Applied Data Science and the Open Innovation Strategies

Valentina Chkoniya
GOVCOPP, ISCA-UA University of Aveiro

Abstract

Smart organizations that can successfully leverage value from their data gain unparalleled competitive advantages in an increasingly challenging and complex digital era. The use of the term “open” has increased exponentially, giving rise to concepts such as open data, open innovation, open science, open knowledge, and open education, among others (Corrales-Garay et al., 2019). A new paradigm of innovation presents a model that uses both external and internal sources of ideas and technologies. As organizations turn to digital transformation strategies, they are also increasingly forming teams around the practice of Data Science, that aims to understand and analyze the vast diversity of phenomena with data and can vary greatly from industry to academy. Applied Data Science busts ideas at the intersections between the digital and physical worlds. After a decade from the introduction of Open Innovation in the vocabulary of Management, the research stream has progressed along multiple paths, crossing the boundaries of the theories on innovation and technology where the concept was originally conceived. Today the combination of Applied Data Science and open innovation strengthens the decision support base and helps to develop new tools. This paper gives an overview of the possible contributions of Applied Data Science and the open innovation strategies to support a data-driven decision-making process. This synthesis of current research aims to help to drive innovation by assisting and inspiring effective applied data science strategy, as well as providing valuable insights for both practitioners and researchers in the field.

Presentation