Saving 10 Hours a Week: What Recruiting Automation Actually Delivers (A Worked Example)

Instead of a single customer story, here's a transparent worked example - the exact numbers naturally depend on your individual application volume, but the order of magnitude is realistic for many SMEs.

The manual effort

Thoroughly reading an application, evaluating the resume, and noting a decision typically takes 10-15 minutes - for a single open role with 40 applications a month, that's 7-10 hours of pure review time.

The automated effort

With automated CV screening, the AI reads each application in under 30 seconds and assigns a score. For the same 40 applications, the only remaining human work is reviewing borderline cases - usually 1-2 hours instead of 7-10.

The worked example

• 40 applications × 12 minutes manually = roughly 8 hours
• Automated pre-selection + manual review of borderline cases = roughly 1.5 hours
• Estimated time saved: around 6.5 hours per open role
• With multiple open roles at once, the savings scale accordingly

Important to know

These numbers are a worked example, not a guaranteed outcome - actual volume, number of roles, and the thoroughness of your previous manual review all affect the real savings. Still, the order of magnitude shows why automation can pay off even at moderate application volumes.