The reader needs a context for interpreting all the data you report.
Imagine that you analyzed the behavior of 100 firms in your industry from several sources. The reader needs to know: Is this a small sample of the industry or is it all firms in the industry? Are the data potentially biased, that is, representing only certain types of firms or only a small number of firms?
Put the information right where it’s needed to keep the numbers in context.
- Remind the reader of the source of the data (e.g., government reports, survey data).
- Provide the sample or sub-sample size.
- Caution the reader if certain results may be biased (e.g., representing only public firms, only the small percentage that provided data).
What should you do?
- Use descriptive titles, headings, subheadings, and footnotes in text, tables, charts and graphs.
- Where necessary, add caveats such as “of the four percent who reported these data” or “of the 22% who reported problems.” Such cautions do not undermine your report but enhance its value in decision-making.
A good test is whether the page or section can stand alone. Does it have all the details needed to interpret the data correctly?