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

In: Design Thinking for Software Engineering

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  • Michael Lewrick

    (Lewrick & Company)

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.

Suggested Citation

  • Michael Lewrick, 2022. "The Hybrid Model: Combination of Big Data Analytics and Design Thinking," Progress in IS, in: Jennifer Hehn & Daniel Mendez & Walter Brenner & Manfred Broy (ed.), Design Thinking for Software Engineering, pages 73-84, Springer.
    • Handle: RePEc:spr:prochp:978-3-030-90594-1_4
    DOI: 10.1007/978-3-030-90594-1_4
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    Keywords

    Design thinking; Big data; AI; Hybrid;
    All these keywords.

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