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 effectively, the analysis was practically applied by F. Zwicky in an aviation company (1942, USA), where in a short time he received several dozen new technical solutions for rocket engines and rockets, among which, as it turned out later, solutions were proposed that repeated the German ones V-1, V-2 missiles.

The method of morphological analysis is based on combinatorics. Its essence lies in the idea of receiving detailed description all existing and possible (admissible) technical systems of the 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 different 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)
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 these four components) 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
			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. Different implementations of each function are then assigned as alternatives. 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 by categories 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 obtained solutions from the point of view of their functional value and the selection of the most desirable specific solutions and their

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 analyzing objective development trends, identifying possible ways to create a new model and obtaining 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 Methodology system 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 methods 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 exponentially, since the formation of the morphology of the system assumes the same 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 level of quality 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 on the market. at this stage 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,) ,
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 process uncertainty factors are completely eliminated promising development impossible, 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 between the technical solution and the known solution, the degree of improvement of the main characteristics of the technical device, the 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=
			R ξ=
				t embedded
				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	Development period and
	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 preferable alternatives of technical appearance, which will become even narrower 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 identification of a critical zone at lower levels of the hierarchy - the levels of aggregates and nodes. 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 needed to make a choice the best option planning decision, is of a qualitative nature and cannot be measured quantitatively (for example, it is impossible to develop a formula for predicting (evaluating) 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; exists large group 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 a 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 strong influence authorities on the opinions of the majority of examination participants, on the difficulties of publicly renouncing one’s point of view and on 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 the judgments of individual experts can be “corrected” when deriving an overall assessment by the entire 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, virtually 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 memorandum) assumes that the expert forecaster independently performs analytical work with an 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 famous 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 to name problems that negatively affect the efficiency of the enterprise, structural unit, process effectiveness, working conditions, or any other aspect of the work performed by common efforts.

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. Special attention given 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 for everyone to see. 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. The number of possible votes can be

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). Then a second round of voting takes place, 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 (specific forecast) that has the highest priority. After determining the 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 give good results if used as a preliminary step before using other stimulation methods creative activity. Typically, during a “reverse brainstorming”, participants must not only find all the weak points of each idea, but also suggest ways to eliminate them.

5. The method of “mental group analysis of a real situation.”This method is used when there is sufficient large composition groups (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. Determine the average estimate and carry out horizontal line, starting from the 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 impersonal 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– most popular for last decades method of expert assessments. The term "script" was first used

used in 1960 by futurist X. Kahn when developing pictures of the future necessary for solving 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 is satisfied that the population will 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: availability large number significant variables, high probability of 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 can have 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 are compared (for example, the possibility of growth due to wider market development) and the selected options for the development of the environment. 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; technology; countries or regions, etc.

In general, the scenario is subordinated to the strategic function of the enterprise and is developed in the process of long-term planning. A wide time frame implies increased uncertainty in the business environment, and therefore the scenario tends to have some uncertainty and an increased number of 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 an integrated approach to its development: in addition to qualitative methods, quantitative methods can also be used - economic-mathematical, modeling, cross-impact analysis, correlation analysis, etc.

7. Goal tree method– widely used for forecasting possible directions development of science, technology, 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 achievement of the top-level goals is ensured. 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 the coefficients of relationships 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 assessments can be replaced by 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. Learn more about the use of the matrix forecasting method 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 is a 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 interview procedure). Once a convergence of opinions begins to appear,

the results are used as a forecast. The application of the Delphi method can be illustrated in following example: An offshore oil company wants to know when it might 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 come from a variety of backgrounds within the 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 wide range 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 at the RAND Corporation, and his colleagues and is probably why, compared to other creative approaches, it provides 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, we 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, a brief description of which is 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, 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 provide a useful means of verifying 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 a very important role in all aspects of internal planning, it is desirable to create a forecast 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 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 forecasts of profit (loss) 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 constraints 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 certain periods, that is, to identify general trend in changing the levels of series, freed from the action 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.

In the description morphological analysis method we will proceed from the understanding that the immediate result research work is an effective solution to the problem.

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.

It 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 hand, decision options among which a choice must be made in order to achieve the result.

