Data-driven begins with DATA : potential of data assets |
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Author: | Hannila, Hannu1; Silvola, Risto1; Härkönen, Janne1; |
Organizations: |
1University of Oulu, Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.3 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2022021418847 |
Language: | English |
Published: |
Informa,
2022
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Publish Date: | 2022-02-14 |
Description: |
AbstractThe objective of this study is to analyze the potential of company data assets for data-driven, fact-based decision-making in product portfolio management (PPM). Data assets are categorized from the PPM standpoint, including (product/customer/ …) master data, transactional data, and interaction data (e.g., IoT data). The study combines literature review and qualitative analysis of eight international companies. The findings underline the crucial role of corporate-widely combined and governed data model. Company business IT is adjusted against the corporate-level data model. The order of importance is data first, and the technology second. The data-driven mind-set and culture creation are also important. The implications include understanding the role and potential of combined data assets that form the basis for data-driven PPM. Facts based on company data assets are essential for decision-making instead of “gut feeling” and emotions. The utilization of the unused potential of data assets is promoted in the transformation toward data-driven PPM. see all
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Series: |
Journal of computer information systems |
ISSN: | 0887-4417 |
ISSN-E: | 2380-2057 |
ISSN-L: | 0887-4417 |
Volume: | 62 |
Issue: | 1 |
Pages: | 29 - 38 |
DOI: | 10.1080/08874417.2019.1683782 |
OADOI: | https://oadoi.org/10.1080/08874417.2019.1683782 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
222 Other engineering and technologies |
Subjects: | |
Copyright information: |
© 2019 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Computer Information Systems on 25 Nov 2019, available online: https://doi.org/10.1080/08874417.2019.1683782. |