Automate Recruitment Process in Oracle HCM To Hire Better & Faster

Here’s one inevitable truth- you can never take “human” out of human resources. There are aspects like creating a job description, interviewing the candidates, sharing the results- whether good or bad and completing the onboarding. Fortunately, there are ample ways you can automate the recruitment process while saving time finding the best-in-class talent without hampering the positive candidate experience and help build your brand.

Automation in recruitment is the upshot of the slow, tedious, and error-prone manual hiring process that carried numerous implications for the companies, some of which included:

• Poor candidate experience

• Frustrated recruiters and hiring managers

• Laid-back talent acquisition process

• Missed hiring potential from high applicant drop off rates

A report published in 2022 states how companies are gearing up to invest nearly 1.8 trillion USD in digital transformation. By 2025, the amount is expected to touch 2.8 trillion USD.

Why Automating the Recruitment Process Is Gaining Momentum?

Lately, diversity and inclusion are the hot topics amongst recruiters, regardless of the industry. Manually conducting the recruitment process meant introducing unconscious bias, including age, gender, race, or religion. This made the Oracle HR users compromise on the quality of hire, creativity, and innovation.

While businesses have for long struggled to create a hiring process that is bias-free and effective, they have now realized that automation could be the key to supporting an all-inclusive hiring process. A study published supports the inclination of HR leaders towards automation.

How RChilli Resume Parser in Oracle HCM  Helps Automate The Recruitment Process?

An AI-driven tool like resume parser that is engineered to uncover talented candidates quickly has helped establish an objective-based decision-making process that’s based on skilled hiring. While there are numerous resume parsers for Oracle Users in the industry, the RChilli resume parser, a deep learning/AI framework, is designed to identify the complete candidate information from the resumes.  

The attributes that set apart RChilli’s resume parser in Oracle Cloud HCM from competitors include:

• Customized Data Fields Extraction

No matter the industry, each Oracle user has their unique hiring process that includes fetching maximum candidate information and selecting the skills for bias-free hiring. Oracle HCM offers users leverage to select a candidate profile based on 30 standard data fields. 

We at RChilli understand how businesses compete to fill the skills gap in their workforce. Whilst the competitors allow selecting half the fields offered by Oracle HCM, RChilli not only populates all the 30 fields but also allows for customization to add custom fields from the 200+ fields of information that RChilli parse.

Dedicated to making hiring seamless and accurate, we help the users map custom fields on the candidate profiles. These include first, middle, and last name, address based on country, city, state, postal code, experience based on profile, employer name, start and end date, licensing and certifications, education, and more. The recruiters can thus shortlist the candidates quickly with the help of extensive and accurately parsed data.

• An Array of 30+ Parsed languages

We understand that the current recruitment industry is uprooted because of the challenges that the skills gap brings to the fore. Many companies have realized that the key to carving a niche in their industry is to have a globally diverse team rather than restricting to local talent.

Expanding a recruiter’s reach across a talent pool that’s spread worldwide means a brand name within the international borders, a revenue stream that is increasing, and a workforce with diverse cultures and a stronger knowledge base. Ask yourself, do you want to compromise or restrict your reach to global candidates with a parser that parses resumes in, say, 20 or even fewer languages?  

RChilli resume parser helps the recruiters establish global footprints worldwide by supporting all the 30 languages supported by Oracle. Additionally, the parser also parses in Croatian, Arabic, Latvian, Lithuanian, and Slovenian. To bring accuracy in parsing, the parser is engineered to automatically identify the languages of the resumes and extract exact candidate information.  

• Flexible Pricing Module

How many resumes do you think you’ll be parsing this year? As difficult as it is to answer a tentative figure, imagine a scenario

- Scene 1: You’ve got a parser that charges a particular amount for a set number of resumes parsed in English, say $16,000 for 40,000 extractions. If you exceed that credit by even one resume, you’ll have to purchase a new plan at either the same amount or you, at the beginning itself, go for a higher budgeted plan.

Either this or you purchase a higher plan that includes a set of five languages in which the resumes shall be parsed. In case you want to substitute a language out of the five, you’ll have to pay an additional amount for the supported language.  

- Scene 2: There’s a resume parser that comes at a fixed plan irrespective of the number of languages you want to parse resumes in. There’s a flat pocket-friendly fee, whether you’re parsing a single resume in all 25 languages or parsing hundreds of resumes in a few.   

So, on the one hand, there’s a parser that comes with a complicated pricing plan that’ll either restrict the languages you’ll parse resumes in, or you’ll end up paying an additional amount that’ll burn your pockets. Secondly, you go for the one that’ll ask you to pay a flat fee irrespective of the language.      

RChilli resume parser (the second category) offers a well-defined, transparent, structured pricing module that doesn’t include an additional amount for any language besides English. The recruiters can build a globally talented team without worrying about shelling an extra dime.     

• A Dedicated Account Manager

Resume parser, driven by AI technology backed up by rules-based approach, State-of-the-art neural networks (a.k.a. "deep learning") based upon Artificial Neural Networks (ANNs), which rely upon Recurrent Neural Network (RNN)/Long short-term memory (LSTM), takes technical know-how and expertise to run and function smoothly.

However, there can be instances where a recruiter faces a set-up issue, maintenance issue, or a bug that introduces technical glitches. RChilli’s customer support team, in instances like these, is steadfast towards offering assistance and technical support 24/5 without any add-on charges.  

Not only this, RChilli resume parser in Oracle HCM further helps recruiters and companies bring accuracy to their hiring process by:

• Positive Candidate Experience

RChilli resume parser in Oracle HCM Cloud helps enhance positive candidate experience by enabling the candidates to upload their resume on the website’s career page & apply to the job in a single click. The candidates save time and won’t have to fill in the details already mentioned in their CVs repeatedly.

• Able To Parse Resumes In Different Formats

With RChilli resume parser in Oracle HCM, the HR leaders get access to proficient candidates who share resumes in different formats. Regardless of the document format, such as DOC, DOCX, PDF, RTF, TXT, ODT, HTM and HTML, DOCM, DOTM, DOT, or DOTX, recruiters can be assured of getting accurately parsed candidate data.

Key Takeaways

The recruiting industry is evolving consistently. Staying in sync with AI is the only way to stay at the top of building a top-notch and skilled workforce. RChilli resume parser in Oracle HCM will transform your recruitment approach and reduce the time-consuming process that devalued the time for both you and your potential candidate.

RChilli’s resume parser integration helps you prioritize recruitment to attract the best-in-class talent and speed up your time-to-hire, thus giving you ample time to foster a positive candidate relationship. Let us show you how.

Let’s talk or you can also drop an email and I’ll catch up with you.