Inovação no uso de ferramentas e metodologias de data analytics em empresas de Minas Gerais - Artur Tancredo Guimarães de Alvarenga (2022)
Data analytics is the process of examining, exploring, transforming and analyzing information from raw data, with the objective of identifying trends and patterns that promote meaningful insights and conclusions that will support the decision-making process. This study aimed to identify whether people management influences innovation management, considering the locus of companies located in Minas Gerais, which use data analytics tools and methodologies, in order to propose method(s) and/or process(es) to make innovation management cycles more assertive and agile. The structure of the work includes, at first, an introductory discussion that recovers the conceptual aspects - innovation management, data analytics and people management - outlined for this study. The second part was the definition of the conceptual aspects and analysis variables for the research. This framework allowed the collection of data, firstly, through an analytical analysis in the literature, and soon after, from the implementation of the survey methodology, with the application of a questionnaire to 28 professionals who work with innovation in Minas Gerais, in order to to obtain a broader view of the innovation scenario, the professionals defined for the research were divided into two personas, customers/consumers/managers/leaders and specialist/developers/analysts, in order to analyze their views and concepts differently. Based on the results, it was possible to validate the objective proposed in this study, in such a way that it was possible to find in the results that culture and organizational structure were the two categories that had the greatest influence on innovation management. Another factor to be considered is how these two categories influence this process, it was identified that, for the organizational culture, the motivation and valorization of professionals, the proportion of a data driven work methodology, proportion of new benefits and work flexibility are the factors in this category, as for the organizational structure are the definition of the type of service contracting, team structuring, communication between areas and the standardization of documents and processes. In this way, these results led to the conclusion that, in order to be successful in the data analytics area, companies need to focus on the key to success in innovation management, which are professionals in the area. Therefore, this work can serve as a guide for companies that want to implement data analytics innovation in their organizational environment.