Let’s face it. One-size-fits-all training programs are a thing of the past. Welcome to the era of personalized learning experiences driven by data-informed insights. L&D's future is becoming increasingly intertwined with the power of skills data. So organizations must invest in gathering and analyzing skills data to stay competitive.
But knowing where to find and start using skills data can be challenging. That’s why we’ve designed this blog series—which explores skills data's transformative role in shaping the L&D’s future and how you can use this data to start cultivating a future-proof workforce.
What is skills data, and why should L&D care about it?
Skills data refers to the information about a person's or group’s abilities, knowledge, and qualifications relevant to their performance in a specific job or task. This can range from hard skills, such as project management or structural engineering, to soft skills, like critical thinking or conflict resolution.
This data also can be quantified (e.g., how many years of experience a person has in a certain skill or industry or the score or grade they gained from an exam or qualification) or qualified (e.g., performance review feedback or self-reflective review scores).
As a result, skills data and the resulting analytics are critical in shaping an organization’s success. From recruitment to strategic planning, skills data aids decision-making processes and fosters an environment where employees can grow and thrive.
So it’s imperative for organizations to invest in gathering and analyzing skills data if they want to stay competitive.
This quote from our respected friend and recognized thought leader Lori Niles-Hoffman showcases the fine nuances that surround skills and, therefore, the importance of getting your approach correct:
“A barista in Starbucks is not the same as a barista in Milan. Yet, on paper, they share the same title. If we only use titles and ignore skills analytics, we could find someone struggling to make a cortado for a customer or wasting their latte foam art talents. Skills analytics are the only way for companies to truly identify their gaps and strategically close them."
Let skills data inform your L&D strategy
Skills data should play a crucial role in informing a comprehensive strategy for L&D, as it provides a comprehensive view of your workforce's current skill sets.
Using this skills data, for example, you can:
- Identify skill gaps. Once you know where training is needed, you can develop a strategy that ensures learners stay on track and updated on their unique skill sets.
- Determine which areas require additional training. Create an L&D strategy that includes regularly monitoring skill competencies to help ensure everyone works to their full potential.
- Optimize L&D’s operations. Stop wasting time (and money) on bad content. Once you've identified skills needs, you can consider if your current programs are redundant and build a strategy that ensures L&D meets learners’ needs by offering the content they want and need.
The significance of skills data in talent development
We can't overemphasize the importance of skills data in talent development. Organizations must continuously adapt and evolve to thrive and remain relevant in today's competitive environment.
When it comes to industry-specific knowledge and related training, the growing prevalence of electric vehicles (EVs) is hard to ignore. The demand for this new and evolving technology means EV technicians need proper, up-to-date training.
For instance, one Watershed client identified a skills gap after noticing an increase in auto repair technicians searching for information on batteries in their learning platform. The L&D team then addressed the issue by creating additional content to meet the technicians’ needs and close the skills gap.
One key factor driving this need for constant growth is the rapid pace of technological advancements and the corresponding demand for new skills. That means companies must invest in their employees' development to ensure they have the skills needed to excel.
And data is a critical part of this process—enabling organizations to:
- identify skill gaps,
- design targeted training programs to address those gaps, and
- monitor ongoing progress.
This is especially relevant as Gartner reports that 64% of managers don't think their employees can keep pace with future skill needs. Furthermore, 70% of employees say they haven't mastered the needed job skills.
Skills data also can help you make informed decisions about talent development, ensuring your investments in training are both efficient and effective. By analyzing skills data, you can pinpoint the areas where employees need improvement and tailor their training accordingly.
As a result, this targeted approach helps you maximize the return on your investment in L&D, as employees are more likely to develop and apply the required skills in their daily work.
And finally, skills data helps you pinpoint high-potential employees and foster their growth. By tracking the development of individual skills, you can recognize top performers and offer opportunities for further development and advancement.
This approach benefits employees and contributes to the organization's overall success, as skilled and motivated employees are essential for driving innovation and growth.
The shift from traditional training and development to data-driven L&D
Traditional L&D approaches often rely on one-size-fits-all learning programs that don’t address the unique needs of each employee.
However, data-driven L&D combines learning, skills, and HRIS data to create personalized employee learning experiences. This shift toward a more customized approach means a more effective skills development process and helps boost employee engagement and satisfaction.
Another advantage to data-driven L&D is instant employee performance feedback. You can continuously monitor skills data to identify areas where employees struggle and provide targeted support.
This real-time approach helps you address skill gaps before they become critical, ensuring employees remain competent and confident in their roles.
A data-driven approach also helps you stay ahead of the curve because you can anticipate and respond to emerging trends and skill requirements.
By analyzing skills data, you can identify emerging in-demand skills (i.e., predictive analytics) and develop training programs to address these needs proactively (i.e., prescriptive analytics). As a result, you can future-proof your workforce while maintaining a competitive edge.
Blog Series Key Takeaways
In this blog series, you’ll learn:
- How to access and analyze organizational skills data. When you have tens of thousands of employees, you also have a lot of potential data and related sources pertaining to employee skills. So where and how do you get started?
- How to get a comprehensive view of your skills data across the organization. To effectively upskill, reskill, or hire new employees, you must know what skills already exist in the organization. That’s why you need a global view of all your skills data to help you make informed decisions.
- How to assess skills competency levels. Are you missing out on untapped potential, increased productivity and engagement, or maximizing L&D’s budget?
- How to reveal skills gaps and opportunities for improvement. See how you can pinpoint and rectify skills gaps—which can result in declining productivity, time wasting processes, and errors and accidents.
- How to align self-skills competency ratings with managers. Just because someone possesses a skill doesn’t mean they’re automatically an expert on the matter. Learn how to accurately rate people’s skill levels and provide the appropriate solutions.
- How to differentiate between trending and emerging skills. Why should you keep tabs on what skills are new or growing in popularity? Here’s what you need to know so you can maximize your L&D efforts.
- How L&D can embrace skills data. We’ll wrap things up by reviewing best practices for integrating skills data into your L&D strategy and discussing the skills data trends we hope to see in the future.
Up Next: How to access and analyze skills data
Before you can aggregate the learning and skills data from all your systems and sources into one place, you’ll need to create a learning ecosystem where you can track everything. And we’re not just talking about what people learn, but how and where they learn and in what format.
Join us for the next blog post in this series, which dives into how you can access and analyze skills data across the organization.
About the author
As the Director of Customer Success at Watershed, Peter Dobinson is passionate about developing connected learning ecosystems that empower organizations to deliver exceptional learning experiences. With a strong foundation in product design and management, e-learning interoperability, system integrations, user-centered design, and data analytics, he thrives in helping organizations get the most out of Watershed’s capabilities. Peter's background in learning technology means he has the knowledge and expertise needed to drive the implementation of innovative solutions such as xAPI within the L&D industry. He also works closely with clients to ensure they understand Watershed's full potential and can maximize its power to create lasting, positive impacts. In other words, Peter helps organizations unlock the true potential of learning—one ecosystem at a time.
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