The rapidly fluctuating price of minerals, increasing competition, and volatile financial markets have placed the mining industry in a position of ever-increasing risk. How do you:

• Accurately forecast production?
• Predict prices, supply/demand volumes, imports, exports, operating costs?
• Improve the accuracy of cost estimates for sites?
• Evaluate the inherent risk in achieving financial targets for acquisitions?
• Figure commercial terms for service offerings?
• Determine optimum replacement rates for equipment and maintenance?
  

While Microsoft® Excel® is a popular tool for building models to assess risk, it cannot succeed alone because it has no way to account for the inherent uncertainty in market, operational, and financial forecasts. Without a tool to address uncertainty, mining companies expose themselves to risks that include overestimating costs based on the changes of mineral prices in the market and fluctuating market demand and production levels.

Crystal Ball is a Microsoft Excel®-based suite of analytical tools that adds to the power of Excel by including the ability to do Monte Carlo simulation, optimization, and forecasting. With little effort, you can apply these advanced analytical techniques to your new or existing spreadsheets to create more accurate financial and operational predictions and better informed business decisions.

With Crystal Ball, you can:

• Increase the efficiency of your capital allocation. Incorporate the appropriate measure of risk in capital project evaluations so you can determine which projects will be strong contributors to the company and which will be a waste of corporate time and effort.
• Gain a better understanding of risk. Mining exploration deals with many unknowns, with high risk and uncertainty an inherent part of the industry. The management of risk in extractive industries has always been a difficult subject. Stochastic analysis methods allow you to gain a better understanding of risk.
• Account for strategic flexibility in project valuations. Add real options to your discounted cash flow analysis to accurately account for the impact of positive uncertainty in estimating your project's value, particularly when there is high volatility in future phases.
  

Key features of interest to your industry include sensitivity analysis, correlation, and historical data fitting. The sensitivity analysis helps you to understand which of the uncertain input variables are most critical and drive the uncertainty of your model. Correlation lets you link uncertain inputs and account for their positive or negative dependencies. If historical data does exist, the data fitting feature will compare the data to the distribution algorithms and calculate the best possible fit and parameters for your data.

Oracle's powerful, yet easy-to-use Crystal Ball software has allowed companies like Newmont Mining, Barrick Gold, and Metallica Minerals to make better and more lucrative decisions in the face of these industry-specific risks. You can focus your resources on the right problem and complete analysis sooner with less effort.

LEARN MORE ABOUT CRYSTAL BALL FOR MINING

This page offers links to a growing number of resources, including recorded Web seminars, articles, white papers, case studies, and example models. Additionally, you can view a list of common uses and examples reported directly from customers using Crystal Ball. You can also download a free trial version of Crystal Ball to see how it can help improve your business forecasts and decisions!

RECORDED WEB SEMINARS

Evaluating Mining Projects Using Monte Carlo Simulation Shows how input parameters such as capital, operating costs, mining rates, recoveries, and metal prices can easily be varied in order to determine which of them will have the greatest impact on the project’s economic success. Presented by Nathan Stubina of Barrick Gold Recorded August 7, 2007	View recording Download files

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WHITE PAPERS

Market Risk for a South African Gold Miner: Implications for EPS, Cash Flow & Valuations By Alex James (MSc Imperial College London)	Download
Optimizing the Growth Portfolio of a Diversified Mining Company Thomas de Lange, Manager Strategy, Kumba Resources	Download
Process Operating Costs with Applications in Mine Planning and Risk Analysis By Doug Halbe and T.J. Smolik (Presented at the SME Mineral Processing 2002 Symposium)	Download

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CASE STUDIES

Forecasting Mine Production Decisioneering Services helps one of the largest copper companies accurately forecast mine production using Monte Carlo simulation	Download
Property Valuation Crystal Ball Taught for Valuing Properties at Colorado School of Mines	Download

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EXAMPLE MODELS

Drill Bit Replacement Detail: When drilling wells in certain types of terrain, the performance of a drill bit erodes with time because of wear. The problem is to determine the optimum replacement policy; that is, the drilling cycle between replacements. Includes optimizations setting file and defines time as a decision variable.	Download For: Crystal Ball Level: Moderate- advanced
Mine Project Valuation Using Monte Carlo Analysis From: By Alpay Sergi, Visiting Scholar, and Graham A. Davis, Associate Professor (gdavis@mines.edu), Division of Economics and Business, Colorado School of Mines, Golden, CO Detail: A mining corporation is evaluating a small underground gold mining project containing an estimated one million ounces of gold. The project is based on the example given in "Optimum Production Rate Selection" by Bruce Cavender, Mining Engineering,1992. The problem is to value the project using traditional DCF analysis, but to take the valuation impacts of these geological and economic uncertainties into account. Monte Carlo analysis is useful in this case because 1) the correlations between the uncertain variables that are multiplicands, and 2) the non-linearities in the cash flows created by taxes and an uncertain mine life mean that the expected NPV value from a static analysis is not equal to the mean NPV value from the Monte Carlo exercise. In fact, the only way to estimate an expected value for this project is via Monte Carlo analysis.	Download For: Crystal Ball Level: Moderate

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COMMON USES & EXAMPLES

The following examples were provided by our customers and represent only some of the potential mining applications for Crystal Ball.

• Assessing comparative operational costs
• Develop risk profiles and NPV valuations of development projects
• Evaluation of engineering alternatives for environmental remediation projects
• Evaluation of operational and technical risks
• Evaluation of strategic coal supply options and investments
• Feasibility analysis on new projects and expansions
• Manage of Capital Investment Evaluation and Project Control
• Mine planning and mine operation decisions
• Probabilistic evaluation of various technologies and R&D projects
• Quantifying risks in terms of time and money for dredging tenders
• Run Monte Carlo simulations for real options analysis in capital investments
• Techno-economic evaluations and business planning
• Validate estimation cost and schedule

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