Abstract

Compose Inc. (Compose), a database-as-a-service startup that offered cloud hosted, fully managed database services, found that the conventional approach to hiring mainly from internal sources such as referrals from friends and trusted acquaintances, consumed a lot of time, besides which the percentage of candidates who made it to the interview stage was minimal. The company wanted to make the hiring process more transparent, less subjective, and less biased. Compose introduced the blind hiring approach in its hiring process that comprised the application and work sample and work-a-day stages. To begin with, an extension to its internal project tracking tool Fizz was created. The application helped to partially automate the hiring process, eliminating manual tracking of applications and the hiring stage for each applicant. In addition, different reviewers were randomly assigned work samples based on the roles for which the applicant had applied. Scores were averaged for each applicant by the application itself and the real-time status was then displayed on the dashboard. Applicants who had high scores in all the stages were selected and offer letters were issued to them. Compose moved a step further and discarded Fizz for Interviewed, a third-party application. This helped the company not only to automate all the stages of the hiring but further streamlined the process. The new application had a dashboard function where statistics once requiring a week-long analysis were collected, organized, and presented automatically in real-time for the HR team.

Learning Objectives

The case is structured to achieve the following Learning Objectives:

• Describe the importance of blind hiring and its advantages
• How critical is job and culture fit in start-ups
• Understand the challenges and benefits of using automation
• Examine the initiatives needed to automate the hiring process in a company
• Understand the importance of selecting the right candidates for a role

Keywords

Automation; Blind Hiring; Hiring; Start-up; Database; HR Policy; Human resource planning; Talent Management; Recruitment; Interviewed; Job Fitment; Bias; Process Analysis; Innovation