Lisa O’Brien wasn’t satisfied with having to use spreadsheets or other manual processes to track and update the skills of the workforce at Unum, the employee benefits provider where she works as director of global human resource information systems. For Unum’s leaders to make better-informed decisions about how to recruit and develop employees to meet the changing needs of the business, O’Brien knew the company needed a more automated, real-time inventory of the skills Unum employees have so it could identify and close any glaring gaps.
For help, O’Brien turned to skills intelligence software, a new breed of technology that automates the collection, organization, updating and analysis of workforce skills, typically featuring a skills taxonomy as a core element. The scalable technology is increasingly used by companies adopting a skills-based talent management approach, through which they hire and promote workers based more on their verifiable skills than on traditional credentials, such as educational degrees or job histories. Talent acquisition experts see a “skills-first” approach like this as a way to democratize the recruitment and promotion process, as well as to broaden the talent pools available for hiring.
“The software allows us to access a relational library of machine-learning-curated skills that’s far more extensive and robust than what we would have been able to build and maintain on our own,” O’Brien says, in reference to the “skills cloud” product she uses from Pleasanton, Calif.-based vendor Workday, which incorporates skills data from outside of Unum.
O’Brien says a more comprehensive skills inventory and user-friendly skills software platform have become essential to Unum’s workforce planning.
“We’re launching a new campaign to encourage our employees to update their skills in the software,” she says. “As an outcome of the initiative, we hope to better understand the skills landscape at Unum, identify where we may have skill gaps and make more informed decisions about how to develop our workforce.”
Skills Intelligence Software Integrates Data
HR professionals have long compiled lists of employee capabilities in the form of complex competency models or job architectures designed to help guide recruiting and training practices in their organizations. Skills intelligence software represents a leap forward by creating a more automated way to compile and integrate skills data from internal and external sources and more easily update databases as employee skills are added or subtracted from organizations.
Skills taxonomies in these platforms organize employee skills into hierarchies featuring groups and clusters, focus more on the granular skills needed to perform specific jobs than on broader competencies, and also enable line managers to validate workers’ skills. A skills “ontology” is a similar concept but focuses more on attributes that define relationships between different skills in the framework.
A more agile skills taxonomy is increasingly essential to workforce planning, given how quickly organizations’ skills needs can change. For example, recent data by research and advisory firm Gartner showed that nearly one-third of the skills needed for a job in 2018 wouldn’t be needed by 2022 and beyond, and that the average number of skills needed for a single job has been increasing 10 percent year-over-year since 2017. Gartner’s research also found that 47 percent of HR leaders reported not knowing what skills gaps exist among their current employees.
Skills data historically has been kept scattered in silos throughout an organization, with little connective tissue between those disparate systems. Recruiting platforms extract and store skills data from job candidate assessments, resumes and LinkedIn profiles; learning management systems glean skills gained by employees through learning courses; and human capital management platforms capture skills from performance reviews, internal job relocations, onboarding data and more. Yet, each of these different databases has its own vernacular, compiles different forms of data and often orbits in its own universe.
Next-generation skills intelligence software attempts to integrate and normalize that dispersed data to create “one source of skills truth” to give CHROs and other talent leaders a more holistic, real-time view of workforce skills. Without such data, workforce experts say, leaders are left to make “gut feeling” decisions about where employees’ skills gaps lie or how to best redeploy workers to meet changing business needs.
“Access to that kind of comprehensive skills data can help leaders make much better strategic decisions about talent management,” says Dani Johnson, co-founder and principal analyst of RedThread Research, an HR advisory and research firm in Woodside, Calif.
A 2022 study by RedThread Research found that the skills technology market is rapidly growing, with 90 percent of the 45 technology vendors profiled in the study offering skills-tracking functionality. A sample of providers large and small in the market includes Workday, -ServiceNow, Eightfold, Fuel50, Gloat, TechWolf, SkyHive and Neobrain, as well as learning technology companies such as Degreed and EdCast.
New features offered by these vendors also make it easier to combine a company’s own skills taxonomy with third-party sources of skills data to broaden the universe of skills that can be tracked to include external market data. Customers of Degreed, for example, can combine their own taxonomies with the vendor’s vast skills inventory amassed from years of compiling training data from users of its platform.
“Many organizations find the ability to create such a hybrid skills taxonomy valuable,” says Steve Boucher, director of strategic initiatives for Degreed. “Our customers can upload and integrate their own specific taxonomies with our skills inventory so it becomes more comprehensive and also customizable to their unique talent management needs.”
No Quick Fix
Reaping the benefits from skills intelligence platforms isn’t as easy as simply purchasing and activating the software. HR technology analysts say the heavy lifting has only begun when you decide to invest in a platform, particularly when it comes to building a useful skills ontology.
