Evaluation and analysis methods – How to draw the right conclusions from employee surveys

Once the answers of a survey are collected, they need to be analyzed and set into context. With the right methods, the thought patterns and opinions of your employees can be identified. In turn, you can use the information gained to solve problems and optimize processes.

The following steps will help you get the most out of your survey results:

1. Preparing your data

Before starting the analysis of the survey, the gathered data should be prepared carefully. This guarantees a smooth procedure and improves the efficiency of the analysis. Two questions are crucial to be answered before starting the analysis.

What do we want to measure with our questions?

• Define the objectives of the survey. What do we want to know? The individual variables may be, for example, job satisfaction, turnover intention, well-being, or team spirit.

Which questions measure the same variable?

• Sometimes, several questions are used to understand one individual variable in a more thorough way. For example, “How satisfied are you with your workload?” and “How comfortable do you feel at your job?” could both question the variable “job satisfaction”.

Broadly speaking, there are different types of data analysis that can be used to retrieve information from the survey. Although these overlap and connect to each other, they can be separated into Descriptive Analysis, Diagnostic Analysis, and Prescriptive Analysis.

2. Descriptive Analysis – What happened?

The simplest way to start analyzing your data is to create descriptive statistics. They summarize information such as gender, age, education, or years employed. They also provide an overview of the variables that were measured.

The descriptive analysis can also be used to understand which variables are especially high or low in certain groups. Let’s assume that the goal of an employee survey is to understand the job satisfaction of your employees. The descriptive analysis summarizes the score of job satisfaction based on factors such as gender, age group, or department.

3. Diagnostic Analysis – Why did it happen?

The second step is a diagnostic analysis which answers the question of “What happened and why did it happen?”. Suppose the descriptive analysis showed a surprising result, for example, significantly lower job satisfaction in the sales department than in the finance department. In that case, it is now time to examine the reasons for this deviation. This step can often be done by observing additional variables and analyzing how they correlate. For example, it may be examined that the sales department has a lower team cohesion, which is the reason for the lower job satisfaction.

4. Prescriptive Analysis – What do we do now?

In the last step, the newly gained information is used to determine a course of action. In this process, solutions are sought for the problems uncovered.

If the previous analysis showed that job satisfaction in the sales department is lower due to less team cohesion, one solution may be to integrate regular team-building measures.

5. Open questions – Providing context to the results

Open questions offer insights into more in-depth results and provide more details. They also play an important role in the prescriptive analysis. Understanding thought patterns and gaining insight into employees’ ideas and wishes helps to improve processes and solve problems. 

Overall, open questions should be used as a complementary source of information that helps to put the results into context.

Analyzing engagement surveys can feel like opening a can of worms. Drawing the right conclusions from survey data requires a lot of skill and knowledge. At Edl Consulting, we have experience evaluating surveys and are happy to help. Contact us to learn more about employee surveys and to understand the patterns of your collected data.