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Mitigate Interview Inconsistencies with HackerRank Benchmarking

Written By Mohit Prakash | January 22, 2021

Illustration of two people waving to each other from browser tabs, with a third tab showing a headshot of a man

Interview feedback is extremely subjective. 

Every interviewer has their own style, questions, and expectations when they meet with a candidate. While it’s important to get these different perspectives and input, it can be challenging when it comes to making a hiring decision. 

“We have a full spectrum of interviewers strict and lenient who are assessing candidates’ skills. This makes hiring decisions more complex and time-consuming”. This feedback came directly from a HackerRank customer.

The above problem resonates with a lot of our customers. 

The bottom line is this: An interviewer's feedback is usually subjective, and each interviewer follows a different scale when rating a candidate.  

Unlike a test with an absolute measure of performance, the challenge here is that two interviewers may capture entirely different ratings for the same skill during an interview because of their personal grading styles. For example, if an interviewer uses a 1-5 rating scale, but the average rating they give candidates is a 2, then a 3 or 4 rating would technically be an above-average rating for them.

At the beginning of last year, we introduced an Interviewer scorecard in live interviews. This scorecard is a private scorecard for interviewers to manually evaluate candidate skills during an interview. It displays a set of skills to be analyzed based on the role that the candidate is getting hired for. Scorecards make interviews more structured and provide valuable data related to the interviewer—which can help minimize inconsistencies.

Interview Scorecard

Benchmarking can surface and resolve inconsistencies in an interviewer’s ratings by providing more context to the hiring panel. With Benchmarking, the interviewer's rating can be compared to their historical ratings for a skill. This allows the hiring team to better understand the relative intent of each interviewer’s score and thus start looking at each subjective rating more objectively as a whole. 

Let's dive into one example: Take a look at Visa’s Candidate Packet. 

HackerRank Candidate Packet

At a glance, she nailed her skill scores in the screening (100%), and she did great across the interview loop by getting 4 and 5 ratings, but she received a 2 from Dan (another interviewer). Is 2 a bad score? Well, according to the Benchmark, receiving a 2 from Dan is average. It turns out, Dan gives everybody a 2.

A 2 score from Dan has the same weight as a 5 score from Oded. Perhaps he’s burned out (a common problem with interviewers), or maybe his expectations are not aligned with the other interviewers.

The point is, you probably have a Dan hidden in your interview loop and don’t see it. The Candidate Packet and Interview Benchmarks create a consistent baseline for interview scoring so you can make well-informed hiring decisions.

Start Benchmarking your interviews today! 

The benchmarking capabilities are available for all customers who have Projects enabled. 

Click here to learn more about HackerRank Benchmarking and how it can be used to effectively screen and interview your technical candidates. 

 


Mohit Prakash headshotMohit Prakash is a Senior Product Manager at HackerRank for Data & Analytics. Mohit is passionate about building products that make data accessible so customers can make data-driven decisions. He leverages his engineering & product background to help companies optimize their hiring process by surfacing the right insights into their own data. Previously, he worked as a product manager at AtHoc and BlackBerry.