Product-level profitability

Hannu Hannila (Department of Industrial Engineering and Management, University of Oulu, Oulu, Finland)
Joni Koskinen (Department of Industrial Engineering and Management, University of Oulu, Oulu, Finland)
Janne Harkonen (Department of Industrial Engineering and Management, University of Oulu, Oulu, Finland)
Harri Haapasalo (Department of Industrial Engineering and Management, University of Oulu, Oulu, Finland)

Journal of Enterprise Information Management

ISSN: 1741-0398

Publication date: 25 September 2019

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.

Keywords

Citation

Hannila, H., Koskinen, J., Harkonen, J. and Haapasalo, H. (2019), "Product-level profitability", Journal of Enterprise Information Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEIM-05-2019-0127

Download as .RIS

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

Please note you might not have access to this content

You may be able to access this content by login via Shibboleth, Open Athens or with your Emerald account.
If you would like to contact us about accessing this content, click the button and fill out the form.