Business Case Studies & Business Publications

The Silver Crest Mine

Alizamir, Saed, Ba...

Case

The Silver Crest Mine

Alizamir, Saed; Baucells, Manel

QA-0964 | Published August 13, 2025 | 9 Pages Case

Collection: Darden School of Business

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In this case, students explore decision-making under uncertainty and apply dynamic programming (DP), a powerful tool for optimizing sequential decisions. Set in the context of the ore mining industry, the case revolves around a strategic auction for a 10-year lease of the Silver Crest Mine (Silver Crest), recently reopened due to a rise in silver prices. Two firms—TerraGold and MineralCorp—are the sole qualified bidders. The auction winner secures exclusive rights to operate the mine for the next decade and can make annual decisions on whether to keep the mine open or close it down. Silver produced during any operational year is sold at that year’s prevailing market price, which is highly volatile and follows a stochastic process. The central challenge lies in valuing the lease. To do so, each firm must account not only for the expected future trajectory of silver prices but also for the irreversible fixed costs of opening and closing the mine. Further, MineralCorp benefits from access to a high-efficiency continuous miner, which reduces its per-ounce operating cost, while TerraGold possesses advanced analytical expertise and leverages DP to construct an operating policy adaptable to evolving market conditions. Working from TerraGold’s perspective, students develop a bidding strategy informed by dynamic optimization. At the University of Virginia Darden School of Business, this case is used in the Executive MBA core Decision Analysis course as part of a three-session module on DP. It can be taught in a core course in Decision Analysis or Business Analytics, or as part of an elective on Optimization or Quantitative Methods for Management. In all settings, we strongly recommend using this case with the companion technical note, “Introduction to Dynamic Programming” (UVA-QA-0955).

- Apply decision-making tools under uncertainty, including expected value, binomial trees, and discounted cash flow (DCF), in a realistic, stochastic setting. - Understand the fundamentals of DP—including system states, actions, transition probabilities, immediate rewards, and value-to-go—and how the method supports optimal sequential decision-making. - Contrast static versus dynamic strategies, and recognize the strategic advantage of flexible, state-dependent policies in managing operational decisions. - Evaluate the economic value of flexibility, especially in contexts where fixed costs and uncertain market conditions create meaningful trade-offs over time. - Interpret and implement dynamic policies, using dynamic programming outputs to determine optimal decisions across different price paths and mine statuses. - Compare dynamic valuation with traditional DCF approaches, highlighting when and why DCF may underestimate the value of projects with embedded options or path dependencies. - Appreciate how analytical sophistication can drive strategic advantage, particularly when competing firms differ in tools, capabilities, or cost structures.