Navigating the World of L&D Technologies and Data with Confidence

In this three-part blog series, I am taking a look at how to build confidence in using HR/people technology and data. This second blog in the series offers a focus on L&D.

For many years, implementing learning technology mainly involved deploying Learning Management Systems (LMS) and using content authoring tools, to produce and serve up content and manage training delivery schedules. Today this has fundamentally changed as technology has advanced, user requirements have become more sophisticated and our access to knowledge has been revolutionised. The pandemic driven acceleration in the adoption and application of technology for learning has also caused some permanent shifts. L&D professionals are now faced with trying to make sense of a large number and wide variety of tools and technologies, in a cluttered, evolving $360 billion market.

Most HR and L&D professionals talk about people, human interaction, creativity and the opportunity to make a difference and support others as their reasons for doing and loving the job they do. Far fewer mention data and technology as their passions or key areas of expertise; for the majority, these represent the opposite of their comfort zone and areas of interest. So, it’s not surprising that many people find the L&D technology market confusing and frustrating. Some of the key areas of confusion in my experience are caused by:

• The multiple terms used to describe the market – edTech, LearningTech, SkillsTech, HR Tech etc.

• The varied descriptions of the technologies on offer – Learning management systems (LMS), learning experience platforms (LXP), applications, portals, record stores, libraries, marketplaces, suites, academies, tools etc.

• The different underlying technologies that drive the functionality of these systems – SCORM, xAPI, VR, AR, ML, AI, XR, gamification, virtual classrooms etc.

• The ever-shifting terms vendors use to promote the outcomes their systems can help achieve: improved management, experience, engagement, collaboration, retention, satisfaction, productivity, personalisation, skills, learning etc.

Some of this really is just the use of different language to describe the same thing. For example, whether you refer collectively to the technology you have as your EdTech or LearnTech really does not matter. In other cases, these terms do refer to different things and understanding the difference really does matter. For example, knowing if a piece of tech has the core functionality common to a Learning Management System (LMS) or a Learning Record Store (LRS), really matters.

You need to make some sense of the above before you can begin to try to answer some key questions. For example, is it better to seek an all-in-one learning tech solution or build a tech stack from best of breed tools?

If you are responsible for making or influencing decisions about which technologies to buy and/or how they are deployed in an organisation, developing your understanding and confidence is crucial. So, you do need to do your research; invest some time and energy into understanding the market, the technologies and what each of them does for learning and engagement. It really is not ok to leave it to your IT team or hope your choices will become clear if you fling an RFP out and see what comes back.

Options include:

• Attending trade shows and conferences.

• Reading/listening to case studies, white papers, market reviews, thought pieces etc.

• Talking with vendors (current and potential) and their customers and ex-customers.

• Signing up for webinars.

• Engaging with your network to share experiences, ideas and challenges.

• Conducting pilots and experiments.

There are also some great advisors, consultants, research organisations, analysts and vendor review services that can help with a more personalised service, if that’s what you’d like, and you have the budget. Beware though, some are biased towards vendors that pay them/with which they are affiliated, so take time to do your research on them too.

It is easy to get overwhelmed so stay focused on your needs:

• Improved value: Perhaps start with better understanding the functionality in the technology you already have and how you could get more value from it. New tech may not be the answer!

• Key challenges: Alternatively, spend time on a key problem you need to solve e.g., if people are struggling to locate relevant content, focus on understanding how technology could improve personalisation or user experience. This is where an LXP might be the right choice. Think: I am not deploying a technology, I am deploying a solution.

• Think ahead: How are the needs of your organisation changing and what will likely be needed to support those changes? Selecting and implementing new technology effectively can take months, if not years, so developing your long-term thinking is important. For example, AI is the hot topic in 2023. In the context you are working in, do you need to make sure your learning tech is AI enabled for the future? Only by learning more about these technologies can you answer questions like this.

