Title: Product and supply chain related data, processes and information systems for product portfolio management

Authors: Hannu Hannila; Arto Tolonen; Janne Harkonen; Harri Haapasalo

Addresses: Industrial Engineering and Management, University of Oulu, P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, P.O. Box 4610, FI-90014, Finland

Abstract: Traditional product data management (PDM) systems have evolved to support the product lifecycle management (PLM). The combination, also referred to as PDM/PLM has developed into a product master data (PMD) repository. The PMD and business process related data are utilised in product portfolio management (PPM). However, companies' tendency to have productrelated data in silos among multiple business processes and information systems (IS) results in uncertain information for PPM. This study focuses on data, processes and information systems related to PMD and supply chain product data (SCPD), PPM and supply chain (SC) processes and information systems. The study highlights the related challenges in providing fact-based data for PPM analysis and decision-making. The results indicate that the key PMD and SCPD have not been connected back to PPM as automated and integrated data flow from enterprise resource planning (ERP) system to the PDM/PLM system. The key SCPD consists of product-related volume and cost information that should be linked to PPM analysis and decision making. These findings are critical to further develop data, processes and IS to support strategic and financial PPM analysis and decision making on what products a company should have in the portfolio.

Keywords: product portfolio management; product lifecycle management; PLM; product master data; PMD; supply chain product data; SCPD; supply chain process; product data management; PDM; enterprise resource planning; ERP.

DOI: 10.1504/IJPLM.2019.104352

International Journal of Product Lifecycle Management, 2019 Vol.12 No.1, pp.1 - 19

Received: 21 Nov 2018
Accepted: 19 Jan 2019
Published online: 06 Jan 2020 *

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