Method of morphological analysis

The essence of the method is that several characteristic (structural or functional) features are identified in the system. Each of them can characterize some parameter or characteristic of the system on which the solution to the problem depends. For each selected characteristic, a list of its various alternatives is compiled. Characteristics with alternatives are placed in a table - a “morphological box”. By going through all possible combinations of these alternatives, new solutions can be identified. Modifications of the morphological method - matrix methods.

Morphological analysis - effective way solving system problems that require an unconventional, original solution. The ideas of modern morphological analysis were first tested by the monk Raymond Lullius (ca. 1235 - 1316). The method was given a second life by the famous Swiss astrophysicist, Fritz Zwicky, who worked in the USA in the mid-20th century. Using his method, F. Zwicky was able to generate an impressive number of original solutions for rocket science problems. The name of the method “morphological” is often replaced by the term “Zwicky method”. Nowadays, morphological analysis is widely used in various areas of human activity. The development of the method has formed a separate direction - the Theory of Inventive Problem Solving (TRIZ by G.S. Altshuller).

The main idea of ​​morphological analysis is to streamline the process of putting forward and considering various options for solving a problem. The calculation is based on the fact that options that were not previously considered may come into view. The principle of morphological analysis is easily implemented using computer tools. Morphological analysis is based on the following sequential steps - an algorithm.

Figure 7.3.1 Algorithm for conducting morphological analysis

The principle of morphological analysis is rational for fairly simple systems - advertising, design, etc. For objects having large number elements and many options, the table becomes cumbersome and the method becomes labor-intensive. A table for analyzing options for pairwise combinations and selecting the optimal one is given below.

Table 7.3.1 Morphological analysis table

for pairwise combination of options

	Option 1	Option 2	Option 3	Option 4
Option 1
Option 2
Option 3
Option 4

The main advantages of morphological analysis are:

· equivalence of all elements of the analyzed object;

· maximum clarity in the formulation of the task;

· removing restrictions in the analysis of elements of the object under study;

· the opportunity to obtain new and/or develop existing ideas.

Basic schemes of morphological analysis:

A method for identifying the supporting elements of the system under study and working with combinations of solution options;

Method of negation and construction. This method of morphological analysis is based on the replacement of formulated ideas with opposite ones and the analysis of inconsistencies;

Morphological box method (most suitable for large and complex objects). Consists of determining all possible parameters for solving a problem, forming a matrix and analyzing various combinations before choosing the best option combinations.

Observation method

The observation method is one of the main methods of collecting primary information. Observation is a simple and widespread method due to its cheapness and availability. According to these characteristics, observation can perhaps only be overcome by the meeting method.

Observation- this is the receipt of information (collection and registration) in an open or hidden version about the process of behavior and about the properties of the object being studied.

The main tasks of surveillance, for example, in a trading organization, are:

Determining the frequency of visits

Determining the gender and age of clients

Determining the duration of the purchasing process, the product selection process, etc.

Assessing the effectiveness of the facility location and the possibility of approach routes to this point.

When conducting observation, special instruments are required. This could be: an observation diary, registration cards, an observation protocol, audiovisual recording aids.

The validity and reliability of observational data can be increased by following following rules:

· Record elements of observed events in as detailed a manner as possible, using clear criteria (indicators).

· The same object should be observed in different situations. For example, psychological and sociological observations of employees can be carried out in normal, stressful, standard and conflict situations.

· Control the accuracy of the description of actual events or their elements, without replacing them with emotional or desired ideas.

· It is preferable to carry out basic observations by several persons using a single technology in order to compare impressions, assessments, and interpretations.

Figure 7.4.1 Observation steps

Observations can be classified according to various signs: according to the degree of formalization, according to the position of observation, according to the conditions for organizing observation, according to the regularity of observation.

Table 7.4.1 Classification of types of observation

Classification feature (criterion)	Type of observation	Peculiarities
According to the degree of formalization	Controlled Observations	Organized according to a clear formalized plan and procedures. It is mandatory to have a developed list of signs of events, instructions for observers, and registration tools.
Uncontrolled observations (non-standardized, unstructured)	Observations are carried out only according to a general fundamental plan, the results are recorded in free form.
According to the observation position principle	Participant observations	Entry into the object’s environment, adaptation and collection of information “from the inside” is simulated. The researcher can work in both open and closed (incognito) modes.
Observations not included (simple)	Registration of events is carried out “from the outside”. In this case, it is advisable for the observer to be “invisible” in order to reduce the interference introduced during his study.
According to the conditions of organization of observation	Field observations	Observation is carried out in natural conditions.
Laboratory observations	The situation for observation is created experimentally, artificially.
According to the regularity of observation	Systematic observations	Regular fixation, usually on a specific schedule in accordance with the observation program.
Random observations (non-systematic)	Observations not included in the research program.

In conclusion, I would like to note that observation with a research, scientific purpose differs from ordinary observation, first of all, in that it is subject to a clear goal and objectives, and secondly, it is planned and carried out according to a special procedure.

system (sample, complex) to eliminate its inherent shortcomings. This goal predetermines the following action plan:

– identify the fundamental shortcomings of the existing system;

– establish the causes of these shortcomings;

– identify new types of system components that can eliminate its inherent shortcomings;

– determine the sequence of changes (transformation path or evolutionary trajectory) that will allow existing components of the system to evolve into qualitatively new ones.

It is easy to see that the method can be widely used in determining ways to modernize a sample. However, this approach does not guarantee success when searching for fundamentally new ideas and technical solutions, since the procedure is based on the analysis of a prototype, which, with its structures, somewhat limits the permissible area of ​​solutions. In principle, such a guarantee is provided by the morphological approach.

8.1. Morphological analysis

The term "morphology" is used in many sciences and refers to the study of the shape or structure of the object being studied.

The use of morphological analysis (and synthesis) in forecasting was borrowed from the Swiss astronomer F. Zwicky, who developed it in the 30s for the design of astronomical instruments. For the first time, very effective analysis was practically applied by F. Zwicky in an aviation company (1942, USA), where he short time received several dozen new technical solutions rocket engines and missiles, among which, as it turned out later, solutions were proposed that replicated the German V-1 and V-2 missiles.

The method of morphological analysis is based on combinatorics. Its essence lies in the idea of ​​obtaining a detailed description of all existing and possible (admissible) technical systems class under study with

subsequent search on this set for a description of the technical system that most fully corresponds to the goal. To do this, a group of main design or other features is identified in the product or object of interest. For each characteristic, alternative options are chosen, that is possible options its execution. By combining them you can get many various solutions, including those of practical interest.

For example, consider the morphology of the mechanical equipment of a wheeled crane installation. There are four main components: the engine, the drive axles, the supports (jacks) and the guide boom. A crane installation may have a varying number of these components. In Fig. Figure 8.1 shows a morphological description of the mechanical equipment of the crane installation. Historically, the number of engines (propulsion) varied between 0 and 2, drive axles - between 0 and 6, guides and supports (jacks) - between 0 and 4.

