When wrong is right: leaving room for error in innovation measurement

Research output: Contribution to journalArticlepeer-review

Abstract

To date, measuring innovation has not been an exact science. As in many areas of organizational life, errors in measuring innovation are a recurring fact. Innovation researchers and practitioners alike have become increasingly interested in understanding the occurrence of organizational errors and how these errors affect innovation and its measurement. This empirical study aims to address this under-explored area by utilizing a qualitative in-depth case study at the innovation department of an organization with production sites and sales organizations worldwide. A total of 28 semi-structured interviews at several organizational levels were conducted, with innovation managers, project managers, senior managers, and staff. Based on the findings in this case study, three explanations are presented on how organizational errors occur when using innovation KPIs (key performance indicators). The first explanation can be connected to the increasing complexity of innovation and its intangible nature. Another explanation can be traced to the difference between innovation strategy and innovation KPIs. Lastly, room for organizational errors can be related to the multitude of individuals and organizational levels involved in innovation and its measurement. The implications for practitioners are that innovation KPIs are not precise metrics but should be seen as estimates with organizational errors. Whether or not these innovation KPIs can be used as tools to turn innovation into competitive advantages largely depends on whether wrong is right. Future research should focus on the metrics that are implemented and actually in use, as this future path would highlight the function and dysfunction that organizational errors in innovation KPIs can have.
Original languageEnglish
Article number332
JournalJournal of Risk and Financial Management
Volume14
Issue number7
DOIs
Publication statusPublished - 2021 Jul 17

Subject classification (UKÄ)

  • Production Engineering, Human Work Science and Ergonomics

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