MAGAZINE  №2-3 (103) - 2021

AUTHOR СHERNYAEVA Y.G. - Expert, Sberbank (Moscow, Russia)

CATEGORY  Information technologies in logistics and SCM Supply chain management


During the pandemic, Russian pharmaceutical companies faced the problem of not being able to make quick decisions due to the lack of high – quality data and the problems of obtaining them in real time, which does not allow them to manage risks, conduct a reasonable analysis of consumer demand and make medium-term (and even more so-long-term) forecasts.

Digitalization provides flexibility in supply planning, taking into account the high volatility of demand. The effectiveness of digitalization of supply chains in previously existing studies is taken for granted, but during the pandemic, after receiving real negative experience, it became necessary to re-evaluate the importance of digital solutions in supply chain management, to consider digital solutions that allow evaluating the effectiveness of not individual participants in the supply chain, but the entire chain as a whole. An analysis of the existing digital solutions used in the pharmaceutical industry's supply chain management, namely the COVID-19 vaccine supply chain, is of strategic importance for the entire global community and all supply chains during the pandemic, as the economy will not recover as long as the public health crisis continues.

The article analyzes the international scientific literature devoted to the research of problems in the supply chains of the pharmaceutical industry, identifies key problems, as a digital solution in the management of the supply chains of vaccines from COVID-19, a digital twin is proposed, the conceptual model of which is described using the SCOR methodology, and the e-SCOR technology is proposed for the implementation of the Digital twin.

The article conceptually describes the application of the digital twin in the supply chain management of COVID-19 vaccines, taking into account the increase in chain transparency, demand forecasting, increased response in the supply chain, inventory, warehouse and transport capacity management, routing changes when replacing / increasing production locations, cold chain monitoring, risk management to improve the efficiency of supply chains, return flow management.

The research methods used in this article are analysis, comparison, generalization, graphical representation of data, reference models of processes, simulation modeling, methods of big data analysis, digital technologies.

 Electronic version



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