Engines
Drive axles
Guides
Supports (jacks)

Rice. 8.1. Morphological model of the mechanical equipment of a crane installation

It is possible to fully describe the mechanical equipment of a crane installation (with respect to the four components specified) by selecting one of the elements of each row (that is, selecting the number of axle motors, guides and supports). The figure shows a total of 3 7 8 5 5 = 525 possible

m i j .

combinations of mechanical equipment of the installation. Perhaps most of them were never actually implemented, but none of them are fundamentally unfeasible.

Thus, the algorithm for applying the method is as follows. The problem is divided into parts that can be considered independent, and for each part the maximum number of solutions or approaches is found.

At the first stage, the most important aspects characterizing the problem (object of study) are identified, which subsequently act as the basis for dividing Pi. Then, for each i -th aspect of the problem, they identify

possible solutions

Let’s say there can be n possible aspects of the problem, that is, i = 1, 2,...,n, and possible options for the development of the i-th aspect – k i, that is, j = 1, 2,...,k i.

The entire specified set of aspects of the problem and methods for solving it can be presented in the form of a system of matrices (in the form of a “morphological set”):

	(m11 ,m12 ,...,m1 k ) ;
						2k 2
................................
	(mn 1 ,mn 2 ,...,mnk n
or in the form of a “morphological box” (Table 8.1).
Table 8.1. Morphological box
Aspects of the problem							Solution options m i j
							m11 ,m12 ,...,m1 k 1
							m21 ,m22 ,...,m2 k
							..........................
							mn 1 ,mn 2 ,...,mnk n

If in each row of this matrix (box) we circle one of the elements m j and then connect all the circled elements, then the resulting

the chain of elements will represent one of the possible solutions to the problem. Some single solution to a problem can be represented by a system of elements

P1 m1 j 1 , P2 m2 j 2 , P3 m3 j 3 ,..., Pn mn jn .

The next step is to determine which of these solutions are actually feasible. It is necessary that all feasible solutions be examined before the best solution is selected. One consequence of this may be that the systematic study of all possible combinations of solutions to individual parts of the problem will lead to the identification of fundamentally new solutions to the entire problem as a whole.

After all unfeasible solutions have been discarded, the technical effectiveness of all remaining solutions is assessed and the most rational ones are selected.

It should be noted that both the elements (assemblies, parts) of the sample under consideration and their functions can be assigned as aspects of the problem. Then as alternative options different implementations of each function are assigned. The following can be used:

– own knowledge and results of a survey of specialists;

– reference books and encyclopedias;

– dictionaries of technical functions;

– international classifier of inventions and patent descriptions according to headings of interest;

– exhibition catalogs to search for technical solutions for elements that correspond to the level of the world's best samples.

The most difficult aspect of morphological analysis is the study of all solutions obtained from the point of view of their functional value and the selection of the most desirable ones concrete solutions and them

implementation. For this purpose, a rating scale is established, and the most general criteria can be used to evaluate solutions.

The method of morphological analysis is of interest for predicting the technical appearance of a promising sample.

8.2. Forecasting the technical appearance of a promising model

Search forecasting, carried out as part of the justification of the main directions of technology development, involves the analysis of objective development trends, determination possible ways creating a new model and getting an idea of ​​both the main technical and other quantitative characteristics, and the technical appearance of future systems.

The concept of the appearance of a technical system, or the technical appearance of a system, is relatively new, it appeared in connection with the rapidly developing theory of large technical systems and has not yet been sufficiently defined in practice.

Turning to the methodology of systems analysis, we can conclude: being a category of systemology, the concept of technical appearance should reflect not only the configuration of the sample, not only its structure, but also the relationships of the subsystems and elements that make up complex objects in the multitude of interrelated properties (characteristics) and functions inherent in them. Designed to describe hierarchical structures, this concept is also

x ξ ϕ ξ

Fig.8.2. Graph model of technical appearance

hierarchical in content and clarified as the specific system is detailed. The concept of appearance can be most fully reflected in the form of a graph model (Figure 8.2)

The vertices of the graph are: w ξ – technical appearance of the system; v ξ –

a set of subsystems and elements of the system; x ξ is a set of defining characteristics (parameters); ϕ ξ is a set of functions performed, where ξ is the hierarchy level.

v ξ ,x ξ ,ϕ ξ jointly determine the appearance of the system at the ξ -th level of its study

w ξ= U N (x ξ, ϕ ξ,v ξ) ,

where N is the number of hierarchy levels.

Thus, we can conclude that the technical appearance is a set of structural and parametric data reflecting the most significant technical solutions and features of the sample (complex, system), composition and method of combining its functionally related elements with each other.

Based on the above definition, predicting the technical appearance involves generating many alternatives to the possible structure of the sample, for which it is necessary to systematize, review and analyze the entire set of functional subsystems and units, hierarchically limited by certain structural characteristics and ways of defining them. Obviously, such a problem can be solved using the method of morphological analysis. The difficulty lies in the fact that with the introduction of new elements into the morphological matrix, the combinatorial process grows into geometric progression, since the formation of the morphology of the system assumes the equal importance of all cells of the morphological box.

The dimension of the problem can be significantly reduced (or streamlined) by giving each morphological cell some “weight” relative to the selected preference criterion.

Based on the fact that in a predictive system, at the stage of selecting a set of preferred alternatives for the technical appearance (TO) of a sample, such a criterion is usually specified in the form

K = f(α i ,ki ) , i= 1 ,n,

where k i are the components of the preference criterion;

α i – weight of the criterion component,∑ α i = 1,0 ≤ α i ​​≤ 1, each

i=1

an alternative appearance can be assigned a certain priority assessment (rank) according to the K indicator.

Since already when predicting the technical appearance of a promising model, the quality level of the future system is set, the selection of a set of preferable alternatives should be carried out according to components (single criteria) that would take into account the uncertainty factors existing at this stage of development. These factors include uncertainty in assessing the true requirements for a sample new technology(applicability assessment), technical uncertainty (prospectivity assessment) and technical and economic uncertainty (risk assessment).

Thus, the complex preference criterion must include:

– assessing the applicability of the option[P];

– assessment of the prospects of the option[Q];

– implementation risk assessment[R],

K = f(α 1 P,α 2 Q,α 3 R,) ,
	∑ α i= 1 .
	i=1

The applicability component P characterizes the ability of a system of a certain alternative appearance to expand the scope of tasks performed, the ability to flexibly respond to changes in the system of goals, the emergence of new types and types of subsystems, and so on.

The introduction of the promising component Q into the criterion is primarily due to the ambiguity of the structure of samples of new technology. The multivariance of the structure, in turn, is due to the many types of elements and their parameters.

