In today’s competitive business landscape, Learning and Development (L&D) programs are key drivers of employee growth, retention, and overall business success. Learning Management Systems (LMS) give organizations access to vast amounts of data on employee training performance. However, the real value of this data lies in how it’s analyzed and used to make informed, data-driven decisions. LMS Learning Analytics According to the 2021 Training Industry Report, training expenditure in the US rose to $92.3 billion in 2020–21.
This blog will explore how companies can harness LMS data analytics to improve corporate training programs. We will examine the types of data that LMS platforms generate, how to combine LMS and HR data for deeper insights, and how to turn that data into actionable decisions that can enhance employee development and boost business outcomes.
Why LMS Data Analytics Matters
Learning Management Systems collect a wealth of information on learners—everything from course completion rates to assessment scores and engagement levels. This data is a goldmine for organizations looking to:
- Evaluate the effectiveness of their training programs.
- Identify areas where employees may need additional support.
- Align learning initiatives with broader business goals.
- Justify the return on investment (ROI) of L&D initiatives.
With the right data analytics strategy, companies can move beyond surface-level insights and dig deeper into how their training programs are performing—and, more importantly, how they can improve.
Types of Data Available in LMS Systems
According to our 2024 Customer Education Benchmarks & Trends report—in which we commissioned Forrester to survey 300 education leaders at the director level or above—80% of high-success organizations consider “access to multiple types of data” important to running a successful customer education program.
Before diving into how to use LMS data analytics, it’s important to understand the kinds of data that are typically available. The following are key data points that an LMS generates, all of which can be used to inform decision-making
1. Course Completion Rates
One of the most basic data points is whether or not employees are completing assigned courses. High completion rates suggest that learners are engaged and motivated, while low rates may indicate that courses are too long, difficult, or not aligned with employees’ needs.
2. Time Spent on Training
The amount of time employees spend on training can reveal how invested they are in the learning material. Are learners rushing through courses, or are they taking the time to digest the content? This data can help L&D teams identify which courses are engaging employees and which might need adjustments.
3. Assessment Scores
Scores from quizzes and exams provide insight into how well employees are retaining the training material. High scores suggest that employees are mastering the content, while low scores may indicate that the material is too complex or not being delivered effectively.
4. Engagement Metrics
Engagement data includes metrics like how often employees log in, interact with content, and participate in discussions or collaborative learning activities. These insights can help L&D teams understand which aspects of the training are resonating with employees and which might need enhancement.
5. Competency Progress
Many LMS platforms allow organizations to track employee progress toward specific competencies or skills. This data is crucial for identifying skill gaps and tailoring training programs to ensure employees are developing the skills necessary to succeed in their roles.
Combining LMS and HR Data for Enhanced Decision-Making
While LMS data on its own provides valuable insights into employee learning, it becomes even more powerful when combined with HR data. By integrating data from both systems, organizations can gain a holistic view of their employee’s performance and development, making it easier to draw connections between training and overall business outcomes.
Here’s how you can combine LMS and HR data:
1. Employee Turnover vs. Training Engagement
By analyzing training engagement alongside employee turnover data, you can determine if there’s a correlation between employees who engage in training and those who stay with the company. If the data shows that employees who regularly participate in training programs are more likely to stay, it could indicate that training is contributing to employee satisfaction and retention.
2. Performance Reviews vs. Skill Development
Linking performance review data with LMS data allows you to see how training impacts job performance. For example, if employees who completed certain training programs receive higher performance ratings, it suggests that the training is effectively building the skills necessary for success in their roles.
3. Succession Planning and Learning Paths
HR data on employee tenure, potential, and career goals can be combined with LMS data on learning paths and competency development. This helps organizations identify high-potential employees who are excelling in their development programs and may be ready for leadership roles or promotions.
From Data to Decisions: How to Make LMS Insights Actionable
Once you have collected and integrated LMS and HR data, the next step is to synthesize it into actionable insights that inform decision-making. Here are some practical ways to leverage this data,
1. Evaluating Training Effectiveness
By analyzing course completion rates, assessment scores, and engagement metrics, you can identify which training programs are most effective. For example, if employees consistently score well on certain courses and engage with them regularly, it’s a sign that the material is resonating. Conversely, if a course has low completion rates and poor assessment scores, it may need to be revised or replaced.
2. Designing Personalized Learning Paths
LMS data allows you to see which employees are excelling and which may need additional support. By combining this data with HR information on job roles and performance, you can create personalized learning paths that address each employee’s specific needs. For example, high-performing employees might benefit from advanced training, while others may need refresher courses or additional support on key topics.
3. Measuring ROI on Training Programs
One of the most important benefits of LMS data analytics is its ability to measure the ROI of training programs. By comparing training investment to business outcomes such as improved performance, increased productivity, or reduced turnover, you can justify the cost of L&D initiatives and make informed decisions about future training investments.
4. Identifying Skill Gaps
Data on competency progress can help you identify skill gaps within your organization. For example, if certain teams or departments consistently struggle to develop key competencies, you can allocate resources to provide additional training and support. This ensures that employees are continuously developing the skills they need to meet organizational goals.
Examples of Data-Driven Decisions in Corporate Training
Let’s take a look at some real-world examples of decisions that can be informed by LMS data:
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Resource Allocation
If the data shows that certain courses have high completion rates and strong assessment scores, it makes sense to allocate more budget and resources to expand those programs. On the other hand, programs with low engagement and poor results may be discontinued or revamped.
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Talent Development
By tracking competency progress and combining it with HR data, organizations can identify employees who are excelling in their learning paths. These employees can be targeted for leadership development programs or other talent development initiatives.
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Compliance Adjustments
Compliance training is essential in many industries, and LMS data can reveal whether employees are completing mandatory courses on time. If certain regions or departments struggle with compliance training, you can adjust deadlines, provide reminders, or explore alternative formats to improve completion rates.
Conclusion: Making Smarter Decisions with LMS Data Analytics
LMS data analytics offers a powerful way to drive better decision-making in corporate training. By understanding the types of data available, combining LMS data with HR metrics, and synthesizing these insights, organizations can make informed decisions that lead to improved employee performance, higher engagement, and better business outcomes.
Organizations that effectively leverage LMS data can not only optimize their training programs but also align their learning initiatives with broader business goals. In the end, a data-driven approach to corporate training leads to more efficient use of resources and a more skilled, engaged workforce.