Structural shifts in the economy in the context of macroeconomic instability determine the promising profile of technologies and products. This paper considers a model for identifying and forecasting fast-growing organizations using the mechanical engineering industry as an example. The threshold of average annual revenue growth of 50% in current prices is used as a criterion for identifying fast-growing organizations. Big data analysis methods are used to identify fast-growing organizations within the segment under consideration. 1.8 thousand fast-growing organizations in the Russian industry with revenues exceeding 100 million rubles have been identified. An assessment of their growth using a sigmoid (logistic curve) shows a significant growth potential of 150%. The parameters of the logistic curve are identified using the least squares method. The data source is open data from the electronic Government of Russia, primarily from the Russian Federal Tax Service.