I reviewed a marketing deck last month that contained seven charts. Three had truncated axes that exaggerated differences. Two used 3D effects that inverted apparent magnitudes. One used a pie chart to compare six similar-sized segments. None of the charts communicated what their creators apparently intended. This is far from unusual—chart mistakes are endemic in business communication, and they're not harmless. Bad charts lead to bad decisions based on misread data. The first mistake is truncating axes to exaggerate differences. A bar chart showing values of 98, 99, 100, and 101 with an axis starting at 97 makes the differences look dramatic. Starting the axis at zero shows the actual comparative magnitudes. Truncated axes are sometimes acceptable—for example, when showing temperature changes where zero isn't a meaningful baseline—but the choice must be intentional and disclosed. The second mistake is using 3D effects that distort data relationships. 3D pie charts make rear slices appear smaller than front slices of equal value. 3D bar charts with perspective make rear bars appear shorter or taller than front bars regardless of actual values. These effects don't add visual interest; they add confusion and inaccuracy. Use flat design everywhere. The third mistake is inappropriate pie chart use. Pie charts comparing more than four categories, pie charts with similar-sized slices, pie charts without labels, and pie charts in 3D all fail to communicate effectively. If you find yourself wanting a pie chart, ask whether a bar chart would serve the same comparison better. The answer is usually yes. The fourth mistake is ignoring the baseline in line charts. When line charts don't start at zero, apparent trends can be entirely misleading. A chart showing values jumping from 80 to 95 might look like explosive growth when the actual change is modest relative to the full scale. Use consistent baselines or clearly annotate non-zero baselines when they're necessary. The fifth mistake is overwhelming charts with excessive data. A line chart showing twelve different series becomes unreadable noise. A bar chart comparing twenty categories produces comparison fatigue. When you have too much data, consider small multiples, filtering to show only the most important series, or breaking the analysis into multiple focused charts. The sixth mistake is ignoring the colorblind. Red-green encoding—common in business reporting for highlighting negative versus positive values—excludes viewers with red-green color vision deficiency. Use colorblind-safe palettes or encode the same information through multiple channels (color plus symbol, or color plus line style). The seventh mistake is missing or inadequate labeling. Charts without clear titles, axis labels, and legends force viewers to guess at meaning. Every chart should be self-explanatory: someone seeing it without context should understand what it's showing without requiring explanation from you. The eighth mistake is inconsistent scaling across panels. In dashboards or reports with multiple charts, each chart should use consistent scales unless inconsistency is intentional and meaningful. Inconsistent scales across similar charts create confusion and make comparison impossible. The ninth mistake is choosing the wrong chart type for the data story. Using a pie chart for trend data, a line chart for categorical comparison, a bar chart for distribution—these mismatches force viewers to work against the visualization's natural reading. Match chart type to communication goal. The tenth mistake is presenting charts without context. Numbers without context require mental math to interpret. A revenue figure of 2.3 million means nothing without knowing whether that's above or below target, better or worse than last year, good or bad relative to peers. Provide context that lets viewers immediately understand whether the data is positive or negative, on-track or concerning.