori uncertainty is possible by constructing adaptive control algorithms
Choice Under Uncertainty
This area represents the core of decision theory.
The term "expected value" (now called expectation) has been known since the 17th century. Blaise Pascal used this in his famous bet (see below), which is contained in his Thoughts on Religion and Other Subjects, published in . The idea of expected value is that in the face of multiple actions, where each of them can produce several possible outcomes with different probabilities, a rational procedure should identify all possible outcomes, determine their values (positive or negative, costs or benefits) and probabilities, then multiply the corresponding values and probabilities and add to give the "expected value". The action to be chosen should give the highest expected value.
Alternatives to probability theory
A very controversial issue is whether the use of probability in decision theory can be replaced by other alternatives. Proponents of fuzzy logic, possibility theory, Dempster-Schafer evidence theory, and others support the view that probability is only one of many alternatives and point to many examples where non-standard alternatives have been used with apparent success. Defenders of probability theory point to:
- the work of Richard Threlkeld Cox in justifying the axioms of probability theory;
- the paradoxes of Bruno de Finetti as an illustration of the theoretical difficulties that can arise from the rejection of the axioms of probability theory;
- perfect class theorems, which show that all admissible decision rules are equivalent Bayesian decision rule with some prior distribution (possibly inappropriate) and some utility function . Thus, for any decision rule generated by improbability methods, either there is an equivalent Bayesian rule, or there is a Bayesian rule that is never worse, but (at least) sometimes better.
The validity of the probability measure was called into question only once - by J. M. Keynes in his treatise "Probability" (1910). But the author himself in the 30s called this work "the worst and most naive" of his works. And in the 30s he became an active supporter of the axiomatics of Kolmogorov - R. von Mises and never questioned it. Finiteness of probability and countable additivity are strong limitations, but an attempt to remove them without destroying the buildings of the whole theory turned out to be futile. This was recognized in 1974 by one of the brightest critics of Kolmogorov's axiomatics, Bruno de Finetti.
Moreover, he actually showed the opposite - the rejection of countable additivity makes the operations of integration and differentiation impossible and, therefore, makes it impossible to use the apparatus of mathematical analysis in probability theory. Therefore, the task of abandoning countable additivity is not the task of reforming the theory of probability, it is the task of abandoning the use of methods of mathematical analysis in the study of the real world.
Attempts to abandon the finiteness of probabilities led to the construction of a probability theory with several probability spaces on each, of which the Kolmogorov axioms were satisfied, but the total probability should no longer be finite. But so far no meaningful results are known that could be obtained within the framework of this axiomatic, but not within the framework of Kolmogorov's axiomatics. Therefore, this generalization of Kolmogorov's axioms is still purely scholastic.
S. Gafurov believed that the fundamental difference between Keynes' probability theory (and, consequently, mathematical statistics) and Kolmogorov's (Von Mises, etc.) is that Keynes considers statistics from the point of view of decision theory for non-stationary series…. For Kolmogorov, Von Mises, Fischer, etc., statistics and probability are applied to essentially stationary and ergodic (with properly selected data) series - the series around us physical world…
Wikimedia Foundation. 2010 .
Decision making as a connecting process.
To be able to manage means to be able to choose.
The role and place of decision-making in the process of managing an organization is manifested through the basic functions of management, which include planning, organization, motivation, and control. These functions are interconnected by two connecting processes - decision-making and information exchange.
According to this approach management and decision-making processes are closely interconnected and inseparable from one another. At the same time, it should be noted that decision-making is not one of the management functions, but permeates this entire process, being carried out continuously in each management function. Decision-making links all management functions together, which is why decision-making is considered as an important connecting process within the framework of a broad management process.
In support of the above, we can give examples of decisions that are used by managers in the implementation of each management function.
In the planning process, decisions are made:
About the mission and goals of the organization;
About the state external environment and its impact on other organizations;
On the strategy and tactics of achieving the set goals;
About the budget of the organization;
About choice investment projects;
About the pricing strategy.
In the process of organizational activity, the following decisions are made:
On the ways of organizing the interaction of departments and employees of the organization;
About organizational structure;
On the limits and distribution of power;
On the reorganization of the company due to a change in the purpose and state of the external environment of the enterprise.
In the process of motivation:
About the needs and requirements of subordinates;
What needs to be done to improve the work of subordinates;
On the methods and techniques of motivating employees.
During the control process, the following decisions can be made:
How and by what indicators should performance be evaluated;
How often should the value of these indicators be changed;
What changes need to be made in order to improve the performance of your company.
The above examples show that the decision-making process is present at any stage of the management process.
The theory of decision making originated around the middle of the twentieth century as a response of human practice to the increased difficulties and responsibility in decision making.
The main task of this theory was the need to explain how a person or group of people make decisions, as well as to develop special methods and techniques in the decision-making process. In this regard, decision theory can be divided into 2 relatively independent parts:
Destriptive (prescriptive);
Prestriptivnaya (describing).
Destriptive component describes the real behavior and thinking of people in the decision-making process and is called the psychological theory of decision.
Prestriptive component describes how people should behave, how to make decisions is called normative decision theory.
