Using Explainable AI to Revolutionize the Recruitment Industry and Candidate Experience
Customer Company Size
Large Corporate
Region
- Europe
Country
- United Kingdom
Product
- DataRobot
Tech Stack
- Machine Learning
- Artificial Intelligence
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Professional Service
Applicable Functions
- Human Resources
Use Cases
- Predictive Quality Analytics
- Predictive Replenishment
Services
- Data Science Services
About The Customer
The Adecco Group, UK & Ireland and its brands are part of The Adecco Group, a Global 500 ranked company with annual revenues over 16.8 billion pounds. The Adecco Group is the world’s leading talent advisory and solutions company. The Adecco Group provides services including temporary staffing, permanent placement, career transition, and talent development as well as business process outsourcing and consulting to up to 150,000 clients every day. The company is headquartered in London, UK and operates in the professional services industry.
The Challenge
The Adecco Group, UK & Ireland, a part of the Global 500 ranked company, The Adecco Group, was facing an efficiency problem in their recruitment process. The traditional recruitment process involved multiple manual interventions, which were prone to mistakes and human interpretation. Recruiters had to sift through high volumes of CVs, making it difficult to match the right candidates to the right job. With recruiters working full throttle, it was easy for data-driven insights to remain hidden. The company was looking for a solution to reduce time and speed to fill open positions and improve their hiring attraction pipeline for client talent pools.
The Solution
The company decided to leverage machine learning (ML) and artificial intelligence (AI) to solve their efficiency problem. They built a data platform to make broader and better use of the data at hand. They then started to look at the advantages to be gained by applying AI to that data. They partnered with DataRobot for an initial project to incorporate MLOps and automate models to reduce the time it took for recruiters to fill jobs, while also building a more appealing pipeline for prospective talent. The project leveraged three metrics to gauge success: productivity, accuracy, and interpretability. The DataRobot models enabled recruiters to sort through resumes more effectively, driving a 37 percent reduction in the number of CVs that had to be reviewed.
Operational Impact
Quantitative Benefit
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