Overview
Global logistics solutions provider GXO created a new Senior Director of Warehouse AI role that would be transformational to the business. The position demanded a very rare combination of talent and high-level academic qualifications in machine learning and AI, along with practical knowledge of logistics and warehousing. The role had been open for over eight months, prompting the GXO internal hiring team to seek the specialist skills and talent network of Proactive Global. This resulted in the rapid identification of a viable shortlist of suitable individuals, one of whom was ultimately successfully hired
The Challenge
Reporting to the Chief Automation Officer, this new role was to become an integral part of a broader initiative to improve efficiency through cutting-edge technology. It required someone who could take machine learning out of the research environment and apply it to the physical realities of a live distribution center - including safety, inventory accuracy and shipping throughput.
The job specification called for a Master’s or PhD in computer science or machine learning, combined with genuine operational experience inside a warehouse. The Venn diagram intersection of these skillsets and qualifications is almost non-existent. Proactive Global utilised its access to talent, along with extensive research to pinpoint the number of credible candidates in the United States at just 30 individuals. Of the total estimated workforce of 162.7 million people in the USA, this really was a case of finding a proverbial needle in a haystack.
The search
Proactive Global added a very specific value to the search process. The level of granular detail and focused investigation facilitated by a specialist recruiter would not be feasible for any in-house team. Through a detailed briefing process, it was decided that standard competitor mapping was never going to surface a population this niche. The nature of the role required Cian Denvir, VP of Proactive Global North America, to spend the first two weeks scoping rather than sourcing. So, the search was built around the academic route instead: leveraging existing networks and identifying institutions with strong AI and machine learning programs that also carried a deep engineering and supply chain heritage. Georgia Tech was one of several such institutions.
That investigation produced a mapped, addressable pool of 70 people nationwide. Rather than sample it, Cian contacted all of them. Screening was deliberately unforgiving. The disqualifying question was not academic credibility, it was whether the candidate had spent real time inside a warehouse and understood how one actually operates. More than 60 out of the 70 were ruled out on that basis or on availability.
Four candidates were submitted to GXO. One was hired.
The results
The appointed candidate has now been in seat for two years and is building a team underneath her, which is the clearest evidence available that her appointment was a great fit, and the right choice. GXO has subsequently deployed AI across its infrastructure, providing a clear ROI from AI, which is being passed on to its customer base.