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Conspiracies. drawing up conspiracies on your own Conspiracies In the old days, the difference between a conspiracy and a prayer was insignificant. Early Christians included holy names in spells, believing that their effectiveness was based on faith in God. Here is a broad example

Making your own conspiracies The Bible says that “in the beginning was the Word.” That is, the whole world came from him, since “the Word was God.” In many ways it has remained so to this day, because even now you can kill with a word, but you can resurrect, if, as they say, it is said

Step 12 Drawing up programs for someone else's consciousness

Trend building

A trend is the general long-term tendency of a time series to change, underlying its dynamics. If a time series has seasonal variation, then the moving average method is usually used. The traditional method of predicting the future value of an indicator is to average its n past values. Mathematically, a moving average is expressed as:

Moving average = sum of demand for previous n-periods/n

Average sales volume for the first 4 quarters is:

(34200+9000+23400+45000)/4 = 27900 thousand rubles.

Average sales for the next 4 quarters are:

(9000+23400+45000+36000)/4 = 28350 thousand rubles.

Further calculations continue in a similar way until the last four quarters for which data are available. The first calculated average shows the average sales for the first year and is located halfway between the sales data for the 2nd and 3rd quarters of 2010. The average for the next four quarters is placed between the sales for the 3rd and 4th quarters, then between the 4th quarter of 2010 and the 1st quarter 2011 and after between the 1st and 2nd quarter of 2011

To obtain a trend, it is necessary to center the moving averages by adding adjacent values ​​and dividing them in half; the calculation results are shown in the first column of Table 3.2.

To make a forecast for 2012, we will perform a linear approximation of the trend values ​​and calculate the trend value in each quarter of 2012.

In order to make a realistic forecast for each quarter, it is necessary to consider the quarterly dynamics of sales volume and calculate the seasonal variation. Since a multiplicative model will be used for time series analysis, it is necessary to divide each sales indicator by the trend value, as shown in the following formula.

Multiplicative model = (Trend*Seasonal variation*Residual

variation*Sales volume)/Trend = Seasonal variation*Residual

variation

In order to express the value of the indicators as a percentage, and round them to the first decimal place, we multiply them by 100. Trend and Sales Volume/trend*100 are presented in Table 3.2.

Table 3.2

Calculation results

To create a sales forecast for each quarter of 2012, you need to continue the trend of moving averages on the chart. Since the smoothing process has eliminated all fluctuations around the trend, this will not be difficult to do. To construct a graph, you must use the least squares method. We have the coordinates of 4 points of the trend graph; using the least squares method mentioned above, we calculate the values ​​of a and b for the equation of the straight line

Having calculated the partial derivatives with respect to a and b, we obtain two equations with two unknowns.

From the obtained equations we will find a and b, and find out the required equation of the line. The parameter y found by substituting a and b corresponds to the sales volume for 2012, the data is shown in Table 3.3.

Table 3.3

Trend forecast for 2012

The trend spread is shown by the line in Fig. 3.2. From the graph you can see the forecast for each quarter.

Figure 3.2

To remove residual variation, it is necessary to adjust the means. Over the long term, the amount of sales above trend in good quarters should be equal to the amount that sales are below trend in bad quarters, so that the seasonal components add up to approximately 400%. In this case, the sum of the unadjusted averages is 403.3784. Thus, it is necessary to multiply each average value by a correction factor so that the sum of the averages is 400.

Correction factor = 400/sum of averages

Correction factor = 400/403.3784 = 0.991625

The calculation of seasonal variation is presented in Table 3.4.

Table 3.4

Calculation of seasonal variation

Based on the data in Table 4, it can be predicted, for example, that in the 1st quarter, sales volume will average 96.3% of the trend.

Making a sales forecast

To compile a sales forecast for 2012, the obtained quarterly trend values ​​must be multiplied by the value of the corresponding seasonal variation for each quarter. Data calculations are shown in Table 3.5.

