Product-level profitability : current challenges and preconditions for data-driven, fact-based product portfolio management |
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Author: | Hannila, Hannu1; Koskinen, Joni1; Härkönen, Janne1; |
Organizations: |
1Department of Industrial Engineering and Management, University of Oulu, Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.7 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe202002175594 |
Language: | English |
Published: |
Emerald,
2019
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Publish Date: | 2020-02-17 |
Description: |
AbstractPurpose: The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance. Design/methodology/approach: The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size. Findings: Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation). Practical implications: The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio. Originality/value: The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM. see all
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Series: |
Journal of enterprise information management |
ISSN: | 1741-0398 |
ISSN-E: | 1758-7409 |
ISSN-L: | 1741-0398 |
Volume: | 33 |
Issue: | 1 |
Pages: | 214 - 237 |
DOI: | 10.1108/JEIM-05-2019-0127 |
OADOI: | https://oadoi.org/10.1108/JEIM-05-2019-0127 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
222 Other engineering and technologies |
Subjects: | |
Copyright information: |
© Emerald Publishing Limited. Published in this repository with the kind permission of the publisher. |