The risk component R characterizes the specifics of forecast research as the formation of probabilistic estimates of the possibility of the appearance of certain elements of the system by a fixed point in time in the future. Since it is impossible to completely eliminate the factors of uncertainty in long-term development processes, it is necessary to determine for each alternative a measure of the reality of the occurrence of a particular event, which, in turn, forms a measure of the risk of implementation. These uncertainties are associated with an incomplete understanding of the available technical capabilities or the timing of implementation of system elements. Regarding the appearance alternatives generated in the predictive system, the methods for obtaining estimates P, Q and R will be different. This is due to the definition of alternative technical appearances in the form of hierarchical structures.

The formation of applicability assessments is carried out in the following sequence:

1. Particular indicators of applicability are formed

P = (P1 ,P2 ,P3 ,...,Pm ) .

IN the number of private indicators may include: the possibility of expanding the scope of tasks performed, the possibility of flexible response to changes in the system of goals, the possibility of using new types of subsystems, the possibility of changing application.

2. The “weight” of the particular applicability indicator α 1 j is determined:

0 ≤ α 1 j ≤ 1	∑ α 1j = 1 .
	j = 1

3. Scales for assessing private indicators are being developed.

4. An assessment of the applicability of the appearance alternative is formed. Grade

prospects Q ξ 0 (zero hierarchy indicator) can also be

determined relative to the appearance of the system as a whole. This assessment consists of intra-level assessments of the prospects of the subsystems included in the system. It is natural to assume that assessments of the prospects of system elements at levels close to elementary will have an insignificant impact on the overall assessment.

The formation of an assessment of prospects is carried out in the following sequence:

1. Particular indicators of prospects are formed:

Q = (Q1 ,Q2 ,Q3 ,...,Qϕ ) .

IN the number of private indicators of prospects may include: the degree of improvement of the technical level compared to the prototype, the degree of difference technical solution from a known solution, the degree of improvement of the main characteristics technical device, degree market-licensing significance of a technical device.

2. The “weight” of the particular indicator of prospects α 2 j is determined:

0 ≤ α 2 j ≤ 1;	∑ α 2j = 1 .
	j = 1

3. Scales for assessing private indicators are being developed.

4. Prospects assessments are being formed Q ξ N by levelsN

decompositions. Formation of assessments begins from the first level of the hierarchy.

At all subsequent levels, the assessment of prospects is carried out taking into account their relationships with elements of higher levels Q N = Q Q N N − 1 .

5. An assessment of the prospects of the sample alternative is formed, which can be expressed

				Q = ∑∑ Qq ξ α 2 j ,
				q = 1ξ = 1
	Q – the value of the partial indicator of the prospects of the element q on the ξ -th
hierarchy level;
	The risk assessment, just like the prospectivity assessment, is formed according to ξ -
levels of the hierarchy of appearance alternatives.
	The quantitative expression of the magnitude of risk (Fig. 8.3) can be
obtained by formula
				R ξ=
						t embedded
			– time interval that goes beyond the time T control. , to which
a system must be created and implemented (according to median estimates);
	t embedded – the full period of time for the creation and implementation of elements S i
alternatives to maintenance.
	The risk value R is determined for each level of the system hierarchy
differentiated by elements. Final risk assessment
alternatives are determined by the formula
				R = ∑∑ Rq ξ α 3 j
				q = 1ξ = 1
	Rq ξ			– the value of the risk indicator of element q at the ξ -level of the hierarchy;
				– the number of elements at the ξ-th level of the hierarchy.

	Development period and
development
	implementation t implementation
	Lead period	Implementation
	forecast
	technical appearance

T ext.

Rice. 8.3. Risk assessment

The formation of a risk assessment is carried out in the following sequence: 1. The risk indicator R q ξ is determined for each element of the alternative

at each level of the hierarchy.

2. An assessment of the prospects of an alternative to the technical appearance of the sample is formed.

After the characteristics P, Q and R are determined for each appearance alternative, the value of K is calculated.

Previously, each cell of the “morphological box” receives an estimate K ′ = P ξ R ξ corresponding to its “weight”. In this case, the combinatorics problem is combined with the network problem, which makes it possible to use the mathematical apparatus of network planning. The found critical zone of solutions will be a set of preferred alternatives of technical appearance, narrowing even more as the resulting variants of the predicted weapon system are tested for applicability.

The formulated problem is solved at all levels of the hierarchy of the system of means, that is, the morphological search at the level of subsystems is preceded by the compilation of a morphological box and the allocation of a critical zone to more low levels hierarchy - levels of aggregates and nodes. In this case, the critical zone is formed by sequentially eliminating elements lying on the critical path.

The initial basis for morphological analysis is an information array, which is a set of structural characteristics and the range of their changes within the limits of a possible system of means.

8.3. Other expert forecasting methods

As already noted, expert forecasting methods are used, as a rule, in cases where there are no statistical data on which a quantitative forecast could be based, as, for example, in the case when an enterprise is going to launch a completely new product on the market. But even when statistical information is available, there may be difficulties in using it for forecasting, for example, the original statistical information is often unreliable. However, even with reliable data about the past, they cannot always serve as a reliable basis for making planning decisions aimed at the future; some of the information necessary to select the best option for a planned decision is of a qualitative nature and cannot be measured quantitatively (for example, it is impossible to develop a formula for predicting (assessing) the behavior of people in a given situation, in a production team); at the time of decision-making, the necessary statistical information is not available, and obtaining it requires time or money; There is a large group of factors that will influence the implementation of plans, but when preparing planning decisions they cannot be accurately predicted.

Applying statistical forecasting methods requires research and the services of qualified statisticians, both of which can be expensive. In addition, in the conditions of dynamic development of society, when some fundamental changes occur - in the economy, in the social sphere, in technology, in technology and in other areas - the effectiveness of using statistical methods for forecasting and planning, especially for the long term

period is decreasing. There is also a danger that managers will become overly reliant on statistical methods and their results and may therefore miss significant changes that could be appreciated by someone else. In such conditions, the intuition of specialists, called experts, acquires a special role in predicting the future. Intuition is a person’s ability to make conclusions about the object under study and its future states unconsciously, that is, without awareness of the path of thought to these conclusions. Methods of analysis and generalization of judgments and assumptions with the help of experts are called expert, or methods of expert assessments. The essence of the expert assessment method is that experts carry out an intuitive-logical analysis of the problem with a quantitative assessment of judgments and formal processing of the results. The generalized opinion obtained as a result of processing is accepted as a solution to the problem (in this case, a forecast). The central stage of expert forecasting is conducting a survey of experts. Depending on the goals and objectives of the examination, the essence and complexity of the problem being analyzed; time allocated for the survey and examination in general; and their acceptable cost, as well as the selection of specialists participating in it, a survey method is selected:

− individual or group (collective); personal (full-time) or correspondence (by sending questionnaires);

− oral or

− written;

− open or

− hidden.

