Over the past 15 years, we’ve uncovered essential lessons that provide deep insights into skills development, tagging, content management, discovery, and data in Learning and Development (L&D). Our 100+ page booklet delves into the complexities and cutting-edge best practices that are shaping the future of L&D today.
Skills: beyond the buzzwords
L&D conversations are increasingly dominated by skills. But it’s not enough to just talk about them; they need clear definitions. Take 'resilience' for example: is it more about self-awareness or grit? Not all skills are the same—some require different levels of mastery, and not all follow a neat, linear progression. A 1–5 scale may oversimplify the growth path of nuanced skills.
In the workplace, skills are taking centre stage as job roles become more fluid. With lateral career moves becoming more common, rigid job descriptions are becoming less relevant. Instead, workers and employers are focusing on the granular skill sets that make up each role. But it’s not just about skills—values, attitudes, and mindsets also play crucial roles in employee development.
Moreover, skills gaps are a pressing concern for many industries. Technological advances, like generative AI, demand that workers adapt and acquire new capabilities. L&D professionals need to offer tailored, agile solutions to help employees close these gaps.
↪ 100 Skills Every Corporate Needs
Tagging: a complex necessity
Tagging content with skills might seem straightforward, but the reality is much more complicated. As soon as you have over 50 skills, tagging manually becomes a Herculean task. Yet, accurate tagging is vital—it’s essential that tagging accuracy sits above 80%, or risk ineffective content discovery. False positives and true negatives are common issues that require careful management.
What’s more, tagging often oversimplifies content by classifying it as either relevant to a skill or not. In reality, most pieces touch on multiple skills, making binary tagging an imperfect solution. To improve content discovery, organisations need to consider more imaginative tagging strategies—think beyond skills to other content characteristics, such as whether it’s evergreen or perishable.
Great search capabilities may reduce our reliance on rigid tagging systems, but ranked scoring of content can provide a more effective alternative. By assigning a ranked score rather than simply tagging it, L&D professionals can prioritise content from top to bottom (literally).
↪ How we helped Ericsson achieved 79% skills tagging accuracy
Content: quality over quantity
Content audits that ignore internal content are incomplete. Internal content—especially that generated by subject matter experts or employees themselves—can be a rich resource. However, when sourcing external content, businesses don’t need endless libraries; even Fortune 500 companies typically only need a couple of comprehensive content libraries to cover the essential skills.
Yet, many companies struggle with content chaos—huge libraries of learning assets lead to poorly organised pathways, which can overwhelm rather than aid learners. Additionally, much learning content is criticised for being too generic to be truly useful. When selecting vendors, it’s important to choose a combination of suppliers that will meet the organisation’s specific skill and topic needs, rather than going for the vendor with the biggest library.
↪ How Imperial Brands Reduced Pathway Curation Time by 83%
Discovery: surfacing the right content
Content discovery remains one of the biggest challenges for L&D professionals. It’s not enough to have the right materials—you need to ensure learners can actually find them. This is where tagging, search, recommendations, and pathways all play a role. But with discovery comes complexity. Many companies struggle to balance the abundance of content with making it accessible and relevant.
It’s vital to measure the effectiveness of your discovery tools. Metrics like search success rates, usage data, and feedback surveys can all offer insights into whether employees are finding what they need. AI can assist with content discovery, but it can’t fully grasp business context or individual needs, meaning human intervention is still essential for the final mile.
↪ Taming Pathway Chaos: Pathway Auditing Service
Data: the backbone of business
Data is a powerful tool for driving change and proving the impact of L&D initiatives. Unfortunately, L&D departments often struggle to leverage it effectively. The right data can provide the confidence needed to make informed decisions and drive improvements in L&D strategy.
For companies exploring AI, the importance of clean, structured data cannot be overstated. 'Garbage in, garbage out' rings true—without solid data foundations, AI will be ineffective at best and counterproductive at worst.
↪ Unlocking the Power of Filtered Analytics
A final thought: combining skills, content, and data
As we move further into 2024, L&D professionals must master the delicate balance between skills, content, and data. The rise of AI and the increasing importance of skills taxonomies and frameworks mean that businesses need to focus on building flexible, scalable systems. Filtered, with 15 years of experience in the industry, is ready to help organisations build these frameworks, ensuring their L&D strategies remain agile, effective, and future-proofed.
This comprehensive 100+ page booklet offers a wealth of insights, drawn from extensive experience and analysis. Whether you're grappling with content discovery, skills development, or optimising your data, there's a lesson here for everyone involved in L&D.
If you’re ready to enhance your organisation’s L&D strategy, Filtered is here to help. Let’s turn these lessons from 15 years of experience into actions and ensure your workforce is equipped with the skills they need to thrive in the modern workplace.