Table 3.5

Compiling a sales forecast by quarter for 2012

In Fig. 3.3 shows a graph of sales volumes from 2010 to 2012.

1. Development of technical condition for the forecast of an object and subject

2. Set tasks

4. Indicators

2. stage Collection of objective information

3. stage Sampling and its compilation

4. Drawing up a search forecast

5. Regulatory forecast

6. We give it to specialists for examination

7. Collective export assessment

8. We make adjustments to our forecast

9. We hand over to the customer

10. We implement

11. We make adjustments to the forecast

12. Summing up

13. Criteria for the truth of social forecasts and projects.

The value of social forecasts is determined not only by the social significance of the predicted phenomenon, but also by the degree of its accuracy and reliability. The level of reliability of forecasts determines both the outcome of future events and the timeliness of impacts on the processes of the present, from which the future is born. The present represents the only period of time flow in which people influence the historical process. The degree of this impact depends on the expected outcome of future events, on the degree of probable implementation of the forecasts. Making decisions in the present, making plans for the future, determining immediate tasks and more distant goals both in individual human behavior and in the activities of individual teams, social groups and the entire society as a whole - all this puts the problem of the truth or reliability of social forecasts at the center scientific research.

Forecasting is a necessary link in the process of cognition; it is organically included in it and is subject to all its laws and principles. The most important of these principles is a correct understanding of the essence of social practice, its role in the process of cognition. Being the basis, goal and criterion of the truth and reliability of human knowledge, practice plays a similar role in relation to the predictive function of the cognition process. Here, as in the entire process of cognition, practice appears in dialectical unity, that is, as the basis, goal and criterion of the reliability of our knowledge about the future.

However, social forecasting has its own specifics, arising from the peculiarities of the manifestation and implementation of the laws of social life through the conscious, purposeful activities of people. The study of these laws and, on this basis, a scientific assumption of the direction and nature of their action in the future constitute, in essence, the basis of social forecasting. Consequently, the role of practice in social forecasting must inevitably be characterized by the same specificity that distinguishes social forecasting from the process of cognition as a whole and from forecasting in general. Of course, any forecasting as a function of social consciousness is social, meaning a forecast of social processes directly, i.e. a forecast of the development and further functioning of the social organism itself, social forecasting V in the proper sense of the word.

Reliability of the forecast. The reliability of a forecast is understood as the necessary or at least sufficient degree of probability of the justification of the developed forecasts. The reliability of forecasts depends on a number of factors: the depth and clarity of our knowledge of objective patterns and laws that determine the development of various social systems; the ability to correctly display and “model” social systems. An important role is played by the degree of knowledge of specific social processes, the completeness of information about the conditions and cause-and-effect relationships that determine the development of a particular social process, as well as the timeliness and speed of processing the flow of information data about specific social processes and relationships. The quality, completeness, and reliability of social information, as a rule, are directly proportional to the reliability of the social forecast.

The above allows us to draw some general theoretical and methodological conclusions that are fundamental for any prognostic activity. Firstly, It becomes obvious how important the theory is for prognostication. Without theoretical insight into the essence of ongoing processes and without practical experience, without the creative application of scientific theory, scientific forecasting is generally unthinkable. Forecasting activity is primarily a scientific and theoretical activity. In any area of ​​public life it must be understood and implemented as a continuous constant creative process. The point is not to hastily draw up some picture of the future, to imagine the future in accordance with some arbitrary requirements, but to organize responsible, purposeful and continuous scientific activity, which must be free from any assault and incompetent supervision.

Secondly, The decisive condition for any forecasting is the completeness of information regarding the laws that determine the course of the predicted process; without this, creating a serious forecast is generally impossible. Of course, it is impossible to obtain complete information about all applicable laws. In many cases you will have to deal with hypotheses about patterns. However, you need to know in advance that the reliability of the forecast, as a rule, decreases the more you have to resort to hypothetical statements about the law, so that ultimately the forecast may lose value. Therefore, analysis of the law of development (and this is an important theoretical condition) is the “alpha and omega” of any forecast.

