This article describes forecasting methods, their meaning, classification, and brief characteristics. The main selection criteria for these methods are presented and examples of their effective practical application are given. The special role of forecasting methodology in the modern world of increased instability is also emphasized.
The essence and significance of the forecasting methodology
In the general concept, forecasting is a process of predetermining the future on the basis of initial parameters (experience, identified patterns, trends, relationships, possible prospects, etc.). On a scientific basis, forecasting is used in various fields of human activity: economics, sociology, demography, political science, meteorology, genetics and many others. The most telling example of the use of forecasting in a person’s daily life is the daily weather forecast familiar to everyone.
In turn, the effective use of forecasts on a scientific basis requires the use of certain techniques, including a number of forecasting methods. At the beginning of the last century, at the origin of scientific research in this area, only a few such methods were proposed with a limited range of applications. At the moment, there are many such methods (more than 150), although in practice no more than a few dozen basic forecasting methods are used. At the same time, the choice of certain methods depends both on the scope of their application and on the set goals of ongoing predictive research, as well as on the availability of specific forecasting tools for the researcher.
Basic concepts in forecasting methodology
The forecasting method is a specific method aimed at studying the forecasting object in order to obtain a target forecast.
Forecasting methodology - a general body of knowledge about forecasting methods, techniques and tools.
Forecasting technique - a combination of methods, techniques and tools selected to obtain a targeted forecast.
The object of forecasting is a specific area of processes within which research is conducted on the subject of forecasting.
The subject of forecasting is a legal or natural person carrying out research work in order to obtain forecasts.
Differences and the relationship of planning with the forecasting process
Forecasting as opposed to planning:
- is informative rather than prescriptive;
- It covers not only the activities of a particular enterprise or organization, but the entire totality of the external and internal environment;
- may be more long-term;
- does not require significant detail.
However, with all the differences, forecasting and planning have a close relationship, especially in the economic field. The obtained target forecast shows an area of potential risks and opportunities, in the context of which specific problems, tasks and goals are formed that need to be solved and taken into account when drawing up plans of various forms (strategic, operational, etc.). In addition, forecasts provide an analytically sound multivariate view of potential development, which is necessary to build alternative plans. In a general sense, we can say that the relationship between forecasting and planning lies in the fact that although the forecast does not determine specific planning tasks, it contains the necessary informative materials for the implementation of effective target planning.
The main classifiers in the forecasting methodology
The main classification of forecasting methods is usually carried out according to the following criteria:
By degree of formalization:
- intuitive (heuristic) methods that are used in difficult to predict tasks using expert judgment (interviews, scripting method, Delphi method, brainstorming, etc.);
- formalized methods, which mainly imply a more accurate mathematical calculation (extrapolation method, least squares method, etc., as well as various modeling methods).
By the nature of the prognostic process:
- quality methods based on expert judgment and analytics;
- quantitative methods based on mathematical methods;
- combined methods, including (synthesizing) elements of both qualitative and quantitative methods.
By the method of obtaining and processing information data:
- statistical methods involving the use of quantitative (dynamic) structural patterns for processing information data;
- methods of analogies based on logical conclusions about the similarity of the patterns of development of various processes;
- leading methods, characterized by the ability to build forecasts based on the latest trends and patterns of development of the studied object.
Also, the totality of these methods can be divided into general forecasting methods and specialized methods. Common methods include those that cover a wide range of solutions to prognostic tasks in various spheres of life. An example of such forecasts are expert assessments in various fields. On the other hand, there are methods that focus only on a specific area of activity, such as, for example, the balance sheet method that has become widespread in the economic sphere and focused on accounting information.
Brief description of forecasting methods
As already noted, in forecasting at the moment there are many methods. The main forecasting methods include those that are currently most widely used and applied in various fields.
- Method of expert assessments. Since when solving many forecasting problems, often not enough reliable formalized, including mathematical, data, this method is quite popular. It is based on the professional opinion of experienced experts and specialists in various fields, followed by processing and analysis of the polls.
- The extrapolation method is used for stable system dynamics of various processes, when development trends persist in the long term and there is the possibility of projecting them onto future results. Also, this method is used for objects of the same field of activity with similar parameters, assuming that the impact of certain processes on one object that caused certain consequences will cause similar results in other similar objects. Such forecasting is also called the analogy method.
