From data insight to data driven strategy – exploiting the power of predictive analytics
Predictive analytics should allow companies to design a data driven strategy, ranging from improving operations, increasing revenues and market share, designing and customizing product/services, monetizing on owned data. Based on our on-the-field research, we discuss how companies in different industries can benefit from this evolution, how their organization and processes should be arranged to best achieve the goal, what are the main barriers to overcome. We also address future developments made possible by prescriptive and automated analytics, whose potential will be further enhanced by the bursting digital landscape of social data and sensors.
Carlo Vercellis is Full Professor of Computer Science at Politecnico di Milano, where he teaches courses in Optimization, Business Intelligence and Data Mining. He is director of door, the data mining and optimization research group (www.door.polimi.it), which conducts leading research and world-class applied projects on predictive and optimization analytics, data mining, machine learning and pattern recognition. He is also director of the Observatory on Big Data Analytics & Business Intelligence, and director of the International Master in Business Analytics and Big Data at MIP-Politecnico di Milano.
Previously, after his graduation in Mathematics at Università degli Studi di Milano, he has been with National Research Council (CNR), Bocconi University and Università degli Studi di Milano. He developed projects with several companies on big data analytics, sentiment analysis, marketing, data analysis, predictive modeling, data mining, risk analysis, supply chain optimization, quality control.
He is author of more than 80 scientific writings, among which 6 books and more than 60 papers in high-rank international journals and books. He has been associate editor of several journals. He co-organized several international conferences, and has been invited to discuss his research work in leading research institutions.