The data-driven organization: Intelligence at SCALE
Sasson, Amir (red.). At the Forefront, Looking Ahead: Research-Based Answers to Contemporary Uncertainties of Management
Evolving at an unprecedented pace, digital technologies promise to automate not only labor-intensive and repetitive work, but also the traditional and exclusive domain of educated humans—knowledge work. This is evident in the new ways of reaching customers and coordinating activities, as well as in the fact that companies conducting a business built on the new technologies now constitute the world’s largest enterprises. The presence and evolution of these companies challenge established divisions of labor between man and machine, and almost casually redraws the boundaries between industries. Machine learning and analytics challenge the managers leading and the managerial scientists studying organizations. Everybody says they want to be data driven—but what does a company really need to do to achieve that? This article will explore the managerial, organizational, and strategic implications of allowing an ever increasing number of organizational decisions to be taken not by managers employing intuition and common sense, but by algorithms and learning systems based on massive amounts of data derived from electronically based customer interactions. We argue that these companies can be thought of as “intelligent enterprises” with enhanced abilities to sense, comprehend, act, learn and explain (SCALE) their environment and their interactions with it. To acquire these capabilities, managers need to cede authority over some decisions while acquiring new capabilities and roles for themselves.
Sasson, Amir & Johnson, John Chandler (2016)
The 3D printing order: variability, supercenters and supply chain reconfigurations
International Journal of Physical Distribution & Logistics Management, 46(1), s. 82- 94. Doi: 10.1108/IJPDLM-10-2015-0257
