Better Matching of Candidates with Job Roles through AI
The Adecco Group is one of the top five human resources providers in the world with a comprehensive service offering that includes temporary and contract staffing, outsourcing, permanent recruitment, outplacement and career services. They generate $33 billion annually with 35,000 employees worldwide.
Over the past two years, Rachik Laouar and Bryan Leung have been working along with The Adecco Group UK&I’s talented group of governance & legal specialists, transforming teams and business experts to revolutionalise their recruitment process from traditional manually driven recruitment and sales to become intelligently automated by combining The Adecco Group UK&I’s domain expertise with explainable AI-driven recommendations from DataRobot. The results are already showing a greatly enhanced ability for recruiters to fill job roles with the most aligned candidates, on a much faster basis, with minimized bias common in the industry. These results, generated within a couple of months, have the verified potential to improve success for their clients and are already solidifying The Adecco Group UK&I’s brand reputation in the competitive market.
They started in the U.K. with about 1,000 recruiters and sales specialists, and a million candidates annually. The traditional manual-intensive approach of humans reading through resumes and business profiles was hard to scale. In addition, there was a lack of transparency in the process, and Rachik and Bryan’s work added improved explainability, leading to candidates not being sure why they were not matched with a role. Rachik and Bryan are changing all of this using trusted AI solutions to scale AI recruitment and sales.
Foundation for Sustained Success
Overcoming data challenges was a foundational step. How do you standardise and match company names, job titles, skill sets, and common text phrases? What are job and skill hierarchies? What features indicate likely success or failure: How do you account for grammatical errors and what does this predict about a candidate? Is a longer or shorter CV indicative of an outcome? How should candidates be segmented?
Building on this foundation, the team was able to create and deploy models through DataRobot MLOps to provide insights on profitability, margin, and success rates. To amplify the value even more broadly, the team rolled out their first business-wide dashboards for democratisation of AI-driven insights from the data science team into the business users such as recruiters.
The Importance of AI Ethics and Trust
Rachik and Bryan realise the importance of equal opportunity, diversity, and inclusiveness of people of all backgrounds. They have made it a priority to leverage DataRobot’s Ethical AI, bias detection and mitigation capabilities, and to mitigate direct and indirect bias that exist in the global recruitment sector.
Looking Towards the Future
Rachik and Bryan are going to build upon their success with future use cases. “We plan to embed AI across the entire process, from when a client requests a hire all the way through to the end of their engagement and redeployment,” says Rachik.
With the existing data, there are dozens of new use cases ideating. For example, matching candidates that have the highest earning potential with jobs that have the highest pay could improve the success rate short-term and long-term. Also having transparency with explainable AI and Ethical AI will provide candidates needed information covering why they were seen as a match or not. It will provide recruiters insights into who the best candidate might be for a given role and why, in addition to their strengths and weaknesses. And it will provide companies the comfort that The Adecco Group UK&I is lining up candidates that position everyone for the best chance for success.
Understanding what features are important, finding the right candidate, and giving them the opportunity to work for the best company they can work for, that for me is the goal. It’s not building the model, it’s the outcome. That’s what we’re going for.
DataRobot’s platform makes my work exciting, my job fun, and the results more accurate and timely – it’s almost like magic!
I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.