The Convergence Exposure Premium: A Risk-Adjusted Model for Industrial Digital Transformation and IT/OT Connectivity

Abstract

Industrial digital transformation is frequently justified through expected productivity, visibility, and analytics gains, yet investment cases often omit outright failure, value-destructive underperformance, lifecycle support, cyber exposure, and connectivity debt. This paper develops the Convergence Exposure Premium (CEP) and Risk-Adjusted Industrial Transformation Value (RAITV) framework for evaluating industrial digital transformation and information technology/operational technology (IT/OT) connectivity. Unlike conventional risk-adjusted net present value, expected-loss, cybersecurity-investment, and real-options approaches, the framework isolates the incremental cyber loss attributable to a proposed connectivity architecture and combines it with maturity-adjusted success, underperformance, and failure branches. An integrative evidence synthesis and model-based sensitivity analysis were used. All monetary inputs were defined as five-year discounted present values, using an illustrative 8% discount rate, and normalized to base-year annual revenue of 100 units. Under the stated triangular assumptions, a fixed-seed Monte Carlo analysis of 20,000 runs produced a median RAITV of −0.040 and 51.6% negative runs; these values describe model behavior rather than an industry failure rate. Scenario results show that broad convergence can be negative-value when benefits are modest and exposure is high, while selective digitalization on mature operations can remain positive. The contribution is an architecture-sensitive, reproducible investment framework that treats non-connection, read-only exchange, and bidirectional convergence as explicit alternatives rather than assuming convergence is inevitable.