“The real challenge is implementation, because comprehensive skills ontology software doesn’t work right out of the box,” says Josh Bersin, a global HR industry analyst and CEO of the Josh Bersin Company in Oakland, Calif.
Making this technology pay off requires doing the difficult work of integrating many disparate sources of skills data from across an organization and from third parties, which demands that HR first get its own processes and data in order.
“There still isn’t one end-to-end vendor solution that incorporates all skills data in a company,” Bersin says. “I’ve seen many companies that do a good job of implementing taxonomies in specific domains or for specific job functions or roles, but creating a comprehensive system that incorporates skills data from recruiting, learning, HR, compensation or succession is still a big project for most organizations to take on.”
Given how quickly new employee skill requirements are emerging in many industries and existing ones are growing obsolete, a skills intelligence platform also must be highly agile and strike the right balance between focusing on internal and external skills data.
“Creating a skills ontology is a more complicated challenge than most people think because it’s a constantly changing database that requires external data to be effective,” Bersin says.
“If you’re a pharmaceutical company, for example, you need to know what kind of advances in science are happening in the outside world that will change the type of skills you need internally,” Bersin adds. “But the skills technology vendors are constantly learning from this, and their products continue to be what I call a ‘work in process.’ ” —D.Z.
Updating and Verifying Employee Skills
Some skills technology platforms are also making it easier for employees to enter or update their own skills in databases. Unum’s O’Brien says the Workday software she uses has improved the end-user experience by making it easier and more intuitive for both employees and job candidates to add skills to databases using an automated “skills suggestion” feature that ensures users don’t overlook any of their relevant capabilities.
“When employees add skills to their internal profiles or candidates add skills to their job applications, they’re presented with skill suggestions driven by machine learning,” O’Brien says.
How the skills added to databases are verified is also vital to how credible and useful skill taxonomies or ontologies become. In many systems, employees self-evaluate their skills and rate their proficiency levels, with managers or subject matter experts often asked to verify the ratings.
Josh Bersin, a global HR industry analyst and CEO of the Josh Bersin Company in Oakland, Calif., says the degree of skills validation an organization chooses should depend on the nature of the job and the company’s goals.
“If you’re trying to certify people to fix the $5 million pump in the oil refinery, you probably want to certify, validate and observe those skills before you bless someone as ‘skilled,’ ” Bersin wrote in a recent blog post on skills intelligence software. “But if you want a global process for validating skills that scales, so that everyone in the company has a reasonable skills profile, I’d keep it simple. You can use self-assessment and manager verification and it works very well.”
More sophisticated skills platforms also use AI to “infer” skills for employees who may not have listed all of their current capabilities on a resume, LinkedIn profile or internal skills database. Inference technology reads, analyzes and harvests data from internal and publicly available external sources to provide a fuller and more up-to-date picture of employees’ skill sets.
Another benefit of this software is its ability to provide hints or inferences about existing employees who are likely to be good at other jobs in a company—inferences that weren’t obvious before. For example, one company using skills software with AI-driven skills-matching capabilities discovered that financial auditors had skills that could be transferred to cybersecurity roles. This helps organizations that are struggling to find job candidates to fill open roles when external talent pools are thin.
“This is an area where many of the vendors look the same but in reality have very different capabilities,” Bersin says. “The more advanced platforms have AI that can examine public data to determine things like what projects you worked on for previous employers, who you worked with, and what code you wrote or learning courses you took, to infer skills you have that weren’t listed on the limited space of a resume or a LinkedIn profile.”
Value of External Data
Some skills intelligence software can also import external data from global labor markets to keep HR leaders informed of which workforce skills may be rising or declining in value. In past years, talent leaders in the automotive industry might have used such intelligence to forecast a coming need for more workers skilled in producing electric vehicles, and CHROs in energy companies could have predicted a need to recruit or develop more employees with skills in renewable energies such as solar and wind.
“Right now, for example, you might see that AI skills are rising in value and some traditional software programming skills are flat to declining,” says Bersin, who adds that some skills platforms can also help companies gather intelligence in areas such as available talent pools in geographies where they’re considering expanding or can benchmark their workers’ skill sets against the competition’s.
“You could compare the engineering skill sets in your company to a competitors’ engineering skill sets, for example,” Bersin says. “Or if you’re thinking of opening an office or a distribution warehouse in a new city, skills technologies that import external data could give you an idea of the talent pool available there versus in other cities.”
Employees can also benefit from access to this kind of market intelligence, Bersin says.
“Workers could use the data to figure out what type of training or job experiences they need to make them more marketable in a current climate,” he says. “Employees may not be aware there’s an emerging surplus of skills in some areas and a dearth in others, for example. That can help them make decisions like learning new programming languages that are rising in value, rather than those that are declining."
Dave Zielinski is a freelance business journalist in Minneapolis.
Illustration by Michael Korfhage for HR Magazine.