TY - JOUR T1 - Data Science as an Innovation Challenge: From Big Data to Value Proposition JF - Technology Innovation Management Review Y1 - 2018 A1 - Victoria Kayser A1 - Bastian Nehrke A1 - Damir Zubovic KW - analytics KW - big data KW - digital innovation KW - idea generation KW - innovation process AB - 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. PB - Talent First Network CY - Ottawa VL - 8 UR - http://timreview.ca/article/1143 IS - 3 U1 - Ernst and Young Victoria Kayser is a Data Scientist in Ernst & Young’s Advisory Organization. Her research is focused on the intersection of analytics and innovation management. Her PhD examined the contribution of text mining to foresight and future planning. She has worked in the fields of innovation research and strategy development as well as in the automotive sector. She holds a Master of Science degree in Information Engineering and Management. U2 - Ernst and Young Bastian Nehrke is a Manager with Ernst and Young’s Advisory in Stuttgart. He specializes in developing organizational analytics capabilities and supports clients in setting up their own analytics hubs and CoEs as well as innovation and data thinking methods. He is a certified Project Manager, Business Analyst, and Requirements Engineer and studied International Management and Innovation and Technology Management in Frankfurt and Heilbronn. U3 - Ernst and Young Damir Zubovic leads Ernst and Young’s Data and Analytics Practices in Germany, Switzerland, and Austria as Partner. With 15 years of professional experience in leading business intelligence, analytics and big data initiatives, he is responsible for business development, specializing in analytics applications in the automotive and life sciences sectors and in consumer and retail products. His extensive experience in the field makes him an experienced mentor who also acts as coach, lecturer, and keynote speaker. ER -