We always had lots of applications for our data entry position, and since that’s a job that doesn’t have many requirements, we had lots of applications. Separating good candidates from the bad ones was hard and we spent 25 minutes on average evaluating each person before even interviewing them. We needed to make this process feasible by reducing the time required for hiring each person.
But there was one other major problem, most people quit the job without even working for a year. We needed to increase the retention rate drastically!
We created automation, which would make candidates self-qualify themselves for an interview. First, we had a fully automated system, which would eliminate the candidates who knew for a fact that weren’t a good fit. A partly automated second stage would require us to spend 5 minutes at most on each candidate and qualify them for an interview.
To solve the problem with the retention rate, we took a closer look at the data we had. We decided to create a system that would eliminate the people that wouldn’t be a good fit, which was also the first stage of the funnel.
74% Reduction in Time Spent on Each Hire
We used to spend 25 minutes on each applicant and 30 minutes on each interview and total time spent on each hire were 233 minutes. After we created the hiring funnel, we started spending only 5 minutes on each qualified applicant and spent 30 minutes on each interview. Which made the total time spent on each hire 61 minutes.
229% Increase in Employee Retention
While spending more time with a person helps to get to know that person better, it is not the most effective way. After identifying the what makes a bad candidate and a good candidate for the jobs, we managed to find the right people for the job. Fewer people quit, raising our retention rates for employees who worked for more than a year, by 229%.