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Unpacking human systems in data science innovations: Key innovator perspectives

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  • Li, Keyao
  • Griffin, Mark A.

Abstract

Despite optimistic forecasts, industry innovations in data science have extraordinarily high rates of failure. It is essential to minimise the failure of data science projects, for both businesses and data professionals. Human systems are critical to the success of data science innovations. However, the human aspects of innovation management are often neglected or omitted in most guidelines and frameworks for data science. This provides limited guidance about the necessary human conditions for successful data science innovations. In this article we address this concern by developing a systematic framework for understanding human systems that support data science innovations.

Suggested Citation

  • Li, Keyao & Griffin, Mark A., 2023. "Unpacking human systems in data science innovations: Key innovator perspectives," Technovation, Elsevier, vol. 128(C).
    • Handle: RePEc:eee:techno:v:128:y:2023:i:c:s0166497223001803
    DOI: 10.1016/j.technovation.2023.102869
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