For example, such parameters may be timeliness of execution, uniformity of workload, innovativeness of activities, and quality of work. These are all control parameters. What factors determine their achievement or implementation? Execution control, clarity of orders, workload accounting, workload standards, information support, work planning, personnel distribution, personnel training, execution motivation, quality criteria, quality motivation, etc. All these factors determine possible solutions. But decisions can be key and secondary, intermediate and final. A morphological map allows you to make a choice and justify decisions. The decision must combine all these factors and reflect a set of actions that can change the situation.

The combination of the classification method and the generalization method gives morphological analysis method.

It is built on decomposing the problem into its constituent elements, searching in this scheme for the most promising element of its solution relative to the entire problem.

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 general problem, as well as direct or indirect connection with external environment(sometimes called a supersystem).

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

So, the starting position of morphological analysis is the formulation of the problem. Next, it is decomposed, i.e., divided into components of the problem. As an example, we can name problems of the structure of the management system, professionalism of personnel, motivation of activities, labor intensity of the function, and workload accounting. Other problems may also be mentioned.

But decomposition of problems must be done not only from top to bottom, but also from bottom to top. 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.

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

The limit for the development of a morphological scheme from bottom to top and top to bottom is the possible transition to another class of problems, which will make this scheme endless. This transition should be stopped.

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 statements exist in the form of key questions, the answer to which makes it possible to translate the problem into new level morphological scheme.

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

A certain type 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 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 problem bouquet method is built on.

The technology for using this method includes several stages:

· Statement of the problem in the form in which it is presented in real management practice. For example: how to use a computer in a manager’s activities?

· Summarize this problem, present it in general view. There may be many generalization formulas, as well as levels. In our example: increase the productivity of management activities, ensure professionalism of management, increase 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.

· Identify an analogue problem. These actions consist of searching for similar problems in other areas of activity or areas of nature. Based on the problem we initially posed, we can formulate an analogue of “grow a second head”, “increase the speed of thought”, “ensure survival”, etc.

· Establish the role and interactions of the problem in a complex of other problems. Maybe you can solve a problem not by itself, but through solving another problem: maybe the solution to the problem will happen as a consequence. For example, according to our original problem this could be replacing the 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 programs for using a computer that are accessible to the ignorant to a person.

· Formulate the opposite problem. This can be very useful, as it can suggest a solution and guide the researcher to a successful option. For example, 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.

5.2 Methods of proof

The concept of evidence in research practice is considered as the presentation of any arguments confirming a certain position. Such arguments can be facts, proven provisions, conclusions, points of view of recognized authorities, or experimental results.

Not everything can not always be proven with the help of facts, and there are not always facts accessible to perception. In this case, the propositions being proven are derived from others, the reliability of which is assumed to be established.

Reliability of evidence is determined by argumentation, factuality, the methodology of its construction, formal logical adherence, readiness to perceive arguments and facts.

Proof- this is an intellectual operation consisting of establishing the truth of a certain judgment, through its derivation from other judgments, the truth of which is assumed to be established before this operation and independently of it, as well as through confirmation by facts and practical activity.

Depending on the nature and characteristics of the subject of research and the possibilities of conducting it, the forms of evidence may be different.

There is factual evidence, based mainly on factual material; formal-logical, the main support of which is the laws of formal logic; experimental - built on experiment; empirical - based on meaningful and generalized experience.

The correctness of a proof is determined by its structure. In every proof there are three elements: thesis, arguments (grounds), demonstration.

Thesis- this is a judgment, the truth and acceptance of which is established in evidence; arguments - judgments from which the thesis is derived; demonstration is a logical form of connection between these two elements, necessitating the derivation of one from the other, a thesis from an argument.

There are many different methods and methods of proof:

Proof from definition. It is built on a clear definition of key categories, so “that the definitions of these categories do not raise doubts about their adequacy to real phenomena and practical experience.

Proof to the contrary. If arguments about the absurdity of the opposite of what is being proven are accepted, then the original judgment is considered to be true or at least correct.

A proof based on an analysis of the properties of the object under study.

Proof based on the principle of reduction to absurdity. This is a technique for refuting the assumption of truth, which turns out to be absurdity.

Proof based on the classification of factors, which allows us to establish the properties of the object of study and the reasons for its original behavior.

