The Hybrid Model: Combination of Big Data Analytics and Design Thinking

Michael Lewrick ()
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Michael Lewrick: Lewrick & Company

A chapter in Design Thinking for Software Engineering, 2022, pp 73-84 from Springer

Abstract: Abstract Today more than ever, the Design Thinking Mindset is at the center of companies’ efforts to develop radical innovations. New or changing customer needs require an agile and goal-oriented approach that creates new products, services, and entire business ecosystems. Design Thinking offers the ideal basis for understanding the respective needs, deriving points of views from the insights and finally using various creativity techniques to design solutions that solve the customer problem in the best possible way. Design Thinking is already a very strong paradigm that helps to interact close to the customer. However, this approach also has its limitations, and observations are mostly qualitative and limited by the amount of interactions. With the hybrid model of Design Thinking and Big Data Analytics, such limitations can be overcome and even better and more personalized solutions for the customer/user can be realized. With AI-enhanced data processing tools there are different approaches to integrate Data Science into the design of products, services, and even entire business ecosystems.

Keywords: Design thinking; Big data; AI; Hybrid (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-030-90594-1_4

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DOI: 10.1007/978-3-030-90594-1_4

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