Learning professionals need a concrete strategy to develop a strong workforce. Corporate learning analytics is the most integral piece of this strategy that has a crucial role in cultivating a solid workforce. Collecting and analyzing people's learning data allows organizations to take action on opportunities to improve job performance.

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Learning analytics is essential for corporates to mitigate risk. It drives business performance. Risk and learner gap assessments allow organizations to make the best decisions for the business. This article discusses corporate learning analytics. Continue reading you understand how learning analytics can transform your organization!

What is Corporate Learning Analytics?

Corporate learning analytics is defined as “the measurement, collection, analysis, and reporting of data about learners, learning experiences, and learning programs, for purposes of understanding and optimizing learning and its impact on an organization’s performance.”

An essential component that completes the L&D activities, organizations, use analytics to check their efficiency, optimize costs, improve performance. Consequently, it supports its strategic objectives and positively influences employee engagement.

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Levels of learning analytics

Learning analytics has three levels:

  1. The learner: You should understand how learners interact and the content. Find out who is taking the course, who has completed it, who is doing and who needs support.
  2. The experience: At this level, you must examine if the content and structure align with the objectives. Please have a look at the feedback from the learners and how their engagement with the course. Ensure that the learning experience is adequate.
  3. The program: Evaluate the performance of the program. If you see any adoption trends, adopt them. Find out if you can qualify your return of investment.

How do you get this data?

You may get this data from you’re the following places:

  1. corporate learning management system
  2. from employee surveys
  3. human resources information system
  4. association management system

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What are the types of analytics?

The following are the different types of analytics based on the users’ needs. They help organizations to find answers to particular questions using various data types.

1. Descriptive analytics

The most basic form of analytics, descriptive analytics, collects data from various sources. The information you gain by applying it can help you make decisions regarding future training plans.

Descriptive analytics will help you find out:

Though these results will not give you a detailed insight, they will show you the outcomes. Descriptive analytics gives you a chance to make your conclusions and improvement plans. However, it does not provide many details.

2. Diagnostic analytics

Diagnostic analytics will help you determine both the outcomes and the causes of past events. It is limited to providing advanced practical information. It discovers the cause of a problem. However, a detailed study can reveal the scale of the situation. It can determine the areas that need further analysis.

3. Predictive analytics

Though it is impossible to foresee the future, the advanced data collection processes allow estimating. You can count the consequences of particular actions with predictive analytics. It is also able to find the probability of a given occurrence. It is based on approximate predictions and changes when other variables are introduced.

Modern predictive analytics tools are based on data science technologies. They use complicated algorithms and statistics. As it acquires data from several sources, its efficacy is improved. The use of predictive analytics in L&D is adapting the form of a course to the participants. Follow their previous preferences and engagement in learning processes.

4. Prescriptive analytics

Prescriptive analytics makes better and more precise decisions. It is pretty advanced and employs specialized algorithms to support optimization. Prescriptive analytics is used where there are large amounts.

Remember, you must decide if your organization must follow the generated recommendations. Your organization’s activities must be based on continuous and active cooperation with L&D experts, stakeholders, analysts, and planners, who can jointly make the best decisions supported by reliable data.

Best Practices for Analyzing Corporate Learning Programs

1. Proficiency Data

Learning analytics measures proficiency. Proficiency refers to the measurement of initial and subsequent understanding of a topic. But, why is it important? Simply because it is evidence of the growing skill sets of people. Without it, you will find it challenging to establish alignment between L&D initiatives and business goals.

2. Scenario-Based Assessment

Scenario-based assessments exhibit an accurate picture of learners’ capabilities. They engage learners at high levels and solve problems by activating cognitive and critical thinking.

3. Informative Analytics

Learning data helps executives figure out the business risks in their organization. They can self-reflect on managerial performance according to team preparedness. Through proficiency metrics, learners are provided transparent feedback to self-reflect and evaluate their own learning needs, performance, and progress.

How Can You Use Learning Analytics to Achieve Business Objectives?

According to L&D heads, the top teams want a data-driven approach from them. Learning analytics is gaining importance in the L&D skillset. So, what should you, as a learning professional, do to offer value to the business through learning analytics? Always start by looking at things from the customer’s point of view. Ask yourself, “What do they as a business organization need from me being their learning professional”?

How can my team use Learning Analytics to design a course?

1. Designing course content

L&D teams can design new course content by using data on employee performance history. This data can act as the foundation of your design process. The data regarding the interaction and engagement of the learner in the previous courses will help you understand what elements must be added to your course.

2. Adapting training courses

Existing content can be optimized by using data. There are course design approaches that promote content flexibility. Adaptive learning courses can offer tailored content depending on the learner’s behavior and performance. These can be understood using learning analytics.

