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Journal of the Southern African Institute of Mining and Metallurgy

On-line version ISSN 2411-9717
Print version ISSN 0038-223X

Abstract

HAGER, J.; YADAVALLI, V.S.S.  and  WEBBER-YOUNGMAN, R.. Stochastic simulation for budget prediction for large surface mines in the South African mining industry. J. S. Afr. Inst. Min. Metall. [online]. 2015, vol.115, n.6, pp.531-539. ISSN 2411-9717.

This article investigates the complex problem of a budgeting process for a large mining operation. Strict adherence to budget infers that financial results align with goals. In reality, the budget is not a predetermined entity but emerges as the sum of the enterprise's operational plans. These are highly interdependent, being influenced by unforeseeable events and operational decision-making. Limitations of stochastic simulations, normally applied in the project environment but not in budgeting, are examined and a model enabling their application is proposed. A better understanding of budget failure in large mines emerges, showing that the budget should be viewed as a probability distribution rather than a single deterministic value. The strength of the model application lies with the combining of stochastic simulation, probability theory, financial budgeting, and practical scheduling to predict budget achievement, reflected as a probability distribution. The principal finding is the interpretation of the risk associated with, and constraints pertaining to, the budget. The model utilizes a four-dimensional (space and time) schedule, linking key drivers through activity-based costing to the budget. It offers a highly expressive account of deduction regarding fund application for budget achievement, emphasizing that 'it is better to be approximately right than precisely wrong'.

Keywords : probabilistic logic; Monte Carlo; simulation; NPV; budget.

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