How to Use Social Analytics in Organisational Learning?
Nowadays, the HR and L&D functions of organisations are increasingly data-driven. Many employ analytics to aid in decision making processes and to try to analyse e.g. the effectiveness of learning initiatives. While there’s a lot of ways to use learning analytics, we found that organisations are underutilising a particular type of data. While digital learning platforms increasingly come with social features (walls, blogs, news feeds, etc.), not many are yet paying attention to how people use these social elements, and the potential implications for the organisation. Thus, here are three cases for using social analytics in organisational learning.
1. Measuring interactions between learners
If we want to understand learning on a holistic level, it’s important to also understand it granularly. Hence, one good use of social analytics is to analyse interaction between the learners. Some example data points for these interactions could be:
- How many times was a particular piece of content or user submission liked/shared?
- The number of comments that a post or a piece of content attracted
- How often/for how long are users interacting with each other?
The first two examples above could help you to understand what kind of content works the best or sparks the most discussion. The latter one could help in understanding how people collaborate with each other.
2. Measuring the quality of interactions and organisational influence
Naturally, quantitative data only gets us so far and it’s important to understand the quality of the “social” as well. Empty comments that don’t contribute to the discussion are not likely to create value. Hence, organisations could consider using semantic analysis, powered by NLP algorithms to gauge “what” is being talked about, and whether the social discourse is contributions or just mere commenting. The benefits of semantic analysis are two-fold. It may, again, help you to spot problem areas in your content (e.g. when learners need to clarify concepts to each other). But perhaps more importantly, it can provide you information on who are the “contributors” in your organisation.
Also, it’s important to understand “who” are interacting and “how” they interact. This level of analysis could be helpful in determining organisational influence. Who are the individuals with networks across the organisation, or liked by their peers, or helping everyone. These people may even go unnoticed if not for the social analytics, but maybe they could be among the future leadership potential in the organisation. Even if not, there’s a good chance that these may be local opinion leaders that you could utilise to execute your strategy in the future.
3. Sourcing ideas and innovation from the ground up
Finally, a potentially highly impactful application of social analytics is in sourcing information, ideas and innovation from within your own organisation. Often, the people doing a particular job have a lot of ideas on how to improve. It’s just that these ideas rarely reach the top, due to organisational layers, bureaucracy, culture etc. Could we help in that?
With social analytics, you could effectively set up hidden knowledge collection tool. By analysing discussions/sharing/likes around content or user submissions, you could establish a direct flow of information from the line of duty all the way to the decision makers in the upper echelon’s of the organisation. The decision makers would see what kind of work practices/ideas/methods gain the most traction, and then find ways of replicating them across the organisation. On a technical level, such flows are not hard to set up. Mostly, you just need quantitative data, or a combination of quantitative and semantics, depending on the case.
All in all, there’s a lot of under-utilised value in social analytics for workplace learning and organisational development purposes. As learning is fundamentally a social experience, this data helps in understanding the learning that is taking place. So, as you’ll get deeper into the world of learning data, don’t just focus on the traditional metrics like course completions etc. A more social data set might provide much better insights. And if you need help in social learning or hidden knowledge collection, we can help. Just contact us here.