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Project 500

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Sagar Raina

The document discusses plans to improve the technology hiring process at a company. It proposes increasing candidate outreach by 50% through alternative sourcing channels like GitHub and LinkedIn groups. It also suggests introducing coding tests and hackathons to better evaluate candidates' skills and filter out weaker performers. Examples are provided of innovative hiring practices used by other companies, such as predictive candidate engagement software and skill-specific coding challenges.

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Tech Hiring Plan Project 500
5000No. of Interviews 500Offers!! 50+ Recruitment drives Targeting TAT of 30 days 50% through Direct sourcing 10,000+ Applications! Hiring Exercise TAT
Passive candidates are open to opportunities. 74% of employees are open to the right opportunity* - despite the fact that many of them are satisfied in their current one! Time and Money is spent on attracting talent that isnt right for you
Technology Sourcing platforms Current sourcing channels Referrals & Vendors LinkedInNaukri Consultant, 1652, 81.02% Employee referral, 15, 0.25% Web, 382, 18.73% Source Mix (Oct'17 - Mar'18) Consultant Employee referral Web Current sourcing mix for Technology hiring Currently used Sourcing Platforms in Technology hiring Total profiles sourced during the duration of past six months was 2039. Out of that 19% were sourced through web and majorly from Naukri. Current positions closure Analysis Naukri has largest database repository of Tech profiles. You can reach out to active candidates Candidates location, job details, educational qualifications, ctc* are easily available You are unable to find the references to the work done for review as on GitHub or StackOverflow. Nor number of followers. 70% Of the candidates are passive candidates. The pool is restricted and hence repetitive. With many candidates not updating the details Naukri Sourcing Platform Conversion rate ~<10% Web comprises of 19% sourcing mix and 30% of closure in Tech Hiring Consultan t, 40, 58%Employee Referral, 8, 12% Web, 21, 30% Consultant Employee Referral Web Source Effectiveness (Final Offer) Web/ Direct sourcing Need to explore alternate sourcing channels Consultant Max % of profiles vis-a lowest Hit Ratio Employee Referral- Best selection% We need to improve Candidate funnel and Selection%. Consultants Selection Ratios are lowest & highest on cost
Increase Candidate Outreach by 50% through other portals Target Passive candidates, identified Organizations/ Colleges, sourcing huddles Promote referrals Introduce Coding Tests, Hackathons, Architecture reviews/ assignments to augment current selection process & filter out the bottom performers. Improve selection Ratios Improve Recruitment funnel/ Alternate Sourcing Platform GitHub Stack Overflow Google (Boolean Search) LinkedIn Tech Groups YouTube Tutorials Employee Referrals 2017-18- The year of Algorithm - John Sullivan Limited Talent Pool At any given point avg 48% employees consider a job change, while only 22% make a switch 80% of our pool already exhausted by the vendors of tier 1 & product companies. Hit Ratio <10% Industry Avg 51% of the hiring managers use coding tests/Take home assignments. We are yet to explore this in depth 32% candidates on an avg get rejected during resume screening , not based on their actual competencies. Due to Lack of effective Employer Branding we are unable to tap the pool of passive candidates ~ 70% of the pool. Sourcing Top challenges Sourcing Funnel Strategy Search According to Language, Location, contributions in the last year, No of followers Search according to Top tags, Contribution, communities, Social link Twitter, blogs, LinkedIn Boolean characters AND OR NOT/ - Brackets () Quotation marks Blogs/ Specific Tech groups- hiring managers & Panels can contribute Employer branding - Day in a life @MMT - Infographic - Achievements/ Innovations Referral schemes Introduced Gamification of Referral Scheme Referral Thursdays Monthly/ Quarterly- recognition. Road shows Direct sourcing through web portals targeted to ~>60% from 18% Hackathon/ Coding tests planned for Java & Data Science positions Better alignment with Tech panels on selection parameters Target organization based sourcing plans Proposed alternate sourcing channels