Keep in mind too that the fundamentals of how people learn don’t change and any new tech is only as powerful as the context it’s used in. Doing your research will help ensure you don’t buy this or that system because organisation x did. Their needs and context might have been entirely different to yours. Just because they are a similar size or in the same industry, does not mean their choice would be right for your organisation. Some organisations will gain most benefit from deploying a selection of specialist technologies to meet their needs, while others will find the kind of integrated technology stack that vendors like Cornerstone offer is the right choice.

Finally, don’t fall into the trap of thinking just about what the tech can do and ignoring the wider tech landscape and strategy in which your organisation’s learning technology exists. Most (if not all) of the people you are trying to support with learning resources and experiences won’t know or care if the system they are using to help them learn is classified as a “learning” system. As Jane Hart’s fabulous “Top 100 Tools for Learning” surveyreminds us annually, most of the tools people say they find most useful to learn are not usually classified as such.

What people will care about is that any “learning technologies” are intentionally stitched into the wider ecosystem of systems and tools that people must use to do their jobs, in a way that makes sense and makes them easy to use as part of work processes and tasks. Some people call this learning in the flow of work, and getting it right in your technology set up relies on a lot of things, including the effective use of APIs. Both should also be topics you have at least a working knowledge of, and if you don’t have a good relationship with your colleagues in your wider business systems and IT teams, get started on fixing that today!

L&D data and metrics have been a constant - and lively - topic of conversation for decades. Often, the focus has been on trying to connect learning activities with business impact. After all, L&D is usually considered a cost centre, so L&D leaders are often focused on justifying spend and identifying how it delivers a sound return on the investment (ROI). Even if this is potentially a red herring.

So, you might be forgiven for thinking that most L&D professionals are now usually highly proficient in data collection and analysis. You might feel as if your colleagues are likely all confident data users who know exactly how to use data to inform their practice. But when it comes to using data effectively, surveys of the profession perennially indicate that many are still not making evidence informed decisions, often because they lack confidence and capability. Common challenges include:

• Identifying what to collect/measure.

• Too much data, sitting in different silos, that may be difficult to identify and access and difficult to bring together.

• Lack of ability to use data effectively/data skills.

• Contextual barriers, such as lack of time, lack of support from L&D leadership, lack of budget etc.

Data analytics is a huge topic and it’s not necessary for learning professionals to become data analysts. If you can bring these skills into your team, that’s great – even if you must “borrow” them part time from another team. Gaining a working understanding of how data can be effectively applied in L&D will though go a long way towards building your confidence. And it’s a hot topic right now.

Here are my top tips for getting started:

Start with the data sources you have. Make a list of the data sources you have, what they contain and how you can access them. This should be easier to do if you have first done as recommended above and taken time to understand the technology you have. Try this handy list as a prompt when exploring with your vendors the data their tech can provide.

Stop and Think: Take some time to think carefully about what data you do and don’t have, how relevant it is and where it is before you jump in. This is likely much easier said than done – lack of time is often one of the most mentioned barriers to effective analysis. So, you’ll need to make space for this.

Educate yourself: You might need to upskill yourself e.g., to make sound judgments about the data you have. You could start with this 30 minute LinkedIn course on Data Driven Learning Design from Lori Niles-Hofmann and perhaps progress to deep dive into this 50-70 hour People Analytics program from the CIPD. Or try these ideas from Jam Pan.

Start small: Perhaps with a set of four or five things that you want to be using data for. Examples could include:

• Tracking skill movement in a specific population.

• Using data to automate personalised learning.

• Content evaluation. AstraZeneca were able to realise a 41% reduction in content spend by using data to identify overlapping content.

• Using data to uncover the pain points of a target audience, so designed solutions help people with their day-today work challenges.

Move beyond description: Try to move from using data to describe what has happened (how many content completions, did people enjoy the learning experience etc.) to diagnosing why things are happening (why did the same content that helped one group perform well not help another?). And then on to predictive analytics.

Build Relationships: Link up with your colleagues to connect L&D data to business data, like finance and sales data. And not just for a single project, this should be a journey together.

You can learn more here about how Cornerstone supports modern work with modern learning.

In the final instalment of this three-part series, I’ll talk about how building your confidence using data driven technology can help transform your approach to talent management.

Author - Helen Smyth