The Background
The National University of Singapore (NUS) is one of the top public universities in Singapore and aspires to be a vital community of academics, researchers, staff, students, and alumni working together in a spirit of innovation and enterprise for a better world. NUS annually invites applications for its distinguished Associate Management Program, an initiative designed to shape the leaders of tomorrow that attracts a significant number of aspiring applicants.
The Challenge
The National University of Singapore experiences a high influx of applicants each year, and managing the manual recruitment process has become difficult. The recruitment team faces several hurdles, including:
- Traditional recruitment process: The existing system lacks interactivity and relies on form filling. The system does not allow candidates to pause and resume their applications, and it deletes all information, including uploaded resumes, every time the system is refreshed, resulting in a substantial candidate drop-off rate.
- Limited employer branding: During the application process, the current method cannot engage candidates with the program or the university, missing crucial opportunities to promote the program and enhance the institution’s brand reputation.
- Improper candidate screening and reporting: The team faces difficulties in explaining ratings, scores, and the criteria for pre-selection and shortlisting of candidates. Processing candidate scores and generating reports also present a substantial challenge.
- Poor candidate engagement: Recruiters are required to invest considerable time and effort in addressing common queries, while real-time updates or communication with candidates are lacking. Recruiters are unable to offer sufficient candidate support during the application stage, which also creates a lack of transparency in the recruitment process, leading to a poor candidate experience.
- Non-availability of a talent pool: The current system lacks a centralized database for accumulating quality candidates from various programs and applications to create a reliable talent pipeline.
- Manual interview scheduling: The existing process demands manual scheduling and considerable effort from the Talent Acquisition team to follow up with candidates.
The Solution
impress.ai had digitized the current recruitment process by offering a suite of customized solutions through its recruitment automation platform, addressing the client’s major concerns.
- Employer branding and candidate engagement: The AI-powered intelligent virtual assistant by impress.ai guided candidates throughout the hiring process, providing an opportunity to enhance and reinforce the employer brand at every stage of the hiring cycle.
- Interactive talent engagement & screening: impress.ai’s automation platform parsed candidate resumes into structured data, storing it in a centralized repository. Candidates participated in an interactive pre-screening and deep-screening process with impress.ai’s virtual assistant, allowing them to complete the application at their convenience without losing unsaved answers. Candidate queries were handled by impress.ai’s intelligent and interactive virtual assistant leading to high engagement and less candidate drop-off.
- Automated resume scoring & ranking: After the screening, candidate resumes were scored, ranked, and sorted, simplifying the shortlisting process for recruiters. The platform used machine learning-based keyword scoring to facilitate candidate selection, eliminating manual effort.
- Automated Scheduling: The automated self-scheduling feature of impress.ai helped recruiters schedule interviews without manual intervention, saving time and effort. Integrated with the virtual assistant, this feature managed automated notifications for candidates, eliminating the need for manual follow-ups.
- Talent Pipeline: The platform empowered recruiters to shortlist top candidates from various programs and roles, creating an internal talent pipeline.
The Results
- 91.2% Candidate CSAT score
- 18 recruiter days saved for time-to-shortlist
- 63% reduction in candidate drop-off
- AI-powered virtual assistant addressed candidate queries with a 99.4 % accuracy rate
