Learning and development leaders have plenty to consider right now. Upskilling and reskilling at faster rates than ever before are roundly agreed to be crucial for corporate success.
Perhaps understandably, changes in working practices resulting from the COVID-19 pandemic will have led many organizations creating or purchasing more learning content as means of meeting their upskilling and reskilling targets.
But, for learning content, more is not more. The more content you make available, the longer it takes your people to find what they need when they need it. As their trust fades, the less likely they are to look.
And, worse still, the more content there is, the less appreciation that learning is not all about content, but also about learning from peers and primarily about learning through real-world experience.
Our Content Discoverability Framework is intended as a practical tool for organizations to help their people to find learning content they need, when they need it.
This framework may be most useful to ensure that multidisciplinary teams don’t drop balls when sharing responsibility between learning tech teams, content owners and business partners. Different skills are required to apply the elements of the framework.
The five elements of the framework, in order of application, are:
- Applicability
- Awareness
- Navigability
- Personalization
- Help
Applicability
Focusing on high-quality content that is relevant to your organization is an obvious but often overlooked first step to help people find what they need. The less irrelevant content you have, the more readily the other elements of this framework will apply.
A first step and probably the most cost-effective route to relevant content is to put learning content standards into place, accompanied by sensible governance processes.
At their simplest, these should pose two questions:
• Is a learning intervention truly the solution for the issue that has been identified?
• Do we already have resources designed for that purpose which we could use or adapt?
And, three set learning intervention requirements:
- A clearly-defined target audience.
- Objectives — describing what people will do differently as a result of participation.
- Measures of success in meeting those objectives.
To save duplication and outdated content obscuring the relevant, you will also need a learning content management process which stores editable source files with naming conventions to help identification, the details of the business owner and set review dates for the owner.
Purchasing third-party content libraries allows access to generic content which is managed and updated by the vendor. AstraZeneca has successfully used Filtered’s Content Intelligence to ensure that content which is procured is relevant and its relevance quantified, all relative to the organisation’s priority capabilities and the specific skills they comprise.
Possible metrics: coverage of key skills; cost; cost per relevant asset.
Awareness
Once you have measures to ensure applicable content, you need to ensure that people know that it exists and where to find it. While performance consulting and ensuring the application of standards that fall within the traditional expertise of learning professionals, building awareness and engagement are complementary skills, for which some teams hire dedicated marketing professionals.
This is not a one-off activity associated with launching platforms.
Awareness messaging needs to be a constant drumbeat, embedded in your operating context, in the same way that your company continues to market its offer to clients and potential clients, relating to their needs in the context of their markets. It is also intrinsic to your approach to learning culture — how do people become aware of, understand, discuss and share learning?
Some of Filtered’s clients have found that email campaigns with vibrant, high-quality surprising content can be hugely effective at spreading the word.
Possible metrics: average monthly active users, proportion of workforce who are aware; open rates, click-through rates and downstream positivity about the learning experience.
Navigability
In the same way as we have an expectation of the layout of public buildings we visit, learning content architecture should be intuitive to navigate. Contributing factors to navigability are uncluttered landing pages, sensible and consistent naming conventions, with governance rules and processes to ensure application.
Tagging to a relevant taxonomy will also make a huge difference to searching for the content you need within the structure. Think carefully about the skills taxonomy that makes sense for your organization. Is it joined up with talent initiatives? Does it include terms that people actually search for (the most common search terms across corporates are still: excel, agile, leadership and project management)? Is it reasonably future-proofed (skills of the future, extensible and flexible)? Finally, what about things that aren’t skills, such as behaviors, values, topics, themes, tasks? Should your taxonomy be limited to skills?
Tagging of content to skills is an area of business where algorithms really have overtaken human level performance. Find a vendor that knows their stuff and is willing to prove it.
Curation of learning pathways is now an important mechanism to direct the attention of your people to curated content. Again, algorithms can be used to help to accelerate the process.
Possible metrics: NPS score for the LMS/LXP; search success percent; tagging accuracy; survey feedback for pathway users.
Personalization
Much has been made of the potential of learning experience platforms, and indeed of some commercial content vendor platforms, to deliver personalized experiences.
For this potential to be realized, tagging to a relevant taxonomy is necessary, but not sufficient.
Also required are meaningful user profiles, built from a combination of HR system information such as role and location, and user-generated data such as skills, career interests and levels, influencers they follow and other activity on the site.
But be warned: The impact of personalization is much harder to prove on learning systems than on much more popular media and social media platforms. For one thing, those platforms enjoy a tremendous amount of traffic. And for another, they are optimized for clicks and plays. In L&D, we are trying to optimize for much more worthy and much more difficult: performance improvement.
Possible metrics: percent of returning users; NPS score.
Help
Finally, if the system hasn’t got the user to the learning content they need together, you need a viable back-up plan. It should be clear when and how to be in touch with someone, and how long it will take to receive a response. This should be for a bare minimum of users as the huge majority of your workforce’s discoverability needs should be provided by the previous four elements of the framework.
To conclude
The benefits of succeeding with learning content discoverability are enormous, including employee engagement, fulfillment and purpose, and organizational productivity.
We will continue to test and iterate the framework and invite you to use and repurpose it, and share your experiences in doing so.
