Hannu Hannila, Seppo Kuula, Janne Harkonen & Harri Haapasalo (2022) Digitalisation of a company decision-making system: a concept for data-driven and fact-based product portfolio management, Journal of Decision Systems, 31:3, 258-279, DOI:10.1080/12460125.2020.1829386
Digitalisation of a company decision-making system : a concept for data-driven and fact-based product portfolio management
|Author:||Hannila, Hannu1; Kuula, Seppo1; Härkönen, Janne1;|
1Industrial Engineering and Management, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022102763554
|Publish Date:|| 2022-10-27
The objective is to conceptualise data-driven and fact-based product portfolio management (PPM). The study examines how PPM process is internalised in companies and proposes a concept that covers all PPM performance management areas (strategic fit, value maximisation, and portfolio balance) to transform profitability analysis from company-level to product-level. The study is founded by focusing on PPM process and other key business processes, data-driven decision-making, company data assets, and business information technology (IT). The findings highlight how the strategic role of PPM process and related targets and key performance indicators must be internalised before adjusting business IT to utilise data assets for data-driven, fact-based PPM. The means for a data-driven approach are provided by the effective connection of the PPM process, company-widely governed data assets, and business IT systems to realise their full potential for fact-based decision-making over lifecycle. New contribution relates to introducing a technology-independent concept for data-driven, fact-based PPM.
Journal of decision systems
|Pages:||258 - 279|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
222 Other engineering and technologies
© 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Decision Systems on 5 Oct 2020, available at: http://www.tandfonline.com/10.1080/12460125.2020.1829386.