Business Intelligence Helped Us Hire Better

How is data helping us hire better? What were our struggles? Why are old metrics a waste of time (time to fill, number of hires, number of phone calls made)? Read ahead to find out more! This is a preview to my presentation and group discussion at the upcoming ERE Recruiting Conference in San Diego from April 18-20. Join me Thursday, April 20, at 2:30 p.m. at the Marriott West Harbor in San Diego.

Why Recruiter Metrics Make Bad Statistics for Hiring Success

In the past, companies used to look at recruiting statistics to measure the success of their hiring process in a company. Companies used to measure a recruiter’s success by how many phone calls they made, how many interviews they scheduled, and how many offers were made.

But in the age of e-mail, is 100 phone calls in a day really a measure of a great recruiter? If a manager has high expectations, is having 20 onsite interviews for a role really a measure of a great screening process? And if one recruiter is working on 10 technical engineer roles and another working on 10 customer-service roles — who would you expect to hire more and faster?

Our Struggle

We no longer could measure our success on our recruiters purely on measurable actions that had no bearing on actual hiring. Hiring may require a recruiter with salesmen-like qualities, but it is not as easy to measure success as a sales associate would by the amount of money they generated. Today we must go beyond how the sheer quantity of people we put through the process and focus on how candidates research, apply, and find interest in jobs today.

What we focused on:

We dug in deeper into the following:

Sourcing Analytics: Where are candidates applying from? Where do they see our jobs? How many click “apply” (whether they finish the application or not) after seeing our job description? Shift funds and source more in the spaces that bring you the most success. (Indeed and Craigslist are your biggest bang for your buck.)We also used this to realize where candidates saw our brand (Glassdoor, LinkedIn, Indeed) and spent more time on branding, creating a story instead of a job description and attracted a candidate to our company before we even spoke to them.
Team Metrics: Take the same team metrics, but instead of holding recruiters accountable for them — how do we hold candidates and hiring managers accountable? For example: If we had 20 interviews for one role and no hire, is that a recruiter problem or a hiring manager problem?
Machine Learning/AI: How can technology improve our hiring process? And how does that technology determine what characteristics to measure to score a candidate higher? Knowing how technology works (and not just using them) can grow your skills as a recruiter!

Interviewer Reviews: How do you review a candidate after an interview? Are you tracking how interviewers rank candidates? Use data to ensure your hiring team is being held accountable for how they measure a good fit for the job — and being fair!

Tools to Help: Modern technology is evolving. Take advantage. Machine Learning, text recognition, SMS/texting campaigns, your ATS … let them take your data and make it work for you!

Want more information? Dig in deeper into these categories with me at the ERE Recruiting Conference in San Diego on April 20 and join our group discussion to figure out what your pain points are and see how others use their data to hire better.

image from bigstock

Why Recruiter Metrics Make Bad Statistics for Hiring Success

Our Struggle

What we focused on:

We dug in deeper into the following:

Sourcing Analytics: Where are candidates applying from? Where do they see our jobs? How many click “apply” (whether they finish the application or not) after seeing our job description? Shift funds and source more in the spaces that bring you the most success. (Indeed and Craigslist are your biggest bang for your buck.)We also used this to realize where candidates saw our brand (Glassdoor, LinkedIn, Indeed) and spent more time on branding, creating a story instead of a job description and attracted a candidate to our company before we even spoke to them.

Team Metrics: Take the same team metrics, but instead of holding recruiters accountable for them — how do we hold candidates and hiring managers accountable? For example: If we had 20 interviews for one role and no hire, is that a recruiter problem or a hiring manager problem?

Machine Learning/AI: How can technology improve our hiring process? And how does that technology determine what characteristics to measure to score a candidate higher? Knowing how technology works (and not just using them) can grow your skills as a recruiter!

Interviewer Reviews: How do you review a candidate after an interview? Are you tracking how interviewers rank candidates? Use data to ensure your hiring team is being held accountable for how they measure a good fit for the job — and being fair!

Tools to Help: Modern technology is evolving. Take advantage. Machine Learning, text recognition, SMS/texting campaigns, your ATS … let them take your data and make it work for you!

image from bigstock