An individual survey allows you to make maximum use of the abilities and knowledge of each specialist. Unlike an individual survey, during a group survey, experts can exchange opinions, take into account what each of the few missed, and adjust their assessment. An exchange of views is usually a stimulating start to the nomination and

creative development of new ideas. At the same time, the disadvantages of such a survey are the strong influence of authorities on the opinions of the majority of participants in the examination, the difficulty of publicly renouncing one’s point of view, and a number of other factors of psychophysiological compatibility. From the above it is clear that individual survey methods place higher demands on the expert compared to a group survey, in which erroneous opinions

And judgments of individual experts can be “corrected” when deducing overall assessment the whole group. Among the methods of individual expert forecasting, one should highlight the interview method, analytical expert assessments (for example, in the form of a report), morphological analysis, etc., although some of them, for example, the method of generating ideas, expert assessments and others, can also be used in a collective version.

Let us present the characteristics of some expert forecasting methods.

1. The interview method involves a conversation between the organizer of forecasting activities and an expert forecaster about the future state of the enterprise and its environment. This method requires the expert to be able to quickly, almost impromptu, give quality advice on the questions posed. Several experts can be interviewed at the same time, but in this case there is a danger of losing the independence of the experts and, in addition, the interview threatens to turn into a discussion. The interview method is in essence (but not in form) very similar to the face-to-face survey method. Questioning consists of presenting the expert with a questionnaire, to which he must respond in writing (while interviewing involves an oral response from the expert to the interviewer). The survey may be

And in absentia, when there is no direct contact between the expert and the organizer of the forecasting activity.

2. Method of analytical memos(analytical expert assessments in the form of a report) assumes that the expert forecaster performs independently analytical work with assessment

state and ways of development, expressing their thoughts in writing. At the same time, to identify the importance of problems and solutions, the method of preference and the method of ranks are used. When using the preference method, the expert must number the possible options, methods, etc. in order of preference, putting 1 as the most important criterion, 2 as the least important, etc. When using the rank method, the expert is asked to arrange the options under consideration along a scale having a certain number divisions (for example, from 0 to 10). It is allowed to place options (methods) at intermediate points between divisions, as well as to correlate several options to one division of the scale.

3. Method of “brainstorming” (“brainstorming”).

This method is the most well-known and widely used method for collective idea generation and creative problem solving. It is a free, unstructured process of generating all kinds of ideas on a given problem, spontaneously proposed by participants. The forms of using the brainstorming method (“attack”) can be very different. Let's consider two of the possible options:

A). Regular meeting. At such a meeting, the manager, in turn, interviews each participant in the meeting and asks them to name problems that negatively affect the efficiency of the enterprise, structural unit, the effectiveness of a process, the state of working conditions, or any other aspect of the work performed by a common effort.

Each problem identified is listed and numbered. This list is then posted for everyone to see.

Criticism or evaluation of ideas is not permitted. Particular importance is placed on creating a free and creative environment that allows all employees (experts) to freely express their ideas and suggestions.

The number of proposals submitted or ideas expressed is also of great importance. Everyone should be involved in the process of submitting proposals and ideas. Particular attention is paid to proposals submitted

impromptu, since such proposals are often the most effective.

If the ideation process is not active, it is advisable to end the meeting and reschedule it for another day. This measure promotes the “maturation” of ideas.

B). Conducting a round-robin meeting. A group of specialists is divided into subgroups consisting of 3 or 4 people, each of whom writes down two or three ideas on a piece of paper or cards. Then, within the subgroup, cards are exchanged, the ideas written on them are developed by other participants and supplemented by new ones. After three exchanges, each subgroup compiles a consolidated list of ideas put forward. Then the whole group meets and reports on the work done in the subgroups are presented to all group members. Holding such a meeting allows you to increase the activity of everyone participating in it without verbal encouragement to express ideas from the facilitator. This form is advisable to use when activity decreases or when participants are distracted while waiting for their turn. In addition, it allows you to refine and improve the submitted proposals and generate new ideas.

Determining priorities when using brainstorming methods. The list of ideas put forward as a result of a brainstorming session is usually quite long (twenty or more ideas). In this regard, it is recommended to use the following method to determine priority tasks. The list of ideas is posted in plain sight. Each idea has a serial number. Each group member is entitled to five votes, which he can use as he wishes: one vote for each of the five ideas, all five for one idea, two votes for one idea and one for each of the other three, etc. This approach allows each group member to give preference to certain ideas. Number possible votes maybe

others - depending on the number of ideas put forward and the size of the group.

At the group meeting, each idea is read out under its own number. All group members vote by raising their hands. The number of outstretched fingers on a raised hand indicates the number of votes that a particular group member gives for a given idea. The secretary counts the number of votes and puts the total against the idea written in the list. After voting on all ideas, the secretary checks to see if the total number of votes matches the assigned number (for example, with six people participating with five votes each, the total number of votes would be 30). A second round of voting is then held, during which the ideas with the fewest votes are considered. What constitutes the smallest number of votes is determined by the group by consensus when considering the allocated votes. For example, a group decides that only ideas with three or more votes will be considered for a second round of voting. This approach allows votes cast for other ideas (for example, for which one or two votes were cast) to be redistributed. To establish clear priorities, the process is repeated as many times as necessary. A final check is then conducted to determine the consensus on the idea (particular forecast) that has the highest priority. After defining priority task the group moves on to consider the remaining proposals.

4. Reverse brainstorming method. Reverse Brainstorming is much like a regular brainstorming session, but allows for criticism. Or rather, it’s not so much that it’s even allowed, but that the whole method is built on ensuring that all group members identify the shortcomings of the proposed ideas. Such meetings must be held very responsibly so that the participants in the discussion behave correctly towards each other. Reverse brainstorming method

can produce good results if used as a preliminary step before other methods of stimulating creativity. Typically, during a reverse brainstorming session, participants must not only find everything weak points each idea, but also suggest ways to eliminate them.

5. Mental Group Analysis Method real situation». This method is used when the group size is large enough (about 20 people), when the question concerns an entire situation (process) that can be quantified based on intuition or common sense, and when group discussion or interaction is required. The following stages are typical for such an analysis.

Mental group analysis of a real situation. Draw a vertical axis, scale it from 0 to 100 at intervals of 10 units. Invite team members to quantify the projected “quality level” of the work, process, or nature of the situation. Plot each score to create a scatterplot. Define average rating and draw a horizontal line emanating from a point on the vertical axis corresponding to this assessment, write the wording of the question under consideration at the right edge of this line. Draw arrows “pushing” the horizontal line up (driving forces) and arrows “pushing” the horizontal line down (restraining forces). Then, using the round robin method of making anonymous proposals described above, invite group members to identify the restraining and driving forces. The opinions expressed are recorded. In subsequent meetings, group members identify priorities regarding constraining forces, which are then considered as problems to be solved. In addition, measures can be taken to strengthen the driving forces.

6. Scenario Method– the most popular method of expert assessments over the past decades. The term "script" was first used

used in 1960 by futurologist X. Kahn when developing pictures of the future necessary to solve strategic issues in the military field.

