INESC TEC Science Bits # 1 Business Analytics

Published: Feb. 28, 2020, 12:02 p.m.

b'INESC TEC Science Bits is a podcast, produced by INESC TEC and Engenharia R\\xe1dio, which aims to shed a light on the latest trends in science and technology, trying to dive deeper in each subject with the help of INESC TEC experts and researchers.
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\\nIn this first episode, two researchers from INESC TEC Centre for Industrial Engineering and Management talk about Business Analytics,\\xa0namely Prescriptive Analytics, a research line with the potential to be a leading-edge element in management and industry.
\\nDuring this conversation, the guest speakers explain\\xa0what is Business Analytics and the sequence according to which the different types of Analytics should be conducted – giving examples of Prescriptive Analytics in Business or in Industry and trying to forecast the future developments in Prescriptive Analytics.
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\\nBernardo Almada Lobo is a Full Professor at Industrial Engineering and Management, FEUP, and a Member of the Board at INESC TEC. He is also a co-founder of LTPlabs (INESC TEC and FEUP spin-off) and member of the Board of Trustees of the Funda\\xe7\\xe3o Belmiro de Azevedo. His main area of activity is Science Management /Operations Research. He develops and applies advanced analytical models and methods to help make better decisions, thus helping solve managerial problems in various sectors (manufacturing, health, retail and mobility) – with a special focus on Operations Management.
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\\nGon\\xe7alo Figueira\\xa0is a researcher at INESC TEC Centre for Industrial Engineering and Management, and a visiting lecturer at the Department of Industrial Engineering and Management at FEUP. His research interests include supply chain management, operations research and decision support systems. Gon\\xe7alo Figueira has published in international journals and worked as a researcher/consultant in several R&D projects, namely in the fields of production planning, supply chain design, scheduling, disturbance management and inventory replenishment.
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