Technology express analysis of large missives of data on reversible assets of industrial enterprises

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Gross indicators of industrial organizations in Russia increased significantly in 2003-2017. (with some decline in the financial crisis of 2009). Due to this, the Russian economy in size was able to take a worthy place in the world. For further advancement, not only extensive growth is necessary, but also an increase in the efficiency of Russian enterprises, which, unfortunately, has not improved systemically in recent years. The most significant indicators of economic activity: profitability (and the unit costs associated with it) and turnover periods vary in a relatively small range, with a tendency towards deterioration in the turnover period. Managing operational efficiency is key to growth. The paper shows an example of using OLAP technology of big data analysis (BigData) to increase the efficiency of financial and economic management of an enterprise, in particular, on current assets. The use of this approach allows the analysis in the express mode, for a period of 5-10 times less than with traditional methods of analysis. On a sample of about 10 enterprises of the real sector, according to the results of in-depth analyzes in the process of consulting projects, it was shown that the share of inefficient stocks (illiquid assets and excess standards) is 35-40 % of their total value. The analytical model of value as a tool for express analysis makes it possible to assess the consequences of managing current assets by influencing the company's fundamental value. Model calculations show that a one-time reduction in the turnover of current assets by 20 % provides for a 35 % increase in the fundamental value. If this result is replicated to all industrial enterprises of the country, the effect on additional cash flow will amount to 5.8 trillion rubles, to increase in value - about 3 trillion rubles.

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Olap, bi, sixth technological order, big data analysis, decision making, development program, express mode, modeling, business value, financial forecasting

Короткий адрес: https://sciup.org/147232257

IDR: 147232257   |   DOI: 10.14529/ctcr190208

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