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How Recruiters Scale Human Judgement
Most hiring systems are designed to answer one question:
Can this person do the job?
Recruiters spend their time answering a very different one:
Will this person thrive here?
That distinction sits at the heart of Episode 6 of The Signal Lab. In the second installment of our five-part investigation into how hiring decisions are really made, Ian Davidson sits down with Jordan Franklin, co-founder and CEO of Stratus Consulting, an IT staffing firm that speaks with hundreds of candidates every week and has placed thousands of professionals into organizations ranging from Northwest Arkansas startups to Fortune 1 companies.
What emerges from the conversation is a fascinating realization: staffing firms aren't simply matching resumes to job descriptions. They're filling in the gaps left by the hiring systems we've built.
Jordan explains that her recruiters certainly evaluate technical skills—but they lean heavily on assessments to validate those. The real work happens somewhere else.
Most importantly, they try to answer a question no résumé can:
What will this person actually be like to work with?
Along the way, Jordan shares why many of her clients never publicly post open positions, why passive candidates often become the strongest hires, and why staffing firms function as trusted advisors for both employers and candidates.
She also introduces the philosophy behind Gumption, the AI-powered platform Stratus is building after years of learning what traditional hiring systems fail to capture. Rather than simply matching people to jobs, Gumption aims to understand the human behind the résumé and match people to the teams where they'll actually succeed.
Signal Mapping Connection
Throughout this series, The Signal Lab is reverse-engineering hiring.
Hiring managers look for trust, character, and judgment.
Recruiters look for motivation, culture fit, and long-term success.
Assessments validate technical capability.
Each stage relies on different signals.
If we hope to build better digital credentials, better learner records, better AI, and better workforce systems, we first need to understand what information humans actually use to make hiring decisions.
Recruiters have quietly spent decades building richer profiles because the systems around them haven't.
Perhaps the next generation of workforce infrastructure shouldn't replace that understanding.
It should make it portable.
Resources
Jordan Franklin
LinkedIn: https://www.linkedin.com/in/jordan-franklin-gumption/
Stratice Consulting: https://mystratice.com/
Signol Labs: https://signollabs.com/
Signal Mapping: https://signollabs.com/blog-signal-mapping/
Connect with Ian Davidson: https://www.linkedin.com/in/ianwdavidson/
Schedule a conversation: https://signollabs.com/contact-us/
If your organization is designing hiring technology, talent marketplaces, digital credentials, Learning and Employment Records, or workforce infrastructure, we'd love to compare notes. This investigation is helping shape a practical framework for understanding the signals that actually drive hiring decisions.
View all episodes
By Ian DavidsonMost hiring systems are designed to answer one question:
Can this person do the job?
Recruiters spend their time answering a very different one:
Will this person thrive here?
That distinction sits at the heart of Episode 6 of The Signal Lab. In the second installment of our five-part investigation into how hiring decisions are really made, Ian Davidson sits down with Jordan Franklin, co-founder and CEO of Stratus Consulting, an IT staffing firm that speaks with hundreds of candidates every week and has placed thousands of professionals into organizations ranging from Northwest Arkansas startups to Fortune 1 companies.
What emerges from the conversation is a fascinating realization: staffing firms aren't simply matching resumes to job descriptions. They're filling in the gaps left by the hiring systems we've built.
Jordan explains that her recruiters certainly evaluate technical skills—but they lean heavily on assessments to validate those. The real work happens somewhere else.
Most importantly, they try to answer a question no résumé can:
What will this person actually be like to work with?
Along the way, Jordan shares why many of her clients never publicly post open positions, why passive candidates often become the strongest hires, and why staffing firms function as trusted advisors for both employers and candidates.
She also introduces the philosophy behind Gumption, the AI-powered platform Stratus is building after years of learning what traditional hiring systems fail to capture. Rather than simply matching people to jobs, Gumption aims to understand the human behind the résumé and match people to the teams where they'll actually succeed.
Signal Mapping Connection
Throughout this series, The Signal Lab is reverse-engineering hiring.
Hiring managers look for trust, character, and judgment.
Recruiters look for motivation, culture fit, and long-term success.
Assessments validate technical capability.
Each stage relies on different signals.
If we hope to build better digital credentials, better learner records, better AI, and better workforce systems, we first need to understand what information humans actually use to make hiring decisions.
Recruiters have quietly spent decades building richer profiles because the systems around them haven't.
Perhaps the next generation of workforce infrastructure shouldn't replace that understanding.
It should make it portable.
Resources
Jordan Franklin
LinkedIn: https://www.linkedin.com/in/jordan-franklin-gumption/
Stratice Consulting: https://mystratice.com/
Signol Labs: https://signollabs.com/
Signal Mapping: https://signollabs.com/blog-signal-mapping/
Connect with Ian Davidson: https://www.linkedin.com/in/ianwdavidson/
Schedule a conversation: https://signollabs.com/contact-us/
If your organization is designing hiring technology, talent marketplaces, digital credentials, Learning and Employment Records, or workforce infrastructure, we'd love to compare notes. This investigation is helping shape a practical framework for understanding the signals that actually drive hiring decisions.