There is more to learning and development (L&D) than simply creating a learning program and checking a box. There’s a multitude of considerations that influence an effective L&D plan – from the state of the business market to the organization’s goals to the needs of employees.
Organizations must remain competitive, innovative and agile to stay relevant in today’s market. This requires employees to be prepared to meet and deliver on changing expectations, which requires training.
Time is a precious commodity. Who has time to dedicate days or even hours to learning? Yes, those days spent in training are worthwhile. However, if employees return to their jobs only to continue checking off items from their to-do list, the training is wasted. The learning must be applied to the job in order to become an engrained behavior.
To streamline learning and application, employees need training personalized to their job role and function. They need training that closes skills gaps in an efficient and timely manner. They need learning solutions available on the job to solve immediate problems. To do all that effectively, L&D needs data to deliver quality training.
Learning Analytics 101
The idea of gathering learning data and analytics may sound overwhelming – and it is – but the trick is to start small. Think about a question you have; what data do you need to answer it? Then, collect and analyze the data that you need to answer that question.
Review the metrics that you have available to you and start investigating. Why are learners returning to a specific page in your e-learning programs? How many people shared an article in your learning management system (LMS)? Are completion rates suffering or soaring in specific online programs?
There are a multitude of metrics available to us. Pinpointing the right things to measure is the hard part; finding the answers to questions that are meaningful to strategic goals is the key.
Improving Training Effectiveness
“You can’t manage what you can’t measure,” said organizational development and management expert Peter Drucker. And if you can’t measure it, then you certainly can’t improve it, Drucker believed.
L&D professionals understand that learning programs must impact business results for it to be a worthwhile investment. In fact, their training budgets often depend on how well they can validate the connection between training and business outcomes. However, making that connection is challenging.
Data can help to make those connections and provide L&D with the information they need to prove the value of training. In his article, “Learning Data: The real definition and how you can prove business impact,” JD Dillon, chief learning architect at Axonify, highlights four learning metrics to improve the impact of a learning strategy:
• Learner engagement: Engagement must extend beyond course completion rates and track participation in training. This engagement score will allow L&D to connect learning activity with other metrics.
• Knowledge assessments: Learning must be continuous for it to be effective. Assessments should be built into learning activities that occur routinely throughout an employee’s life cycle to accurately assess knowledge over time.
• Learner confidence: Confidence is an often overlooked component in training. Low confidence is a barrier to proficiency. L&D must move beyond assessing knowledge through tests and assess the confidence of learners as they apply the knowledge on the job.
• Behavior change: Assessing how the behavior of learners has changed since returning to the job can help L&D connect knowledge growth to real-world application. Managers should be heavily involved in this process to correct any issues before they become engrained behaviors.
The culmination of these metrics can help L&D professionals prove the value of training. Collecting and analyzing learning data is not easy but can help L&D improve the effectiveness of training through the development of more targeted, impactful learning solutions.