Alternates to Inc. Funnel Monjin Online Test E- Litmus An online test for all SSE1 candidates who are in the experience range of 2-4 years Hacker rank can be used for all SSE2. -It would help in faster screening & swifter evaluation Online video interview platform - An external panel can interview and evaluate candidates - Reduction in No. of Interviews
Sample Drive Plan Weekend Drive Month Week Location Rec. Lead Skill Level Evaluations Exp. Selection March W1 Delhi Rec 1 Java SSE1/SSE2 100 10 W2 Bangalore Rec 2 Data LSE 50 5 W3 Hyderabad Rec 3 Java PSE 40 4 W4 Delhi Rec 1 Java SSE1/SSE2/LSE/PSE 120 12 April W1 Hyderabad Rec 2 Data SSE1/SSE2/LSE/PSE 150 15 W2 Bangalore Rec 3 Data SSE1/SSE2/LSE/PSE 150 15 W3 Hyderabad Rec 2 Java PSE 50 5 W4 Bangalore Rec 1 Java LSE 100 4 May W1 Hyderabad Rec 2 Java SSE1/SSE2 75 8 W2 Bangalore Rec 1 Data SSE1/SSE2/LSE/PSE 150 15 W3 Delhi Rec 2 Data SSE1/SSE2/LSE/PSE 140 14 W4 Bangalore Rec 3 Java SSE1/SSE2/LSE/PSE 140 14 Total 1265 121
Recruitment Dashboard Company X Quality Of Hire Operational Excellence Improve Talent Mix Across Critical Teams Improve Candidate Experience Hiring Manager Surveys Performance Offer Aborts (Decline) Offers Cost/Hire TAT Source Mix Criteria > 50%=110%, 30-50 % =100%, 20-30%=90%, 10-20%=80 , <10=Zero NPS>40=110%, 30-40=100% , 20- 30=90%, 10- 20=80%, <10=Zero >4=110%, 3.5- 4=100%, 3- 3.5=90%, <3= 0% <10 % Abort, 100% between 10-20%, 90% between 20- 30%, >30%= 0% Overall offers 10% Below Last year Average M & Above 45 Days DM & Below 40 Days Web (Naukri, Linkeedin,IIM jobs,Direct,C Hire,Conv) Employee Referral Consultant s Target- FY2017-18 >50% >40 4 10% NA 39069 45 40 68% 25% 7% Achived-FY2017-18 52% 38 3.90 13% 76 -16% 41 21 66% 24% 11% AA 52% 18 3.98 0% 12 -100% 0 21 0% 100% 0% BB 44% 32 3.91 13% 18 942% 37 13 25% 38% 38% CC 28% 53 4.18 13% 28 -75% 0 36 88% 13% 0% DD 72% 25 3.94 10% 10 -66% 44 24 100% 0% 0% EE 49% 62 3.79 6% 16 -57% 0 14 69% 13% 19% FF 30% 44 3.77 18% 33 -29% 0 22 61% 33% 6% >=4 >30% >=-10% <=45 <=40 >=68% >=25% >7% 3.5-4 >=20%-30% <10% >45 >40 60-68% 20-25% <=7% 3-3.5 >=10%-20% <60% <20% <3 <10%
Illustration of Innovative Hiring Practices
Belong: Predictive outbound hiring software Machine learning powered search to surface the most relevant candidates and predict their openness to new opportunities Automated, personalized candidate engagement for great candidate experience and high engagement rates
Project 500
Introduction to Coding Challenges/Hackathons Evaluation based on Logical Correctness: Each question has a set of test cases. These test cases are designed to cover all possible scenarios that may occur in the problem statement. Code Execution Time: Code execution time is calculated by taking cumulative against each test case. Memory consumed in code execution: Memory consumption is calculated by taking cumulative against each test case. Size of the code, semantic analysis of code Advantages Great way to target top candidates (3-8 yrs. Experience) for a skill Can be done as real-time problem solving contest, Ux Design Competition, Gamification etc Take a series of contest for branding & engagement of dedicated skill professionals This platform supports multiple languages including C, C++, C++, Java, JavaScript, PHP, Perl, etc.
13 Illustration :Job Oriented Coding Challenge McAfees second coding competition powered by Hacker Earth held on 19th September We have 3000+ developers registered. Focusing on Java/PHP/Python Problems were simulations of real time problems faced by the team Made 6 Offers within 30 days of launching this Coding Challenge.