Axiomatic proof. Initially, an axiom is formulated - an indisputable, understandable and accepted position, then a proof is built, based, as a rule, on several axioms.

Factual evidence in which main role systematization of facts plays a role.

Proof of a working hypothesis or concept (hypothetical, conceptual proof).

Experimental proof. Here main support- experiment and its results.

Proof by concentration of facts. This or that position, conclusion or idea can be proven not by individual or scattered facts, but by their certain concentration and design. Facts must be accumulated and systematized.

The effectiveness of the proof is determined the right choice its techniques in accordance with the subject and nature of the research, the features and purpose of its results.

In a generalized view, the effectiveness of evidence depends on many epistemological, methodological, socio-psychological, and rhetorical factors. But the most important role is played by factors reflecting the content of the evidence.

The thesis or position being proven must comply with the rule of precision of formulation and invariance at all stages of proof. In practice, one often observes a substitution of the thesis, a substitution of concepts. This error manifests itself in the fact that the thesis put forward at the beginning of the proof is replaced by another during the proof process. There is a substitution of the quantitative characteristics of the thesis (what is proven regarding a part of the object is transferred to the entire object), a substitution of modality (probability is passed off as reliability).

To ensure the effectiveness of proof, it is necessary to follow the rule of truth of arguments. Errors of unproven grounds often occur. One common mistake is the "circle in the proof". It lies in the isolation of arguments that do not lead to a thesis. The principle that warns against these mistakes is the principle of evidentiary independence of arguments.

If an argumentative procedure is not a logically rigorous proof, but provides a certain degree of probability to a certain judgment, it is called justification.

Morphological analysis (TRIZ)

Morphological analysis- an example of a systematic approach in the field of invention. The method was developed by the famous Swiss astronomer F. Zwicky. Thanks to this method, he was able to obtain a significant number of original technical solutions in rocket science in a short time.

To carry out a morphological analysis, an accurate formulation of the problem is necessary, and regardless of what is in the original problem we're talking about only about one specific system, generalizes the research to all possible systems with a similar structure, and ultimately provides an answer to a more general question.

Example

For example, it is necessary to study the morphological nature of all types of vehicles and propose a new effective design for a device for transportation on snow - a snowmobile.

An accurate definition of the class of systems (devices) under study allows us to reveal the main characteristics or parameters that facilitate the search for new solutions. In relation to a vehicle (snowmobile), the morphological features can be the functional components of a snowmobile: A - engine, B - propulsion device, C - cabin support, D - control, E - providing reverse gear, etc.

Each characteristic (parameter) has a certain number of different independent properties. So, engines: A 1 - internal combustion, A 2 - gas turbine, A 3 - electric motor, A 4 - jet engine, etc.;
propellers: B 1 - propeller, B 2 - tracks, B 3 - skis, B 4 - snow thrower, B 5 - augers, etc.;
cabin support: B 1 - cabin support on the snow, B 2 - on the engine, B 3 - on the mover, etc.;

For a given problem in matrix expression ( morphological box) the most significant parameters are recorded.
For example, for a snowmobile the matrix will look like:

(A 1 A 2 A 3 A 4)

(B 1 B 2 B 3 B 4 B 5)

(B 1 B 2 B 3)

Possible combinations: A 1, B 3, C 2, or A 1, B 2, C 3, or A 2, B 1, C 2 etc.

Morphological box

		1	2	3	4	5	…
	characteristic	properties
A	engine	internal combustion	gas turbine	electric motor	jet engine	5	…
B	mover	propeller	caterpillars	skis	snow blower	augers	…
IN	cabin support	to the snow	to the engine	to the propulsion	4	5	…
G	control	1	2	3	4	5	…
D	providing reverse gear	1	2	3	4	5	…

Links

Morphological analysis as a way to solve business problems

F. Zwicky, Discovery Invention, Research Through the Morphological Approach. McMillan, 1969.

J.C. Jones, Design Methods. Wiley, 1981.

R.U. Ayres, Technological Forecasting and Long-Time Planning. McGraw-Hill, 1969.

Mark Sh. Levin, Composite Systems Decisions, Springer, 2006.

Mark Sh. Levin, Combinatorial Engineering of Decomposable Systems, Kluwer, 1998.

