It's Not You, It's Us: Using Data for Employee Retention
Chances are, your company's human resources (HR) department has a serious problem. If your company is like most, your HR team receives the least amount of analytics support of any department.
That's a shame because, given the high value of data about a company's most valuable resource, — its employees — a lack of analytics can lead to problems that drag down the bottom line.
For example, without proper analysis, it can be difficult to identify bad managers. The typical HR surveys often give decision-makers an overly general, subjective sense of how employees, including managers, are doing. However, hard data can provide a much clearer picture of employee performance based on nuanced, objective measures. These measures can include analysis of separation and promotion rates, salary increases, evaluation scores, employee engagement, and more.
Why doesn't every HR organization analyze this really important data in depth, just as the marketing department might analyze customers? Because conventional analysis takes too much time to be of any use before the damage is done. Damage in the form of missed earnings, under-performing employees, or the lose star performers who feel under-appreciated.
But here's the good news: there is a way to speed up the analysis of employee data: with data and artificial intelligence (AI).
Using AI To Understand Retention
AI can handle many of the tasks that have historically been handled by human analysts. This can be especially valuable to HR departments that don't have the resources to hire analysts. In addition, working on its own or in conjunction with human analysts, AI can yield significant additional benefits, such as:
- It has less chance of displaying bias in the decisions it helps to make, as long as the data underpinning those decisions is reliable.
- It's confidential; managers never need worry about it talking about what it's learned at the water cooler.
- It allows HR managers to deploy a data-driven approach to identifying the best employees within an organization based on objective factors. Armed with that knowledge, managers can take steps to increase the odds that those people will stay.
These advantages can make all the difference for HR departments and the organizations they serve—especially in competitive markets where employee retention is critical to success.
AI allows organizations to take a proactive approach to employee retention. It does so by predicting future retention rates from available data with the help of data modeling.
But you don't have to worry about how it works with the right platform. That's because an AI system does the number crunching for you in the background. Within just minutes, it can provide you with key insights for dramatically improving retention.
For example, consider an HR department with difficulty retaining technical personnel in a competitive field. The HR professionals in the department have always assumed they needed to throw money at the problem. So, their solution is to continually raise salaries. And it isn't long before they reach a higher salary than the national average for the specialties they need—without solving the retention problem.
After deploying an AI, like Ki, the HR team can plug in all their own employee data as well as third party data—for example, national compensation rates. As a result, they might find that their employees are not so much salary-sensitive as benefits-sensitive. In other words, the employees want more in company retirement matching, student loan repayment programs, and so on. Armed with the right answers, the team can then give employees what they need to feel happy about staying with the company, without unsustainable salary increases.
The analysis that helps solve previously intractable problems gets done quickly with the right data and metrics in combination with a powerful, yet easy-to-use AI-driven analytics platform. With good data analyzed by AI, HR teams can automatically find true correlations in their data instead of going with gut instinct that may lead them astray.
Taking a Proactive Approach
To identify employees most at risk of leaving, it's useful to sort them into meaningful segments based on various factors such as their tenure with your organization.
In the example above, an AI delivered insights into why employees were leaving a company. Going further, it can also estimate each employee's chances of staying within a given period, expressed as retention percentage. But it can also segment groups of those employees and give predicted retention percentages given different retention strategies applied to each segment.
For example, short-term employees may care more about continuous managerial feedback and review. Long-term employees probably care about retirement benefits, and professionals in creative fields may care about flex time. An AI can take in the unique wants and needs of each segment to help HR teams craft targeted retention strategies.
These are just some of the insights that AI can give you—providing that you keep track of the right data and metrics—and which allow you to take a proactive approach to employee retention.
Harnessing Data and AI for the Long Haul
Adopting a data-driven approach to retention can also serve your organization over the long haul by helping you adjust strategies as you go. Did a particular employee incentive plan deliver results? What about that compensation package designed to keep employees in a competitive industry?
A data-driven approach informed by AI will help you more quickly identify what's working and what isn't, empowering you to make adjustments much faster than you would in conventional approaches to employee retention.
In other words, data and AI give you the tools you need go from gut instinct to faster, more accurate analysis and execution.
Keyence has more than 40 years of success using data-guided business practices. Learn more about using AI and data to retain employees. Start by thinking of them as your most valuable customers, and download our guide: How to Target and Retain Your Best Customers.
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