Bias Temperature Instability (BTI) is one of the most crucial reliability issues in modern CMOS technology. It leads to shift in device parameters, which eventually affect circuit performance. SRAM is a widely used circuit which occupies a considerable area in microprocessors. Hence it is important to understand the impact of BTI on performance/stability of SRAM. As device degradation due to BTI depends on gate activity, SRAM performance strongly depends on the data stored in the cell. In this paper, the gate activity is incorporated by activity factor ‘α’ which takes into account the various data patterns stored in the cell. Although many studies have reported the impact of BTI on SRAM performance, none focused on the worst degradation scenario. Our analysis with varying activity factor ‘α’ provides an opportunity to identify the data pattern for worst case degradation. Shift in threshold voltage due to BTI is modelled according to continuous and non-continuous applied gate bias, using physics-based compact model. Process variability is incorporated using Monte Carlo (MC) simulations and worst-case degradation at distribution tail is identified. In this paper, we consolidate various SRAM performance metrics from literature over the last three decades and demonstrate the impact of BTI and process variability with activity factor ‘α’ on these metrics. © 2020 Elsevier B.V.