Conventionally, randomized controlled trials focus on the overall effect of a treatment on the primary efficacy endpoint, assuming that the overall treatment effect is applicable to the entire patient population under study. This paper presentation explores some approaches for possible improvement on the design and analysis of conventional subgroup analysis in a fixed design setting. I shall articulate on formation of clinically relevant subgroups from baseline characteristics, the probability of observing directionally-statistically consistent-inconsistent treatment effects, an interaction-to-overall effect ratio relative to likelihood of a predictor, the roles of interaction test, design consideration, and challenges with full reliance of a single controlled trial. In contrast to the commonly used forest plot for subgroup result summary, a standardized forest plot will be introduced for pre-specified baseline subgrouping factors that may be of supportive interests. Hypothetical or published examples will be used for illustration.