Common Challenges In Resume Parsing
For organizations using Oracle Recruiting Cloud or any Applicant Tracking System (ATS), harnessing the full potential often requires solutions that address data extraction and candidate experience challenges. Parsing resumes effectively is crucial, yet many platforms face issues such as:
- Incomplete or Inconsistent Data Quality: Parsing errors can result in candidate profiles that lack essential details, impacting data reliability and searchability for recruiters.
- Limited Multilingual Support: With global recruitment, a lack of robust multilingual capabilities can leave non-English resumes incomplete or incorrectly parsed.
- Candidate Drop-Offs: Long application forms can discourage candidates, leading to a high rate of incomplete submissions on job portals.
- Incomplete Profiles Affecting Searchability: Missing fields in candidate profiles can make it harder for recruiters to find top candidates quickly and effectively.
These challenges are particularly relevant for organizations using Oracle Recruiting Cloud to support a global talent pool. While Oracle Recruiting Cloud is a powerful platform, optimizing its effectiveness requires solutions that enhance data quality, candidate experience, and searchability. In the sections below, we’ll explore how overcoming these limitations can unlock the real value of Oracle Recruiting Cloud.
How to optimize resume parsing in Oracle Recruiting Cloud
Streamlining the Candidate Experience for Higher Completion Rates
Today’s candidates expect a seamless and user-friendly experience on platforms like Oracle Recruiting Cloud. However, candidates often upload their resumes only to face long profile forms requiring additional details across sections like job history, education, and skills. This repetitive, time-consuming process can lead to drop-offs.
With the right parsing solution, this challenge becomes an opportunity. The AI-powered multi-language parsing technology can automatically extract essential data from a candidate’s resume and map it directly to the Oracle Recruiting candidate profile fields. This saves candidates from re-entering information, helping them complete their profiles more quickly and with less frustration—ultimately improving their experience and increasing the likelihood that they’ll complete the application.
Zack Kikendall
Global Technology and Process Leader at Cummins
Boosting Data Quality, Building Richer, More Accurate Candidate Profiles
Incomplete candidate profiles are a common issue for recruiters, making it harder to evaluate qualifications accurately and match candidates to job requirements. With an advanced parsing integration, candidate profiles are enriched with precise, detailed data that includes each candidate’s work history, education, and skills. The result is a richer candidate database filled with complete profiles, providing a clearer picture of each applicant’s potential fit.
Not only does this lead to a more comprehensive talent pool, but the higher-quality data ensures that recruiters have the accurate information they need to make more informed hiring decisions.
Additionally, a parsing solution with OCR capabilities expands the range of documents that Oracle Recruiting Cloud can handle. OCR technology supports scanned PDFs, ensuring that even resumes submitted as images can be processed and mapped to profile fields. This capability opens up access to more candidates and reduces manual data entry by converting all resume formats into searchable, structured data.
“Integrating Textkernel’s semantic search technology into Oracle Taleo can help surface 5x more skills in CVs than without. Based on these overwhelming positive results, recruiters can now search their own databases before even posting a job ad.” ENGIE Benelux case study.
Enhanced Database Search and Smarter Candidate Matching
When candidate profiles are fully populated with high-quality data, recruiters can easily search for candidates with specific skills, experiences, or qualifications. By applying advanced, AI-powered semantic search help recruiters search for keywords beyond the search words; the system can interpret and expand on search terms, identifying profiles with related or synonymous skills and qualifications.
For example, a search for “data analysis” might automatically pull profiles with terms like “data analytics,” “quantitative analysis,” or specific tools such as “SQL” or “Python.” This semantic approach ensures recruiters access more relevant results without needing to enter every possible keyword variation manually.
“For us, Textkernel’s technology is a way to do things differently and make our recruitment future-proof. We can find the right talent in less time and are two steps ahead of the competition. We have only started and it’s already adding value.” Frédéric Verkaeren HRIS Solutions Manager, ENGIE Belgium.
A Multilingual Solution for a Global Talent Pool
With today’s increasingly global job market, many organizations need a parsing solution that supports multiple languages to capture the best talent. An ideal parsing solution should handle multiple languages, allowing candidates to complete their profiles accurately, regardless of their language background. For organizations with international recruitment goals, this multilingual support ensures consistent data accuracy and a more inclusive approach to global hiring.
Why Textkernel for Oracle Recruiting Cloud?
Textkernel’s integration with Oracle Recruiting Cloud enhances recruitment in five impactful ways:
- Higher Conversion Rates: By simplifying the application process, Textkernel’s parser minimizes the effort candidates need to complete their profiles, reducing drop-offs and leading to more completed submissions on your Oracle Job Portal.
- Detailed, Complete Candidate Profiles: Textkernel’s accurate data extraction enriches profiles with comprehensive information on work history, education, and skills, giving recruiters a richer, more complete database of qualified candidates.
- Improved Searchability: With fully populated profiles, recruiters can conduct more effective searches, filtering by specific skills or experiences to find top talent quickly. Textkernel’s parsing integration optimizes Oracle Recruiting’s search capabilities, enabling faster, more precise hiring decisions.
- Multilingual Support: With parsing available in 29 languages, Textkernel enables organizations to reach a global talent pool. This multilingual capability ensures that candidates from diverse linguistic backgrounds are accurately represented in your system, enhancing data quality and inclusivity.
- OCR for Scanned Documents: Textkernel’s Optical Character Recognition (OCR) capability allows for seamless processing of scanned PDFs, which Oracle Recruiting Cloud alone does not support. This ensures that data from scanned resumes is captured accurately, expanding accessibility and eliminating manual entry for recruiters.
Together, Textkernel and Oracle Recruiting Cloud provide a powerful blend of technology and enhanced candidate experience, leading to smarter, faster hiring decisions and improved recruitment outcomes.
Learn more about Textkernel Parsing:
- Multilingual Parsing With The Highest Level of Accuracy in Oracle Recruiting Cloud
- Cummins Inc. Chooses Textkernel To Enhance Global Recruiting Process With Advanced Parsing Technology in Oracle Recruiting
- How ENGIE Benelux Armed Its Talent Recruiters To Speed Up Hiring In A Saturated Technical Employment Market
