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Digital transformation and smartization projects in industrial enterprises have become increasingly prevalent in recent years, aiming to enhance operational efficiency, productivity, and sustainability. Assessing the outcomes of such projects is crucial to determine their effectiveness in enabling sustainability. In this context, a model for evaluating digital transformation smartization projects (DTSP) outcomes can be developed to provide a comprehensive assessment framework. This study aims to develop and test a model for diagnosing the results of implementing digital transformation smartization projects for industrial enterprises. The methodology presented in this article involves using statistical tests to detect multicollinearity and heteroskedasticity in regression models. It also proposes an economic–mathematical model with three objective functions to optimize the implementation of smartization projects, considering cost minimization, deviations from planned business indicators, and production rhythm disruptions. The most important results of the survey are (1) a proposed matrix for the selection of indicators for diagnosing the results of the implementation of digital transformation smartization projects for industrial enterprises, (2) a two-level model for the economic evaluation of diagnosed digital transformation smartization projects, which can be used at any stage of the digital transformation smartization project and based on it, conclusions can be drawn regarding the effectiveness of the implementation of both the entire project and its individual stages, objects, or elements. The advantage of the model is the possibility of its decomposition, that is, a division into separate parts with the possibility of introducing additional restrictions or, conversely, reducing the level of requirements for some of them. The results were tested at industrial enterprises in Ukraine and proved their practical significance.
Digital transformation and smartization projects in industrial enterprises have become increasingly prevalent in recent years, aiming to enhance operational efficiency, productivity, and sustainability. Assessing the outcomes of such projects is crucial to determine their effectiveness in enabling sustainability. In this context, a model for evaluating digital transformation smartization projects (DTSP) outcomes can be developed to provide a comprehensive assessment framework. This study aims to develop and test a model for diagnosing the results of implementing digital transformation smartization projects for industrial enterprises. The methodology presented in this article involves using statistical tests to detect multicollinearity and heteroskedasticity in regression models. It also proposes an economic–mathematical model with three objective functions to optimize the implementation of smartization projects, considering cost minimization, deviations from planned business indicators, and production rhythm disruptions. The most important results of the survey are (1) a proposed matrix for the selection of indicators for diagnosing the results of the implementation of digital transformation smartization projects for industrial enterprises, (2) a two-level model for the economic evaluation of diagnosed digital transformation smartization projects, which can be used at any stage of the digital transformation smartization project and based on it, conclusions can be drawn regarding the effectiveness of the implementation of both the entire project and its individual stages, objects, or elements. The advantage of the model is the possibility of its decomposition, that is, a division into separate parts with the possibility of introducing additional restrictions or, conversely, reducing the level of requirements for some of them. The results were tested at industrial enterprises in Ukraine and proved their practical significance.
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