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OPTIMISATION OF CAPITAL BUDGETS TO MAXIMISE VALUE AND MINIMISE RISK

Furlong, A. Garnaut, A.

Many alumina refineries, facing unfavourable economic circumstances, are looking to improve the long term sustainability of their business. Economic challenges that face many refineries are varied in nature including low alumina prices, aging facilities, high labour costs and a shortage of available capital. Refineries also face the growing influence of non-technical risks such as tightening regulations, community awareness and activism, increasing waste management costs and increases in regional supply chain costs for major sources such as energy and water. In this context, it is important that operational planning maximises the value achieved with every dollar of sustaining capital investment and minimises the exposure to future business risks.

This paper presents a process for optimising capital projects within the context of a broader portfolio management program. It addresses common weaknesses and brings greater rigour and definition to the project portfolio selection and implementation process. It specifically focuses on the recognition that within an operational portfolio, brownfield improvements, maintenance and expansion projects are developed to target a range of business drivers, possibly across a number of business units. Further complexity is added by the competition for limited resources and capital, and competing (and sometimes conflicting) priorities and constraints.

The paper describes the effectiveness of a robust and dynamic portfolio evaluation platform that systematically includes the potential life cycle value changes that impact upon portfolio selection. Central to the approach is the capacity to utilize real option, risk and holistic economic valuation to incorporate non-technical factors (e.g. safety, emissions etc.) alongside standard financial factors (Opex and Capex etc.) in a common evaluation structure to define the highest value and least risk portfolio. This dynamic process incorporates a range of sensitivities and constraint modelling processes to enable refinery operators to rapidly identify those projects that provide greatest value and robustness over the long term.