We are moving into an era where we experience the consequences of the skills crisis - namely many resource models have been generated by inexperienced people under pressure to deliver high quality resource estimates in unsupported environments, often without technical mentors. These resource models form the basis of our decision to pursue actual mining. This begs the question: how valid are the resource models that form the basis of our mining decisions? This paper presents various model validation tools such as comparison of input and output statistics, swath plots, sectional or bench comparisons between drill holes and models as well as a variety of other approaches._x000D_
Each model validation tool currently used in industry is examined: how the tool generates results, what assumptions exist, what constitutes a pass/fail in the test, and what interpretations to consider when using the validation tool._x000D_
Each validation tool's suitability and the inherent flaws in the underlying assumptions are also discussed. These are supported with examples of good versus bad validations._x000D_
Our principles based reporting codes provide flexibility in how models are generated and what approaches and/or parameters are used to generate resource estimates. This flexibility works well when used by experienced practitioners. However, our reporting codes assume a level of experience not always available in the current skills crisis. This paper seeks to provide minimum model validation prerequisites for model acceptance and suitability, regardless of the resource analyst's experience. As we move forward, our immediate challenge is to ensure our baseline resource models are material, transparent and competent.