Product-level profitability : current challenges and preconditions for data-driven, fact-based product portfolio management
Hannila, Hannu; Koskinen, Joni; Härkönen, Janne; Haapasalo, Harri (2019-09-25)
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. https://doi.org/10.1108/JEIM-05-2019-0127
© Emerald Publishing Limited. Published in this repository with the kind permission of the publisher.
https://rightsstatements.org/vocab/InC/1.0/
https://urn.fi/URN:NBN:fi-fe202002175594
Tiivistelmä
Abstract
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.
Kokoelmat
- Avoin saatavuus [32026]