- Modeling Methods. Model development is carried out on the basis of evaluating data on certain objects or systems, their elements and processes, followed by experimental testing of the constructed model and making the necessary adjustments to it. At present, predictive modeling methods have the widest range of applications in various fields from biology to the socio-economic sphere. In particular, the possibilities of this technique were revealed with the advent of modern computer technology.
- The normative method is also one of the main methods. It implies an approach to making forecasts focused on specific goals and objectives formulated by the subject of forecasting with the installation of certain standard values.
- The method of scenarios gained distribution in the development of managerial decisions, allowing to evaluate the probabilistic development of events and possible results. That is, this method involves the analysis of the situation with the subsequent determination of the likely trends of its development under the influence of the adoption of certain managerial decisions.
- Foresight methods. The latest technique, which includes a whole range of different methods and techniques aimed not only at the analysis and forecast of the future, but also at its formation.
Statistical Forecasting Methods
One of the main forecasting methods is statistical methods. Predictions developed by such methods can be most accurate, provided the completeness and reliability of the initial information data for the analysis of the necessary quantitative and semi-quantitative characteristics of forecasting objects. These methods are a form of mathematical methods of forecasting, which make it possible to build promising time series. Statistical forecasting methods include:
- research and application of modern mathematical and statistical methods for forecasting based on objective data;
- theoretical and practical research in the field of probabilistic-statistical modeling of expert forecasting methods;
- theoretical and practical research of forecasting in a risky environment, as well as combined methods of symbiosis of economic, mathematical and econometric (including formalized and expert) models.
Auxiliary tools for forecasting methodology
The auxiliary tools of heuristic forecasting methods include: questionnaires, maps, questionnaires, various graphic material, etc.
The tools of formalized and mixed methods include a wide range of tools and techniques of the auxiliary mathematical apparatus. In particular:
- linear and nonlinear functions;
- differential functions;
- statistical and mathematical tools for correlation and regression;
- least square method;
- matrix techniques, apparatus of neural and analytical networks;
- the apparatus of the multidimensional central limit theorem of probability theory;
- apparatus of fuzzy sets, etc.
Criteria and factors for the selection of certain methods in making forecasts
Various factors influence the choice of forecasting methods. So operational tasks require more operational methods. At the same time, long-term (strategic forecasts) require the application of integrated forecasting methods of a comprehensive nature. The choice of certain methods also depends on the scope, availability of relevant information, the possibility of obtaining formalized (quantitative) estimates, qualifications and technical equipment of forecasting subjects, etc.
The main criteria of the technique can be:
- systemic nature in the formation of forecasts;
- adaptability (variability) to possible parametric changes;
- the validity of the choice of methodology in terms of reliability and relative accuracy of the forecast;
- continuity of the forecasting process (if one-time task is not set);
- economic feasibility - the costs of the forecasting process should not exceed the effect of the practical application of its results, especially in the economic sphere.
Examples of effective use of the existing prognostic apparatus
Effective practical application of forecasting methods, an example of which is most common at the moment, is their use in the business environment. Thus, the most progressive firms can no longer do without making forecasts when carrying out full-fledged planning of their activities. In this context, forecasts of market conditions, dynamics of prices, demand, innovative prospects and other prognostic indicators up to seasonal and climatic natural fluctuations and socio-political climate are important.
In addition, there are many examples of the effective application of the forecasting methodology in various areas of human activity :
- the use of mathematical modeling to predict potential emergencies in hazardous enterprises;
- systemic environmental and economic forecasting by country and regions;
- socio-economic forecasting of development trends of society as a whole and its individual elements;
- forecasting in the field of quantum physics, new biotechnologies, information technologies and many other fields.
The role of forecasting methodology in the modern world of increased uncertainty and global risks
In conclusion, it must be said that the forecasting methodology has long been fully included in the life of a person, however, it acquires the greatest relevance today. This trend is associated both with the rapid development of technological processes in the world, and with an increase in uncertainty in the internal and external environment. Numerous crisis phenomena in the economy, politics, and the social sphere provoke an increase in the risk burden in all areas of activity. The deepening globalization processes have led to the emergence of systemic global risks generating a possible domino effect, when problems in individual corporations or countries have a serious negative impact on the economic and political condition of the entire world community. Recently, the risks associated with climatic instability, large technological disasters, and military-political crises have intensified recently. All this testifies to the special role of forecasting both potential global and current individual risk events in the modern world. Effective system forecasting that meets modern challenges can avoid or reduce the consequences of many threats and even transform them into advantages.