Full professor, FON
Gordana Savić is a Full professor in the Operational Research, Performance and Business Analytics at the University of Belgrade-Faculty of Organizational Sciences and Faculty of Agriculture. She received a PhD degree in Operations Research from the University of Belgrade, Faculty of Organizational Sciences in 2012. She has been serving as a head of Laboratory for Operational Research and Centre for Efficiency Analysis as well as head of Business analytics module and deputy chair of Operational research and Statistics department. Gordana has more than 25 years of experience in education and science. Her teaching and research interests include mathematical modelling, optimization, business and performance analytics. Gordana is an author or co-author of more than 150 scientific and research papers. Out of them, more than 30 are monograph chapters and papers in leading scientific journals including European Journal of Operational Research, Expert Systems with Application, Higher Education and Scientometrics. Gordana serves as a reviewer, editor, and guest editor in several leading international and national journals. Furthermore, she has been active in organizing of scientific conferences as chair of organizing and member of scientific and organizing committees (KES International, BALCOR; SYM-OP-IS and SymOrg). She has been a member of the projects team in more than ten national and international projects and participant in several research projects. She has also been a participant, coordinator, or leader of a wide range of practical projects and training courses in the fields of ICT consulting, business and performance analytics, mathematical modelling and optimization (Danish Refugee Council, GlaxoSmithCline, Zavod za izradu novčanica i kovanog novca – Narodna banka Srbije, GIZ, GETBGD, Delhaize Srbija, ProPositiv) and a lecturer at Akademija of Big Data and Business Analytics (Koncept Makedonija).
Business analytics is a powerful tool that can be used to make better decisions and craft business strategies. Today’s organizations generate and gather vast amounts of data that need to be interpreted and analyzed in order to generate valuable information. Business analytics is the process of using quantitative methods to derive meaning from data to make informed business decisions. Core business analysis techniques are descriptive, diagnostic, predictive and prescriptive analytics. Descriptive analytics is focused on the interpretation of historical data to identify trends and patterns using business intelligence tools, data visualization and dashboards. Diagnostic analytics is focused on the interpretation of historical data to determine why something has happened using drill-down and data mining techniques. Predictive analytics uses statistics and quantitative methods to forecast future outcomes. It relies primarily on techniques such as predictive modelling, regression analysis, forecasting, multivariate statistics, pattern matching or machine learning. As the most complex, prescriptive analytics applies simulation and optimization techniques to determine which outcome will yield the best business results. The goal of this lecture is to introduce the following: