As part of our ongoing research on skills and competencies, we recently gathered leaders for the second roundtable on skills. This session focused on the question of finding and using skills data. Some of the questions we discussed were:

• Why is skills data “hot” or important right now?
• How does skills data differ from competency data?
• What sources of skills data are orgs using?
• How are orgs using skills data?
• What do you imagine skills tech will enable orgs to do in the future?

Mindmap of Finding & Using Skills Data roundtable

The mindmap below outlines the conversations we heard as part of this roundtable.

Key takeaways

We had an engaging, energetic conversation that helped us better understand how skills data is being used in orgs, the challenges associated with skills data, and some possibilities for the future. Here are 5 key takeaways.

Skills connect work and talent

Leaders agreed there is an increasingly core connection between work and talent. Particularly since the pandemic began, orgs find themselves needing to pivot quickly to respond to rapidly evolving environments.

Agility has become a survival imperative, which means it’s critical for orgs to be able to put the right people in the right places…fast.

Skills are the way orgs can figure out who the “right people” are. With insight into who has what skills – and where those skills are needed – orgs can quickly move key resources to the places and projects they’re needed most. Some leaders noted that skills apply not only to individuals, but also to teams.

Skills data sources are everywhere

When we asked leaders to name some sources of skills data, the answers flooded in. We counted at least 15 types of skill data sources, including job descriptions, talent profiles, job histories, education history, certifications, social profiles like LinkedIn, collaboration sites like GitHub, productivity software like Asana and Jira, and even communications platforms like Microsoft Teams, Slack, or email.

One challenge is that most of these sources are currently not well integrated, making it difficult for orgs to identify all the potentially relevant skills an employee has. Skills data remains siloed or, in some cases, hidden. In one example, a leader pointed out that an employee might develop skills through volunteer experience – but those skills may never be reported in their skills profile at work.

Partly due to this fractioned information, leaders still struggle to understand what skills exist in their org. This makes evaluation and planning difficult. As one leader pointed out, “Without a baseline of where we are now, it’s hard to understand if upskilling efforts are effective.” It’s also hard to know what skills to develop.

Think carefully about use cases

There remains real confusion in orgs about skills vs. competencies. Leaders reported they sometimes struggle to clearly articulate the differences between the two to others in their orgs. This confusion can create resistance to change.

A few participants reported they tackle this challenge by identifying use cases for skills vs. competencies. They ask, "In what situations might skills be appropriate? In what situations might competencies be better?"

In response to these questions, many leaders agreed that competencies may be most appropriate in cases where it’s critical to understand proficiency – for example, in talent acquisition and performance management. By contrast, skills may be more appropriate when the goal is agility, mobility, or employee development.

Skills verification and proficiency rating remain difficult

Many skills platforms currently offer a skills tracking functionality that indicates whether a person has a skill or not. Often this data is self-reported, selected in the platform by the employee.

Some leaders want to complement this self-reported, yes/no data with more meaty, contextual information. They want to know whether the employee really has the reported skill (skill verification) and how well the employee can perform the skill (proficiency rating). They noted that self-reported data introduces the risk that individuals may under- or over-estimate their own skills. They also highlighted the potential diversity, equity, and inclusion implications of self-reporting, as some populations tend to consistently under- or over-report their skills. Skills verification and proficiency ratings could help reduce these reporting biases as well as give leaders better data for resource planning.

A few leaders voiced concern that current methods of skills verification may ask too much of employees. If too many requirements are put on users, they may stop reporting their skills altogether. They wondered: Can we find ways to verify skills, measure proficiency, and provide a simple, fun, and easy user experience for the average employee?

Tech can help make skills fun and easy

Leaders imagined that in the future, skills tech will be so fun and easy to use that it will become part of everyone’s job to be transparent about their skills and development goals.

Generational or tenure-related challenges may hinder widespread adoption of skills, however. Whereas younger or less experienced employees may be motivated to report their skills and to use skills platforms to build social communities, employees closer to retirement may see less incentive to do so. It will be important to make skills fun, easy, and clearly beneficial to all employees if skills tech is to be widely adopted.

Some orgs have successfully demonstrated the benefits of skills by pre-populating employees’ skill profiles, then asking employees to review and approve or update their profiles. With this approach, employees see an immediate and concrete benefit: the recommended learning opportunities the system generates based on the gaps in their profile.

Data integration, analytics, and reporting are other areas leaders highlighted for the future of skills tech. Currently, some platforms pull together data from a variety of disparate sources. Building on this capability, leaders would like to see all available data in one place, with robust reporting and analytics support. They also envision more adaptability to specific use cases, more tailored reporting in response to specific inquiries, and more efficient aggregation and sorting.

A special thanks

This session helped us more clearly understand the ways skills data is being identified and used in orgs, the challenges associated with using this data, and the hopes leaders have for the future of skills data in their orgs. Thank you again to those of you who attended and enriched our discussion. And as always, we welcome your suggestions and feedback at [email protected].