And just like that…World of Learning 2023 is complete! 

When Alex and I were asked to present one of the seminars at WOL2023, we wanted to bring value and insight into how we ‘create learning that lasts a lifetime’ with our mix of skillsets and experience. 

It’s that mix of L&D and Technology that formed the basis of our talk: Intel = L&D = Intel.

Data collection and analysis is an ongoing topic within the L&D industry, and we not only understand but have experienced the challenges of adopting a data-driven approach to learning. Over the years, I have heard many different challenges when it comes to data and I’m pretty sure, I’m not alone in some of these… 

‘It’s too time-consuming’ 

‘Don’t worry about that, just make our people better’ 

‘I don’t know how to…’ 

The benefits of a data-driven approach 

The reality is, that the benefits of a data-driven approach to learning far outweigh the challenges:

  • Improved learning outcomes 
  • Personalised learning paths 
  • Real-time feedback and assessment 
  • Cost reduction 
  • Employee engagement

But where can you get the data from? 

There’s a huge variety of data sources out there. Some of them may be obvious such as your LMS or from quizzes and surveys, but there are some less obvious ones too.

For example, you can usually find usage analytics from any social learning platform or supporting apps you use, digital courses, and most interestingly, content interactions. Looking at how your people interact with videos, audio or interactive exercises is a great place to start. 

To bring a couple of these examples to life, we’ll look at platforms and quizzes in more detail.  

On one particular client project, we were set the challenge of finding the best times for scheduling push notifications to a management audience. The first thing we did was to look at the times of day people were using the platform in question. We then broke that down to specifically look at managers. From this, we were able to identify when organic platform usage was strongest. It would be easy to stop there and say, send every notification at the time when usage is highest. However, rather than just accepting that, we conducted A/B testing by sending an array of notifications at different times over four weeks and the results we got were rather insightful. 

There was a time of day when people would typically engage with the platform and a time when they were more than happy to read notifications. We followed this up by looking at typical workloads and noise times throughout the day and established an optimal time for notifications. There was also a happy accident that occurred by doing this. Platform usage tailed off at a certain point, and by timing these notifications correctly, we were also able to sustain high engagement levels for an additional two hours.  

Another example is how we used intel to determine how much time should be allocated to a timed quiz. The quiz in question was taking place within a piece of eLearning. To calculate the time allocation we used some existing data which was the length of time people were spending going through the different modules. 

Once we had these times, we could see on average, which modules they were able to complete more quickly, and those which took a bit more thinking power. This was important because it allowed us to pinpoint those modules where more time was typically required to complete the quiz than would normally be permitted.  

And so these are just a few examples of what you can get from some of these data sources. When it comes to content interactions and usage analytics there are loads more but hopefully, this gives you an idea of where you can begin to gather some of your intel data from.

Some key hints and tips to get you started 

  • Remain ethical – In today’s data-driven world, it’s crucial to keep ethics at the forefront of your mind. As we harness the power of data intelligence for learning and development it’s important that privacy and security are treated with the utmost importance and that your people are fully aware and consenting to data-gathering practices. 
  • Set your data strategy from the start of the L&D cycle – What do you want to gather and why? 
  • Encourage collaboration – Seek collaboration between HR, IT, and L&D teams to ensure that your data intelligence efforts are aligned with your organisation’s goals.
  • Don’t collect data for the sake of collecting data – Not all data is useful or insightful.

If you’d like to learn more, you can also read about how we used the power of data, feedback and intel to shape our approach to an organisational transformation program in our change management blog.

If you have any questions, please get in touch.

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