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The purpose of article is to substantiate formation of financial and non-financial reporting of enterprises in context of changes in external environment and assess possibilities of using reporting data in development management system. Substantiation of formation financial statements and non-financial reporting of domestic enterprises in context of constant changes in external environment and possibility of using reporting data in development management system is relevant today. Foreign experience in compiling and structuring non-financial reports is analyzed. The article summarizes approaches for development of methodological provisions for compiling a non-financial report, which provide for structuring of selected report in areas of socially responsible policy by systematizing relevant indicators. It is recommended to structure non-financial report according to indicators provided in the GRI (Global Reporting Initiative), taking into account economic, environmental and social criteria of efficiency, which will promote transparency company for different stakeholder groups. The algorithm for generating a non-financial report is substantiated and its main components are outlined in accordance with indicators and sections of the GRI standard. When publishing the report, companies must justify choice of indicators and their reliability, note reasons and factors for not disclosing information about other important indicators. Emphasis is placed on need to be guided by qualitative characteristics for preparation of financial statements in accordance with international standards, which should be followed in implementation of economic, environmental and social activities to make informed management decisions. The factors which cause complication of formation of financial statements of enterprises in modern conditions are defined. The proposed recommendations require the use of technology to provide real-time data collection, analysis and reporting, as well as following processes: independent verification of reports, improving quality of data, their reliability and comparability. |
