Sieving through resumes. Smartly.

Automation of recruitment activities has been gaining massive adoption in organizations around the world, due to the need for cutting time, cost, and bias issues associated with human analysis. Recruitment companies are now taking assistance from the advanced technologies of artificial intelligence and big data analytics to find the right candidate from the dynamic job market and heavy competition. The key module in any recruitment software deals with the candidate evaluation /selection processes - the most time-consuming part of recruiting.

Business opportunity: Integrating for success

Our client needed an intelligent candidate evaluation platform for recruiters to rank the candidates based on the particular job requirements and resumes. Using automated processes for evaluating dozens to hundreds of resumes would help the recruiters to identify the most suitable candidates quickly, accurately and efficiently. A unique product differentiation was to have a scoring system concept for ranking the candidates, which was analysed, designed and implemented by Cabot. But all these could start only after we got the individual resumes properly parsed to extract its data in a usable format.

The overarching challenge was about selecting one of the two possible options - developing a parser from scratch or integrating with a suitable third party application. For any startup business, an important consideration is testing the market with the core feature as soon as possible.

Challenge 1:

Resumes are usually in different file formats, content layouts, information arrangement and so on. Relevant data will need to be extracted regardless of these differences and compared by the system quickly from an often huge volume of resumes. Accuracy and reliability are critical given the goal of the exercise and affords no room for error. Technically, this would pose the biggest challenge as it is also the core value or selling point.

Solution:

The first step was extensive market research and internal discussions on the technical scenarios. For building Resume Sieve Cabot went deep into various resume parsing softwares and consulted with experts in this field. Finally we agreed with a Resume parsing software called Rchilli. Amongst the various parsing softwares out there, Rchilli was found to have a definite upperhand, Rchilli can extract resume information into 140+ fields. The Optical Character Recognition (OCR) add-on feature can scan the printed document and digitize the whole text

Challenge 2:

Most of the recruiters are using other established applications for job posting and receiving resumes. Would it make sense for our client to elaborate on developing and marketing these capabilities and try to compete? The client also wanted to send the candidate for a behavioral assessment from Resume sieve.

Solution:

Instead of trying to develop functionalities already provided by other players, Resume sieve decided to integrate with multiple established job posting and candidate application systems such as Zoho Recruit, Greenhouse and Bullhorn. The application architecture is designed in such a way that, in the future, it will be possible to integrate with other similar players with minimal effort. Using this integration, resume sieve recruiters can import resumes and jobs from these portals into Resume Sieve. For the behavioural assessment part, Cabot and the client opted to integrate with another player for providing that competent feature quickly. So we mutually agreed to go with Think-X. Think-X is an application which gives a behavioral score against each candidate by evaluating some questionnaire responses filled by candidates. Cabot developers integrated Think-X webhook with Resume sieve and enabled the application to provide a seamless experience for its users.

Result:

The third party tools were successfully integrated. Resume sieve has now become a full-fledged candidate ranking system empowered to absorb and process Jobs and Resumes from popular ATS tools such as Zoho Recruit, Greenhouse and Bullhorn. The competent behavioural assessment feature integrated into Resume Sieve also makes it a differentiator with distinct competitive advantage that takes it ahead of its competitors in the market.

Technology and Tools

.NET Core, PostgreSQL, React JS, Azure