A fantastic onboarding program launched recently. Learners showed up, were engaged and everyone was happy. Right? The following month a leader asks the question: What data do you have to support the program was successful? If measurement is a part of your training design process, the answer should be easy — if it isn’t then that’s another story.

Nobody wants to be in a situation in which they’re unable to justify the effort and cost to design, develop and deliver training programs and whether the desired learning outcomes were actually achieved. However, many learning leaders don’t measure or prove training effectiveness because the data is too difficult to track and manage or they lack the understanding of what training analytics are available to them. This is why learning leaders must educate themselves on digital literacy and its importance.

Training analytics are the first step to understanding training effectiveness. By analyzing data on learner engagement, you can determine how effective your training program is so opportunities for improvement can be identified. In this article, we’ll review training analytics and how a learning leader can utilize it to assess training effectiveness. Before we look at that, let’s review what training analytics are.

What are Training Analytics?

Training analytics are the process of collecting, analyzing and interpreting data related to training programs. Training analytics can provide valuable insights into the effectiveness of training programs through identifying areas of improvement and validating the business impact for the organization.

Recommended training analytics to collect to support initial training effectiveness include:

Learner engagement. A training analytic that helps prove training effectiveness is learner engagement. Learner engagement measures learner participation and their engagement in the program. Learners who are engaged are more likely to recommend the program to others in the organization. Here are some best practices to measuring learner engagement:

• Feedback surveys are a simple and effective way to gather basic feedback from learners with questions usually relating to:
  • If the learner would recommend the training to a friend.
  • If the learner was satisfied with the training.
  • If the technology supported the learner adequately.
  • If the learner anticipates the learnings could apply to their work.

This information may be utilized to make improvements to the training or determine if the training is still needed.

• Learning management system (LMS) platforms track the time learners spend on each module, which modules they complete and assessment data including scoring and number of attempts. This data can be utilized to understand if learners are struggling or if improvements are warranted for the training to improve the learning experience.

Analytic tools. These collect data on training effectiveness. This may help determine if users viewed certain content information but did not consume the learning solution. Learning leaders use analytic tools in conjunction with a learning management system, learning experience platform or learning record store. Examples of common analytic tools could be Google Analytics or Adobe Analytics. These are commonly utilized to:

• Collect data on website traffic, user behavior, social media or other online activity.
• Process data such as filtering, sorting or aggregating data to determine trends.
• Visualize data such as charts, heatmaps or graphs.
• Provide insights related to website performance.

These tools can provide a learning leader with data to support improvement of the user experience or optimization of platform access.

Training Analytics To Improve Training

Once data is collected to establish training effectiveness, the next step is to analyze the data to validate the need for improvements. The following are steps may be taken to validate the data and to assess if improvements should be made:

Review the data: By analyzing learner engagement data, areas where learners are struggling or are disengaged may be identified. For example, if learners are skipping a particular section, this may indicate that the content is not relevant or engaging. You can use this information to make improvements to the training program, such as revising the content or adding more interactive elements.

Validate learner engagement against feedback data: Learner engagement data can help with personalization of the learning experience. For example, if learners are struggling with a particular topic or a particular question, changes can be applied to improve the experience and effectiveness.

Measure Impact against Outcomes: The best way to be able to answer the question all leaders must answer is to ensure you have documented clear outcomes of your training. What will learners do differently after the training and how that will impact the business. Learning leaders may fall short by creating a training outcome but never correlate this to how the change will impact the business when achieved. It’s also important to understand what the business impact will be if you do not meet your intended outcomes. How will this negatively impact the business?

If you follow the best practices laid out in this article, when the question about training effectiveness is asked, the answer will be clear.