he hypothetical employee satisfaction study in Exhibit 1 shows us how actual distribution and respondent distribution can impact analyses.
The Sales Department represents less than a fifth of employees (17%), yet they represented more than a quarter of feedback on the survey (27%). If the Sales Department feels strongly toward a specific question, it can give the appearance that the company feels this way as well. This department is over represented in the respondent based results/analysis.
On the other hand, a third (33%) of the company’s employees works in the Production Department, yet less than a fifth (16%) of the survey respondents works within this department. If their responses feel strongly toward a specific question, it may not be as evident in the overall results. This department is under represented in the respondent based results/analysis.
Apply or removing weight can help alleviate the issues of under or over representation. See Exhibit 2 for an example of the difference in results to questions when they are analyzed with and without weighting.
How to create/calculate basic weights
Using the same hypothetical employee survey from “ACME Corporation,” I will show you a simple means of creating individual weights to apply to each respondent’s answers. First, we need to determine to complexity of our weighting. In our example, we simply want to ensure each department has equal representation in the overall results, which means each respondent will have 1 of 8 possible weights apply to their responses.
How do we know these weights are accurate? First, when each weight is applied to the 750 respondents, the sum of the weights equals 750. Second, the sum of each department’s weights divided by the sum (750) equals the same percentage of the actual employee count. See Exhibit 4 for a demonstration.