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How Gett's George Nichkov designed a process to make data-driven, unbiased decisions

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UK, Israel, USA, Russia

  • Human biases in hiring decisions
  • Automate recruitment to make data-driven decisions
  • Remote proctoring with anti-cheating mechanism
  • Online assessment without human invigilation
  • Skill wise extensive reports with comparative analysis

The Company

Gett, previously known as GetTaxi, is a global on-demand mobility company that connects customers with transportation, goods and services. Customers can order a taxi or courier either through the company's website or by using the company's GPS-based smartphone app.

Gett is of the fastest growing mobility services in the world. Fueled by a simple motto, quality begets quality, Gett has focused on providing the best services to drivers, who in turn, ensure that the same quality is extended to their rides as well.

In 2018, Gett has achieved the remarkable feat of becoming a “Unicorn”, valued at 1.4 billion.

Like any successful business enterprise, Gett prides itself on having the best workforce and are keen to maintain the high bar set for its team.

With a focus on quality internally as well as externally, Gett is focused on building their winning team, which comes with its own set of challenges. Recently, our customer success team worked closely with George Nichkov, Global Analytics Team Lead, when he was looking to hire a Business Analyst. This brought forward a few insights from him on recruitment which are worth sharing

“When hiring Business Analysts, I had to assess the applicants on their logical reasoning & aptitude. However, assessing a large pool of candidates & acquiring unbiased results without any human hustle is difficult without an automated solution. With iMocha, I was able to filter more than 500 candidates within a short span of time.”

George Nichkov,
Global Analytics Team Lead, Gett

What has been the biggest challenge in recruiting for Gett?

The challenge that I faced while hiring for Business Analyst or any other position in my team is reaching out to the right candidate. A typical job opening at Gett attracts almost 80-90 resumes. While, on paper, maybe 50 of them fit the bill, there is no sure way of knowing the right fit unless each one is interviewed individually.

And filtering through those 50 is no mean feat - telephone interviews, followed by personal interviews, and discussions which involved a considerable amount of time. This impacted us a great deal as the time to hire ratio was much higher and nobody wants to spend time on irrelevant candidates.

Another challenge was eliminating the human bias while hiring. Since, our process was so dependent on resumes, telephonic, and personal interviews, there was a possibility however marginal that human biases could creep in. In the larger scheme of things, this played out as a significant factor

How did iMocha help to counter these challenges?

As an analytics team head, I have a firm belief in data and data-driven decision making. With iMocha, we got the clarity we were looking for. I created a BA assessment emphasizing on analytical and logical thinking skills. These assessments were used for 1st level screening. This eliminated over dependency on resumes.

Firstly, we could weed out irrelevant candidates in the first phase. Assessments gave us the head start to assess skills, evaluate candidates, and incorporate them in the interview funnel. It reduced our time to hire by half.

Secondly, there was utmost transparency in the process. The assessment report spoke for itself. Only those candidates who had fared well on assessments were called for interview. We even found out that majority of the candidates who did well on the assessments performed well in the interview as well. The reports also gave us a skill-wise comparative analysis that helped in decision making.

A major advantage is that there is absolutely no need for the candidates to travel down to our office, they can appear for the assessment from anywhere and iMocha's powerful anti-cheating measures ensure that it's a fair attempt.

What has been the impact on hiring after this process was set?

We got the apt candidate for Business Analyst position, that too in one-fourth of the time it would have normally taken us. Our earlier process put a lot of stress and workload on the team. Since we have incorporated this process, we spend time only on relevant candidates.
Hiring team has so far assessed close to 500 candidates for various job roles and hiring is no more a pain for my team

Want to know how to reduce hiring time by 50%?


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