A scenario is a description (picture) of the future, compiled taking into account plausible assumptions. Forecasting a situation is usually characterized by the existence of a certain number of probable development options. Therefore, the forecast usually includes several scenarios. In most cases, these are three scenarios: optimistic, pessimistic and average - the most likely, expected. Drawing up a script, as a rule, includes several stages:

1) structuring and formulation of the question. The issue chosen for analysis should be defined as precisely as possible.

At this stage, basic information should be collected and analyzed. The assigned task must be agreed upon by all project participants. It is necessary to highlight the structural characteristics and internal problems of the project;

2) definition and grouping of spheres of influence. To implement this stage, it is necessary to critically highlight the business environment and assess their impact on the future of the enterprise;

3) establishing indicators for the future development of critical environmental factors of the enterprise. After the main spheres of influence have been identified, it is necessary to determine their possible state in the future, based on the goals set by the enterprise. Indicators of the future state should not be overly prosperous or ambitious. For areas where development may include several options, the future state should be described using several alternative indicators (for example, the enterprise wants the population to increase by 2.3 or

4) generating and selecting consistent sets of assumptions. If at the previous stage the enterprise determined the future state of the environment and its impact on the enterprise based on its own goals, then at this stage

the possible development of spheres of influence is determined based on their current state and all possible changes. At the same time, various alternative assumptions about the future state of the most significant components of the environment are combined into sets. The generation of sets of assumptions is usually carried out using computer programs. As a rule, three sets are selected from the received sets. The selection is carried out based on the following criteria: high compatibility of assumptions included in the set: the presence of a large number of significant variables, high probability events related to a set of assumptions;

5) comparison of planned indicators of the future state of spheres of influence with assumptions about their development. At this stage, the results of the third and fourth stages are compared. Increased or decreased indicators of the state of the environment are corrected using data obtained at the fourth stage. For example, if at the third stage an enterprise predicted an increase in the birth rate in the region in 2003 by 3%, and analysis at the fourth stage showed that there would be a deterioration in the economic situation, the environmental situation, and political and social conflicts were possible, then at the fifth stage the figure should be 3%. changed downward, for example, to 1%. For a more accurate forecast, it is necessary to reduce the interval between today and the final forecast time. For example, if a forecast is compiled in 1999 for 2004, then the forecasting period should be divided into two stages of three years: first develop a scenario for 2001, and only then until 2004;

6) An introduction to the analysis of disruptive events. Destructive event

– it is a sudden incident that was not previously predicted and that can change the direction of the trend. Disruptive events can have both negative character(floods, earthquakes, accidents nuclear reactors etc.) and positive (technological explosions, political reconciliation between former opponents, etc.).

Of the possible destructive events, it is necessary to identify those that are capable of having the greatest impact and take them into account when drawing up scenarios. Let us continue our consideration of the above example: the state of the birth rate in the region can be affected by: firstly, an accident in nuclear power plant; secondly, the likelihood of local conflict; thirdly, the discovery of a new deposit. However, only the first of the events can have a real impact;

7) establishing consequences. At this stage, the strategic problems of the enterprise (for example, the possibility of growth through wider market development) and the selected options for environmental development are compared. The nature and degree of impact of certain development options on the strategic areas of the enterprise’s actions is determined;

8) taking action. In a narrow sense, this stage no longer refers to analysis, but it naturally follows from the previous stages. Scenarios are developed to define the framework for future development: market segments; technologies; countries or regions, etc.

In general, the scenario is subordinated to the strategic function of the enterprise and is developed in the process long-term planning. A wide time frame implies increased uncertainty in the business environment, and therefore the scenario is typically characterized by some uncertainty and increased amount errors. Since determining the quantitative parameters of the future is difficult (for example, it is difficult to determine the amount of sales of an enterprise in 5 years), when drawing up scenarios, qualitative methods and interval forecasts of indicators are most often used. At the same time, the scenario assumes integrated approach for its development: in addition to qualitative methods, quantitative methods can also be used - economic-mathematical, modeling, cross-influence analysis, correlation analysis, etc.

7. Goal tree method– widely used to predict possible directions for the development of science, technology, and technology. The so-called

The goal tree closely links long-term goals and specific tasks at each level of the hierarchy. In this case, a higher-order goal corresponds to the top of the tree, and below, in several tiers, local goals (tasks) are located, with the help of which the goals are achieved top level. An assessment of the relative importance of goals and the significance of the connections between them is carried out with the help of experts, and to consistently determine the significance of goals and objectives at various levels, evaluation matrices are usually used (dividing goals into subgoals and tasks): I-V - levels of the system; 1-39 – system elements. The assessment of relationship coefficients using these matrices is carried out, for example, as follows: 10 points evaluate the influence of one factor on another, without which it is impossible to solve the problem. The influence without which the solution of the problem will be difficult to a strong, medium and weak degree, respectively, is estimated at 9.8 and 7 points. Scores of 6.5 and 4 points are assigned in cases where the influence of one factor can, to one degree or another (strong, medium, weak), accelerate the development of another factor or the solution of a problem. The minimum level of influence of one factor on another is assessed as 1 point.

8. Matrix method– widely used in planning and forecasting. For example, in marketing practice, the matrix method is used as a method for assessing the position of an enterprise in the market, which allows one to decide on the choice of one of the possible strategies: an attack strategy with a favorable position (C1); defense strategies for an average, uncertain position (C2); Retreat strategies in case of an unfavorable position (SZ).

This is the so-called strategic matrix, formed by the intersection of coordinates that reflect the magnitude of two factors, usually characterizing the market situation (A) and the enterprise’s own capabilities (competitiveness) (B).

Algorithm for strategic marketing matrix. Decisions about market behavior (C) are made based on which field (quadrant)

matrix formed by a combination of factors, according to its parameters this enterprise falls. The minimum number of quadrants should be four, although in principle the matrix can contain any number of quadrants. The optimal number is considered to be 9-16, since otherwise the results are difficult to interpret. Quantitative assessments of factors (strategic indices) are determined by experts (in points) depending on the magnitude and strength of the factor. However, for the sake of simplicity quantitative estimates can be replaced with equivalent qualitative ones, for example: good, high (rank 1), bad, weak (rank 2). The position of an enterprise in marketing dictates one of the strategies: attack strategy (C1), when the enterprise takes a strong position; defense strategy (C2), when the position is assessed as average; a retreat strategy (RS), when the position is clearly unfavorable, weak. The RN, PC and PB indices indicate the level of commercial risk - low, medium and high, respectively. Application details matrix method forecasting in marketing practice (in combination with statistical methods).

