Sber assessed the growth dynamics of the process analytics market

The volume of the Russian market of process analytics (Process Mining, PM) last year amounted to about 900 million rubles. Such data was presented at the Sber Process Mining conference, according to Sber's press service.

Taras Skvortsov, Sberbank's Senior Vice President, Head of Finance, noted that demand for PM solutions is increasing, "the scope of their use is expanding, more and more processes are being digitalized, and Process Mining tools themselves are rapidly improving, providing new opportunities for business.

Experts expect the PM market to grow at a compound annual growth rate of 69% through 2028.

Skvortsov added that Process Mining is increasingly being used by large and medium-sized companies, as well as the public sector - this is due to the increasing complexity of processes, higher levels of digitalization and the growing availability of PM solutions. "Russian solutions can already reduce the duration of business processes by up to 50% and halve labor costs," emphasized the bank's Senior Vice President.

According to a joint study by Sber and Trust Technologies, 45% of Russian companies are now planning to use PM - this is 3% more than a year ago. Financial companies, metallurgical and mining companies, as well as retailers are the most active in announcing their desire to implement Process Mining, but more and more often they are joined by heavy industry, machine building, agriculture and food processing companies.

Anastasia Kabaeva, partner of the technology practice at Trust Technologies, said that at the moment companies primarily use PM to optimize processes such as procurement and order management, customer interaction, production and IT processes. "But we expect a significant expansion of the areas of application of this technology," she said.

Process Mining is a tool for analyzing business processes based on their digital footprints in information systems. It helps optimize processes through deep analytics and generate recommendations based on machine learning and data visualization technologies.