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The article focuses on the problem of designing, constructing, measuring and interpreting indices for assessing the digital transformation of manufacturing companies. We analyse the compositional features, advantages and limitations of the three indices, which are a fairly focused on comparing industrial sectors (or at least extended groups of industries) according to their level of digital transformation or digital maturity: Industrial Digitalisation Index MGI McKinsey, Smart Industry Readiness Index (SIRI) of the World Economic Forum, Digitalisation Index for Economy and Social Sectors by the Higher School of Economics. The main thesis of the article is the need to develop a unified, continuous and relevant index of digital transformation for manufacturing companies, taking into account all the positive experiences in the conceptual and methodological development of digitalisation assessment indices that research and analysis teams have managed to develop so far. At the same time, the author points out the need to avoid retrospective construction of indices based on lagging statistical data. It seems very important to take into account the need to introduce a strategic vector when measuring the level of digital transformation of manufacturing companies. It is not enough to simply aggregate indicators of digital adoption and identify certain indices or sub-indices as the main markers of digital transformation. From a statistical point of view, such an approach can be perfectly correct, reliable, and verifiable.Questions arise about the productive potential of clustered technologies in the context of evolving business models, particularly in manufacturing. As a part of constructing any indices and methods for assessing the dynamics of digital maturity, digitalisation, digital transformation, it is better to face the inevitable uncertainty about the potential of some frontier technologies in an attempt to foresee the intersections of technological factors and future niches for business models, than to try to generalise the trajectory already traversed with a more retrospective logic based only on the verified and more tested parts and layers of the technologies. With this approach, digital transformation indices for manufacturing companies take on projective and instrumental functions, as they serve, in a sense, as a roadmap. They make it possible to improve the strategic vision of companies in different sectors, as well as their stakeholders, associations and public authorities (especially those in charge of digitalisation and industrial policy), with a view to achieving later stages of digital maturity.
The article focuses on the problem of designing, constructing, measuring and interpreting indices for assessing the digital transformation of manufacturing companies. We analyse the compositional features, advantages and limitations of the three indices, which are a fairly focused on comparing industrial sectors (or at least extended groups of industries) according to their level of digital transformation or digital maturity: Industrial Digitalisation Index MGI McKinsey, Smart Industry Readiness Index (SIRI) of the World Economic Forum, Digitalisation Index for Economy and Social Sectors by the Higher School of Economics. The main thesis of the article is the need to develop a unified, continuous and relevant index of digital transformation for manufacturing companies, taking into account all the positive experiences in the conceptual and methodological development of digitalisation assessment indices that research and analysis teams have managed to develop so far. At the same time, the author points out the need to avoid retrospective construction of indices based on lagging statistical data. It seems very important to take into account the need to introduce a strategic vector when measuring the level of digital transformation of manufacturing companies. It is not enough to simply aggregate indicators of digital adoption and identify certain indices or sub-indices as the main markers of digital transformation. From a statistical point of view, such an approach can be perfectly correct, reliable, and verifiable.Questions arise about the productive potential of clustered technologies in the context of evolving business models, particularly in manufacturing. As a part of constructing any indices and methods for assessing the dynamics of digital maturity, digitalisation, digital transformation, it is better to face the inevitable uncertainty about the potential of some frontier technologies in an attempt to foresee the intersections of technological factors and future niches for business models, than to try to generalise the trajectory already traversed with a more retrospective logic based only on the verified and more tested parts and layers of the technologies. With this approach, digital transformation indices for manufacturing companies take on projective and instrumental functions, as they serve, in a sense, as a roadmap. They make it possible to improve the strategic vision of companies in different sectors, as well as their stakeholders, associations and public authorities (especially those in charge of digitalisation and industrial policy), with a view to achieving later stages of digital maturity.
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