
Panel Discussion: Identifying Technology Solutions That Will Have the Most Impact on Recruiting
November 9, 2022 · ERE Recruiting Conference ·
About this video
Recruiting leaders from large, complex organizations compare notes on how they choose, budget for, and evaluate the technology that actually moves the needle on hiring.
One approach breaks every tool down to a true cost per hire, treating the applicant tracking system as the biggest line item and rejecting point solutions that only shave a small cost against a modest improvement. Another leans on a lean stack built around a single applicant tracking system with no separate CRM, relying instead on strong community-building, content, and a steady flow of updates to keep passive candidates engaged, alongside a comparison of internal recruiting costs against agency spend to justify when outside help is worth the money.
Several practical points come up repeatedly:
- Boolean search and custom search engines built on free tools remain some of the highest-value skills sourcers can develop, ahead of paid tools that promise to do the same work automatically.
- Candidate texting platforms often deliver their biggest value in unexpected places, such as reminders for drug screens and background checks rather than the initial outreach they were bought for.
- Video interviewing adoption during the pandemic became critical for organizations that stayed customer-facing and could not go fully remote, and job postings mentioning remote work have already started declining as hybrid and on-site expectations settle.
- New technology gets evaluated against one question first: what specific problem exists that current tools cannot solve, and what does leaving it unsolved cost the business. Vendors get asked what already works with systems already purchased, not what works everywhere else.
- Global hiring goals change what diversity sourcing looks like by region, and bringing in local specialists who understand a specific market can outperform importing a domestic playbook.
- Vetting AI and machine learning vendors means asking pointed questions about bias, pulling in internal security and assessment specialists, and calling other companies that have already deployed the tool before signing anything.
- Budget cycles, procurement, and security review timelines shape when new tools can realistically go live, and switching a core system like an ATS only happens when there is no way around it.
Across every example, the underlying discipline is the same: match spending to a clearly defined problem, question vendor promises against real references, and be honest about which tools solve something and which just add noise to the stack.


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