Stochastic simulation for budget prediction for large surface mines in the South African mining industry

Show simple item record

dc.contributor.author Hager, J.
dc.contributor.author Yadavalli, Venkata S. Sarma
dc.contributor.author Webber-Youngman, R.C.W.
dc.date.accessioned 2015-08-28T07:09:12Z
dc.date.available 2015-08-28T07:09:12Z
dc.date.issued 2015-06
dc.description.abstract 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’. en_ZA
dc.description.librarian am2015 en_ZA
dc.description.uri http://www.saimm.co.za/journal-papers en_ZA
dc.identifier.citation Hager, J, Yadavalli, VSS & Webber-Young, R 2015, 'Stochastic simulation for budget prediction for large surface mines in the South African mining industry', Journal of The Southern African Institute of Mining and Metallurgy, vol. 115, pp. 531-539. en_ZA
dc.identifier.issn 0038-223X (print)
dc.identifier.issn 2225-6253 (online)
dc.identifier.uri http://hdl.handle.net/2263/49628
dc.language.iso en en_ZA
dc.publisher Southern African Institute of Mining and Metallurgy en_ZA
dc.rights © The Southern African Institute of Mining and Metallurgy, 2015 en_ZA
dc.subject Budgeting en_ZA
dc.subject Stochastic simulation en_ZA
dc.subject Probability theory en_ZA
dc.subject Financial budgeting en_ZA
dc.subject Practical scheduling en_ZA
dc.subject South African mining industry en_ZA
dc.subject Budget prediction en_ZA
dc.title Stochastic simulation for budget prediction for large surface mines in the South African mining industry en_ZA
dc.type Article en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record