Are your employees engaged at work? Do they feel comfortable in their jobs, and are they likely to stay?
These are important questions for any business, but they’re difficult ones to answer. Although employee engagement is hard to measure, it is an important metric to monitor because it’s directly linked to retention and turnover. Companies with weak employee retention rates can have a revolving door of employees coming in and going out, which can create serious challenges for productivity, efficiency and internal culture.
The good news is that both employee engagement and employee retention can be measured, understood and improved by using data science and people analytics to understand the trends that are happening in your organization.
Figure out why turnover is happening. Maybe there are certain employees in your organization who are most likely to resign. Factors like salary, workload, opportunity for promotion or job function might be at play. Diagnostic analytics can help you better understand these trends and create strategies for the future. If you know which groups of employees are more likely to resign, your contingency planning will be more effective.
Determine what analytic tools you need. Effective data collection is based on choosing the right tools. Start by evaluating the tools you already have in place, such as an applicant tracking system or regular employee surveys. If you don’t have much data to work with yet, you may want to consider investing in new people analytics tools and updating the strategy for the ones you already have.
Clean and organize your data. Once you’ve put the right tools into place to gather data, it’s time to figure out what to do with all the information you’ve collected. Raw data isn’t always useful on its own. Depending on how it was collected, it may need to be organized in a spreadsheet or database. It may also need to be “cleaned” – checked for duplication or inaccuracies.
Build a data culture. Companies that are most likely to succeed with people analytics are those with a strong data culture. Having a data culture means having an organized process in place to deal with data. It means that data isn’t just collected, it’s also regularly used to make decisions. To build a strong data culture, you’ll need to make sure that all stakeholders in your company understand your data program and buy into it.
Keep in mind that people analytics is an ongoing process. Data collection and measurement should be happening continuously, so that you can gather enough meaningful data to identify trends over time.