The Foundation of the Workday Skills Cloud

Skills are quickly becoming the great equalizer. By looking at skills over pedigree or connections, organizations can make smarter hiring decisions in the first place and enrich the employee journey later with upskilling and more internal mobility. Companies can also better identify skills gaps across the organization in light of future business goals and source their talent more strategically to help drive the business forward.

With the ability to rapidly fill roles and staff projects, and connect existing employees with the right development and stretch opportunities, companies can truly harness the strength of their most important asset.

But to effectively connect people with opportunities, organizations first need to understand the skills their people have and then see where in the business there are skills gaps. Employees are always learning and developing new skills through on-the-job experience, courses they might be taking on their own time, or even through hobbies. The business landscape is always evolving, so the skills your company needs now aren’t necessarily the ones it needs next year, to say nothing of five to 10 years from now. Perhaps most difficult to manage, skills are evolving faster than most recruiting and hiring technologies. New or newer versions of programming languages are always popping up. And something like Kubernetes, for instance, might start off as the name of a technology but eventually become known as a skill.

At Workday, we’ve been looking hard and long at how to help our customers better understand the skills they have in their organizations. When we第一个开始技能的旅程,我们介绍了cl技能oud, which we believe is a true technology differentiator as we start to realize our broader talent optimization vision. Some skills platforms are disconnected from workers and rely on a static list of skills that’s often woefully outdated. But at Workday we believe that skills are the fundamental currency of the changing world of work. And, like currencies, their relative values are always changing while their foundational importance stays the same. In other words, our approach to skills reflects an ever-changing reality—the imperfect match between the skills workers have and the skills organizations need—in real time.

Let’s take a closer look at how we engineered skills cloud to give the greatest possible value to our customers.

Machine Learning: The Key to Understanding Relationships Between Skills

Workday’s skills cloud is a universal skills ontology (a way of understanding what makes up a skill and the relationship between different skills) that cleanses, understands, and relates job skills data. Built into the underlying framework ofWorkday Human Capital Management(HCM), the skills cloud foundation leverages machine learning and usesgraph technologyto not only maintain this growing list of skills, but also map how closely skills are related to each other.

And it's not simply that someone with Excel skills likely also has skills in Google Sheets. But taking this example, someone highly skilled in Excel will likely have skills in data analysis, reporting, and other tasks Excel is used for. You wouldn't know this in a typical database of skills. This is important because when it comes to recommending candidates for jobs, for example, you shouldn't have to rely on keyword mapping. The technology should understand how skills relate to one another and evolve over time.

We built skills cloud with data provided by our customers—as well as massive industry-standard sets of training data—so that we can better understand the needs of not just current customers but future ones. We use machine learning and graph technology to map the relationships between skills so that we can dynamically represent these ever-changing relationships.

Extending the Graph

Uniquely, Workday can add even more value for customers by creating a skill-based representation of any professional document, based on our technology's representation of skills. What does this mean? It means we can understand the relevant skills to any structured or unstructured document, for example, a resume, learning content, job description, etc., and extract those pertinent skills and simultaneously represent such a document “spatially.”

Understanding the spatial representation of skills provides a clear picture of how closely skills are related to one another, as well as to those entities represented with skills (jobs, for example). This enables us to determine a more optimal path toward a target result—in this case matching workers or candidates to jobs, content, learning, mentors, etc.; and vice versa, matching jobs to candidates, learning to workers, and more.

This spatial representation of both the underlying skills and documents allows the implicit discovery of skills across workers, candidates, learning content, teams, and organizations, without the addition of explicit work of entering those skills. This also allows a representation of all documents in how they relate to each other in the “language of skills.” This unique observation is the basis of many machine learning-driven solutions and products that we have brought to market, such asWorkday Talent Marketplace, as well as new capabilities across recruiting, talent, learning, compensation, and workforce management.

By transforming that probabilistic graph of skills into a spatial representation of that same data, we can now substantially enrich that base data, and move to higher-value applications. This also enables us to leverage that same foundational base to build a diverse but consistent set of applications—which simply isn’t possible with siloed data sets and traditional development patterns.

Understanding these relationships, in a cloud-native, consistent source of truth, enables us to build out a unique set of skills functionality. With a robust set of worker data stemming from a customer community that includes more than 45 million workers globally, we can rapidly innovate across Workday applications to continue to bring more value to our customers. Think of skills cloud as the heart that pumps lifeblood into all the parts of the corporate body—no matter how it changes or grows, or what new muscles it develops.

The More It’s Used, the Better It Gets

Because skills cloud is woven into the fabric of Workday HCM, it naturally extends to many Workday applications, such asWorkday LearningandWorkday Recruiting. This means that if a worker gains a new skill through Workday Learning or a short-term rotation inside the company, all recommendations in Workday related to learning, gigs, mentors, and opportunity graph will adapt and make different recommendations to either further develop this new skill or suggest what the worker’s next skill should be.

The foundation we’ve created enables us to develop new features and functionality quickly. And as part of the same skills cloud “heart,” they are all evolving simultaneously in real time, without a hiccup, to support customers who are using skills to drive talent optimization.

For example, with our second major release in 2020 (read about our new release schedulehere), we have introduced more than 25 new features, including:

• Suggested skills for candidates
• Suggested skills for workers
• Suggested Workday Learning content
• Skills verification and endorsements
• Suggested gigs
• Jobs matching (in Workday Recruiting)

Importantly, our capabilities driven by skills cloud have grown at such a pace that we’ve been able to deliver our Talent Marketplace, where people and opportunity meet in a smarter way. We look forward to helping our customers leverage the Workday Talent Marketplace, and to expanding the use of our skills cloud, as we continue to help them navigate a changing world of work.