AI Predictive Analytics for Your Employee Engagement Strategy

With data, HR teams can show a causal link between their initiatives and employee engagement. But what if you could draw similar links between variables throughout your organization and future employee engagement trends?

That’s the intersection of predictive analytics and employee engagement: using current information to identify future trends.

Predictive analytics is used in various industries, like HR, hospitality, finance, and military logistics. It consists of reviewing existing data to craft models that help predict future trends with mathematical formulas. This means you can uncover cause-and-effect relationships between present variables and future outcomes, leading to better decision-making.

Employee engagement defines your workforce’s dedication to the company’s mission, how they feel about their job, and their belief that their work contributes to a broader goal. When employee engagement is low, organizations see an increase in absenteeism, more turnover, and lower profits. High employee engagement leads to more productive teams, more creativity throughout the company, and more bang for your HR buck.

Keeping employee engagement high is a complex task. You have to see to each employee’s emotional needs, ensure they have a balanced workload, maintain their psychological safety, and more. There are hundreds of variables at work, and predictive analytics can help you identify which you should care about most and when you should care about them.

15Five’s Predictive Impact Model is just one way you can leverage AI to take on this challenge more efficiently, even if you’re not a data scientist by trade.

Key takeaways

• AI-powered predictive analytics transforms employee engagement strategies.
• Predictive analytics gives HR teams the tools to directly improve morale and employee retention.
• 15Five’s Predictive Impact Model puts AI-powered predictive analytics at your fingertips.
• AI-driven engagement models require careful implementation.
• The impact of predictive analytics can be measured with metrics like turnover, engagement score, and business performance.

Understanding predictive analytics for employee engagement

Predictive analytics requires significant statistical and mathematical know-how if done manually. You need to properly identify and calculate the necessary variables, apply models like linear regressions, and verify the output to avoid potential mistakes. AI-powered predictive analytics eliminates the need for that knowledge, giving you access to an AI data analyst that takes on the heavy lifting. That gives you breathing room to focus on areas where human judgment is actually needed, finding the important variables for your analysis, and using predictive models in your employee engagement initiatives.

Employee engagement can involve hundreds of variables, but its impacts on your organization are very real. Increases in turnover, dips in employee morale, and lower productivity are all examples of how low employee engagement can affect your teams. Predictive analytics gives HR teams the tools to use current data to predict these trends and begin drafting strategies to address them. For example, an HR team might use predictive analytics to estimate how a new hybrid work policy might affect turnover and absenteeism, allowing them to make a plan to mitigate these impacts.

AI-powered predictive analytics lead to real-time, data-driven insights, which are miles ahead of the data HR teams typically get from traditional engagement surveys. Imagine having a consistent stream of employee engagement data at your fingertips and knowing how this data might change in the future, all from a single dashboard. How much more could your teams achieve?

Benefits of AI-powered predictive analytics in employee engagement

For some organizations, using predictive analytics without AI would be essentially impossible, since it requires a significant level of technical skill. That being said, AI-powered predictive analytics comes with significant benefits for all organizations.

Proactive decision-making

Too many HR teams are reactive, dealing with employee engagement issues as they happen instead of trying to plan ahead. This leaves HR professionals on the back foot, needing to adapt to the situation as it happens. AI-powered predictive analytics gives HR a model for anticipating employee engagement trends in their organization without reviewing data manually. With these models, HR teams can regularly look through potential trends and make plans for addressing them.

Personalized engagement strategies

When you leverage AI for predictive data analytics, you significantly reduce the time it takes for your teams to produce models robust enough to build employment engagement strategies. Less time spent building models and crunching data leaves more time for building strategies, allowing you to tailor them to specific scenarios or even personalize them for individual teams.

Increased retention rates

Your organization’s retention rate is one of its most important employee engagement metrics. When replacing a former employee can cost as much as 150% of their annual salary for technical roles and 213% for C-Suite positions, you’ll want to invest in keeping them around. AI-powered predictive analytics can identify potential dips in employee retention before they happen, allowing your HR team to kickstart initiatives for preventing them.

Data-driven performance insights

Data-driven HR teams already have a better understanding of the struggles their workforce faces, which employees are their top performers, and what initiatives drive the best results. By adding predictive analytics to their toolkit, these teams can get that understanding sooner, getting insight into performance organization-wide that they can use to tailor their strategy.

