In industrial processes, the potential benefit that arises from improved control is assessed before the installation of a new control strategy. Estimating the economic benefit motivates the investment in a new control system and minimizes the risk of the new technology not living up to its promises. In this paper, a method for a priori estimation of the benefit from improved process control is presented. The method builds on conventional estimation techniques and evaluates the performance function associated with the controlled variable by assuming a reduction in variance. Three frequently used performance functions, namely, a quadratic performance function, a linear performance function with constraints, and the so-called clifftent performance function, are investigated. The profit index as a function of the variance is computed, and the implications of a reduction in variance for each performance function are assessed. A further contribution of this article is the analytical derivation of the optimal operating point of the controlled variable for a given performance function and a given variance. The estimated benefit from process control originates from a reduction in variance. Several approaches have been proposed to estimate and assess the variance reduction. Here, an index for the assessment of the current economic benefit incorporates the minimum achievable variance to estimate the reduction in variance. The economic benefit resulting from process control and the online monitoring index are demonstrated on an industrial refining process.