3 Ways to Boost Corporate Learning With Predictive Analytics

We know that strong corporate learning and development programs are essential to not only attracting and retaining employees but also ensuring they have the skills required to confidently perform their jobs today and in the future. Yet with the rapid changes facing your organization, how can you make sure your programs are keeping up?

Careful attention to learning analytics can give you the insights you need. While there are many ways to analyze the rich collection of big data that exists in your learning management system (LMS), predictive analytics are among the most powerful. In this post, we’ll define the term and look at some of the ways a corporate learning management system like D2L Brightspace can change the way you engage with learners in your organization.

What Is Predictive Analytics?

Predictive analytics is a specific type of data analysis that uses existing data to predict possible trends and outcomes. In corporate learning, predictive analytics can be used to forecast training needs and personalize the learning experience so that every learner has access to engaging and relevant learning pathways. That sounds straightforward, but in practice it can be a little trickier.

“Organizing data to answer questions about usage and results is simple, but identifying trends isn’t always apparent, especially when you’re facilitating a large group of learners.”

– Randolph Streich, senior solutions engineer, D2L

---

Fortunately, advances in technology, algorithms and machine learning have made complex data analysis accessible to anyone with the right tools. For example, the tools in the D2L Brightspace Performance+ suite can analyze all of the rich data that exists in Brightspace to give administrators insights they can use to support learners.

3 Ways to Use Predictive Analytics to Boost Corporate Learning

1. Personalize the Employee Learning Experience

Personalized learning pathways play a crucial role in employee training and development. Predictive analytics can help with creating and optimizing them by identifying the unique training needs of each employee. Sophisticated algorithms can automatically customize the available content and activities, provide specific resources, and make future course recommendations based on how an individual is performing.

Brightspace Tip: Release Conditions in Brightspace can put these insights into action. Administrators can set parameters that will trigger the release of additional content so that when someone is struggling, they can access content to help close the gap, and where they excel, they can take on more challenging activities.

2. Proactively Identify At-Risk Learners

Since predictive analytics identifies patterns and trends, it can be used to flag when learners could be at risk before their performance falls too far behind. If a learner isn’t doing things that typically lead to successful outcomes, instructors can see that and get involved early so that no one falls through the cracks.

Brightspace Tip: Setting up Intelligent Agents automates the work of being proactive. Instructors can write messages that are sent to learners who trigger specified conditions, nurturing participation and offering helpful suggestions. A friendly nudge to someone who hasn’t logged in for a while, or an invitation to schedule a chat sent when someone doesn’t engage in specific tasks, may be all it takes to get someone back on track.

“If you can dream up an if/then rule, chances are you can figure out a way to reach those learners.”

– Anneka Moline, senior solutions engineer at D2L

---

3. Improve Your Corporate Training Programs

Not only can predictive analytics help individuals succeed on their learning pathways, but it also can help organizations improve their training offerings. For example:

• Trends in enrollment and completion of a module over time mirror trends in perceived relevance of the content. Following these trends will let you know when it’s time to refresh a course or rethink it altogether.
• If the outcomes in a training program don’t predict intended performance on the job or in future training, you know the program is not meeting the goals it was designed to.
• If there are unintended biases or barriers embedded in training programs, predictive analytics can shed light by highlighting areas where factors like employee background or shared experiences at the organization are stronger predictors of success than are behavioral factors.

Insights into changing learner behavior over time can give you strong indications of where your programs are making an impact and where they need to be improved.

Brightspace Tip: The rich data sets and visualization tools in Brightspace make it easy to identify and understand trends and patterns so you know exactly what’s going on in your learning programs. This allows you to make data-driven decisions to optimize both your employees’ learning experiences and the overall value of your learning programs to all stakeholders.

Bonus: Level Up Your Organizational Planning

The benefits of predictive learning analytics aren’t limited to the learning and development function — they also can provide a wealth of insights to boost your planning across the organization. Consider how powerful predictive analytics is for things like:

• detecting and closing specialized skills gaps across the organization
• focusing on the skills and competencies needed to achieve the organizational culture you want to be known for
• spotting individuals with skills and interests you didn’t know they had and making sure they have opportunities to discuss their development with managers or mentors
• identifying high performers who should be considered for leadership development

Predictive analytics provides a wealth of actionable insights that are based on real patterns of behavior and achievement in your learning programs.

Get more information on how D2L can help support your learners by watching our Supporting At-Risk Learners with Predictive Analytics webinar

Written by

Emma Sandrock

Emma Sandrock is a Customer Marketing Manager at D2L, with customer-centric focus in the corporate learning space. She has a passion for creating engaging and valuable experiences for D2L customers through marketing channels. Emma holds a Bachelor of Arts degree from McGill University.