Bringing advanced technology to strategic decision-making: The Decision Intelligence/Data Science (DI/DS) Integration framework

Abstract

There is a widespread stated desire amongst both public and private organizations worldwide to engage in more significant “evidence-based reasoning” and to be more “data-driven.” We argue that these two goals are proxies for the often-unstated goal of improving the exploration of possible futures as foresights that could lead to better strategic decisions and improved business outcomes. From this perspective, data and analytics hold great promise and are necessary—but not sufficient—for improving strategic decision-making. Something more is needed to realize this potential. We specify how to fill this gap using an integration framework between technology and decision-makers, which is especially appropriate in complex and/or volatile environments. Our solution—which comprises a methodology as well as a software architecture—therefore unifies not only human decision makers to technology but each other and also integrates several disciplines that have been hitherto unnecessarily separated. Thereby, it could help organizations to address increasing challenges better as well as improve the exploration of possible futures.