University of Oulu

Hannila, H., Koskinen, J., Harkonen, J. and Haapasalo, H. (2019), "Product-level profitability: Current challenges and preconditions for data-driven, fact-based product portfolio management", Journal of Enterprise Information Management, Vol. 33 No. 1, pp. 214-237.

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:
Language: English
Published: Emerald, 2019
Publish Date: 2020-02-17


Purpose: 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.

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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
Type of Publication: A1 Journal article – refereed
Field of Science: 222 Other engineering and technologies
Copyright information: © Emerald Publishing Limited. Published in this repository with the kind permission of the publisher.