Third, Crucial for the forecast is the most realistic and accurate understanding of the determining conditions under which the predicted processes begin and which influence them. This includes the anticipation of the implementation of the conditions for the operation of a significant (relevant) law for the forecast, and data on other possible conditions and factors that could affect the object of the forecast. As a rule, information about the initial and accompanying conditions of the predicted process is as difficult to obtain as information about the law of development. It is not uncommon to first have to deal with a large number of interacting factors, which can then be included in larger groups. Therefore (especially when forecasting in the field of economic management), the strictest objectivity, scientific reliability, honesty, exclusion of subjectivity and “embellishment” in the analysis and assessment of initial and accompanying conditions are indispensable prerequisites for successful forecasting.

Forecasting- activities aimed at identifying and studying possible alternatives for the future development of the company. The main role here is given to forecasting product sales. The main purpose of the forecast is to determine trends in factors affecting market conditions.

When forecasting, short-term forecasts are usually distinguished - for 1 - 1.5 years, medium-term - for 4-6 years and long-term - for 10-15 years.

The main emphasis when short-term forecasting is done on the quantitative and qualitative assessment of changes in production volume, supply and demand, price levels and indices, currency ratios and credit conditions. Temporary, random factors are also taken into account.

Medium term And long-term forecasting is based on a system of forecasts - the relationship between supply and demand, restrictions on environmental protection, and international trade.

Formalized quantitative methods (factorial, statistical analysis, mathematical modeling), methods of expert assessments based on the experience and intuition of specialists in a given product and market are used as forecasting tools.

The most important forecasts in the activities of companies are sales forecasts, in the development of which the following basic methods can be used:

• survey of a group of managers of various services and departments of the company, and generalization of assessments of individual sales agents of the enterprise and heads of its sales divisions - the forecast is the average of their opinions. The method is used for new firms that do not have experience in using other methods, and also when there is no detailed information about market trends. Within the framework of this method, it is possible to take into account regional characteristics of demand and conditions for selling the company’s products;
• forecasting based on past turnover - the growth rate of sales volume in the reporting year is determined in comparison with the previous one and the assumption is made that the achieved growth rates will continue next year:
  Next year's turnover = Reporting year's turnover x (Current year's turnover: Last year's turnover).
  The method is used for markets with stable conditions, slightly changing assortment, minor fluctuations in turnover and sluggish scientific and technical progress;
• analysis of trends, cycles and factors influencing sales volume. The most significant factors include: long-term growth trends of the company, cyclical fluctuations in business activity, seasonal changes in sales, technical changes, the emergence of new competitors, etc. The method is used for long-term forecasts for a period of at least 3-5 years and is most applicable in capital-intensive activities;
• correlation analysis - complements the previous method, but is based on the use of more complex methods of statistical analysis. The close relationship between the level of sales and various factors influencing it is revealed, on the basis of which the factors are ranked in order of importance. The method requires large expenses associated with in-depth market research, and produces the most accurate results in markets with stable conditions;
• forecasting based on the “market share” of a company’s sales— sales are forecast as a certain percentage of the firm's market share in a given industry. A calculation is made of the company's share in total sales in the market. When using the method, it is important to be confident in the accuracy of the sales forecast for the market as a whole and not to take into account non-price competition;
• end use analysis— the forecast is based on the expected volumes of orders from the company's main customers. Total sales usually exceed this figure by a certain percentage. The method requires conducting research on the main industries that consume the enterprise's products, and is most preferable in the sectors of the raw materials and energy complex and in companies that produce finished products and components;
• product range analysis— sales forecasts for individual types of products are brought together and form the company’s planned turnover. The method is suitable for diversified firms; its accuracy depends on detailed market research for each type of product;
• test marketing - one of the most accurate approaches to sales forecasting. A new product and the system for its promotion on the market (prices, types of advertising, sales channels, type of packaging) are tested in a small regional market, and then information about the sales volume on it is distributed to the entire sales market of the company;
• standard probability distribution methods— three types of sales forecasts are determined by experts: O — optimistic forecast; IN - most likely prognosis; P - pessimistic assessment of the sales forecast. Next, the expected value of the sales forecast (C) is calculated using the formula

C = (O + 4B + P): 6.

