Interviewing is often too subjective. Is it right to decide a candidate's suitability based on an interviewer’s opinion, from a general impression? Carta values data, and so we transformed our interviewers from decision makers into data gatherers. We wrote specific rubrics which objectively capture the attributes we value in a candidate profile, from technical architecture to organizational influence. Instead of simply giving their subjective opinion, interviewers consult the rubrics to measure a candidate's performance.

Our data-driven approach helps us reevaluate and continually improve our overall hiring process. Are candidates consistently scoring lower than expected on some attribute? We can improve that rubric to help us recognize their talent. Are some interviewers struggling to gather specific signals? We can offer training to sharpen their understanding of that topic. And we can now measure if interview outcomes actually correlate to performance outcomes and thereby improve both.

Our rubrics also help with leveling decisions, and the signals we gather help avoid particularly difficult and often arbitrary judgment calls when evaluating more senior engineers.

We would like to discuss how we created our rubrics and introduced them to our organization, and what we have discovered about how the process has affected our hiring outcomes.