How EdGE Networks AI-fied their Product to Revolutionize Talent Acquisition
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EdGE Networks developed an AI-powered talent platform to alleviate search friction for job seekers and employers. They analyzed 3.9 million job descriptions and 22 million profiles to build an 800,000 skill database. The platform started with a search and matching feature for their first customer, Wipro, and has since expanded to 4 service lines with over 15 features. EdGE Networks reinvests in innovation through a data science lab and pipeline to continuously improve the platform using deep neural networks.
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How EdGE Networks AI-fied their Product to Revolutionize Talent Acquisition
- 1. How EdGE Networks AI- fied their Product
- 2. Necessity is the mother of invention
- 3. Challenge meets opportunity Challenge: “What if my next potential candidate lies in the piles of discarded resumes?” Opportunity: Machine Learning with its ability to emulate human brain Eureka!!! Machine Learning based platform that would alleviate search friction for people and jobs
- 4. Demanding yet fulfilling journey Disparate data Legacy systems Talent shortage Market apprehension Machine learning curve
- 5. Demanding yet fulfilling journey Wipro as anchor customer 1 feature: Search & Match 3.9 million JDs and 22 million profiles analyzed 800,000 skills DB 4 service lines with over 15 features
- 6. Platform It’s a relay: Service to Product to Platform Productization of service Services model Design Thinking Approach
- 7. ITC Infotech Tech Mahin dra Zensar Project Mgmt Project Planning Project execution Scrum Master Project Co-ordn Strategic planning Program Mgmt Change Mgmt Skills Title Project Manager Project Co-ord Project Lead Sr. Project Manager Delivery Manager Program Manager Wipro Infy TCS Accen ture Similar Company Infosys Wipro TCS IBM HCL Mindtree Company Function Project Mgmt. Certificate pmp Six sigma green belt Prince 2 Applied PM: Coursera Initiating and Planning Projects:C oursera Into to PM: edx Courses Deep neural networks growing everyday
- 8. Plough back into innovation: Invest and Measure Data science lab Innovation pipeline Data Scientists Technology
- 9. Awareness Education Engagement Influencer CIO Decision maker CHRO Budget owner Business Head Exec sponsor CEO Influencer TA Head Sponsor RMG Head Personalized Sales & Marketing Purchase Retention
- 10. Auto-sourcing Search & Match Business rules JD & Profile analysis iJD Social Search Simplification Profile builder DMS Career Planner Talent Analytics Simplification through AI Domain Expertise Data Science
- 11. CEO CIO TA Specialist RMG The new world of work: Enabled by AI CHRO Employee Course Training Project
- 12. Thank you!!
Hinweis der Redaktion
- The primary driving force for most new inventions is a need. Major inventions and discoveries are all a result of necessities of human life and the desire of human to make the world a better place. Be it cave man inventing fire, Edison the light bulb, Wright brothers created the flying machine, small pox vaccine by Jenner – there are millions of such inventions led by dire need. Necessity compels man to exercise his power.
- Likewise EdGE Networks’ Search and Match algorithm which forms the core even today was an outcome of the need to satisfy a lacuna. During my first venture (a digital learning platform), I was often haunted by a question while recruiting talent, “What if my next potential candidate lies in the piles of discarded resumes?” That is also when I realized that there is a great opportunity for us to utilize this explosion of computing. In other words, artificial intelligence. Machine learning algorithms using NLP can emulate the human brain by reading and understanding millions of JDs and resumes in a second. We have built a neural network of skills and jobs that will learn and grow over time using our source-validate-connect algorithms with NLP. Our weighted search-and-match mechanism scores candidates, ranks them, and brings up the most relevant profiles from multiple databases. This enables hiring managers with intelligence that helps them make hirirng decisions. Driving to build a product now deep learning and machine learning
- However, the journey was laden with many speed breakers. Some of the challenges from the customer are data, integration with legacy systems which slow your platform down and apprehension about an AI platform which is mainly due to lack of awareness. Additionally, as a start-up, talent shortage especially in data science which is the core and the other is the initial teething problems in the algorithms as they go through their learning curve which gets fixed in time.
- While it was demanding, what makes it all worth while is the milestones that you achieve at short intervals – they are gratifying. Our biggest win was getting Wipro in as our first customer – they were our anchor, we built most of our core product during the initial deployment at Wipro. It was a steep learning curve for us people and for our algorithms. From having 1 feature in 2013 which was Search and Match, today, we have 4 full-fledged product with 15 features which makes us an end-to-end talent management platform.
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