Leveraging Analytics to Personalize Employee Development

Data analytics is an increasingly prevalent part of the business landscape. It’s used to predict market changes, develop risk profiles, and even influence investments. But do data analytics have a place in employee learning and development?

The short answer is: Yes.

Each worker has unique skills, challenges, and ambitions. Data analytics can play a powerful role in creating more impactful outcomes by creating personalized learning plans.

Let’s look at how you can leverage analytics to personalize employee development.

Why Personalize Employee Learning & Development?

To adopt and manage data analytics, you need time, expertise, and capital. If that’s the case, we need to understand if it’s worth personalizing employee development, or not.

Personalized training allows you to adapt individual learning paths to better align an employee’s learning with their career goals. Personalization that considers individual employees’ career ambitions can also result in a more diverse range of knowledge and abilities. This practice of engaging and developing employees can make for a more agile and robust business.

3 Examples of Personalized Learning

Personalized learning can come in many forms—and it can be broadly personalized (such as to a team or department) or individually personalized (to each unique employee). 

1. Personalize presentations with employee data.

Some traditional approaches to development tend to be less engaging for learners. The “death by PowerPoint” effect  many companies experience when they rely too heavily on a lecture-and-slide style of delivering information is a good example. Reading directly from text in slides and keeping presentations fast-paced are good practices. However, taking the time to personalize these presentations based on data about your employees can make the presentations more engaging and memorable. For instance, tying examples within the content to team memories, goals, or scenarios.

2. Use role-play to personalize learning.

Role-playing scenarios are another great way to support theory with practice. Role-plays allow you to tailor the script for each scenario to the learner’s personality and their individual challenges with the topic. Employees can also swap role-playing partners to experience a more diverse and unique range of scenarios. 

3. Provide options for learning content.

Using analytics to create a more personalized learning experience can make education more accessible. Not every learner learns the same way. And how they learn can also depend on the topic or learning objectives.For example, some may find written materials more challenging to process, instead grasping concepts better by performing related tasks. Analytics focused on what methods learners are most responsive to can help tailor the curriculum to have the best outcomes for everyone involved. 

4. Use a platform that can personalize learning for you.

Just like how Netflix personalizes suggestions based on your viewing history, you can apply this type of “bottoms-up” personalization to your learning programs. Platforms like Intellum offer AI-driven personalization to reach learners with content that’s relevant for them, based on their role, goals, and past activity.

What Data Should You Use—And Where Can You Find It? 

More and more, there’s an increase in the availability of data you can use to personalize your learning and development programs. Whatever platform you use, make sure it’s able to accurately capture and report on individual, job-level, and team-level data you can use to inform your personalization strategies.

A few tools you might use are:

• HR Analytics software: A solid HR analytics software (sometimes found within your HRIS) captures a range of information on your workforce. In many cases, it will collect data related to attendance, individual employee performance over time, and specific skills gaps in both specific workers and across the company. This can be a useful tool to get bigger-picture insights that enable you to pair employee needs with the company’s needs and establish a mutually beneficial development plan. 
• Learning management software (LMS): Your LMS can provide you with essential data related to each learner’s individual development journey with the company. Choosing the right LMS should enable you to easily access in-built reports on individuals’ progress, including areas the learner may be struggling or excelling. Some platforms (like Intellum) allow you to use the data to trigger personalized recommendations of courses and materials. 
• Survey and feedback platforms: Many of the most useful insights you can gain will be directly from the learners themselves. Conducting employee surveys and using feedback platforms makes it more convenient to deliver employee experience requests regularly and receive nuanced information from individuals so you can personalize their learning. Many also have built-in analytics so you can see common issues across the company to address. If you send employee engagement surveys, these can also provide useful insights for personalization.

Remember: Analytics technology is developing at a rapid pace. A good example of this is the emergence of artificial intelligence (AI) driven predictive analytics software. In the near future, this has the potential to assess holistic and individual development information and make predictions on the types of learning paths that produce the best outcomes. It’s vital to stay on top of these changes to establish how they can fit into your ongoing learning plans. 

Make Data Usage Transparent

Using data to establish more personalized learning plans can be beneficial. Nevertheless, as with any other area of data use, it’s important to approach the process responsibly. One of the best practices is to be transparent with learners about how and why you’re using data to influence your plans for them.

During onboarding—or in one-on-one meetings, if this is a new practice across the company—talk to workers about the data you’re capturing and using. Explain what specific data points are captured and why these are relevant to their personalized learning. Reassure them you’ll only store information that’s strictly necessary for these purposes. This can help to build a more trusting relationship between the business and learners.

Another best practice: Rather than dictating learning plans based on data, make learners a part of the process. Show them the analytics results and talk them through what you think that means for their learning path. Invite them to raise concerns, disagreements, and suggestions. Data analytics isn’t infallible—having a conversation can provide more nuanced insights that inform the process moving forward. Additionally, it can make learners feel actively in control of their path, which may make them more engaged with the process and value your willingness to invest in them.

Lead the Way With Data

Data analytics can be a key to personalized learning that ensures learners get a more engaging experience and companies benefit from workers with the most relevant skills. Efficacy requires adopting reliable analytics tools for your business and keeping learners meaningfully involved with designing their education.Commit to regular analysis of your analytics approach, and keep track of what seems to be working and how accurate the results are. This will allow you to finetune your collection and interpretation processes to get the best insights.