The role of Content Intelligence in skills ecosystems

By Toby Harris and Isael Paz

3 minute read

Missed it? Here’s a recap from the seminar Toby Harris (CMO, Filtered) and Isael Paz (Global Business Solutions, Degreed) gave at LT22UK.

Toby and Isael started by explaining that the basic function of a skills ecosystem is to allow people to achieve career goals. In the simplest terms: to go from A to B - whether that’s a small change or a big one. It sounds simple! In practice, these journeys have become very complex. 

the ideal city of Palmanova

Why? The LMS grew up as a closed system like the ideal city of Palmanova. In theory, we knew all the training everyone needed to do and, in that context, getting from A to B looks easy - it’s all been planned in advance. Palmanova still exists, but that isn’t how most cities turned out. They had to adapt to roads, railways, sewers and powerlines. Urban spaces grew and merged with each other until multiple walled cities started to overlap. Getting from A to B ceased to be simple.

It’s just the same in organisational learning systems. Lots of learning management systems get deployed which are all great on their own but not designed to interoperate. And we’ve added in a lot of content: we started with our own internal or custom content, then came the first wave of paid libraries (like, then came curated content and now there’s a whole new set of digital content providers out there. The result? Journeys through this skills ecosystem can be complex.

mobile phone

When we travel we now use navigation apps to make the journeys efficient and avoid obstacles. Just like a navigation app does for physical travel, an LXP helps you learn your way through a complex landscape to reach career goals. Like travel, there are different ways to get from A to B:

  • Inflexible in-person courses and certifications that deliver defined outcomes - like a flight
  • eLearning pathways that are more like a trainline - a fixed route but you can get on and off
  • Informal, on the job learning from people and resources - like walking, cycling or driving

The first two methods are fast and standardised but there’s always some of the third involved. It’s like the journey to the airport - many of us may take the same plane, but our origins and onward destinations are different. And there are many more than three methods of learning. In fact, RedThread has uncovered more than 60 different learning methods in organisations today.

So the system is complex. The answer is data. Navigation apps depend on a lot of good data going in: they synthesise maps, traffic reports and satellite data into simple instructions. Data is fundamental to making sense of any complex ecosystem and corporate learning is the same.

In our case, definitions of skills that are nuanced to the organizational context are the key route-finders. LXPs line up diverse catalogues and systems behind these skills in a user interface. Filtered’s Content Intelligence is a powerful tool to assist this process, mapping data against skills from the different sources to help learners find the fastest way to get from A to B. 

the role of content intelligence

Filtered and Degreed customers like Edrington are using Content Intelligence in exactly this way. We’re taking multiple content sources and mapping them against the skills defined by the organisation to create structured Pathways to learn about a skill (and to make it easier to search for content related to those skills by adding the right tags to the data). Here’s how it looks:

Edrington content intelligence

Okay, so that’s the theory and a worked example. But how does it look in practice? 

The second half of Toby and Isael’s session was a live demonstration of Content Intelligence in action. The audience shouted out skill names like ‘playing guitar’ or ‘C-level stakeholder’ management’ for Toby to plug into the Content Intelligence algorithm, live, and see what came out. Toby also showed how Content Intelligence allows you to add and edit alternative skill names that define and redefine a generic skill until it’s nuanced to your context. 

The role of the tech, he said, was not to remove the need to think about skills and content but to allow you more time to think about the skills by speeding up the tagging and giving you an easy way to visualise the results. Isael added that a critical challenge for L&D now is taking relatively staid and fixed capability frameworks and turning them into dynamic, living skill definitions that work with real systems and data. This approach enables exactly that.

Having demonstrated the algorithm, Toby showed just how much faster it was to develop a playlist with your content accurately lined up to skills with nuanced definitions. The fun continued at the Filtered stand throughout the two days, where visitors challenged us with even more difficult skills like ‘colour coding’ to see how the algorithm performed… 

Feeling the FOMO? You can catch up via a video Toby shared on LinkedIn the day before the event, where he demonstrated how he could define a nuanced skill like ‘writing persuasively for marketers’ and produce a quality playlist in a few minutes.

Interested in the Filtered / Degreed partnership? See it in action here: 

Filtered's Content Intelligence + Degreed

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