14 Illustration: Skill Specific Challenge http://www.hackerearth.com/malware-analysis-hiring-challenge/
Illustration :Code WISE-Gender Diversity Specific Coding Challenge 15
16 Illustration :Talent Direct Campaign in Partnership with LinkedIn
17 Illustration 2:Talent Direct Campaign in Partnership with LinkedIn for Innovation Product Hiring
Relevant Articles 1. https://www.linkedin.com/pulse/top-5-out-box-recruitment-campaigns- sagar-raina/ 2. https://www.linkedin.com/pulse/building-superstar-recruitment-team- sagar-raina/ 3. https://www.linkedin.com/pulse/innovative-recruitment-campaigns- part-ii-sagar-raina/ 4. https://www.linkedin.com/pulse/designing-killer-employee-referral- program-sagar-raina/ 5. https://www.linkedin.com/pulse/coming-soon-alexa-hire-me-sagar- raina/

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Project 500

  • 2. 5000No. of Interviews 500Offers!! 50+ Recruitment drives Targeting TAT of 30 days 50% through Direct sourcing 10,000+ Applications! Hiring Exercise TAT
  • 3. Passive candidates are open to opportunities. 74% of employees are open to the right opportunity* - despite the fact that many of them are satisfied in their current one! Time and Money is spent on attracting talent that isnt right for you
  • 4. Technology Sourcing platforms Current sourcing channels Referrals & Vendors LinkedInNaukri Consultant, 1652, 81.02% Employee referral, 15, 0.25% Web, 382, 18.73% Source Mix (Oct'17 - Mar'18) Consultant Employee referral Web Current sourcing mix for Technology hiring Currently used Sourcing Platforms in Technology hiring Total profiles sourced during the duration of past six months was 2039. Out of that 19% were sourced through web and majorly from Naukri. Current positions closure Analysis Naukri has largest database repository of Tech profiles. You can reach out to active candidates Candidates location, job details, educational qualifications, ctc* are easily available You are unable to find the references to the work done for review as on GitHub or StackOverflow. Nor number of followers. 70% Of the candidates are passive candidates. The pool is restricted and hence repetitive. With many candidates not updating the details Naukri Sourcing Platform Conversion rate ~<10% Web comprises of 19% sourcing mix and 30% of closure in Tech Hiring Consultan t, 40, 58%Employee Referral, 8, 12% Web, 21, 30% Consultant Employee Referral Web Source Effectiveness (Final Offer) Web/ Direct sourcing Need to explore alternate sourcing channels Consultant Max % of profiles vis-a lowest Hit Ratio Employee Referral- Best selection% We need to improve Candidate funnel and Selection%. Consultants Selection Ratios are lowest & highest on cost
  • 5. Increase Candidate Outreach by 50% through other portals Target Passive candidates, identified Organizations/ Colleges, sourcing huddles Promote referrals Introduce Coding Tests, Hackathons, Architecture reviews/ assignments to augment current selection process & filter out the bottom performers. Improve selection Ratios Improve Recruitment funnel/ Alternate Sourcing Platform GitHub Stack Overflow Google (Boolean Search) LinkedIn Tech Groups YouTube Tutorials Employee Referrals 2017-18- The year of Algorithm - John Sullivan Limited Talent Pool At any given point avg 48% employees consider a job change, while only 22% make a switch 80% of our pool already exhausted by the vendors of tier 1 & product companies. Hit Ratio <10% Industry Avg 51% of the hiring managers use coding tests/Take home assignments. We are yet to explore this in depth 32% candidates on an avg get rejected during resume screening , not based on their actual competencies. Due to Lack of effective Employer Branding we are unable to tap the pool of passive candidates ~ 70% of the pool. Sourcing Top challenges Sourcing Funnel Strategy Search According to Language, Location, contributions in the last year, No of followers Search according to Top tags, Contribution, communities, Social link Twitter, blogs, LinkedIn Boolean characters AND OR NOT/ - Brackets () Quotation marks Blogs/ Specific Tech groups- hiring managers & Panels can contribute Employer branding - Day in a life @MMT - Infographic - Achievements/ Innovations Referral schemes Introduced Gamification of Referral Scheme Referral Thursdays Monthly/ Quarterly- recognition. Road shows Direct sourcing through web portals targeted to ~>60% from 18% Hackathon/ Coding tests planned for Java & Data Science positions Better alignment with Tech panels on selection parameters Target organization based sourcing plans Proposed alternate sourcing channels
