Several Clustering techniques are extensively tested and can be used to understand the employee behaviors using Machine Learning and make it possible for you to have a better insight into your internal Business Analytics. Some of the most effective methods or techniques that can be used for Data Analysis are – to use clustering to understand employees that didn’t take a satisfaction survey.

Some employees do not take the satisfaction survey due to several reasons – The reasons can be personal or based on organizational behavior. However, you need to know the reason behind that is to get optimal results from any employee satisfaction survey being conducted within your organization. 

Let’s explore some Clustering Methods in detail;

•  Density-based methods: These techniques are significantly used to classify a large group of employees to understand a pattern and trend, and also to identify a large number of employees who didn’t take an employee satisfaction survey. Density-based methods collectively classify the employees based on similarities and differences into distinctive groups through Analysis of Data to ensure you are getting a clear picture of the reasons that can cause the employees to not take Employee Satisfaction Survey.

•  Partition-based methods: These methods are proven to work out great to identify the reasons behind the employees not filling out an employee satisfaction survey. Partition-based methods work on ground facts and group the employees based on the reasons they were not able to take the survey; so you can work on eliminating those reasons and make more employees take the survey. The reasons can be employees on vacation, employees with the workload that did not manage to take the survey, and employees who did not want to take the survey. Once you identify these reasons, it will be easier for you to minimize at least two partitions and send-out surveys to employees on vacation and give a break to those with the workload to ensure the maximum number of employees can take the satisfaction survey.

•  Hierarchical Based Method: As the name signifies, Hierarchical based method classifies the employees who did not take employee satisfaction survey based on hierarchy and make you look at the clear picture that – which of the designations were not able to take the employee satisfaction survey. This can help you narrow down the reasons using the Partition Based Method and Density Technique to ensure optimal results through clustering in understanding the reason behind employees not taking the survey. It also helps in making efforts to eliminate those reasons and make it possible for everyone to take the survey.

A combination of different methods of clustering can be deployed to identify the reasons for employees not taking the employee satisfaction survey and eliminating those reasons. It can also help you find a resolution to the problems that are causing any hindrance in employee experience with their job role and the steps you can take to make it better for them. Should you wish to incorporate Clustering techniques to get better insights about your employees, feel free to contact NextBee today.