ABSTRACT

Asset operators face unprecedented challenges: fluctuating resource prices, disrupted supply chains, and demands for sustainability. Simultaneously, they’re expected to reduce costs by 20–40%, increase automation to 60–80%, eliminate incidents, achieve net-zero emissions, and boost production by 5–10%. The rapid proliferation of digital technology into our energy supply chain has unlocked a major new opportunity: the ability to capture and implement engineers’ expertise and deploy it at scale. With 75% of digital initiatives failing to realise value 3–5 years after implementation, effectively prioritising digital initiatives and allocating resources accordingly is crucial for ensuring strong return on investment. We introduce a novel, quantitative methodology for assessing digital initiative value realisation, comprising seven key steps: (1) digital capability assessment; (2) value identification; (3) base case value driver tree development; (4) impact assessment; (5) quantitative modelling; (6) feasibility estimation; and (7) prioritisation and selection. This approach enables organisations to drive successful digital and artificial intelligence transformation through enhanced decision-making and strategic resource allocation. We present two case studies demonstrating its effectiveness: (1) an energy industry megaproject identified 10 high-potential initiatives from over 100, potentially achieving US$96 million per annum operational expenditure (OPEX) savings and 130 ktCO₂e per annum emission reductions. (2) A single supply chain technology application modelled to deliver a net present value exceeding US$70 million through increased asset life and availability, and reduced project delays. These examples illustrate how business process optimisation with quantified initiative value modelling can help asset operators achieve bold transformation goals, ensuring strong returns on digital investments.