Interpreting Survey Results
After you have collected an adequate number of responses to your survey, it's finally time to take a look at the data to see what they say. Gaining an accurate understanding of your survey results is the final step in the survey process (excluding any action you might take based on those results).
These tips are designed for employee satisfaction surveys or employee engagement surveys, but the same principles can be used for other types of surveys as well.
What's your n?
Before digging too far into your results, it's important to be sure you have an adequate number of responses. Whether you are looking at results from "all respondents" or just a demographic slice, you need to be sure enough employees responded to make the survey results statistically meaningful. How many respondents do you need? There is no hard and fast rule, but more is better. Our article on random sampling talks about sample size and statistical accuracy. In practical terms, realize that if you have a smaller number of respondents, you need much stronger results in order to draw conclusions from the numbers. For example, if you have just 10 respondents and they all said "strongly disagree" then you can probably trust that, but if just 7 out of 10 said "strongly disagree" then you might want to collect more data to be sure there is a trend there. On the other hand, if you have 1000 respondents and 700 of them said "strongly disagree" you can be pretty sure that this result is meaningful.
This concept is especially important to remember as you look at results for different employee demographic groups. Pay attention to cases where your n is low and realize that the conclusions you draw from the results for these smaller groups of employees are less certain than for larger groups.
Who's your n?
If you included demographic questions in your survey, then you may have a pretty good idea of who your respondents are, but keep in mind ways in which the respondents might not represent all of the people in your "population". For example, if you are surveying employees and your survey is conducted online, you are not likely to get much feedback from employees who don't use a computer. Every situation is unique and you should spend a bit of time thinking about the kinds of people who might be under represented in your survey results.