4 Data Visualization

Choose a chart for the question

A business visualization turns data into a form people can interpret and act on. A good chart makes the relevant comparison or pattern easy to see without distorting the evidence.

Start by identifying the decision or question the chart should support. Then choose a visual form that makes the relationship clear. Common purposes include comparing values, showing change over time, examining distributions, and describing relationships between variables.

• To compare values across categories, use a Bar chart; for example, compare revenue across product categories.

• To show change over time, use a Line chart; for example, track monthly revenue across several years.

• To examine distributions, use a Histogram or Box plot; examples include order sizes and delivery times.

• To examine whether two measures move together, use a Scatterplot; for example, compare advertising spend with sales by region.

• To show how a total is divided among a few components, use a Stacked bar chart; for example, show a small number of sales channels’ shares of total sales.

Prefer familiar, simple charts. A chart can show several relationships, but combining them may make interpretation harder. Use separate charts when they communicate the point more clearly.

Make comparisons fair

Chart design affects whether comparisons are fair. Bar length encodes magnitude, so use a zero baseline for bar charts; a truncated axis can exaggerate differences. For line charts, a nonzero baseline may be appropriate when the purpose is to show small changes, but label the scale clearly and provide enough context to avoid overstating the trend.

Keep scales consistent when comparing separate charts or groups. Different axis ranges can make similar values appear very different. Label units and time periods so readers can distinguish, for example, dollars from thousands of dollars and monthly totals from annual totals.

Show context that could affect how a result is understood, including targets, benchmarks, sample sizes, and data limitations. Explain any reference line or unusual scale.

Make charts readable and accessible

Write a concise title that states the main finding or comparison. Label axes and categories in plain language, and use direct labels when they make a legend unnecessary. Remove decorative effects such as 3-D shapes, heavy borders, or unnecessary backgrounds when they compete with the data. Use restrained gridlines as reading aids rather than visual features.

Use color purposefully and consistently, but do not rely on color alone to distinguish important groups. Add labels, patterns, or other cues so the chart remains understandable to people with color-vision differences and when printed in grayscale.

For accessibility, provide a text description of the chart’s key message. When readers need to retrieve exact values, also provide the data in a table.

Apply the principles to sales performance

Suppose a manager wants to know whether quarterly revenue is meeting its target. A Line chart can show revenue over time, with the target clearly labeled. Use a consistent currency unit, identify the quarters, and title the chart with the main takeaway, such as “Revenue exceeded the target in three of the last four quarters.”

If the chart compares teams, use the same vertical scale for each team so differences are not caused by inconsistent axes. More broadly, choose charts according to the comparison or pattern the audience needs to understand, and combine honest scales, explicit labels, consistent comparisons, relevant context, and accessible text so business readers can interpret results accurately and use them confidently.