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Analysis, Implementation And Use Of Predictive Data In Business Models Using The Concepts And Paradigms Specific To The Scientific Competence Field Of Machine Learning

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  • Marian-Sorin IONESCU

Abstract

In an economy of implementing the most recent discoveries of scientific progress, competition and positioning as sustainable as possible, with well-defined strategic development perspectives, we identify in the behavior of economic organizations the development of an innovative interface to the external economic macro environment, the massive data collection component.A relatively new field in resolving economic issues and improving business models, Predictive Analysis develops a multitude of algorithms and statistical technologies, from data selection, to generating predictive models, Machine Learning specific approaches, historical analysis and organizational economic performance.The totality of these data, their consequences, their analysis and subsequent interpretation then become the basis for forecasting and development of strategies for consolidation, growth and development.Predictive models are the ones that operationalize business concepts and functional business entities identified in organizational economic history, an analysis similar to the traditional S.W.O.T. approach, identifies real and potential risks and opportunities, their analysis and study are particularly useful milestones in the subsequent decision-making process.Predictive analysis is the scientific tool which provides a predictive scoring for the totality of entities involved in the decision-making process.For economic business organizations and their top management which is in a process of optimal decision elaboration and searching, predictive analysis plays a determining role in marketing components, financial analysis and management, sales power, production management and organizational analysis structured on profit centers.Evaluation models process the organizational economic development strategies, proposed algorithms and procedures, partner and competition data, subsequent forecasts are generated with the probability of reaching all the desired intermediate targets and the final one, to which the entire activity of the economic organization is subjected.

Suggested Citation

  • Marian-Sorin IONESCU, 2018. "Analysis, Implementation And Use Of Predictive Data In Business Models Using The Concepts And Paradigms Specific To The Scientific Competence Field Of Machine Learning," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 12(1), pages 472-484, November.
  • Handle: RePEc:rom:mancon:v:12:y:2018:i:1:p:472-48
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