SAP Fieldglass makes skills-based hiring faster and more accurate. With flexible placement of qualifications, AI-suggested skills, a unified qualifications library, standardized 1–5 rating scales, and smarter candidate matching based on qualifications—not just job codes— buyers and suppliers get clearer insights and better-aligned candidates with less manual effort.
These enhancements help organizations find the right talent quickly and consistently.
1. Enable Skills-Based Hiring Where It Matters Most
Hiring needs differ across contingent types and roles. SAP Fieldglass lets you decide exactly where to apply skills-based hiring—at either the contingent type level or on job posting templates.
This flexibility means the Qualifications section appears where you need it most, ensuring skill requirements are visible and consistent without disrupting existing postings. Buyers can communicate expectations clearly, while suppliers instantly understand what’s required.
Use Case
A professional services firm hiring temporary consultants enabled Skills-Based Hiring on its job posting templates. This enhancement allows hiring managers to review job descriptions and add relevant skills directly within the posting—without navigating across multiple pages. As a result, they can complete job postings more quickly, reducing back-and-forth navigation and saving valuable time.
2. Get Smarter with AI-Powered Qualification Recommendations
Buyers often spend time reviewing old postings trying to remember which skills to include—or forget key qualifications altogether.
With AI-powered qualification recommendations, SAP Fieldglass uses machine learning to analyze your job title and description. It then suggests relevant skills. Buyers can easily add them to postings, ensuring consistency and completeness. Suppliers, in turn, align workforce records to these skills, improving match quality.
Use Case:
A healthcare provider hiring temporary nurses across multiple locations used AI recommendations to surface essential skills like ICU experience and EMR familiarity. By including these automatically suggested qualifications, they received better-aligned candidates and reduced supplier clarifications.
3. Bring Consistency with the Unified Qualification Library
Ever noticed how “Azure Cloud,” “Azure”, and “MS Azure” all describe the same skill? When buyers use varied terminology, comparing candidates’ terminology and the buyer’s terminology becomes a nightmare for the suppliers.
The SAP Fieldglass Unified Qualification Library solves this by consolidating all qualification data into a Unified Qualification Library. Suppliers can merge duplicate skills, retain assessment ratings, and permanently align workforce data with buyer requirements.
This consistency reduces errors, accelerates submissions, and ensures that skills mean the same thing across the board.
Use Case:
A global IT services firm once had to manually reconcile skill names across five suppliers. With the unified library, “Java Developer” and “J2EE Developer” are automatically consolidated, and machine learning flags exact matches to the buyer’s terminology of their requirements. The result? Less admin work and faster, more accurate candidate evaluations.
4. Assessment Scale Normalization
Different buyers often use different rating scales for the same skill—one might rate Excel proficiency 1–3, another 1–5. That inconsistency makes fair comparisons difficult.
SAP Fieldglass now normalizes assessment scales across postings and workforce records. All SAP Fieldglass Unified Qualification scales are standardized to a 1–5 scale, with updates synchronized in real time.
Use Case:
An engineering firm hiring external project managers saw varied skill ratings across buyers. Normalization of the SAP Fieldglass Unified Qualifications on candidate's workforce record to a common 1-5 scale ensures every candidate was evaluated accurately and and that evaluations are easy to maintain.
An Important aspect of this feature is that the workforce record always uses a standardized 1–5 scale. If a buyer uses a different rating scale—for example, 1–10—the system automatically converts the workforce rating to match. So, if a worker’s Java skill is rated 5 on the 1–5 scale, it will display as 10 on the buyer’s 1–10 scale.
5. Skill-based Matching of Potential Candidates
Previously, SAP Fieldglass matched potential candidates only by job code, which sometimes meant great talent slipped through the cracks because the system overlooked highly qualified candidates whose job codes didn’t exactly match.
Now, potential candidates are identified based on either job code or matching qualifications. The enhanced modal appears directly in the Qualifications section and displays match percentages for quick evaluation. Only candidates with at least a 25% qualification match are shown—helping buyers or hiring managers focus on the most relevant profiles.
Use Case:
A company hiring logistics coordinators during peak season found candidates who didn’t share the same job code but matched key qualifications. The system flagged one with a 70% match, helping recruiters fill roles faster.
Quick Tips and Things to Know
Skills-based hiring isn’t just about finding candidates—it’s about finding the right candidates, faster. With these enhancements, SAP Fieldglass empowers organizations to standardize skill data, streamline job postings, and make data-driven hiring decisions with confidence.
Have you tried skills-based hiring in SAP Fieldglass? Share your experiences in the comments, and don’t forget to check the documentation on the SAP Fieldglass Help Portal for more insights.
You can also have a look at the following topics in the What’s New Viewer for SAP Fieldglass for more details:
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