Course on system design M.Sh. Levin, including morphological analysis and its extension in the form of hierarchical morphological multicriteria design

Wikimedia Foundation. 2010.

See what “Morphological analysis (TRIZ)” is in other dictionaries:

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The method of morphological analysis involves special systematic and systematic work with morphological tables and a morphological box. Unlike most TRIZ techniques, these games and exercises cannot be carried out occasionally, unsystematically. But the effort expended is well worth it. The child develops a creative imagination, forms an idea of the world as an endless combination of various elements that can be controlled, the method helps to overcome the inertia of thinking and activate creative processes.Morphological analysis is a method for systematizing the enumeration of options for all theoretically possible solutions, based on an analysis of the structure of the object.

The method of morphological analysis in its modern form appeared in the 30s of the last century. The author of the method is Fritz Zwicky, a Swiss astronomer who used this approach in rocket science. Thanks to the method of morphological analysis, he was able not only to obtain large number original technical solutions, but also to predict the existence of neutron stars, as well as to suggest the existence of “hell stars”, the description of which is extremely similar to black holes discovered forty years later.

But the roots of the method of morphological analysis go back to ancient times. The monk and logician Raymond Lull (1235-1315) in his work “Great Art” wrote that through the systematic combination of a very small number of principles it is possible to solve all the problems of philosophy and metaphysics. The nine principles of R. Lull were embodied in devices where blocks of some circles rotated around others. As a result of moving the circles relative to each other, it was possible to obtain various statements and judgments. In modern TRIZ pedagogy, simplified and modernized “” are used.

Lull had his followers and admirers. Among them are Giordano Bruno, who noted that human knowledge is consistent with nature and the concepts of the mind correspond to the hierarchy of things, and G. Leibniz, who wrote the work “On the Combinative Art.”

Morphological analysis is based on the construction of a table that lists all the main elements that make up the object and indicates, if possible, as many known options for the implementation of these elements as possible. By combining options for implementing the elements of an object, you can get the most unexpected new solutions; options that were not previously considered may come into view.

Sequence of actions during morphological analysis:

1. Precisely formulate the problem.

2. Identify the essential elements.

3. Determine options for the design of elements.

4. Enter them into the table.

5. Evaluate all the options available in the table.

6. Choose the best option.

The morphological table can be represented in the form of two coordinate axes - vertical and horizontal:

For example, let’s take multifunctional furniture that has become popular. This example- one of the simplest. We will not now consider materials, form, functionality, etc. Having mastered the very principle of morphological analysis, you can easily do it yourself if necessary. Undoubtedly, you will recognize the technique, but the Morphological table gives much more options for creativity than sorting through and combining randomly selected furniture objects.

A more complicated version, but also more creative and interesting - parts (subsystems) of objects are laid out vertically and horizontally and combined with each other.

The main purpose of multifunctional furniture is to save residential or office space.

The main elements that we will divide into 2 categories: for storing clothes and things - a closet, shelves, a bedside table; and for relaxation and convenience - a bed, a chair, a table.

By combining objects horizontally and vertically we get:

A1 – wardrobe-bed, A2 – wardrobe-chair, A3 – wardrobe-table

B1 – shelves-bed, B2 – shelves-chair, B3 – shelves-table

B1 – bedside table, B2 – bedside table, B3 – bedside table.

We can also add a third axis - for example, materials: wood, plastic, fabric. Then you will get a Morphological Box, and the number of possible options will triple.

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 method for solving inventive problems presented in the article will help you come up with and select a great variety of interesting solutions, incl. and grocery, for your business.

Application "Morphological Box" method, which will be discussed, 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 scattered 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 is the sister of creativity!

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

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. 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. Construct a morphological box or multidimensional matrix containing all solutions to a given problem. The main recommendation is that no evaluation of options should be carried out until full registration morphological set. An example of object parameters: business card shape (ball, Moebius strip, rectangle, etc.), coating (plastic, cardboard, sausage, etc.).
4. All solutions contained in the morphological box are carefully analyzed and evaluated in terms of the goals that must 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. Select and implement the best solutions (subject to the availability of the necessary funds). Example solutions:

Morphological analysis method