Journal:Data science as an innovation challenge: From big data to value proposition

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Full article title Data science as an innovation challenge: From big data to value proposition
Journal Technology Innovation Management Review
Author(s) Kayser, Victoria; Nehrke, Bastian; Zubovic, Damir
Author affiliation(s) Ernst & Young
Year published 2018
Volume and issue 8(3)
Page(s) 16–25
DOI 10.22215/timreview/1143
ISSN 1927-0321
Distribution license Creative Commons Attribution 3.0 Unported
Website https://timreview.ca/article/1143
Download https://timreview.ca/sites/default/files/article_PDF/Kayser_et_al_TIMReview_March2018.pdf (PDF)

Abstract

Analyzing “big data” holds huge potential for generating business value. The ongoing advancement of tools and technology over recent years has created a new ecosystem full of opportunities for data-driven innovation. However, as the amount of available data rises to new heights, so too does complexity. Organizations are challenged to create the right contexts, by shaping interfaces and processes, and by asking the right questions to guide the data analysis. Lifting the innovation potential requires teaming and focus to efficiently assign available resources to the most promising initiatives. With reference to the innovation process, this article will concentrate on establishing a process for analytics projects from first ideas to realization (in most cases, a running application). The question we tackle is: what can the practical discourse on big data and analytics learn from innovation management? The insights presented in this article are built on our practical experiences in working with various clients. We will classify analytics projects as well as discuss common innovation barriers along this process.

Keywords: analytics, big data, digital innovation, idea generation, innovation process

References

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. Grammar has been updated for clarity. In some cases important information was missing from the references, and that information was added. The original article lists references alphabetically, but this version — by design — lists them in order of appearance.