Learning Data Analytics: Define KPIs, Leverage The Data, Drive Performance
According to Gartner [1], by 2024, organizations that fail to build sustainable and scalable data analytics frameworks will likely experience performance setbacks of at least two years. In Learning and Development (L&D), data analytics has become crucial and will reign supreme in 2023. Collecting data about learner preferences at the individual, cohort, and organizational levels can be not only illuminating but also decisive in driving growth and organizational performance outcomes. This article explores four tactics for leveraging learning data analytics to drive business performance outcomes.
Define Learner-Centric 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 to evaluate learning ROI, including the very effective Kirkpatrick New World Model and the Philips model. Borrowing KPIs from software development and adapting them to learning product-specific Key Performance Indicators (KPIs) can complement measurement insights from these models. KPIs such as product stickiness, product adoption, product growth, and product engagement can provide information about the learner’s behavior and engagement with the learning product. Such data will enable 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 enhance existing products that learners like by sunsetting the ones that learners never engage with and improving the ones that show potential.
Curate Learner-Centric Learning
Numerous Learning Management Systems (LMS) and Learning Experience Systems (LXP) leverage Experience Application Program Interfaces (xAPI) [2], either directly or through a Learning Record Store (LRS). This capability enables you to collect, manage, store, track, and analyze precise data on learner micro-behaviors around various learning experiences. Such data can include the preferred modality each learner has, when they choose to learn, how long they spend learning in each type of asset, what they search for, whom they connect with, and how they prefer to be reminded about learning opportunities, among others. This information is powerful for you, your L&D team, and your broader organization as it can pinpoint learner preferences, needs, and wants at the individual, cohort, and organizational levels, which in turn enables you to curate learner-centric learning.
Optimize L&D Resource Allocation
You can dig deeper into your data to discern which learning assets garner the most learner views, likes, and time spent learning. You can review learner surveys to understand which topics learners prefer and would like to see more of. Using this data, you can make decisions on how, where, and when to allocate Learning and Development resources to sunset or tweak those learning assets and experiences which, based on the data, are not adding value to your learners’ growth and learning journeys. You can create a virtuous cycle of using data to discern the best learning experiences and continuously track resulting learning data analytics to optimize L&D resource allocation.
Influence A Data-Driven Culture
You can influence a data-driven culture in your organization by sharing credible and reliable learning data that emanate from your L&D team. Robust and meaningful data analytics can empower you to positively influence your broader organization to create a data-literacy culture, which in turn fosters a data-driven culture, and make better informed data-driven decisions. Research by Harvard Business Review [3] shows that organizations that leverage data to make decisions show better long-term performance results and have more satisfied employees and customers. Research by data analytics software Qlik [4] also demonstrates that organizations with solid corporate data literacy can outperform other organizations by 5%. In other words, a data-driven culture is good for business because it enables you, your team, and your organization to make data-driven decisions that drive business performance.
Impact Business Performance Results
Robust data analytics can enable L&D to demonstrate how learning contributes to attaining business performance results. The key to designing and curating learning experiences that align with business performance results is to invest in understanding the learner, analyzing the business need, and uncovering the problem to be solved. After distilling the learner need and preferences, your team must analyze the business need emanating from the business unit that requested the training. It is recommended that your L&D team collaborates with the business unit to ensure your analysis of the business need is correct. Next, you can collaborate to curate learning experiences that match the business need with the learner’s needs and preferences. Collaborating will entrench the coalition between L&D and the business unit and underline the support and commitment your L&D team brings to the table to achieve the business performance goals.
Let’s use as an example here the case where the business unit is seeking to strengthen the User Experience (UX) by five basis points on the Net Promoter Score. Your L&D team will need to collaborate with the business unit to coordinate when and how the business unit will collect data on the Net Promoter Score so that your team can schedule the time of the earning delivery as needed. Your team can curate learning, including micro-courses and videos on how to improve the UX, and track the learner performance, engagement, and application of the learnings through xAPI, surveys, and small team discussions. While it may be difficult to pinpoint that the learning alone impacted the Net Promoter Score increase, you can undoubtedly highlight how the learners accessed, engaged with, and applied the UX learned that they garnered from the learning assets your team curated. You will also need to follow up with the supervisors sixty days after the learning was completed to collect qualitative and quantitative data on learner behavioral changes as a result of the learning curated. These behavioral changes will likely drive the change in the Net Promoter Score the business unit was seeking to improve in the first place.
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 to both Learning and Development and the organization as a whole. To reap these benefits as an L&D leader, you can apply several tactics, including defining learner-centric KPIs, curating learner-centric learning, optimizing L&D resource allocation, influencing a data-driven culture, and ultimately, impacting business performance results.
References
[1] Top Trends in Data and Analytics, 2022
[2] Experience API (xAPI) Standard
[3] The New Decision Makers: Equipping Frontline Workers For Success
[4] What is data literacy, and why does it matter for your organization?
