http://mlb.mlb.com/r/game_article?gid=2018_04_13_phimlb_tbamlb_1&mode=recap&c_id=phi
A “hard hit” single in the 9th was all the Phillies needed to pull ahead and win the game. One of the data measures tracked by Major League Baseball is known as “Exit Velocity” and which baseballs are hit above 95 mph aka Hard Hits.
In 2017, hard hits carried a batting average of .558 while those that didn’t had an average of .225. Talk about a performance difference. It makes sense to swing hard.
This data is analogous to capturing candidate data on a daily basis and watching the performance of a recruiter. How “hard” are they swinging? Do they follow up within 24 hours, do they engage with brand assets consistently, do they chase hiring managers?
For our clients, one of the measures we track is the age of the candidate in each stage of the hiring process. It’s not enough that they are progressing through the stages, they need to do so with velocity. It reduces time to fill, increases candidate experience, and increases the number of requisitions a recruiter can execute annually.
How to Do:
You will need candidate data here. Using our AEIOU model (applicant, evaluated, interviewed, offered, unwanted) check the date stamps for each of those states, and calculate the date different between each.
A = Applicants
E = Evaluated
I = Interviewed
O = Offered
U = Unwanted
Y = said yes (the hire)
Then set limits for how long at each stage a candidate is permitted to stay in stage until they are deemed out of compliance. Examples may include you don’t want any candidate being in an applicant only stage for more than 7 days.
A < 4
You may also establish that internal candidates or referral candidates need feedback or advancement faster, like 2 days, so
AI < 2
AR < 2
Now take your optimal time to offer in days, and back into each limit. If you are targeting that 100 percent of roles in your stores will have offers out within 4 weeks, then you are likely having limits like this:
A < 3
E < 2
I < 10
O < 30
The Unwanted limit is not required as it naturally is produced as recruiters are updating data in your systems.
Now that you set your limits, you can track each day where recruiters are hitting it hard. If Applicants are being reviewed, if there are those being screened / evaluated, if there are those being interviewed….and how quickly is each candidate going though the process.
Requisition data and the data we report from it is kind of like only looking at the Win / Loss record of a baseball team. It tells an overall story, but it’s not saying why a team is winning.
Start using candidate data and Speed of AEIOU to reduce time to offer, increase candidate experience, and make recruiters as productive as they can be.