Title: The value of ecosystem collaboration: fleet life cycle data-based cost-benefit model

Authors: Sini-Kaisu Kinnunen; Salla Marttonen-Arola; Timo Kärri

Addresses: Industrial Engineering and Management, School of Engineering Science, LUT University, Yliopistonkatu 34, P.O. Box 20, FI-53851 Lappeenranta, Finland ' Faculty of Technology, University of Sunderland, David Goldman Building, St Peters Campus, Sunderland, SR6 0DD, UK ' Industrial Engineering and Management, School of Engineering Science, LUT University, Yliopistonkatu 34, P.O. Box 20, FI-53851 Lappeenranta, Finland

Abstract: A fleet of assets and fleet data are often distributed globally and into several companies. It is important to demonstrate the value that can be achieved by systematically utilising fleet data as a support of decision-making. There is huge potential to benefit from fleet data due to increasingly gathered data, internet of things technologies, and data analysis tools. In this paper, a model is proposed to illustrate the ecosystem around a fleet and how to evaluate the costs and benefits of fleet data utilisation in an ecosystem. An example ecosystem is proposed, formed by an equipment manufacturer, its customer company, and an information service provider. The model demonstrates the costs and benefits for each actor in the ecosystem and works as a managerial tool to develop collaboration, fleet data utilisation, service development, and value creation from the data. The model is tested with illustrative data in a maintenance context. The results deepen the scientific discussion on the value of information and emphasise the importance of understanding how value can be created from fleet life-cycle data. The challenge lies in determining whose value should be maximised and how the ecosystem could develop collaboration in data utilisation to create value.

Keywords: fleet; asset management; data utilisation; benefits; costs; ecosystem; collaboration; value creation.

DOI: 10.1504/IJISE.2021.115080

International Journal of Industrial and Systems Engineering, 2021 Vol.38 No.1, pp.59 - 83

Received: 05 Apr 2019
Accepted: 01 Jun 2019
Published online: 18 May 2021 *

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