In this paper we present an overview of current status of control performance monitoring using minimum variance principles. Extensions to PID-achievable performance assessment, trade-off between performance and robustness, and trade-off between deterministic and stochastic performance objectives are discussed. Future directions are pointed out for research and practice with regard to root-cause diagnosis, plant-wide performance assessment, multivariable assessment, adequacy assessment of existing control strategies, performance assessment of model predictive control, and the use of intelligent field devices and artificial intelligence to form a systematic diagnostic methodology. A brief tutorial on performance assessment is given in the appendix with an industrial process example.