How 15Five’s Predictive Impact Model enhances employee engagement

15Five’s Predictive Impact Model is the best way to put AI-powered predictive analytics at your HR team’s fingertips. Being part of 15Five’s Engage product, it allows you to get more out of every engagement survey, identifying trends and determining the impact they’ll have on employee engagement throughout your organization. 15Five’s Predictive Impact Model essentially operates in two stages:

• Prediction: Answers from your organization’s employee engagement surveys are compared to a database of over 600,000 surveys and analyzed to determine their impact on overall employee engagement.
• Explanation: 15Five turns each impactful statement into a Predictive Impact Score, which quantifies the improvement in employee engagement if the responses to that statement are improved. Leaders can then determine which areas of employee engagement they should focus on.

Think of 15Five’s Predictive Impact Model as your own private AI model for turning massive amounts of employee engagement data into quantifiable metrics that guide your efforts. Curious how that translates into real-world impacts? Here’s what 15Five customers are getting out of AI-powered engagement surveys:

• 35% of managers at Core Medical Group saw improved employee engagement, performance, and intent to stay throughout their teams.
• Employee turnover decreased by 88% at TrustRadius.
• Kreg Tool saw employee turnover decrease by over 20% and employee engagement skyrocket.

Want to learn more about 15Five’s Predictive Impact Model? Check out this guide, or get an overview of 15Five Engage here.

Implementing AI-driven analytics in your engagement strategy

Convinced AI-driven predictive analytics can impact your team? Here’s a step-by-step guide to implementing this in your organization.

Step 1: Find the right tool

If you’re not already using some kind of HR analytics or performance management platform, you’ll want to find the right one for your organization. Look for a tool that’s robust enough to support your current needs and scale with you as you grow. Evaluate its AI capabilities to determine if it can produce the insights your team needs.

Step 2: Implement employee engagement surveys and feedback channels

Before you can implement predictive analytics, you need data. The tool you select should allow you to send regular employee engagement surveys automatically and centralize replies for analysis. You just need to determine the cadence at which you want to send these surveys.

Step 3: Regularly review engagement data

Some organizations review employee engagement data once a year, while others do it once a quarter. If you want to get the most out of predictive analytics, you should review engagement data regularly to stay aware of evolving trends.

Step 4: Plan employee engagement improvement strategies

Use the employment engagement data your tools collect to inform your strategy. Keep that data available during brainstorming sessions, tie potential initiatives to key metrics, and plan how you’ll review each initiative’s impact.

Step 5: Monitor and improve employee engagement impacts

Regularly review the impacts of employee engagement initiatives on the metrics you track through predictive analytics. If you notice negative impacts on these metrics, make changes to your initiatives as needed. This allows you to consistently improve your employee engagement strategy over time.

Measuring success: Key metrics for AI-driven employee engagement

AI-powered predictive analytics tools will usually give you a crash course in the metrics you need to track employee engagement, but here’s a rundown of the most important ones:

• Engagement score trends: Engagement surveys can be boiled down to a single score that tells you how engaged individual employees are. Predictive analytics turns this data into a broader overview of engagement throughout your organization. You can track this over time to see how your strategy improves employee engagement.
• Turnover prediction vs. actual retention rates: Predictive analytics can turn employee engagement data into a prediction of employee turnover, raising a flag when you need to make reducing turnover a priority. But with these trends in hand, you’ll be able to compare predicted turnover with actual turnover rates, which is essential for determining the effectiveness of your strategy.
• Employee feedback analysis: AI-powered predictive analytics doesn’t just allow you to turn quantitative data into insights. It can also turn qualitative survey responses into data through sentiment analysis. Through this technology, AI tools analyze survey responses to gauge the overall mood and perspective of the writer, allowing you to get a broad view of multiple responses without having to read them all.
• Business performance impact: Predictive analytics gives you the data you need to tie employee engagement directly to business goals. This allows you to see how your strategies help improve your bottom line.

See the future with AI

Predictive analytics allows you to turn today’s data into tomorrow’s predictions. You get a better picture of employee engagement throughout the organization and can build models that tell you what engagement challenges you might run into, allowing you to prepare. The data analysis needed to make this happen is extensive, and doing it manually requires significant technical skill. That’s why AI-driven predictive analytics are growing more popular, and you’ll find this feature in HR platforms more and more.

15Five’s Predictive Impact Model turns employee engagement surveys and other data into actionable insights and models HR professionals can use to increase engagement throughout their organization.

Want to see what it can do? Check out our documentation here.