| Abstract [eng] |
With this Master Thesis it is analysing employee attrition impact to process performance management in international companies. With the first literature part there is analysing and evaluating the connection and impact of employee attrition to process performance management. Process performance, productivity, and efficiency were all affected due to this influence. With the second literature part there was analysed data science techniques used to solve business problems. Moreover, it was analysed earlier research, applied to employee attrition problem. The analysis and the results of earlier research helped to apply the best practice in the current research and to develop employee attrition prediction model. With the methodology part it was described predictive model development (using an open data set), together with all the development stages, and performed statistical analysis to identify the factors, which impacts employee attrition the most. With the practical-deployment part, additional literature analysis has been performed to develop the strategic deployment of employee attrition prediction model. Employee attrition prediction model has been tested by modifying the data and thus to improving working conditions for potential leaver. The results have been tested by re-calculating employee attrition probability. The results showed zero probability to leave the company, because working conditions have been improved. With the last parts it was provided research limitations, conclusions, and recommendations. Master Thesis includes 7 parts: introduction, literature analysis, methodology part, practical part, research limitation, conclusions and recommendations and references. Master Thesis volume – 46 pg. without appendices, 24 figures, 4 tables, 49 references. In additionally added appendices, scientific article with same topic as this Master Thesis, and certificate of participation in the 26th Conference for Young Researchers “Science – future of Lithuania. Economics and Management”. |
