Methodological and practical recommendations for improving the quality of forecasts of innovative development of science, technology and engineering

The generated long-term forecasts for the development of science, technology and engineering are widely used to determine priority areas of scientific and technological development. In an unstable economic situation, it is important to ensure the quality of forecasts, since they determine the priorities and priority areas for financing scientific and technological development projects. Therefore, the problem of improving the quality characteristics of long-term forecasts for the development of science, technology and engineering is relevant. The authors set the goal of determining a set of measures to improve. the quality of the generated forecasts, taking into account modern conditions of economic development, characterized by instability and sanctions restrictions. For this purpose, a systematic and integrated approach to the development of proposals is used. Complexity lies in a comprehensive analysis of the factors influencing the forecast results, and proposals are formed on the basis of a systematic account of the component indicators of forecast quality and mutual connections. The paper presents proposals to improve the accuracy, usefulness, information content, completeness and reliability of forecasts. The similarities and differences between the proposals and the existing ones are shown, and the directions for applying the developed recommendations by the participants in the formation of long-term forecasts for the development of science, technology and engineering are also revealed. The novelty of the article lies in the fact that the authors, based on the use of systematic and integrated approaches, have identified the main methodological and practical proposals for improving the quality characteristics of long-term forecasts for the development of science, technology and engineering. This will help improve the quality of scientific and technological forecasts and effectively spend budget funds to finance new projects formed on the basis of forecasting results.