I jumped straight to chart type and forgot to say anything about the axes for an embarrassingly long time.
Start by clarifying the chart's purpose and audience, then systematically critique it across data integrity, visual encoding, and clarity dimensions. Propose specific redesigns that address each issue, and explicitly discuss tradeoffs such as simplicity vs. detail and accuracy vs. aesthetics. Conclude by tying improvements back to better decision-making for the business.
Pro tip: Frame your critique around how the chart could mislead stakeholders or lead to suboptimal decisions, and always quantify the impact of your proposed changes where possible (e.g., 'reducing clutter could cut interpretation time by 30%').
Ask or infer who will use the chart and what decision it should support. This ensures your critique and redesign are aligned with business needs.
Evaluate the chart for problems in data accuracy, visual encoding (e.g., truncated axes, misleading scales), clarity (e.g., clutter, poor labels), and context (e.g., missing benchmarks).
Suggest specific improvements such as changing chart type, fixing axes, simplifying design, adding annotations, or using small multiples. Prioritize changes by impact.
For each proposed change, explain the tradeoffs: e.g., simplicity vs. detail, accuracy vs. aesthetics, or development effort vs. benefit. Show awareness of constraints.
Summarize how the redesigned chart will lead to better insights, faster decisions, or reduced misinterpretation, tying back to Amazon's customer-obsession and data-driven culture.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.