University of Oulu

Hannu Hannila, Risto Silvola, Janne Harkonen & Harri Haapasalo (2022) Data-driven Begins with DATA; Potential of Data Assets, Journal of Computer Information Systems, 62:1, 29-38, DOI: 10.1080/08874417.2019.1683782

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
Publish Date: 2022-02-14
Description:

Abstract

The 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.

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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.