Crystal Ball Industry Examples

Mining Applications

 

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.

 

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 the mining 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 in Australia like Newmont Mining, Barrick Gold, BHP Billiton and Rio Tinto 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 Crystal Ball.

 

Crystal Ball is the tool chosen by more than 85% of the Fortune 500 companies. Like in the United States, Crystal Ball is the most popular choice in Australia and New Zealand to help improve spreadsheet modelling and risk analysis.

 

Crystal Ball Case Studies

 

Barrick Gold uses Monte Carlo Simulation to Evaluate Mining ProjectsNathan Stubina of Barrick Gold uses Crystal Ball software to perform Monte Carlo simulation and evaluate mining projects. With Crystal Ball, 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. In this way, project engineers can understand where to direct their focus.

 

Nathan Stubina holds a B.Eng from McGill University and a Ph.D in metallurgical engineering from the University of Toronto. Prior to joining Barrick, he worked as a Six Sigma Master Black Belt for Falconbridge and Noranda (now part of the Xstrata Group).  

 

A 1 hour presentation by Nathan Stubina on evaluating mining projects using Monte Carlo simulation is available online. View presentation>>

 

Optimising the Growth Portfolio of Kumba Resources
The application and benefits of Monte Carlo simulation in optimising the growth portfolio of Kumba Resources, a diversified mining company based in South Africa. View PDF report>>

 

Process Operating Costs with Applications in Mine Planning and Risk Analysis
This paper discusses techniques for estimating treatment plant operating costs, including identification of high impact cost areas and expected key cost variations year by year. View PDF report>>

 

Drill Bit Replacement 
Example Model for Crystal Ball, includes optimisations setting file and defines time as a decision variable. 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.

 

Mine Project Valuation Using Monte Carlo Analysis 
Example Model for Crystal Ball, a mining corporation is evaluating a small underground gold mining project containing an estimated one million ounces of gold. 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:

  • The correlations between the uncertain variables that are multiplicands. 

  • 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.
     

Other applications of Crystal Ball in the mining industryThe following examples were provided by 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