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Speed is Significant in Short-Loop Experimental Learning: Iterating and Debugging in High-Tech Product Innovation
Decision Sciences ( IF 2.8 ) Pub Date : 2020-08-12 , DOI: 10.1111/deci.12477
Alex Alblas 1 , Miel Notten 2
Affiliation  

Digital technology is fundamental to experimentation, learning, and the rate of innovation. Digital technology facilitates the rapid distribution of experimental design and debug information. However, we should consider how this fundamentally changes organizational learning and experimentation when managing the rate of product innovation. We address this issue by investigating what drives experimentation-based learning in high-tech product innovation and production. The longitudinal dataset in our study consists of 216 projects over a period of almost 5 years, involving thousands of digitally recorded design iterations and design debugs. Based on a time series linear regression analysis, we demonstrate that learning from an accumulation of completed projects drives learning in experimentation more than failure experience in successfully completed design debugs. Furthermore, we show that processing iterations and debugs rapidly enhances the speed of product innovation learning as this allows for short-loop experimentation that restricts superstitious learning when conditions change over time. The results also show this can be achieved using digital tools as a source of agility.

中文翻译:

短循环实验学习中的速度很重要:高科技产品创新中的迭代和调试

数字技术是实验、学习和创新速度的基础。数字技术促进了实验设计和调试信息的快速分发。但是,在管理产品创新率时,我们应该考虑这如何从根本上改变组织学习和实验。我们通过调查高科技产品创新和生产中基于实验的学习的驱动因素来解决这个问题。我们研究中的纵向数据集由近 5 年的 216 个项目组成,涉及数以千计的数字记录设计迭代和设计调试。基于时间序列线性回归分析,我们证明,从已完成项目的积累中学习比成功完成设计调试中的失败经验更能推动实验中的学习。此外,我们表明,处理迭代和调试可以迅速提高产品创新学习的速度,因为这允许进行短循环实验,从而在条件随时间变化时限制迷信学习。结果还表明,这可以使用数字工具作为敏捷性的来源来实现。
更新日期:2020-08-12
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