9. The Delphi method is the most formal of all expert forecasting methods and is most often used in technological forecasting, the data of which are then used in planning production and sales of products. This group method, in which a group of experts is individually surveyed regarding their beliefs about future developments in various areas where new discoveries or improvements are expected. The survey is conducted anonymously using special questionnaires, that is, personal contacts of experts and collective discussions are excluded. The responses received are collated by special workers, and the summarized results are again sent to group members. Based on such information, group members, still remaining anonymous, make further assumptions about the future, a process that can be repeated several times (the so-called multi-round survey procedure). Once a convergence of opinions begins to appear,

the results are used as a forecast. The use of the Delphi method can be illustrated by the following example: an offshore oil company wants to know when it will be possible to use robots instead of divers to inspect platforms underwater. To begin forecasting using this method, a company must contact a number of experts. These experts should be representatives of the most different areas industry, including divers, oil company engineers, ship captains, maintenance engineers and robot designers. They explain the challenge facing the company, and each expert is asked when, in his opinion, it will be possible to replace divers with robots. The first answers will probably give a very large spread of data, for example, from 2000 to 2050. These responses are processed and returned by experts. In this case, each expert is asked to reconsider his assessment in the light of the responses of other experts. After repeating this procedure several times, the opinions may converge, so that about 80% of the answers will give a period from 2005 to 2015, which will be sufficient for the purposes of planning the production and implementation of robots. The Delphi method is named after the Delphic oracle in Ancient Greece. It was developed by Olaf Helmer, a prominent mathematician from the RAND Corporation, and his colleagues and, probably for this reason, compared to others creative approaches, gives sufficient forecast accuracy. The classification of forecasting methods discussed above, as well as the classification of the forecasts themselves, is not absolutely indisputable; there are other approaches to solving this issue. The success of using each method depends on its suitability for a specific situation, the purpose of forecasting, the forecast horizon, initial data, the qualifications of the forecaster, etc. Thus, when forecasting demand and supply, the following forecasting methods and techniques are used most often: analogue models, when favorable conditions are considered as a forecast indicators of the market situation in any

region or country; simulation models, when instead of real data, constructions created using a special program using a computer are used; normative, or rationalized, forecast calculations, for example, arising from a rational budget or rational recommended consumption standards (this method is more suitable for the market for means of production, where production and technical standards and other determinants play a large role, than for the consumer market, where needs are manifested in form of statistical patterns); forecasting based on expert estimates (usually the Delphi method); extrapolation methods: technical, mechanical methods of smoothing time series, trend models; statistical modeling methods (paired and multivariate regression equations); forecasting using elasticity coefficients.

When forecasting sales based on demand forecasts, statistical and expert forecasting methods are used, as already noted. Among the latter, along with those discussed above, one can also highlight their widely used varieties: the method of obtaining jury opinions, the method of aggregate opinions of sales employees, the method of expected consumer requests, deductive methods, brief description which are given below.

10. Method of obtaining jury opinions - the oldest and simplest method of sales forecasting, since in this case views are simply combined and averaged, often based only on the intuition of senior administrators. In most cases, the final assessment is the opinion of the firm's president, based on consideration of the opinions of other management personnel. The advantages of the method are its accessibility and simplicity, the disadvantages are that the forecasts are based on assumptions, and not on facts and their analysis; averaging opinions reduces responsibility for the accuracy of the forecast; forecasts are usually not

divided into subsections (by product type), time periods or structural divisions.

The jury opinion method is also used in other areas of the enterprise.

11. Method of aggregate opinions of sales employees– one of the most commonly used forecasting methods. It consists in the fact that, based on the opinions of sales agents and heads of sales departments, a cumulative assessment of the likely sales volume is compiled. The method is based on the belief that those who directly deal with sales know the market best, and they also have to implement their forecasts (at least at first). This method allows you to drill down forecasts into sections depending on the type of product, customer or territory. It often turns out that forecasts obtained using the aggregate opinion method of sales employees are confirmed by forecasts compiled using other methods. The amazing reliability of this method is confirmed by the constant comparison by sales workers of the forecasts they made in the past with actual results.

A significant disadvantage of the method is the inability of sales agents,

A often their managers make reliable forecasts for any period other than the near future, since they tend to take into account primarily the conditions existing at the present time.

12. Method of expected consumer requests(consumer expectation model). As the name suggests, a customer expectation model is a forecast based on the results of a survey of a business's customers. They are asked to evaluate their own needs in the future, as well as new requirements. By collecting all the data obtained in this way and making adjustments for overestimation or underestimation based on his own experience, the manager is often able to accurately predict aggregate demand. This method is certainly difficult to apply when the number of consumers is significant, their

difficult to identify or they are not willing to cooperate. Moreover, a needs assessment does not necessarily create a commitment.

13. Deductive methods. Every forecaster must remember to always use sound judgment and be able to draw logical conclusions from facts and relationships. IN general case it comes down to finding out what the current situation is, what the sales situation is and why, and then deductively analyzing, based on both objective circumstances and subjective judgments, the factors that have a decisive influence on sales. The data obtained in this way can be entered into a mathematical model, but may remain unused if it represents an imprecisely correlated conglomerate of facts and estimates. However, they often serve useful tool checking the results obtained using precise methods.

Combination of methods. In practice, there is a tendency to combine different sales forecasting methods. Since the final forecast plays very important role for all aspects of intra-company planning, it is desirable to create a forecasting system in which any input factor can be used. An example of a combination of various methods when forecasting sales is the “Product – Market” matrix.

Drawing up a sales forecast begins with an analysis of sales of existing goods or services and existing consumers over a number of years (sales forecast A). In doing so, it is necessary to answer the following questions.

What was the volume of sales of products (goods/services) at your enterprise over the past 3-5 years and last year? Will consumers continue to purchase your products (goods/services)? Will you be able to count on the same sales volume in the future as in the previous period?

Forecast A is very important, since most likely it is basic and will be more accurate, because it is based on verified information from past years. If

expand the use of expert forecasting methods - first of all, it is necessary to rely on the opinion of your agents (method of aggregate opinions of sales workers), conduct surveys of direct consumers (method of expected consumer requests), and also attract experts in this field “from the outside.” Developing a sales forecast (estimating the expected sales volumes of new goods or services in new markets) is the most difficult, and this method of enterprise development is the most risky. The methods used to forecast sales will likely be similar to those used in developing the previous forecast. When drawing up any of the considered sales forecast options, one should not forget about competitors. It is also necessary to keep in mind that calculating sales volumes is never easy; the accuracy of forecasts cannot be absolute, but they must be carried out, since the accuracy of the profit (loss) forecasts of the enterprise will depend on this. Below are some tips to make your forecasts useful. How to make business forecasts useful. Forecasts are useful for planning and executing business operations only if the components of the forecast are carefully thought out and the limitations contained in the forecast are frankly stated. There are several ways to do this:

1. Ask yourself why the forecast is needed and what decisions will be based on it. This determines the required forecast accuracy. Some decisions are dangerous to make, even if the possible forecast error is less than 10%. Other decisions can be made without fear even with a much higher margin of error.

Determine the changes that must occur for the forecast to be reliable. Then carefully assess the likelihood of relevant events. Identify the components of the forecast. Think about data sources.

