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We are just one week from the start of DevLearn 2019 and I am happy to see I am not the only one getting excited! We are so lucky to have 3 people from our Learning Solutions team attending this year so we can truly divide and conquer! The only time we will probably all be in the same room and session is for the keynotes. Speaking of the keynotes…
As a data science geek, I am especially looking forward to Talitha Williams’ session on “Using Data to Inform Learning and Work”. The next big technological disruption is here and it’s data.
Do we have the right data?
L&D has been gathering data for decades. Smile sheets, course evaluations, surveys, skills assessments and more recently e-learning completion rates, time spent on a screen, website analytics, and the list goes on. But before we do the analytics and try to glean insights about our learners from this data, we need to be sure we are capturing the right data.
We have all been consuming L&D data like candy, but if it isn’t the right data, the information that can tell us about what our learners need and want, then we are just churning out meaningless metrics and measures.
Examples of bad data and insights (and I am just as guilty as the next person):
In order to get to information and insight, we need to gather the right data and we need to get better at it. In the age of xAPI, LXD, AI, Machine Learning and the ability to track nearly every click, search term and user behavior, L&D is still running to catch up. We are trying to use the same measures and data (the “old way”) of measuring learning outcomes and learner performance.
I know I am guilty of using the “old way”: “We have a 56% course completion rate so they must like it. – Success!”
Using the standard data and metrics and asking a different question just isn’t going to work anymore.
Examples of better data and some insights:
“The goal is to turn data into information, and information into insight.” – Carly Fiorina
Once we get over ourselves and stop using the “old ways” to collect data and start collecting the right data, we can then start looking for insight in the information. This is the tough part, what does all this data mean and how can we make decisions and get buy-in from this data? We are finally on the brink of Big Data finding its place in L&D but we need to be the catalyst for change. We have to change how we gather and interpret the data and then change how we distribute this information to the broader organization in a way that is actionable.
Here are some examples of good data, insights and action:
Data: Only 30 out of 60 people attended the training course
Insights: Survey of those that didn’t attend showed that the course was too basic and not in the right modality
Action: Create an advanced module in a different modality that can be completed at any time.
Let’s start learning from our learners – it all begins with the right data and insight from information!