As the prices of metals slide, financial control of mineral processing operations becomes more and more important. Control of a mineral processing operation implies measurement of grades, recoveries and losses, with every effort being made to recover more product from the same feed. Shareholders become more concerned with the transparency of the operations and the corporate governance.There is only one way to achieve this and this is by sampling and making good use of the results of that sampling. Sampling systems that provide only 'rough' figures are not good enough. Similarly, a competitive position in the marketplace demands close control of product quality. Maximisation of product output demands that the product just meet the specification so that product yield is maximised. Decisions based on precise sampling results carry less risk that those based on imprecise results.This paper reports some recent advances in sampling theory that permit full quantification of sampling distributions, not just the sampling variance as has been possible in the past. These advances can be used together with simulation methods to tie down sampling precisions and develop calculations that quantify decision making risk when using the sampling results. A number of examples illustrate the use of the new advances and a final example indicates the development of risk analysis curves in the coupling of sampling precision to sale of a commodity.CITATION:Lyman, G J and Bourgeois, F S, 2015. Sampling, corporate governance and risk analysis, in Proceedings MetPlant 2015, pp 27-34 (The Australasian Institute of Mining and Metallurgy: Melbourne).