CASE STUDY-LEGO SAPIEN
Company Preview
- Company Name – NEURALWAVES SYSTEMS PRIVATE LIMITED
Product Name – Lego Sapien
Product Type – SaaS Based B2B Product
Target Type of Customers – Companies [IT, Logistics, Retail], Recruitment Agencies, Consultancy Companies
Product Overview
In the typical hiring process, companies receive numerous CVs, followed by HR or recruiters contacting candidates for pre-screening to assess fitment, covering aspects such as expected salary and relocation preferences etc to name a few. This phase is often time-consuming, with HR having to manually call candidates, leading to delays when candidates are unavailable or occupied.
Once pre-screening details are gathered, candidates who meet the company’s criteria proceed to the next stage, where they are scheduled for interviews based on mutual availability with interviewers. During these interviews, candidates are evaluated and either progress to subsequent rounds or are rejected.
Industry and internal surveys indicate that only 15% to 30% of candidates advance past the initial interview stage. This high rejection rate underscores the significant time and resources HR and interviewers invest in interviewing candidates who do not proceed further.
Key Pain Points Addressed by Our Product and How It Helps
1. Time Spent on Pre-screening/Fitment
- Our interactive AI system handles pre-screening, engaging with candidates efficiently.(not only over the web but also through WhatsApp)
- AI Interviewers save human interviewer time by conducting multiple interviews concurrently.
2. Interview Scheduling Efficiency
- Automated systems schedule interviews for candidates who clear pre-screening.
3. Consistency in Evaluation
- Ensures consistent evaluation criteria are applied across all candidates.
Demo showcasing the above features available at this link: CandidateInterview.mp4
4. Optimizing Interviewer’s Time
- AI Interviewers save human interviewer time by conducting multiple interviews concurrently.
- They handle a large volume of interviews effectively.
5. Reducing Waiting Time for HR Feedback
- Immediate availability of interview results and notifications to stakeholders streamline decision-making.
6. Managing High Candidate Volume
- Our system efficiently manages large candidate volumes without compromising quality.
Customer Background
The company is an IT services provider specializing in the Robotic process automation and is based out of Pune,India.The company has done our pilot for about 3 of their Job profiles across 35+ candidates is an arm of a global company having its presence across the globe in 7 different companies.
Problem Statement
There were below issues pinpointedly apprised by the recruiters to us:
- Atleast 15-20 minutes of conversation with prospective candidates to check their fitment/suitability for the job they were applying to.
- Scheduling interviews with human interviewers considering multi time zone and candidate availability was proving to slow down their hiring turn around rate and increase in time.
- Interviews were mostly done with static question banks and non AI based.
Solution provided by Lego Sapien
- The product was used in a pilot mode by the client who invited about 38 candidates to interviews for totally 3 job profiles.
The client gave few pre screening questions in a particular job profile and based on responses from the candidates-their interviews were to be conducted.
The interviews sent to candidates had a strike rate of more than 70% and most of them were completed within 48 hours.
- Solution provided was an automated AI based interview solution simulating a human like experience for the candidates where questions with regards to each profile was asked in technical domain along with some pre-configured default questions as requested by the customer.
- The customer was able to conduct interviews for 3 of its job profiles with zero support on the training of tool for the candidates.
- The candidate detailed reports were immediately made available to the customer post the interview completion.
Implementation Process
- Lego Sapien team was involved in the preparation of profiles in the admin module with the customer on the customer’s created account.
- Using the same account-email information, interview details for the position, experience etc were shared to the candidate over a mail.
- The customer had provided us with few default questions and basic skill sets to be configured in the system.
- On clicking the link the candidate was able to take the interviews 24/7 sometimes post office hours, sometimes even over the weekends.
- Once candidate gave the interview the detailed report of the candidate including technical and communication skills were available to the customer to make a decision.
Conclusion
- 3 profiles were evaluated by the customer for which 35 candidates were sent invites for interview.
- Of the same-close to 80% were found to give the interviews within 36 hours.
- 70% of the candidates were seen to take the interviews during off hours (non office/weekends etc).
- There were zero calls for any kind of support/technical walkthroughs or guidance-implying that the User Interface was really simple.
- Technical evaluation by customer team also led to a reiteration on the results that the candidates were rightfully scored/graded basis their reports.
- Considering a per hour candidate rate of 20-25$ for the customer,we can envisage the ROI as below:
Manual interviews for per JD taken by each interviewer -10-12.
Approx.time spent for the same-1 hour (including scheduling/pre screening plus interview).
No of candidates who are filtered for the next round-20-30% of the initial count
Savings with Lego Sapien can be looked as direct 60-70% of savings in time from the initial