  • 6. Alternates to Inc. Funnel Monjin Online Test E- Litmus An online test for all SSE1 candidates who are in the experience range of 2-4 years Hacker rank can be used for all SSE2. -It would help in faster screening & swifter evaluation Online video interview platform - An external panel can interview and evaluate candidates - Reduction in No. of Interviews
  • 7. Sample Drive Plan Weekend Drive Month Week Location Rec. Lead Skill Level Evaluations Exp. Selection March W1 Delhi Rec 1 Java SSE1/SSE2 100 10 W2 Bangalore Rec 2 Data LSE 50 5 W3 Hyderabad Rec 3 Java PSE 40 4 W4 Delhi Rec 1 Java SSE1/SSE2/LSE/PSE 120 12 April W1 Hyderabad Rec 2 Data SSE1/SSE2/LSE/PSE 150 15 W2 Bangalore Rec 3 Data SSE1/SSE2/LSE/PSE 150 15 W3 Hyderabad Rec 2 Java PSE 50 5 W4 Bangalore Rec 1 Java LSE 100 4 May W1 Hyderabad Rec 2 Java SSE1/SSE2 75 8 W2 Bangalore Rec 1 Data SSE1/SSE2/LSE/PSE 150 15 W3 Delhi Rec 2 Data SSE1/SSE2/LSE/PSE 140 14 W4 Bangalore Rec 3 Java SSE1/SSE2/LSE/PSE 140 14 Total 1265 121
  • 8. Recruitment Dashboard Company X Quality Of Hire Operational Excellence Improve Talent Mix Across Critical Teams Improve Candidate Experience Hiring Manager Surveys Performance Offer Aborts (Decline) Offers Cost/Hire TAT Source Mix Criteria > 50%=110%, 30-50 % =100%, 20-30%=90%, 10-20%=80 , <10=Zero NPS>40=110%, 30-40=100% , 20- 30=90%, 10- 20=80%, <10=Zero >4=110%, 3.5- 4=100%, 3- 3.5=90%, <3= 0% <10 % Abort, 100% between 10-20%, 90% between 20- 30%, >30%= 0% Overall offers 10% Below Last year Average M & Above 45 Days DM & Below 40 Days Web (Naukri, Linkeedin,IIM jobs,Direct,C Hire,Conv) Employee Referral Consultant s Target- FY2017-18 >50% >40 4 10% NA 39069 45 40 68% 25% 7% Achived-FY2017-18 52% 38 3.90 13% 76 -16% 41 21 66% 24% 11% AA 52% 18 3.98 0% 12 -100% 0 21 0% 100% 0% BB 44% 32 3.91 13% 18 942% 37 13 25% 38% 38% CC 28% 53 4.18 13% 28 -75% 0 36 88% 13% 0% DD 72% 25 3.94 10% 10 -66% 44 24 100% 0% 0% EE 49% 62 3.79 6% 16 -57% 0 14 69% 13% 19% FF 30% 44 3.77 18% 33 -29% 0 22 61% 33% 6% >=4 >30% >=-10% <=45 <=40 >=68% >=25% >7% 3.5-4 >=20%-30% <10% >45 >40 60-68% 20-25% <=7% 3-3.5 >=10%-20% <60% <20% <3 <10%
  • 9. Illustration of Innovative Hiring Practices
  • 10. Belong: Predictive outbound hiring software Machine learning powered search to surface the most relevant candidates and predict their openness to new opportunities Automated, personalized candidate engagement for great candidate experience and high engagement rates
  • 12. Introduction to Coding Challenges/Hackathons Evaluation based on Logical Correctness: Each question has a set of test cases. These test cases are designed to cover all possible scenarios that may occur in the problem statement. Code Execution Time: Code execution time is calculated by taking cumulative against each test case. Memory consumed in code execution: Memory consumption is calculated by taking cumulative against each test case. Size of the code, semantic analysis of code Advantages Great way to target top candidates (3-8 yrs. Experience) for a skill Can be done as real-time problem solving contest, Ux Design Competition, Gamification etc Take a series of contest for branding & engagement of dedicated skill professionals This platform supports multiple languages including C, C++, C++, Java, JavaScript, PHP, Perl, etc.
  • 13. 13 Illustration :Job Oriented Coding Challenge McAfees second coding competition powered by Hacker Earth held on 19th September We have 3000+ developers registered. Focusing on Java/PHP/Python Problems were simulations of real time problems faced by the team Made 6 Offers within 30 days of launching this Coding Challenge.
  • 14. 14 Illustration: Skill Specific Challenge http://www.hackerearth.com/malware-analysis-hiring-challenge/
  • 15. Illustration :Code WISE-Gender Diversity Specific Coding Challenge 15
  • 16. 16 Illustration :Talent Direct Campaign in Partnership with LinkedIn
  • 17. 17 Illustration 2:Talent Direct Campaign in Partnership with LinkedIn for Innovation Product Hiring
  • 18. Relevant Articles 1. https://www.linkedin.com/pulse/top-5-out-box-recruitment-campaigns- sagar-raina/ 2. https://www.linkedin.com/pulse/building-superstar-recruitment-team- sagar-raina/ 3. https://www.linkedin.com/pulse/innovative-recruitment-campaigns- part-ii-sagar-raina/ 4. https://www.linkedin.com/pulse/designing-killer-employee-referral- program-sagar-raina/ 5. https://www.linkedin.com/pulse/coming-soon-alexa-hire-me-sagar- raina/