This visualization presents a gender-based comparison of hex standoff performance across six variants. Each variant represents a distinct interaction scenario, measured by two cohorts: male and female users. The metric range is 0 to 100, where higher values indicate better performance in terms of efficiency, stability, and user comfort during hex engagement tasks. The goal is to explore whether there are gender-related trends in peak performance when interacting with hex standoffs under varying variants, and to identify which variants provide the most balanced outcomes. From the chart, we observe that for Variant 1 and Variant 2, male performance sits slightly above female by about 7–10 points, suggesting a modest difference in response or manipulation ease under these configurations. In Variant 3, female scores rise closer to male scores, reflecting improved ergonomics or control perception for that variant. Variant 4 shows a pronounced advantage for female users, with scores near parity and a slight female lead at higher engagement demands. Variant 5 again shows a male preference, though the difference narrows. Variant 6 presents the strongest overall results, with both genders achieving high scores, while males maintain a marginal lead. These patterns may reflect several factors, including ergonomics, hand size, force application, and familiarity with similar mechanisms. The results highlight the importance of inclusive design, ensuring that tool interfaces accommodate diverse user attributes so peak performance is accessible across groups. Practically, product teams could use these insights to tune standoff geometry, grip texture, and actuation force to reduce performance gaps and enhance user satisfaction. By continuously monitoring gender-variant performance, manufacturers can improve ergonomic guidelines, refine quality checks, and support a broader range of users to achieve optimal performance in real-world tasks during 2025 and beyond. Additionally, Variant 6 appears to be the most effective overall, suggesting that the design changes align with user preferences and comfort across cohorts. Future work could incorporate more dimensions such as grip strength and prior experience to enrich the model and support data-driven decisions for a wider user base. The analysis demonstrates how data-driven design decisions can help ensure inclusive peak performance across diverse user groups.