Process plants are characterised by variability of performance over a wide range of time-scales; reflected in fluctuations in metal recovery, concentrate grade, plant throughput and reagent costs. In turn, these fluctuations impact financial metrics such as operating costs and revenue. The primary cause of plant variability is variation in the physical, lithological and mineralogical characteristics of the ore fed to the plant. The variability of the ore is driven by the intrinsic heterogeneity of the geology and mineralogy of the orebody, the mining method and mine production plan, the capacity to stockpile and blend, as well as the plant flow sheet and the level of plant automation. Whilst the impact of ore variability on process plants is universally recognised, it is rarely quantified in financial terms. Consequently, opportunities to reduce its impact are often overlooked due to the lack of a basis for a quantifiable cost-benefit analysis to justify improvement initiatives. This paper will present case studies using production data from the Renison tin concentrator and a zinc concentrator. These case studies demonstrate that as the standard deviation of plant head grade increases (as a proxy for ore variability), plant metal recovery subsequently reduces. The metal recovery is then converted into plant revenue losses, to quantify the economic impact of ore variability. The Renison case study demonstrated that whilst a very rare occurrence, revenue losses were as high as 34 per cent (relative to the baseline) when standard deviation was at its highest. The zinc concentrator case study demonstrated that revenue losses were as high as 6 per cent (relative to the baseline) when standard deviation was at its highest. Options are available for reducing and managing ore variability in the process plant. These options include changing mining practices so that the ore is fed to the plant with less variability, more advanced process plant control systems and the use of predictive geometallurgical models.