University students spend a considerable amount of time and money on earning a degree, yet it provides little actual signalling value to recruiters. With each university having different grading standards and practices, how can recruiters reliably interpret the results? By gathering and standardising data on grade distributions and the competitiveness of programmes, CASE’s algorithm places qualifications into context, revealing where applicants stand among their subject-specific peers as well as with all graduates nationwide.
Algorithms play a role in all stages of the HR lifecycle. One important differentiation is between algorithms that support the automation of processes and algorithms that enable analytics.
Algorithms in recruitment can automate processes like applicant tracking or assist with interview scheduling.
This whitepaper by candidate select GmbH (CASE) looks mainly at how algorithms can help to identify the right applicants to hire and what types of mistakes should be avoided.
Download this guide to figure out:
- What type of algorithms are there in hiring?
- Can algorithms help to assess CVs?
- How to combine algorithms and other hiring criteria?
- How to decide if an algorithm is improving hiring?
This guide also includes some useful case studies, including one conducted in partnership with Deutsche Post DHL Group.
Deutsche Post DHL Group combined the CASE Score with assessment tests to create high-quality rules for early selection. CASE identified 53% of applicants deemed unsuitable by the assessment centre beforehand. It was demonstrated that CASE allows better selection, saving 80% of selection costs.
Want to find out more about how algorithms could create efficiencies and cost savings like this in your organization? Download this free guide today!