Taking Better Advantage of Learning Analytics

Analytics serve as barometers of a learner’s training progress. Analytics monitor key aspects of learning, including user engagement, commitment of resources, learner participation, and, of course, outcomes. Analytics accrue and process incredibly valuable information, all of which helps to illuminate Learning and Development programs and answer questions such as:

• Are your employees taking advantage of the training material?
• Is the material communicating the company’s training goals adequately?
• Are employees using the training to make individual progress?
• With the assistance of these analytics, is it apparent that company objectives are being met?
• Does any of the information gathered flag weaknesses, technical gaps, or other areas of concern?

It’s critical stuff.

Over the course of the last decade or so, the world of L&D has quickly evolved, morphing into an AI-driven digital ecosystem capable of serving up targeted, highly individualized learning designed to hit whatever objectives, strategic initiatives and corporate goals leadership deems worthy. The reason this can happen is due largely to the deep analysis learning analytics can produce.

The LinkedIn Workplace Learning Report found that 94% of employees are more likely to stay with an employer who invested in their skills and professional development. Additionally, 49% of workplace executives are concerned that employees do not have the right skills to execute our business strategy. And a full 91% agree that continuous learning is more important than ever for career success. This is why the emphasis has shifted to measuring learning analytics, to get a firm grasp on L&D effectiveness.

What are the Different Types of Learning Analytics?

Analytics can illustrate various aspects of learning. Here’s a breakdown of a few important areas:

• Descriptive: Deriving descriptive analytics uses the data of past events to understand how well the training experience for your employees tells the story of involvement, outcomes, and engagement.
• Diagnostic: Diagnostic analytics provide actionable insights into identifying educational patterns and why those patterns are surfacing.
• Predictive: Predictive analytics refer to the kind of information designed to foresee upcoming learning trends emerging from training or predicting potential outcomes.
• Prescriptive: Prescriptive analytics are designed to give educators recommendations or potential concepts based on a specific learning situation or problem. For example, if a company is experiencing a certain kind of deficit, prescriptive analytics can provide potential recommendations.

What Are the Benefits of Learning Analytics?

Obviously, the more data we can gather to assist us with goal-setting, gap-identification, trendspotting, and storytelling the better. The value mined from these analytics adds incredible insight into the very idea of running a business, let alone helping to guide the work of L&D leadership. Digging deeper, here are a few more:

It takes the guesswork out of making decisions. With so much information derived from analytics, you can see what types of training and education does and doesn’t work within a specific framework, as well as what engages your employees and what doesn’t.

Learning analytics help to predict outcomes and behaviors. Once you have gathered enough information, you can begin applying that data in the design of new/better learning paths or patching pathways that have not been serving up beneficial outcomes. With these sorts of analytics, you can be more strategic, and design learning programs that result in better performances, more engagement, and, ideally, a stronger outcome at the corporate level.

Analytics help to identify any outstanding issues, pinpoint problems along the learning path, and provide feedback to users and educators alike. Personalized data is the best way to determine what information, and what learning is getting through and what isn’t. When a specific educational module results in below-average scores or engagement, it can signify weak content, ill-conceived lessons, or content that is not suited to the user.

Here are a few ways business leaders can make good use of learning analytics tools:

• Identify skill gaps: Analyze data to pinpoint areas where employees require additional training.
• Monitor engagement: Track learner activity and identify potential disengagement issues within courses.
• Personalize learning paths: Adapt training content based on individual learner needs and performance.
• Measure training effectiveness: Evaluate the impact of training programs on employee performance and business outcomes.

How to Take Advantage of Learning Analytics

The success of learning data analysis and the use of the tools designed to extract data essentially relies on the staff charged with overseeing it. It is recommended that business leaders and learning administrators receive adequate training in order to extract, interpret, and apply data insights effectively.

There are a variety of impressive new tools designed to offer data analysis in the L&D world, and perhaps in another installment, we can go over some of the key players. But essentially, look for a few key features.

• Visualization: Most of us need to be able to visualize the data in order to interpret it correctly. Data is often complex, so presenting it visually makes that interpretation more intuitive.
• Customized Reporting: Emerging tools allow the generation of customized reports tailored to specific parameters. They can also identify specific gaps or weaknesses that might be keeping a department or organization from meeting objectives, deadlines, initiatives, or otherwise.
• Predictive Reporting: Forecasting performance based on the data extracted from analytics helps to proactively address blind spots or gaps, as well as areas of strength.
• Friendly Interfaces: Most of us don’t have the technical skills required to analyze data, so it’s critical for your tools to be accessible and user-friendly. There’s nothing more frustrating than mustering up the energy to delve into something super-technical only to discover that it’s way more technical than it needs to be.

A Boon to Business

This wealth of dataflow is a boon to businesses without a doubt, especially those businesses who have capabilities of assessing and deciphering the data—not to mention securing it—and making actionable determinations from it. User-friendly interfaces like dashboards inspire users and educators alike to identify their patterns, strengths, and weaknesses. That same data can also act as an early warning system, flagging issues before they become problems, and helping L&D initiatives keep their forward momentum.

Nearly 50% of career development champions (a designation implemented by LinkedIn) use internal data and analytics tools to identify skill gaps, allowing them to gain quick and critical insight into what may be holding their organization back from meeting its goals. Make no mistake, this is a transformative approach, leveraging data to drive decisions, strengthen performances, personalize learning, refine engagement, and improve outcomes.