A holistic digitalization KPI framework for the aerospace industry - Felix Krol; Muhammad Amad Saeed; Wolfgang Kersten (Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29, 2020)
Purpose: The aerospace supply chain is characterized by a high degree of small andmedium-sized suppliers. To stay competitive, suppliers are facing high pressures todigitalize their business but have limited resources available. Furthermore, aerospacesuppliers lack a framework to measure their current state of digitalization.Therefore, this paper provides a holistic digitalization KPI framework for manufacturingaerospace companies. Methodology: The framework is based on a top-down and bottom-up developmentapproach. Within the top-down approach, 42 digitalization maturity models are beinganalyzed to identify relevant dimensions. To reveal digitalization indicators, acomprehensive literature review is being used as a bottom-up approach. Indicatorsare then assigned to the sub-dimension. Finally, indicators are grouped to similar indicatorsand merged to digitalization KPI. Findings: The developed KPI framework encompasses 89 digitalization KPI amongnine dimensions: Strategy and Organizational Leadership, Governance and TransformationManagement, Digital Skills/Human Capital, Smart Product, Customer Focus,Smart Process/Operations, Digital Technology, Financial Focus, and Network and Security. Originality: The presented digitalization KPI framework provides a scientific foundationfor measuring the digitalization maturity level of aerospace companies.Therefore, maturity models and benchmarking tools can incorporate the developed(sub-) dimensions and KPI to measure and compare the digital readiness of aerospacecompanies as well as to derive guidance for areas of improvement.
urn:nbn:de:gbv:830-882.0114785; hdl:10419/228914; https://econpapers.repec.org/RePEc:zbw:hiclpr:29
Keywords: 650; Logistics; Industry 4.0; Digitalization; Innovation; Supply Chain Management; Artificial Intelligence; Data Science