Earlier in my career I was an eLearning manager acting as a liaison between the trainers and trainees attending process management training, ensuring each session ran smoothly. Part of my preparation process was to brief the trainers on what the trainee makeup looked like for each session in order to give them an opportunity to customize their presentation delivery style to the audience with the goal of providing the most value for the trainees. While I did this by pulling data such as the titles, organizations, industries and any other relevant metadata I had about the audience, adding additional insight about the specific learning or communication preferences was an intuition-driven exercise – even though many trainees took multiple courses and were individually tracked in a Learning Management System (LMS).
This manual, intuition-driven process always seemed like a lost opportunity to really extend the value of training by customizing the delivery to the way the audience preferred to learn. A recent conversation with a training instructor validated the fact this process is all too common in the training world and inspired me to think about ways analytics could extend the value of training by providing an additional lens of insight about the trainees. For example:
- What if training managers could visualize trainees’ learning & communication preferences beforehand – in aggregate?
- Would access to these additional trainee analytics extend the value of training technology platforms?
- Would it be possible to gather objective trainee insight just once per trainee, to be re-used for future training?
- Could the trainee cohort be visualized in the aggregate quickly and easily?
While a lot has been written about customizing content to the training audience, this has typically been outside the purview of the analytics world. Using the Talent Analytics API, analytics-driven talent content can now be embedded inside training technology, making this additional trainee insight possible today – and all the math is done in seconds.
Here’s an example of what an eLearning interface could look like powered by analytics-driven talent content about the trainees with some significant business benefits.
Stronger Training Technology ROI
A modern training platform that includes an employee profile would be enhanced by not only tracking the progress of employees historically towards achieving organizational learning goals and objectives, but also would provide re-usable insight that could inform future instructors. Since the analytics are stable characteristics about the trainees themselves (as described in the image), the data is re-useable without asking the trainees to input data every time they change job titles. This means each trainee’s analytics are a set of numbers associated with each trainee valid from intern to CEO and at every point in between.
Meet Trainees Before Training Starts
Ask any trainer: having the learning preferences would add significant value to their training prep. Analytics can tell them how how the content will land on the trainees ahead of time, allowing them the opportunity to prep accordingly rather than guess. By “knowing” their audience in advance, this simple innovation would reduce the time spent during the training session “getting to know” the trainees, allowing the trainer to get through more content. In aggregate, this leads to fewer sessions required, reducing the cost of the overall interruption to productivity. Very business friendly metric!
Win-win for Trainers and Trainees
To truly optimize training, analytics-driven insight must be delivered to trainers rapidly and easily before every training session. Training that lands closer to how the trainees naturally learn will yield in increased information retention and engagement in the course – all very positive metrics for business-oriented training vendors.
Given trainee analytics are available today via API, isn’t it time to bring your training and eLearning technology to the next level?
Mike Kennedy is a Technical Evangelist at Talent Analytics, Corp. He can be reached via email@example.com and @talentanalytics.