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dc.contributor.author | Hager, J.![]() |
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dc.contributor.author | Yadavalli, Venkata S. Sarma![]() |
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dc.contributor.author | Webber-Youngman, Ronald C.W.![]() |
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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.subject.other | Engineering, built environment and information technology articles SDG-04 | |
dc.subject.other | SDG-04: Quality education | |
dc.subject.other | Engineering, built environment and information technology articles SDG-08 | |
dc.subject.other | SDG-08: Decent work and economic growth | |
dc.subject.other | Engineering, built environment and information technology articles SDG-09 | |
dc.subject.other | SDG-09: Industry, innovation and infrastructure | |
dc.subject.other | Engineering, built environment and information technology articles SDG-12 | |
dc.subject.other | SDG-12: Responsible consumption and production | |
dc.subject.other | Engineering, built environment and information technology articles SDG-17 | |
dc.subject.other | SDG-17: Partnerships for the goals | |
dc.title | Stochastic simulation for budget prediction for large surface mines in the South African mining industry | en_ZA |
dc.type | Article | en_ZA |