Digital Twins as Strategic Assets: Valuation Frameworks for Simulation-Driven Decision Making in Heavy Industry

Digital twins - dynamic simulation models that mirror physical assets, processes, or systems in real time - have evolved from engineering visualization tools into strategic decision-making infrastructure across energy, mining, and heavy manufacturing. Yet despite their growing operational significance, digital twins remain conspicuously absent from corporate balance sheets, investment analyses, and board-level strategic discussions. They are budgeted as engineering expenses rather than valued as strategic assets. This paper argues that this accounting and strategic invisibility produces systematic underinvestment in digital twin infrastructure, and proposes a three-layer valuation framework to correct it. The Digital Twin Valuation Model (DTVM) captures value across three layers: (1) replacement cost - the capital required to reconstruct the simulation infrastructure and recalibrate against physical assets; (2) operational value - the measurable decision quality improvements and efficiency gains the digital twin enables in day-to-day operations; and (3) option value - the strategic flexibility that a well-calibrated digital twin provides for evaluating future capital investments, process changes, and risk scenarios without physical experimentation. Drawing on real options theory and evidence from energy, mining, and heavy manufacturing deployments, the paper demonstrates that option value typically exceeds direct operational savings by 3–5x, fundamentally changing the investment calculus for CFOs and boards. The paper concludes with implications for CFOs structuring digital twin investments, Chief Digital Officers positioning digital twins in enterprise strategy, and board directors exercising oversight on simulation infrastructure as a strategic asset class.