I have a theory – quality of hire can be a standard formula – but the variables can be defined differently for each company. Of the QoH measures I have seen, there is always a multi-metric formula involved. This plus that plus that divided by something and so on. Its certainly made of several variables, constants, and operators.
What I think is that we need a constant rating system – a number that when you say it, people say – WOW that’s a quality hire. So I look to sports – because like math, many sports have international standards and language. The fact is that in golf, as an example, if you score 65 – that’s a good score. It does not matter which course, what tees you play from, or even really the difficulty of the course – that’s a really good score.
As much of a golfer as I am, I struggled to find something in the PGA ranking that was obvious. So I looked around and found another metric I liked – Passer Rating – stolen from the National and Canadian Football Leagues. In the spirit of the Superbowl, I re-configured the Passer Rating formula using some of the same comparison principles we used for the ANSI Cost Per Hire standard, and came up with a formula for Quality of Hire that is actually pretty straightforward, but configurable for virtually ANY position. It allows you to rate an individual within a job, but then also compare that hire with another hire in completely different position. Its like saying that you shot 72 on one golf course from one set of tees, and then 72 on another golf course from the same tees.
In honor of SourceCon 2013 let’s use sourcers as an example:
Metric 1 – Define “Completions and Attempts”. Each job has certain tasks that are supposed to be done according to target. Count how many times an assignment was made, and how many of those assignments had their targets met. For a quarterback, they are supposed to throw the ball (attempts), and its supposed to be caught (completions). For a sourcer, lets use the number of assignments given (A), and the number of times they meet their assignment goal (B). Assignment goals could be get 1 candidate, get two candidates – whatever.
Metric 2 – Define “Total Forward Movement”. Each job has tasks that are supposed to move toward a goal, target, or assignment completion. For a quarterback, its measured in the number of yards. For a sourcer, tally the number of candidates that are submitted across all those assignments (C). You will compare this with the number of assignments given (A)
Metric 3 – Define “Touchdowns”. Each job has a significant score, goal, or accomplishment that clearly are celebrated. For a quarterback, its throwing a touchdown pass. For a sourcer, let’s count how many candidates they recommend that are hired (H). You will again compare this with the number of assignments they are given (A). Update – instead of just hires, you may want to consider tracking number of offers made to recommended candidates (thanks Jan Grohoske at Right Thing).
Metric 4 – Define “Interceptions”. Each job has perceived mishaps or failures. In the NFL/CFL, the quarterback throwing an interception is defined as such. For sourcers, lets count the number of candidates that were recommended by the sourcer to a hiring manager or recruiter, and were rejected because they missed the mark (R). I know thats a little harsh, but we want passes to be smart and complete – not just throwing for the sake of throwing. You are going to compare the rejections to the total candidates submitted (C).
What is REALLY cool about the Passer Rating is that it introduces constants that make the rating a maximum of 158.3 – it can never be higher. 158.3 is perfection. The different constants are weighted by overall impact. It also states that there is a minimum value of zero for every metric, and maximum values for every metric, 2.375.
So lets pull your QoH together for a member of the sourcing team:
Step 1 – Calculate your four metrics
Metric 1 = 5 ((# of times an assignment’s target was met / total # of assignments) – 0.455))
Metric 2 = total # of candidates submitted / total # of assignments
Metric 3 = 20 (total # of submitted candidates hired / total # of assignments)
Metric 4 = 2.375 – (25 (total # of rejected candidates / total # of candidates submitted))
updated on Feb 11
Step 2 – Adjust your scores within minimums and maximums
Across all 4 metrics, if your any metric value is less than 0, then make that metric’s value 0. If a metric’s value is greater than 2.375, then make that metric score 2.375.
Step 3 – Add the four scores together, divide by 6, and multiple by 100
Now you have your rating 🙂 The maximum rating is 153.3. You can do this for a month, a week, a quarter, a year, a group of hires, by business, by function – whatever segmentation you need. Segmenting by business group is interesting when you have a sourcer who covers more than one business – you can see their performance by business or group they support individually and compare to other groups. My appreciation for segmented data is what lead us to develop our business intelligence tool, where you can segment and analyze all of your data from any and all of your HR systems.
This is great for sourcers, but what about recruiters? I tested the formula, and it totally works – except you need to change metric 3. Instead of tracking # of submitted candidates hired, try tracking # of candidates hired that have an exceeds on their next performance review or track the number of hires that are marked by hiring managers and candidates as having a high rating of satisfaction. Ultimately you need to find that “touchdown” for recruiters. Typically, an assigned recruiter ALWAYS gets a hire – eventually. You have the opportunity to define the touchdown based on slate size, feedback, time to fill or whatever. But again, the maximum for metric 3 is still 2.375. Remember, the denominator is the number of assignments, so they should do it some of the time, but its hard to do it all the time.
The key takeaway here is the if we want to be able to compare data we must have standards. Implementing a standard for Quality of Hire is just the beginning.