Learning Data Analytics: 2023 L&D Trends

Learning Data Analytics: Define KPIs, Leverage Data, Increase Performance

According to Gartner [1], by 2024, organizations that fail to build sustainable and scalable data analytics frameworks will likely experience at least two years of performance decline. In learning and development (L&D), data analytics has become key and will rule in 2023. Collecting data on learner preferences at the individual, cohort, and organizational levels can be not only informative, but critical to organizational growth and performance outcomes. This article explores four tactics for using learning analytics data to increase business results.

Define student-centered key performance indicators (KPIs)

Perhaps the most significant challenge L&D has faced over the years is how to measure the return on investment (ROI) of learning. There are more than eight models available in L&D for evaluating the return on investment in learning, including the highly effective Kirkpatrick New World Model and the Philips model. Borrowing KPIs from software development and adapting them to learn product-specific key performance indicators (KPIs) can complement measurement insights from these models. KPIs such as product adherence, product adoption, product growth, and product engagement can provide information about learner behavior and engagement with the learning product. This data will allow you and your L&D team to evaluate your various learning products in terms of their value to the learner and allocate your limited resources accordingly to improve existing products that learners like by scrapping those that learners never engage with, and you improve the ones that show potential.

Student-centered, curated learning

Many learning management systems (LMS) and systems for learning (LXP) use an application program interface (xAPI) [2], either directly or through the Learning Record Store (LRS). This capability enables you to collect, manage, store, track, and analyze accurate data about student microbehaviors across a variety of learning experiences. This data may include each learner’s preferred modality when they choose to learn, how long they spend learning in each type of asset, what they look for, who they connect with, and how they prefer to be reminded of learning opportunities, such as others. This information is useful to you, your L&D team and your wider organization as it can identify learner preferences, needs and wants at individual, cohort and organizational levels, which in turn allows you to curate learner-centred learning.

Optimize the allocation of L&D resources

You can dig deeper into your data to see which learning materials are getting the most views, likes, and time spent learning. You can view student surveys to understand which topics students prefer and would like to see more of. Use this data to make decisions about how, where, and when to allocate learning and development resources to eliminate or improve learning resources and experiences that don’t add data-driven value to your students’ growth and learning. You can create an efficient cycle of using data to discern the best learning experiences and continuously monitor the resulting learning data analysis to optimize the allocation of L&D resources.

Influence a data-driven culture

You can influence a data-driven culture in your organization by sharing trusted and reliable learning data that comes from your L&D team. Robust and meaningful data analysis can enable you to positively impact your wider organization and create a culture of data literacy that in turn supports a data-driven culture and make more informed data-driven decisions. Harvard Business Review Research [3] shows that organizations that use data to make decisions show better long-term performance results and happier employees and customers. Research using Qlik data analysis software [4] also shows that organizations with solid enterprise data literacy can outperform other organizations by 5%. In other words, a data-driven culture is good for business because it empowers you, your team, and your organization to make data-driven decisions that drive business performance.

Influence business performance results

Robust data analytics can enable L&D to demonstrate how learning contributes to business performance outcomes. The key to designing and managing learning experiences that align with business outcomes is to invest in understanding the learner, analyzing the needs of the business, and uncovering the problem that needs to be solved. After identifying the learner’s needs and preferences, your team must analyze the business needs based on the business unit that requested the training. It is recommended that your L&D team work with the business unit to ensure that your business needs analysis is correct. You can also collaborate to design learning experiences that match business needs and learner needs and preferences. Collaboration will strengthen the coalition between L&D and the business unit and underscore the support and commitment your L&D team brings to achieving business performance goals.

Let’s use as an example here a case where a business unit seeks to improve user experience (UX) by five basis points on the Net Promoter Score. Your L&D team will need to work with the business unit to coordinate when and how the business unit will collect Net Promoter Score data so that your team can plan when to deliver earnings as needed. Your team can curate learning, including micro-courses and videos on how to improve UX, and track student performance, engagement, and learning application through xAPI, surveys, and small-team discussions. While it may be difficult to determine that the learning itself had an impact on the Net Promoter Score, you can undoubtedly highlight how students approached, engaged, and applied the UX learning they gained from the learning resources your team selected. Sixty days after the learning has been completed, you will also need to follow up with leaders to collect qualitative and quantitative data on changes in student behavior as a result of the curated learning. These behavioral changes will likely result in a change in the Net Promoter Score that the business unit has been trying to improve.

Conclusion

A key trend that will continue to mature in 2023 is data analytics. Building a robust and sustainable L&D analytics capability can offer several benefits for both learning and development and the organization as a whole. As an L&D leader, there are several tactics you can use to reap these benefits, including defining learner-centric KPIs, curating learner-centric learning, optimizing L&D resource allocation, influencing a data-driven culture, and ultimately influencing business performance outcomes.