3. Course assessment

Analytics can help in the assessment of a course. By collecting learners, you can contextualize your data and understand trends at a greater depth. These reveal areas where L&D teams can update content.

Learning Analytics Can Transform Corporate Training

Analyzing corporate learning can transform the following aspects:

1. The Learning Landscape

Organizations now deliver professional development through interactive online experiences. Learners can access the courses anywhere. Learning analytics helps organizations realize what is working, promote participation and engagement, and connect training impacts to business outcomes.

2. Learning and Organizational Outcomes

With modern corporate LMSs and technologies, it is easier to get data. But, analyzing data prove to be a challenge. Therefore, corporates need a well-defined data strategy. You must identify the data that’s most important to your organization. Prioritize which elements you want to analyze first based on your mission and vision.

3. Data Collection

There is much data out there, but only a small amount of data is being used. Commonly used data includes:

  • adoption
  • engagement
  • time on task
  • activity levels
  • progress

It’s critical that your organization analyzes and interprets its data within the proper context. On its own, an individual data point doesn’t mean much, and it’s easy for your stakeholders to misinterpret it. When you layer on a narrative and bring in your business’s goals and objectives, data becomes valuable, providing insights that can help transform knowledge into action and drive results.

4. Data Security

With more technology, there is more data, and thus the concerns about data increase. The learner, too, can have concerns about how data is used and protected. An organization can do the following things to establish data security:

  • Collect data that are relevant to your organization.
  • You can allow learners to express their opinions about data collection.
  • Store data for a limited amount of time
  • Work with technology providers who prioritize data security.

Organizations are responsible for the data they collect. Therefore, ensure you take the necessary steps to decrease the risk of data exposure.

5. Personalized Learning Experiences

Organizations are concerned about the work environments. Professionals prefer workplaces that put a priority on career development and advancement. According to LinkedIn Learning’s 2019 Workplace Learning Report, 94% of employees would stay with a company longer that invests in their learning and development. Therefore, personalized learning can be incredibly beneficial for both organizations and learners. And to provide personalized learning, it is essential to have data that reveals your employees’ learning styles and preferences.

6. Feedback Optimizes Learning

Creating feedback loops allows optimizing learning. Employees who receive daily feedback from their managers are three times more likely to be more engaged. Feedback could be an in-person conversation or as part of an online training program. However, it must be clear, actionable, and relevant.

Common Mistakes That Cause Failure

The most common mistakes made by L&D teams that use analytics are the following:

  1. The learning analytics strategy must be consistent and align with the organization’s strategic goals.
  2. Sometimes, L&D teams lack support from the organization.
  3. They have inadequate L&D tools. IT departments may treat them with less priority at times.
  4. Limited HR budget is insufficient for the costs of buying adequate tools and employing analytics.
  5. There are high expectations concerning quick return on investment.
  6. Lack of expertise and poor knowledge of basic and advanced tools.
  7. Lack of insightful analysis and understanding of the subject

Final Words

Remember, businesses are interested in what would happen by the year-end or quarter. They want to know how they can be sure that they reach their targets. Therefore, L&D professionals should talk about the data that matters to the business.

Business cares about how a particular situation they are going through would change. Information about the past is only compelling if it can help the business with critical issues it faces now and will meet in the future.

As a learning professional, you would be interested in the metrics that analyze every process stage. But the businesses are more interested in the measurable change in an employee’s performance and ROI. Keeping these in mind will help you make the best of corporate learning analytics and thus gain quantifiable changes.


Corporate Learning Analytics

Corporate Learning Analytics

Frequently Asked Questions (FAQs)

What are examples of learning analytics?

Learning analytics is used in the following cases:

  1. To track the learners’ progress and give feedback
  2. Monitor the learners’ activity
  3. To understand your learners
  4. Measure the impact of student engagement
  5. Help learners monitor their progress

What is learning analytics in business?

Learning analytics measures collect, analyze, and report learning data to understand the learning experiences in an organizational impact. By learning data and analytics, organizations can know if their training courses have desired business outcomes and improve employee productivity.

What are the benefits of learning analytics?

Here are a few reasons why learning analytics is beneficial:

  1. It helps to predict learners’ performance. Learning analytics can provide insight into how a learner will perform throughout the eLearning course.
  2. It provides learners with a personalized eLearning experience.
  3. Through learning analytics, eLearning professionals can custom tailor eLearning experiences for individual learners.
  4. It helps to improve future eLearning courses
  5. It boosts efficiency.

How can learning analytics contribute to human learning?

Learning Analytics provides new tools to study teaching and learning. L&D professionals gain new insights once the learning process is persistent and visible. It helps trainers to provide feedback to learners.

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