Virtual Assistant for Hiring Last-Mile Workforce
Logistics companies, both old and new, have invested heavily in building an efficient frontline workforce to provide swift and convenient services to their users. Timely delivery is often a critical deciding factor for the ever-impatient customers to choose service A over service B. Hence, operations/logistic team is the key enabler here.
The attrition rate in large frontline teams is high, close to 75 percent annually. Yet most companies have aggressive growth targets, necessitating recruitment of high volumes of workers constantly. High-growth companies in this domain like Zomato and Swiggy, grew by more than 50-60 percent by the end of 2018, recruited tens of thousands of delivery boys every month.
At Vahan, we have developed an AI-driven virtual assistant that helps logistics companies scale and automate their hiring process by leveraging the common addiction of messaging applications like WhatsApp and FB messenger.
In this talk, I will cover in detail how we developed a complete data collection and natural language processing pipeline for Indian languages and built a chatbot over Whatsapp which is currently connecting companies like Dunzo, Zomato, Swiggy & Rapido Express with potential frontline workers and fulfilling the hiring requirements of this industry in a scalable and autonomous fashion.
Outline/Structure of the Talk
1. Intro to Last-Mile Recruitment Problem
2. Last Mile Vs Standard Recruitment
3. Design Considerations
4. Addressing Design Considerations
5. Steps to Solution
6. Data Nuances
7. Data Collection
8. NLP Methods
9. Key Performance Metrics
10. Future Work
11. Case Study
12. Key Takeaways
1. Understanding High Volume Recruitment problem
2. Overview of Efforts at Vahan
3. How to build a solution easy enough for users to adopt
4. R&D on Code-Mixed Datasets
5. Data Collection for Indian text utterances
6. Personalization for Regional Persona
NLP Engineers, ML Engineers, Data Scientists/Data Analysts, Product Managers. Logistics/Operation Personnel, CXOs
Prerequisites for Attendees
Basic Knowledge of Machine Learning and Natural Language Processing is required to understand the contents of the talk