Organisations create and collect data across all areas of business and use data analytics to determine high-impact business metrics and return on investment. Data analytics in learning is the process of gathering and analysing data on a variety of learner metrics such as employee performance, application of skills and instructional design decisions.
Why is data analytics important?
Data learning analytics allow organisations to make smarter and more informed decisions, whilst empowering employees by providing them real-time visualisation of their performance. Incorporating analytics with learning, results in more comprehensive and in-depth understanding of our learners.
Data is important when measuring the effectiveness of course components and resources, allowing learning designers and developers to enhance and build better learning experiences, based on deep dives into learning content engagement. Learning designers can also identify patterns to improve student knowledge retention.
Data analytics can help monitor employee performance and application of skills, by analysing data collected on how an employee’s efficiency and performance has changed after completing training. Graphical data representations are a great methos of sharing an employee’s individual performance mapped against team or business area. This insight highlights which employees need support and which are performing well.
The most important business decisions are made using data. Implementing business solutions can be a big financial investment for organisations. Therefore using data to drive your learning development is one way to ensure that you are getting the most for your investment and improving employee performance.