Standard deviation (CO) calculated as C0 = (0 − P) : 6. In accordance with the general theory of statistics, the most probable value of the variable - sales volume with a 95% probability will be within C ±2 CO.

The effectiveness of using a particular method depends on the specifics of the company’s activities. It is usually considered that the forecast has been drawn up correctly if the deviation of actual turnover from the planned one is no more than 5%.

The sales forecast is the basis for drawing up a plan for the production and sale of the company's products.

When developing a sales forecast, an integrated approach, the simultaneous use of several forecasting methods and comparison of the results obtained are important. Among these methods, the most common are the following:

1) Method of expert assessments (including the opinion of a group of managers and a combination of opinions of sales employees). This forecasting method is most suitable for new businesses that do not have enough experience in using other methods. This method is also applicable when there are no detailed calculations about the state of the market, there are no complete statistics on sales trends for certain types of products.

2) Extrapolation of trends and cycle. When using this method, errors are inevitable, but it is invariably used in sales forecasting; the low percentage of predicting the consequences of socio-economic phenomena does not contribute to high accuracy of the forecast. The use of this method is possible if the analyst has at his disposal massive amounts of information on various areas of the company’s activities over the past 10 years.

The use of this method is based on the following techniques:

A) Determination of moving averages.

The product sales diagram most often has an abrupt character. Averaging the observation results will allow us to construct a sales curve over time. A suitable number of observation results are averaged. It can use quarters, which means adding the first three results and dividing the sum by three. Then the results of the second, third and fourth observations are added and divided by three, etc. The result is a quarterly moving average. The constructed graph determines the prospective sales values.

B) Smoothing models.

Over time, more and more observations are made and the size of the forecast errors is determined. At the same time, it seems rational to take past mistakes into account when predicting the future. One way is to add a fixed percentage of last month's error to last month's actual sales and use the result to forecast the next month. Using this method, you can get quite good short-term forecasts. Such forecasts are useful for production planning and inventory management, but are practically inapplicable for financial planning.

3) Forecasting based on a portfolio of orders, that is, based on existing or expected orders from potential buyers of products, which is preferable for generating sales volume in high-tech industries. The application of this method requires conducting special research on the main industries consuming the products of a given enterprise, collecting and processing significant statistical and factual material. This method is preferable in the raw materials and energy sectors, as well as in enterprises that produce components and components.

4) Correlation analysis, that is, the identification of statistically significant factors influencing the sales of the company’s products. Using the correlation relationship, the closeness of the connection between the level of sales and various results of the enterprise’s economic activity is determined, the impact on sales of which can be logically proven and justified. Thus, the most significant factors, depending on which the sales volume may change in the future, are identified and ranked (according to the degree of their influence). This method requires special and expensive research. The most accurate results can be obtained in the most stable industries in terms of economic conditions.

The effectiveness of using a particular method depends entirely on competitive conditions and the specifics of the enterprise’s economic activity and can only be determined in a system of general market research activities. In marketing-oriented companies, several forecast options are compiled using various methods (3-4 methods). The resulting estimates are then compared to identify any differences in estimates that may arise. It is usually considered that the forecast is made correctly if the difference between the estimated and actual sales does not exceed 5%. If these discrepancies are significant (the spread of sales forecast indicators using various methods exceeds 10%), then most likely errors were made when drawing up the sales forecast using some method.