Analytics is the process of or approach to analyzing activities, processes or events. Learning analytics refers to the process or act of measuring an individual, system or organization’s performance. It can support the evaluation and improvement of training programs and identify areas of growth for individual learners, teams and organizations.

4 Components of Learning Analytics

There are four components of learning analytics: gathering, cleaning and validating, analyzing, and reporting on data.

1. Gathering Data

The first step in any analytics project is gathering data. In a training organization, there are many sources of such data, including a learning management system (LMS), performance management platforms and tools (e.g., performance reviews and 360-degree assessments), human resources (HR) platforms, customer relationship management (CRM) platforms, and other company repositories of information related to employee performance and training programs.

2. Cleaning and Validating Data

This step involves “scrubbing” data to ensure its accuracy and format it in a way that will be useful. The method used to clean and validate data varies depending on the program used for data collection and analysis. Regardless, it’s important to have accurate, easy-to-use data in order to analyze and interpret it correctly.

3. Analyzing Data

The process of data analysis typically involves using a program — anything from Excel to a sophisticated statistics program such as Tableau, R, SPSS or SAS — to create insights that can then be used to make decisions about training.

4. Reporting on Data

Finally, reporting involves putting the analyzed data into a format that is easy to consume, whether it’s a report, presentation or other format. This report typically includes not just the data but an interpretation of the data and recommendations based on the data — for example, not only the results of a training program but also recommendations on how to improve the program moving forward. The ability to communicate with data is a key skill for training managers; learning how to connect the data to your audience and then turn it into action will make your learning analytics more valuable.

Best Practices for Learning Analytics

Use Relevant Data

Data may be interesting to you, but if it’s not relevant to training or business goals, don’t include it in your analysis or reporting.

Use Technology

Many LMSs and other types of training software include some type of data collection, analysis and/or reporting feature. If you are unable to perform learning analytics with your existing tools, it may be a good idea to consider looking for an LMS that gives you those capabilities.

Develop a Learning Analytics Strategy

Don’t collect and analyze data without purpose. Establish clear objectives for your learning analytics initiatives, aligned to business goals, and develop a plan to meet those objective. Then, evaluate as needed.

Build Data Analysis Skills

Whether it means taking some training to upskill yourself or hiring a data analyst for your L&D team, ensure you have in-house capabilities to understand, interpret and use data.

Partner as Needed

On the other hand, Training Industry, Inc., research has found that of the one-third of training organizations that partner with vendors to offer training, half of them source learning analytics from a content development vendor, while others have a dedicated analytics vendor. If you don’t have analytics expertise in house, or if the analytics you are doing is particularly complex, look for a partner who can work with you in this area.

As technology advances, improving methods for collecting and analyzing data, and as the amount of data grows and grows, learning analytics presents an important opportunity for training teams to demonstrate and improve their impact.

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