PTR is a system of statements that reveal the inner content of activities and people's behavior in the decision-making process. These statements allow us to answer the following questions:
How do people get an idea of the situation when making decisions?
People differently assess the situation in which they find themselves and in which they have to make decisions. Such a representation is a subjective model of a particular situation. Practice shows that people tend to simplify the real situation, to miss many points that sometimes have a serious impact on decision-making.
How do people evaluate the consequences of their decisions?
The consequences of decisions are also subjective. The evaluation of the consequences of the decisions made takes place in accordance with individual ideas about values. Because of this, an individual assessment of the consequences of decisions made can have a significant impact on the final decision.
How do people evaluate the probabilities of various factors that influence decision making?
Psychologists have found that people often overestimate the likelihood of more understandable and desirable events for them, although objectively they may be unlikely.
What rules and strategies do people use for different decision situations?
Experience shows that when choosing an alternative, people use a variety of rules that do not have a strict justification, but once took place and could bring some success.
How are people influenced by various factors that govern the decision-making process?
Basic concepts of decision theory. Classification of management decisions according to various criteria
Management - purposeful impact on the system, ensuring the preservation of its certain structures, maintaining the regime and / or achieving the goal of the activity.
management decision, abbreviated SD - a choice that in the process of managing and solving specific organizational problems, the manager must make in writing or orally. A management decision should be the result of analysis, forecasting, economic justification and the choice of one alternative from a variety of options to achieve the set specific goal of the system.
Decision Maker, abbreviated as LPR - the one who is responsible for the decision made, the one who signs the order or other document in which the decision is expressed. Usually this CEO or the chairman of the board of the company, the commander of a military unit, the mayor of the city, etc., in a word - responsible worker. But sometimes there may be a collective decision maker, for example, the City Duma of a city or The State Duma Russian Federation. As a rule, in large organizations a draft decision is prepared by specialists, as they say, "the apparatus of the decision maker", often together with employees of other structures. If the decision maker trusts his assistants, he may not even read the text, but simply sign it. But the responsibility still lies with the decision maker, and not with those who participated in the preparation of the decision.
Regulations - definition of work order. It is customary to begin any meeting with the approval of the chairman and the agenda of the meeting, and the work of any enterprise or public association- with the approval of its Charter, which defines the rules of work and interaction of participants in the process, work.
Goals and resources. In commercial structures, as a rule, the main goal is to make a profit. Frequently used wording " maximum profit at minimum cost" is self-contradictory. The minimum cost is 0 when no work is done, but then the profit is also 0. If the profit is large, then the costs are high, since both are related to the volume of production. One can either maximize profit at fixed costs, or minimize costs at a given profit.Each decision involves the use of certain resources.In everyday life, we most often make decisions by buying goods and services.And here it is quite clear what resources are - this is the amount of money in our wallet.
Risks and uncertainties. Many decisions are made under conditions of risk, i.e. with the possible danger of loss This is due to the various uncertainties surrounding us. In addition to negative surprises, there are positive ones - we call them good luck. Usually, as the profit increases, so does the risk - the possibility of losing everything. The most profitable in Russia were financial pyramids like MMM. Someone managed to sell the shares in time, having “welded” thousands of percent of the profit on them. The overwhelming majority lost their money, leaving them with "priceless" (priceless) pieces of paper in their hands.
Alternatives- one of two or more mutually exclusive possibilities, one of the available options for action, one of the solutions that must be chosen. Alternatives are dependent and independent. Independent - these are alternatives - any actions with which they do not affect the quality of other alternatives. When dependent - the evaluation of some alternatives affect the quality of others.
Solution Evaluation Criteria- means for comparing acceptable alternatives. The quality criterion of an alternative can be any of its features, the value of which can be fixed at least on an ordinal scale. After such a characteristic is found (the criterion is defined), it becomes possible to set selection and optimization problems.
As well as alternatives, criteria are dependent and independent.
Dependent - criteria that change, affect other criteria. Independent - respectively, do not influence. Consider the example of the process of choosing a car when buying it. Let's take three criteria for consideration: price, color and gearbox. According to the criteria “price” and “gearbox”, the criteria are dependent. Determining the value of a criterion for a given alternative is essentially an indirect measure of its suitability as a means to an end. For a pair of "color" and "price", most often the criteria are independent.
The number of criteria influences the complexity of tasks in decision making. It is rarely possible to express one goal by one criterion. This causes the multicriteria of real tasks. On the one hand, a set of criteria is a way to increase the accuracy of describing the goal and choosing a way to achieve it, and on the other hand, it increases the complexity of solving the problem. Therefore, it is necessary to strive to minimize the number of criteria used, but at the same time they should describe all the important aspects of the goal quite fully. This is possible if the criteria are independent. Then the evaluation procedure is reduced to combining the criteria into groups according to their semantic meaning and determining their pluses and minuses.
Expert or experts- a professional (professionals, specialists) in a particular field, to whom they turn for assessments and recommendations.
Classification of management decisions
In the endless variety of managerial decisions, there is only one possibility "not to get lost" - the formalization of the set according to certain criteria. In the table below, on the left - the criteria, on the right - the main groups of SD determined by this criterion.
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