Product-level profitability
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.
Year of publication: |
2019
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Authors: | Hannila, Hannu ; Koskinen, Joni ; Harkonen, Janne ; Haapasalo, Harri |
Published in: |
Journal of Enterprise Information Management. - Emerald, ISSN 1741-0398, ZDB-ID 2144850-4. - Vol. 33.2019, 1 (25.09.), p. 214-237
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Publisher: |
Emerald |
Saved in:
Online Resource
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