2. Determine how valuable past experience is in making a forecast. Is the change so rapid that a forecast based on experience will

enterprise, and primarily for marketing purposes, it is necessary to ensure the implementation of the forecasting function.

14 9. Methods for identifying the “seasonal” component in time series

The levels of a number of dynamics are formed under the influence of the interaction of many factors, some of which, being basic, determine the pattern, the trend of development, others, random, cause fluctuations in levels.

As previously noted, the dynamics of the series includes three components:

− long-term movement (the so-called trend);

− short-term systematic movement (for example, seasonal fluctuations);

− unsystematic random movement that causes fluctuations in relative trend levels.

By studying time series, researchers try to separate these components and identify the main pattern of development of the phenomenon in individual periods, that is, to identify a general trend in changes in the levels of the series, freed from the influence of random factors. For this purpose (to eliminate fluctuations caused by random causes), the dynamics series are processed.

There are several methods for processing time series that help to identify the main trend in changes in the level of the series, namely: the method of strengthening intervals, the moving average method and analytical leveling. In all methods, instead of actual levels when processing a series, other (calculated) levels are calculated, in which the effect of random factors is cancelled, in one way or another, and thereby the fluctuation of levels is reduced. As a result, the latter become, as it were, “aligned”, “smoothed out” in relation to the original actual data. Such methods of processing series are called smoothing, or

alignment, rows of dynamics.

Morphological analysis

Brainstorming method

The brainstorming method consists of a collective attack on a problem that has arisen in order to select the most successful proposed idea. This method, also known as ʼʼ brainstormingʼʼ, ʼʼconference of ideasʼʼ, was proposed by the American scientist Alex Osborne in 1955.

The brainstorming method is based on the following principles:

1. Two groups of people participate in solving the problem: idea generators and experts. Idea generators connect people with creative thinking, with imagination and knowledge in the field of science, technology and economics. Experts are usually people with a large amount of knowledge and a critical mind. Experts play the role of analysts.

2. There are no restrictions on years when generating. Any ideas can be expressed, incl. obviously erroneous, humorous, without any evidence or feasibility study.

The ideas expressed are usually recorded in a protocol, on a computer, on magnetic tape, etc. (ᴛ.ᴇ. recorded), and then analyzed by experts who select the most rational ideas. However, the basis of the method is the separation of the process of integrating ideas from the process of their evaluation. The generation of ideas is carried out in conditions where criticism is prohibited and even, on the contrary, any obviously ridiculous idea is encouraged.

The full power of brainstorming manifests itself in the ban on criticism. But the ban on criticism is also a weakness of brainstorming. To develop an idea, you need to identify its shortcomings. And for this we need criticism of this idea.

When solving problems, the number of people, both generators and experts, usually does not exceed six people, and the duration of the assault is no more than 20 minutes.

There is also a “reverse assault”. Reverse storming means that stormers look for shortcomings in a new product or operation, eliminate these shortcomings, and come up with new problems.

The method of morphological analysis was proposed by the Swiss astronomer F. Zwicky in 1942. The term morphological (Greek morphз - form) means appearance. The purpose of using the method of morphological analysis is a systematic study of all conceivable options for solving a problem, which makes it possible to cover all unexpected and unusual issues with research.

The method of morphological analysis is at the same time a method of psychological activation of the creative process. His dignity is that it helps overcome the difficulties of considering a significant number of combinations of possible solutions.

Essence The method of morphological analysis consists in combining into a single system of methods for identifying, designating, counting and classifying all selected options for any innovation. Morphological analysis is carried out according to the following scheme, consisting of six successive stages:

Stage 1: problem formulation;

Stage 2: problem statement;

Stage 3: compiling a list of all the characteristics of the examined (alleged) product or operation.

Stage 4: compiling a list of possible solutions for each characteristic. This list consists of a table called a “morphological box” - a multidimensional table.

Stage 5: analysis of combinations.

Stage 6: choosing the best combination.

The choice is usually made by searching through all options without exception. Consequently, this is quite labor-intensive work (this is its flaw) .

Morphological analysis - concept and types. Classification and features of the category "Morphological analysis" 2017, 2018.

- A10 Morphological analysis of the word

The task tests the ability to recognize words as parts of speech in context, especially pronouns, adverbs, participles, and particles. We remind you that a part of speech is determined by its grammatical meaning, question, grammatical features, typical suffixes, and syntactic role. So, uh... .

- Morphological analysis of the organism.

Introduction to morphology Lecture 1 Introduction. Saratov 2011 Unproductive livestock farming Production of livestock products by industry Animal science Part I Short course... .

- Morphological analysis

The morphological approach in a systematic form was first developed and applied by the Swiss astronomer F. Zwicky and for a long time was known as the Zwicky method. Currently, the most widely used method is the “morphological box” or as it is called now...

The main task of the research is to find a solution to the problem that either eliminates the existing obstacle to development or establishes a fact normal functioning. But the solution obtained as a result of the study may be different. It may take the form of some kind of act, or it may be an entire concept of activity for the near future.

In describing the method of morphological analysis, we will proceed from the understanding that the immediate result research work is effective solution problems. Then the research can be reduced to the analysis of solution options for a certain set of their parameters. This characterizes the morphological research method.

This method can be implemented by drawing up so-called morphological maps, which contain, on the one hand, a list of necessary parameters reflecting the intended and expected result, and on the other, decision options among which a choice must be made in order to achieve the result.

Such parameters may be, for example, timeliness of execution, uniformity of workload, innovativeness of activities, quality of work. These are all control parameters. Their implementation depends on factors such as control of execution, clarity of orders, load accounting, load standards, information support, work planning, personnel distribution, personnel training, performance motivation, quality criteria, quality motivation, etc. All these factors determine possible solutions. But decisions can be key and secondary, intermediate and final. The choice and justification of decisions is what a morphological map allows you to make. The decision must combine all these factors and reflect a set of actions that can change the situation.

The morphological analysis method (sometimes called the morphological box method) is a combination of a classification method and a generalization method. Its essence lies in decomposing the problem into its constituent elements, searching in this scheme for the most promising element of its solution relative to the entire problem.

However, morphological analysis does not involve simple decomposition, i.e. decomposition of the whole into its constituent parts, but the selection of elements according to the principles of functional significance and role, i.e. the influence of an element or subproblem on the overall problem, as well as direct or indirect connection with external environment(sometimes called a supersystem).

Let's take the problem of distribution of functions as an example. The manager noticed that in management processes there are very often delays in making decisions, preparing documents or responding to orders (resolutions). Many explain this situation by the unsuccessful distribution of functions and powers between departments and uneven workload.

You can correct the situation based on these reasonable explanations, but the manager must understand that the reason may be deeper and include many factors in the effective performance of staff. It is necessary to solve the problem comprehensively, based on a deep and comprehensive analysis of the existing state of affairs. To do this, it is necessary to conduct a morphological analysis of the problem of distribution of functions.

