To twin or not to twin, that is the question: evaluating the business justification for digital twins in legacy systems

Abstract The adoption of Digital Twins (DT) in legacy manufacturing environments holds significant potential but remains hindered by unclear business justification, particularly in the fast-moving consumer goods (FMCG) sector, where ageing infrastructure and operational constraints dominate. While DTs are widely recognised for their role in predictive maintenance, process optimisation, and real-time decision-making, their implementation in legacy FMCG systems remains limited, partly due to uncertainties around cost, integration feasibility, and return on investment (ROI). This study explores the business justification for DT adoption in legacy FMCG manufacturing through a dual-method approach, (1) a meta-level systematic literature review (SLR) of recent meta-analyses and (2) an industry survey capturing practitioner perspectives from FMCG manufacturing and digital transformation roles. Findings reveal a persistent gap: while academic models emphasise ROI and structured evaluation, industry stakeholders rely on informal, heuristic processes shaped by risk aversion, digital immaturity, and strategic uncertainty. The paper explores the alignment between academic frameworks and industry needs and decision-making processes, particularly in relation to impact measurement under uncertainty. The findings suggest that while the theoretical value of DTs is well-established, practical adoption is hindered by a lack of standardised tools for pre-implementation business case modelling. This paper contributes one of the first comparative syntheses of academic and industry perspectives on Digital Twins in legacy manufacturing, identifying areas of overlap and divergence in research areas and industry requirements. This is one of the first dual-method studies to triangulate academic and industry perspectives in assessing the business justification of Digital Twins in legacy FMCG systems.