The age of analytics: competing in a data-driven world

By Nicolaus Henke, J. Bughin, Michael Chui, J. Manyika, Tamim Saleh, Bill Wiseman. 2016

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Industry 4.0, global value chains and international business (2017, background): “…of value for ﬁ rms, but successful ﬁ rms will require a range of technical and governance capabilities to analyse and operationalise that data so as to realise the potential bene ﬁ ts (Davenport et al ., 2012; McAfee and Brynjolfsson, 2012; Constantiou and Kallinikos, 2015; Henke et al. , 2016).”
Introduction to MAchine Learning & Knowledge Extraction (MAKE) (2017, background): “Meanwhile industry from Amazon to Zalando is investing a lot into research as they envision enormous business potential in the near future which also stimulates fruitful cooperation between academia and industry, and even small companies have identified the value of ML for solving a large variety of”
Deep learning in business analytics and operations research: Models, applications and managerial implications (2018, unknown): “This fact also holds true for a majority of enterprises: a 2016 report on “The Age of Analytics” by the McKinsey Global Institute refers to deep learning as “the coming wave” (Henke et al., 2016).”