Are you using data to continually improve and enhance your learning offering? Well that’s the difference between good and great learning experiences!
If you’re striving to provide a truly modern, personalised learning experience for your people, it’s time to stop overlooking data. Until fairly recently, our learning technology wouldn’t provide a great deal of information about our learners. We’d simply know whether they completed a course and if they passed or failed. But modern learning solutions provide real, actionable insights into our people’s performance. It shows us where skills gaps are, where employees are lacking in engagement and where they might be searching for something that does not yet exist.
Using this data as the foundation of your learning programme is great. But using it to continually improve and enhance your learning offering? Well that’s the difference between good and great learning experiences. Especially when it comes to programme-based or programmatic learning. Programmatic learning is a long-term, blended approach to learning that combines data with personalised learning, people interaction, practice and feedback to create real behavioural change. In this sixth and final instalment of our programmatic blog series, we will explore how data can enhance your learning offering and improve the learner experience.
The L&D data revolution
Data in L&D hasn’t always been exceptionally useful. Although we will always want to know if a learner has completed a course, and if they passed or failed an assessment, this data doesn’t really tell us anything of substance. It doesn’t tell us why an individual dropped out of a course early, or which resources they had (or hadn’t) accessed before taking an assessment. Instead it shows us one piece of information, in complete isolation from the much bigger picture. This doesn’t help us to refine and improve our learning experiences. Instead, we need data that shows utilisation of resources and the impact of different learning interventions on outcomes. It’s this kind of data that will create the real impact needed in our organisations.
Since the early 2000’s the concept of ‘big data’ has come into the business world. Big data is a combination of structured, semistructured and unstructured data collected by organisations that can be mined for information and used in machine learning projects. And over the years there have been many discussions about using big data in HR and L&D. Many refute the claim that we should utilise big data in our industry, simply because they do not believe it exists. Most companies have thousands of employees, not millions, so the data we hold in our teams is actually fairly ‘small’. But everybody is in agreement about one thing: data (no matter the type) should be used to improve our employee experience and learning provision.
And using data has become even more important in recent months. The onset of the Covid-19 pandemic caused L&D professionals to spin on their heels, pivot, and transform the way in which they offered learning to their people. L&D said goodbye to the comfort of the training room and face-to-face courses, and delivered their programmes virtually. But the change to virtual learning didn’t just mean learning new digital tools, it meant losing the trainer’s most valuable datapoint: body language. As such, it is more important than ever to use data from our learning technology stack to assess learner progress throughout a programme, to pinpoint any learners that are struggling, and identify how to help and support them throughout the programme.
Changing mindsets about data
Many L&D professionals overlook the importance of analysing data in L&D. Instead, they simply create learning programmes, roll them out to learners, and rarely look back to see what worked, what didn’t and what can be improved in future. It’s time this changed. L&D must become hypercritical of their output and hold themselves accountable to learner success. And this is going to take a shift in mindset.
Often data in L&D is viewed as performance data on the learning team’s output. If assessment pass rates are high, the team did a good job. Conversely if they’re low, the team did something wrong. This mindset needs to change. We know that assessments are a small part of a much wider learning programme. There are numerous reasons assessment scores can be extremely high, or terribly low – but these alone should not be indicative of success or failure of the L&D department.
Instead, we need to use data as pointers for improvement. Low pass rates could mean that learners need more on-the-job training, or perhaps more time to practice. They could also mean that the learning emphasis is on the wrong section, and you need to rejig your programme to meet your learners needs and plug skills gaps in relevant places. If you change your mindset and see data as a way to empower the L&D team, and in turn help more learners – then before you know it, you’ll be embracing data at every opportunity.
Data in programmatic learning
Programmatic learning is a framework designed to target more complex organisational issues through the acquisition and application of new skills and knowledge. But organisational needs evolve, as do the skills our people need throughout their career. As one cohort of learners finish the programme, another will just be starting. If you were to never update and enhance your learning programme, you’d be doing your learners a real injustice. And no, this doesn’t mean tweaking the design slightly over the years to make it look nicer. You need to enhance the content included to ensure it meets your learners changing needs and environment.
But how will you find out what to change in your learning programme? With data, of course.
Data and intelligence are a crucial step of the programmatic learning framework. Applying the framework should start with data. Such as:
- What do your people need to know?
- How are they currently performing?
- How do they currently feel?
Once you know this, you need to design personalised learning journeys, full of people interaction, practice and feedback based on the needs highlighted from this initial data.
But the real effectiveness of programmatic learning comes from the fact that it is a cyclical, never-ending journey of continuous evolution. And the data from the start of your journey is just that: the start. Over time you can evaluate your blended learning journey, and assess what works, for example:
- What’s having the biggest impact on your learners?
- What steps are they overlooking?
- How does the blend you’ve put together impact their performance?
- What do they need to know better?
- How can you better portray that information?
And then you start again, tweaking, refining and enhancing your learning programme – boosting learning attainment and performance each time you loop around the programmatic learning circle.
In doing so, you will be continually improving the learning experience. By evolving and improving your offering to learners, you will be leading by example. You will fuel an organisation of motivated, lifelong learners. But to do this, you cannot use data alone, you must integrate your data with the rest of the programmatic learning framework to make a real impact. To learn more about programmatic learning, download our free e book now.