So, the starting position of morphological analysis is the formulation of the problem. Next, its decomposition is carried out, i.e. division into components. As an example, we can name problems of the structure of the management system, personnel professionalism, motivation of activities, labor intensity of the function, load accounting, etc.

But the decomposition of problems must be done not only “downwards”, but also “upwards”. After all, the distribution of functions depends not only on the internal state of the control system, but also on external factors its functioning: competition, economic situation, market for specialists, training system, government regulation etc.

In this way, a morphological diagram of problems is constructed, and on its basis, an analysis of each of the problems is carried out in order to find the main one and connect it with others. When analyzing problems, you can use other research methods, such as brainstorming, synectics, etc.

The limit to the development of a morphological scheme up and down is the possible transition to another class of problems, which will make this scheme infinite.

In order for the morphological scheme to be constructed correctly, a number of operators should be used, through which one can check whether a problem belongs to one or another hierarchical level or move from one level to another when decomposing problems. These operators exist in the form of key questions, the answer to which makes it possible to transfer the problem to a new stage of the morphological scheme.

Any problem can be formulated in the form of an initial action. For example, change the distribution of functions. This is the original problem (IP).

The first operator of morphological analysis: why is it needed? Target settings (TS): create an innovative climate, increase the professionalism of activities, ensure the rhythm of work.

The second operator of morphological analysis: how can this be done? Problem solving mechanism (MP): issue a general order, change the leadership structure (redistribute personnel), use computer programs, change the structure of the management system, train personnel.

It is important to include in the morphological analysis and decomposition of the causes of problems, and to differentiate the causes into external and internal. Question: why did the problem (VP) arise? In our example, this could be a change in the structure of information, development goals, management style, the emergence of negative traditions, irrational use of management techniques, and a decrease in professional level. External reasons may consist of socio-psychological overloads of urbanized life, shortages or high cost computer equipment, general change mentality.

Morphological analysis helps to better understand the content of the problem and not only find its solution, but also choose the most successful one, taking into account the means and methods, causes and consequences.

A variation of morphological analysis is another research method - the “bouquet of problems” method. It is based on the search for a formulation of the problem that is more conducive to finding its solution.

The fact is that the solution to any problem largely depends on how it is posed, how questions are formulated that reflect the essence of this problem. The correct formulation of a question always reflects knowledge of the way to solve it. This is what the “bouquet of problems” method is built on. The technology for using this method includes several stages (Fig. 2.13).

• 1. Statement of the problem as it is presented in real management practice. For example, how to use a computer in a manager's activities?
• 2. Generalization of the problem, presenting it in general form. Many formulas and levels of generalization can be used here. In our example, it is to increase the productivity of management activities, ensure the professionalism of management, raise the authority of the manager, etc. Generalization allows us to determine the class of the problem, its origins, and the main thing in choosing its solution.

Rice. 2.13. Technology of using the morphological analysis method (the “bouquet of problems” method)

• 3. Definition of an analogue problem. These actions consist of searching for similar problems in other areas of activity or natural areas. Based on the problem we posed above (how to use a computer in a manager’s activities), we can formulate an analogue as follows: “grow a second head”, “increase the speed of thought”, “ensure survival”, etc. This sounds paradoxical, but in research there is no need to be afraid of paradoxes. They can suggest successful solutions, convince of the need to solve the problem, show its importance, they determine the attitude towards the problem, and allow you to see the original problem from a new perspective.
• 4. Establishing the role and principles of interaction of the problem in a complex of other problems. Maybe you can solve the problem not by itself, but by solving another problem, i.e. the solution to the original problem will be a consequence of the solution to another problem. For example, in our example, this could be replacing a manager with another person who owns a computer, changing the distribution of functions and powers in the management system so that the manager does not need individual computer ownership, creating the position of a personal assistant to a manager who owns computer equipment, developing extremely simple computer programs etc.
• 5. Formulation of the inverse problem. This can be very useful, because such a problem can suggest a solution and lead the researcher to a successful option. Let's consider our option. Computerization of a manager’s activities reduces the effect of the human factor of management, and this negatively affects the effectiveness of management at any level of its technical equipment. This formulation of the inverse problem allows us to see the danger of unsuccessful decisions and establish criteria for selecting successful decisions.

Why do you think there are so many interesting and outlandish things in Artemy Lebedev’s store? I think, also because the company has a competent generation and selection of ideas. The solution method presented in the article inventive problems will help you come up with and select a great variety of interesting solutions, incl. and grocery, for your business.

Application "Morphological Box" method about which we'll talk, is most rational for simple objects and where it is possible to find a new idea through a combination of known solutions. Examples of tasks:

• Develop a unique design for a barbecue, bookshelf, or doghouse.
• Analyze devices for hair removal on the human body.
• Find a girl with “blue eyes and splayed eyebrows, and a snub nose” if you saw her only once on an oncoming escalator in the subway during rush hours :).

Author of the method. Fritz Zwicky (Zwicky, Fritz) (1898-1974), Swiss astronomer and physicist. Worked at the California Institute of Technology (Pasadena, USA). Zwicky was chief scientific consultant to Aerojet General Corporation (Azusa, California). He owns 50 patents, mostly in the field of rocketry; Zwicky invented a number of jet and hydroturbine jet engines.

The essence of the method is to construct a matrix (table, box), where all the constituent elements of the research object are listed and all possible options for implementing these elements are indicated. By varying all known options for implementing object elements, you can get the most unexpected new solutions. Manipulation - sister creativity!

Stages of the morphological box method (according to Zwicky's recommendations)

1. 1. Precisely formulate the problem to be solved. Look at what objects of similar purpose are known and what such objects could be. Research the problem. The main recommendation at this stage is the most precise formulation of the goal of the morphological study, removing the emphasis on directiveness, and possible reformulation or clarification of the goal. An example of a simple object: a business card (more precisely: a bright, unique dentist business card that is difficult to forget).
2. 2. Identify and characterize all the parameters that could be included in solving a given problem. When analyzing tasks “per device”, a parameter should be understood as a functional unit of this device; when analyzing tasks “per method” - an operation that achieves a particular target function. The main recommendation is that all parameters should be approximately equivalent from the point of view of the goal. An example of object parameters: shape, cover of a business card.
3. 3. Construct a morphological box or multidimensional matrix containing all solutions to a given problem. The main recommendation is that no assessments of options should be carried out until the morphological set is fully formed. An example of object parameters: business card shape (ball, Moebius strip, rectangle, etc.), coating (plastic, cardboard, sausage, etc.).
4. 4. All solutions contained in the morphological box are carefully analyzed and evaluated in terms of the goals to be achieved. The main recommendation is to check for each row of the morphological table whether the particular implementations of the parameter are alternative and whether the “absent” option is meaningful. Examples of solutions: round edible, rectangular made of plastic, etc.
5. 5. Select and implement the best solutions (subject to the availability of the necessary funds). Example solutions: