A(I) Smarter Way to Hire
Hiring in the cleaning and facility solutions industry has never been simple.
Unlike many office-based industries, where applicants can show up at the door or click “apply” online, service providers contend with high applicant volume, unpredictable schedules, and a largely deskless, constantly on-the-move workforce.
Traditional recruiting playbooks simply do not translate well in a landscape defined by reliability and real-world performance.
Wells Ye is the founder of EmployJoy.ai, an artificial intelligence-powered recruiting platform designed specifically for this industry. Ye’s perspective is shaped by his years running a house cleaning business in Evanston, Illinois. He found that recruiting and hiring dominated his operation in ways few operators anticipated. That experience led him to develop a platform rooted in measurable hiring outcomes.
Balancing intuition with data in hiring decisions
Ye noted that what sets this discussion apart from past hiring conversations is its emphasis not only on intuition but also on the balance between intuition and hard data. “My old way of recruiting was very much based on intuition,” he remembered. He explained that research shows recruiters often form opinions unconsciously, sometimes within five minutes of meeting an applicant. That early instinct then becomes the lens through which the rest of the process unfolds. The result, Ye said, is a feedback loop that confirms bias rather than uncovering true potential.
The data-driven approach Ye advocated focused on collecting objective information and delaying judgment until the facts were in front of decision-makers. Only then could intuition play a constructive role.
Ye also explained how hiring evaluations vary between commercial and residential cleaning. He used the example of hiring in residential cleaning versus commercial cleaning to show how hiring needs can differ even within the same industry. In both cases, physical ability, coachability, and outlook are important. However, residential work usually involves more face-to-face interaction with individual clients, while commercial roles may require less direct customer contact but need greater consistency and schedule management.
Regardless of the setting, Ye said the mindset and the fundamental hiring process remain the same: define what success looks like, apply consistent criteria, and then examine the data.
A key part of this, he said, was linking assessment data to performance data after a hire. That connection allows employers to see which combinations of traits correlate with success and which do not. “AI and statistics are very powerful tools for that kind of analysis,” he said. But it’s not the tools themselves that matter most, but how they are used to combine insight with experience.
Defining success and using technology to hire for it
One of the biggest frustrations in cleaning and facilities hiring is the feeling that good candidates can be plentiful one moment and disappear the next. Traditional job postings and hope-and-pray methods rarely work. Ye explained that the data-driven approach starts before the posting goes live. Employers need to understand and clearly convey what truly matters in the role—including reliability, physical demands, learning capacity, and more—and then let that guide how roles are presented to potential applicants.
Reflecting on the candidate experience with AI recruiting tools, Ye emphasized that transparency is key. When employers use technology to help with evaluations, applicants should be aware of this and have the option to opt in or out. “We believe AI is a great tool, and people know about it,” he said, “and they have a choice to opt in and opt out.” He highlighted that if someone preferred a human review, that preference is respected, a point he said is essential for fairness and trust.
When it comes to identifying the traits that most reliably indicate future success, Ye highlighted two in particular: conscientiousness and coachability. Conscientious applicants tend to be aware, careful in their work, and motivated to perform well. Coachability, he shared, matters because cleaning and facilities work are dynamic, with new methods evolving and new standards emerging, and employees must be willing and able to learn.
Ye stated that technology is especially skilled at recognizing patterns in these traits and consistently evaluating applicants, enabling employers to base decisions on a mix of data and informed judgment rather than intuition alone.
From filling shifts to building high-performing teams
Ye offered practical advice for hiring managers who may be hesitant to adopt new tools or processes. “It’s easier than you think,” he said. Many modern solutions are ready to use and don’t require employers to become data scientists. What matters more than technical skills, he noted, is a willingness to adopt a process based on evidence and humility.
“The mindset is that I don’t want to be overly confident in my initial intuition,” he explained. Recognizing that instinct alone is a weak predictor when isolated and then pairing it with data to make better decisions, is at the core of improved hiring—faster, more accurate, and less prone to turnover.
The result, he pointed out, is not just hires that stay, but teams that outperform expectations over time.
Jeff Cross is the media director for ISSA, which publishes three print media brands. He can be reached at [email protected] or 740-973-4236.
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