Sensitivity analysis has been identified as a very important tool for the quantification of the impact of uncertain parameters on the result of a model simulation. Take for instance, the case of a Swedish commercial real estate firm performing a financial assessment of various heat supply option for their property portfolio; for example between air source heat pumps and district heating. Given nominal values (i.e. "guesstimates") of parameters, the firm will be able to do a calculation of the net present value of both options and determine which of them the most cost effective one is. However the assumption of these calculations is that all parameters are known with certainty and that they do not evolve over time. It is however crucial to consider the effect of varying electricity prices, district heat prices, service maintenance costs, interest rates, coefficient of performance for the heat pump, capital costs assumptions of connection costs for district heating or for necessary reinforcement of the electric grid to install a heat pump etc. It is already easy to see that an apparently simple economic calculation requires a careful assessment of uncertainty.

Most existing commercial sensitivity analysis tools are based on "one-factor-at-a-time" (OAT) methods that do not consider interactions between parameters. Ockham is based on the class of "global sensitivity analysis" methods (GSA) which consider these parameter interactions and have been recognized as a safer way to perform uncertainty assessment.