Case Study

In-House Contact Center Finds Interviews Useless

Case Study

In-House Contact Center Finds Interviews Useless

Summary
10,000 agent call center replaces face-to-face interviews with HiringBranch and sees better quality hires, while freeing up loads of time for the hiring team.

Introduction

When this contact center veteran of 20 years left a business process outsourcing firm to go in-house as Operations Director with a tech giant, he knew one thing: he did not want to use a legacy language test to assess his candidates. It never produced trustworthy results for him in the past.

This is a story about one HiringBranch customer and their journey implementing a no-interview hiring model.

Problem

Language assessments and manual interviews aren't good enough

Language assessments and manual interviews weren't effective for this contact center that received 300 job applications a week. They had 15 hiring managers conducting non-stop, face-to-face interviews to decide (subjectively) which candidates to train and hire. This went on for one year under the new Operations Director… until he found HiringBranch.

100%
no interview hiring model

Solution

Assess more than language in a streamlined test

Impressed with the HiringBranch assessment, the Operations Director had his team of 15 managers try it too. After meeting internally to discuss the assessment experience, here's what the Director had to say:

“We immediately saw value in its comprehension capabilities. HiringBranch doesn’t just assess for language proficiency, they evaluate a candidate’s ability to understand instructions and whether they can do a job well”.

The team agreed to pilot HiringBranch on a batch of candidates.

“We immediately saw value in its comprehension capabilities. HiringBranch doesn’t just assess for language proficiency, they evaluate a candidate’s ability to understand instructions and whether they can do a job well”.
Operations Director

Interviews become useless, recruiters wary

The team agreed to pilot HiringBranch on a batch of candidates.

After piloting HiringBranch, the results were so impressive that hiring managers deemed interviews useless. The managers felt that candidates who pass HiringBranch were ‘hire worthy’.

While the hiring managers were excited at the prospect of not having to interview, recruiters worried that HiringBranch’s pass threshold was too strict and would decrease the volume of candidate throughput. The operations and recruitment teams were now at odds.

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100%

no interview hiring model

Results

Bringing Recruiting and Operations Together

Both recruiters and operations agreed on a test to determine which model satisfied both groups and proved to be the most economical. After a candidate passed the recruiter screening, they would take the HiringBranch assessment and depending on how that candidate scored they would either go straight to job offer or have to take an interview. The scoring rubric was broken down as such:

- High pass: straight to job offer
- Low pass: straight to job offer
- Fail: sent to an operational interview (with the call center hiring manager)

After 45 days, the test revealed that the percentage of fails who passed an operational interview and were hired was so small that it simply wasn't worth interviewing those candidates. Plus, the quality of candidates who passed the assessment was at a level they’d never seen before.

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Inside the Best Language Model for Soft Skill Measurement

HiringBranch put their soft skills AI technology to the test. Does it read soft skills more accurately with proprietary data or the nearest best open-source language models?
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Organizations need to be able to measure soft skills accurately during the hiring process in order to take advantage of the skills-based hiring trend that’s happening now.
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What’s inside?

Packed with rich insights, this is an exclusive look inside HiringBranch data science. This study delivers hard proof around algorithm accuracy while revealing significant implications for high-volume hiring teams.

You’ll walk away with:

  • The results of this epic language model battle - who can measure soft skills most accurately?
  • A greater understanding of problem-solving techniques using data science and AI
  • An appreciation for the need for accuracy in the technologies driving hiring and operating processes today
Download My Free White Paper

Accurate Soft Skill Measurement Matters

Soft skills can and should be measured accurately, whether that is a reality for most organizations today or not. Soft skills account for 85% of career success!



Skills-based hiring (measuring both soft and hard skills instead of degrees, experience, etc.) is a priority for approximately three-quarters of recruiting pros because it has been proven to improve candidate quality, reduce bad hire rates, increase revenue, and more.
"Thank you for calling. That is frustrating when your video freezes during a work call.   I can definitely help you troubleshoot what is happening and see if it is related to the speed of your internet"
78%
Acknowledgement
91%
Empathy
75%
Positive Language
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Download your copy of the HiringBranch whitepaper now for exclusive insights about why and how to measure soft skills accurately.
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The experts weigh in on HiringBranch
The risk of using AI will be quickly outweighed by the benefits. Technologies that can show strong predictive results will be the game changers in moving hiring practices to the next level.
Howard Flint
WorkTech Advisory
The risk of using AI will be quickly outweighed by the benefits. Technologies that can show strong predictive results will be the game changers in moving hiring practices to the next level.
Howard Flint
WorkTech Advisory
Curious about soft skill measurement?
Check out these other great resources from HiringBranch.
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Skill-based hiring performance report:
AI edition

Skills-based hiring is on the rise. But how much does it improve performance? The results are in: skills-based hiring works. Find out just how much in this no-fluff, data-packed report on skills-hiring case studies from 100,000+ employee companies.
  • Data from over 5000 skills-hired candidates in 16 countries
  • 5 proprietary research studies
  • Metric analysis on high vs low skilled hires, attrition, and more
  • Expert input from AI scientists and leading HR influencers
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Soft skills are indicators of job performance

Skills-based hiring is still emerging, and early adopting organisations are already benefiting from the ability to measure soft skills and link this practice to hiring quality. HiringBranch soft skills AI is capable of better results than traditional methods of hiring.
HR technology vendors… claim to measure soft skills, but few validate job performance.
- Jon Sumser, HR Examiner
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What’s inside?

Learn what AI and skill-based hiring is capable of. Employers and contact centres can benchmark their performance, get cues for optimization strategies, implementation and more. Inside, we prove that:

  • Top-skilled candidates become top performers
  • Assessing language alone doesn’t improve performance
  • Highly-skilled candidates attrit less
  • Hiring for skills improves bad hire rates
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The experts weigh in on HiringBranch’s performance report
The risk of using AI will be quickly outweighed by the benefits. Technologies that can show strong predictive results will be the game changers in moving hiring practices to the next level.
Howard Flint
WorkTech Advisory
The risk of using AI will be quickly outweighed by the benefits. Technologies that can show strong predictive results will be the game changers in moving hiring practices to the next level.
Howard Flint
WorkTech Advisory

About HiringBranch

HiringBranch is an award-winning soft skills assessment tailored to high-volume hiring roles.  Only 30% of your candidate pool has the soft skills needed for job success and HiringBranch shows you who they are, before you even meet them. Powered by responsible and native AI, HiringBranch assessments uniquely measure skills in tailored, open-ended voice and chat scenarios with 98% accuracy. Start evaluating candidates for skills and select the top performers, every time.

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