I have written a number of posts on learning & development analytics and what I'm writing in this post is sort of a summary of what i have written before. I have read a number of articles and posts about learning and development analytics and I do find a lot of what is written confusing or not clear in terms of what direction i should take when it comes to learning and development analytics. I like to keep things simple and i believe that when it comes to L&D analytics we should follow the same principle too. So having said that, here are my core principles for doing learning and development analytics.

1. In reality there is no such thing as learning and development analytics. There is data analytics applied to the domain of learning and development. Therefore if you want to do learning and development analytics, see yourself as applying data analytic techniques to learning and development.
2. Understand that data analytics is the process of collecting, preparing and analysing data for the purpose of deriving information that can be used to make better L&D decisions. It's that simple.
3. Start your analytics with a question or problem definition. For example, How many people attended the Time Management training? How many managers have been able to complete their performance reviews after attending the training? How many people are using the Care Planning System properly after the training? Starting with a clear question or problem definition will aid you to take the next step.
4. The next step is to identify what data you need to answer your question and where you will get if from. If you defined your question properly in the first place, you will have a good idea of what data you need and where to get it from (or not). At this stage your main challenge might be you don't have access to the data you need to answer the question or it doesn't exist because you did'nt collect it in the first place. So you need to think about how to collect the data. Applying this process to designing and developing learning interventions can help with designing effective evaluation strategies. If you are rolling out a programme, a crucial question should be, how will we know this programme was successful? But don't stop there, back it up with another question which is, what data do we need to collect to show that the programme was successful or not? Don't start developing and implementing an intervention without answering these questions unless you will not be able to evaluate it.
5. The next two steps are technical ones, firstly, how you will analyse your data. I believe this is where a L&D practitioners struggle. My advice is, learn Excel and basic descriptive statistics which will help you to explore and understand what your data is telling you. There are many good courses out there that you can take for free to get these skills. In future posts i will suggest some.
6. Final step is how to communicate your data. Again learning how to build simple dashbaords with Excel (my preferred tool, since it is accessible and simple) or other more sophisticated dashboard tools such as Power BI or Tableau is a good skill to have. And of course good old PowerPoint to summarise your conclusions from the data analysis.

There you go, those are my simple tips for applying data analytics to learning and development. Hope you find this useful.