Dialing for Dollars: Calculating the Costs of Hiring Decisions

After I became a graduate student for the second time, I learned that Maslow’s “hierarchy of needs” was thoroughly unproven as a management motivator. When I was a trainer, I consistently praised the benefits of the “Hawthorne Effect” (i.e., production increases when management pays attention to workers). Then I learned the training materials always stopped short of adding the rest of the Hawthorne story: “after a short time, production returned to pre-observation rates.” (There are many more examples of misinformation, but I have limited space). Mediocre performance is another one of those bogus misconceptions. People seem to take it for granted that interviews and unvalidated tests predict high job performance. They preserve this myth by:

poorly, if ever, following up on hiring predictions

remembering successes and forgetting failures
ignoring 50 years of research showing better ways to hire
being ignorant of DOL “Uniform Guidelines” best practices (and proud of it!)
confusing “cultural diversity” with “skills diversity”
not wanting to work very hard
(the worst of all) believing mediocrity is normal

Dialing for Dollars One way I get people to pay attention to the benefits of good hiring is to get them focused on calculating both cost and the return on investment. And nothing works better than a sales example. First, think of hiring as having an “effectiveness dial.” This dial starts at “zero” (i.e., hire everyone and see who survives) and goes to “max” (hire only applicants who pass the most rigorous tryouts). Most recruiters seem to think a “50%” setting is nice. They can ask questions, get to know the applicant, eliminate folks who give unsatisfactory answers, ask sales candidates to “sell the pencil,” and bet the organization’s money on the remainder. A 50% setting delivers a 50% result: about half the salespeople become high producers. 50% Dial Setting We’ll do some basic sales math to see what a 50% dial setting really costs. Here are 10 salespeople and their sales numbers. Like most sales groups, a few salespeople deliver most of the sales. The rest just manage to get by. For the purposes of this example, we’ll assume all salespeople all are at least “grudgingly” satisfactory. The percentages are rounded.

Molly	$5,000,000	(33%)
Fred	$4,000,000	(26%)
Sarah	$2,000,000	(13%)
Ted	$1,000,000	(7%)
Mary	$700,000	(5%)
——- Halfway ——–
Frank	$700,000	(5%)
Linda	$500,000	(3%)
Chris	$500,000	(3%)
Marsha	$300,000	(2%)
Saddam	$200,000	(1%)

People above 50% produce an average $2,540,000 per salesperson. People below 50% produce an average $480,000 per salesperson. This difference costs the organization $10.3 million in lost sales ($2,540,000 – $480,000 = $2,060,000; $2,060,000 x 5 = $10.3 million) every year. 60% Dial Setting Now let’s set the dial up to 60%. A 60% setting means we’ll probably delete the bottom 20% in the pre-hire phase (i.e., 60-50 = 10 and 10/50 = 20%). Here we go again with our numbers:

Molly	$5,000,000
Fred	$4,000,000
Sarah	$2,000,000
Ted	$1,000,000
Mary	$700,000
—– Halfway ——
Frank	$700,000
Linda	$500,000
Chris	$500,000
Nancy	$500,000
Clyde	$500,000

Now the average sales for the bottom half is $540,000. A tweak of the dial has added another $300,000 to the bottom line ($2,540,000 – $540,000 = $2,000,000; $2,000,000 x 5 = $10,000,000; and $10,300,000 – $10,000,000 = $300,000). 80% Dial Setting Now let’s set the dial to 80%. An 80% setting means we’ll probably delete the bottom 60% in the pre-hire phase (i.e., 80% – 50% = 30% and 30% / 50% = 60%). And the numbers, please!

Molly	$5,000,000
Fred	$4,000,000
Sarah	$2,000,000
Ted	$1,000,000
Mary	$700,000
—– Halfway ——
Bill	$700,000
Wanda	$700,000
Harry	$700,000
Beth	$700,000
Newt	$700,000

Now the average sales for the bottom half is $700,000, and the annual added bottom line contribution is $1,020,000 ($2,540,000 – $700,000 = $1,840,000; $1,840,000 x 5 = $9,280,000; and $10,300,000 – $9,280,000 = $1,020,000). These figures are a basic example of how profitable better sales screening can become (clients actually report much higher results). Use your own sales numbers and go through the same drill to see what sales hiring mistakes really cost. The premise in both situations is the same: you can screen out weak salespeople in pre-hire or screen them out on the job. Danger! Danger! Nothing is perfect. Usually the best that can be accomplished is a 90% dial rate. Why? Too many things interfere with selling. So what can you do?

Sales managers need to change their, “I know ’em when I see ’em” attitude to a “I know ’em when I see their sales skills” attitude.
Recruiters need to pre-screen applicants for their: 1) ability to learn and solve sales problems, 2) willingness to sell, 3) ability to discover information and present ideas persuasively, and 4) ability to plan and organize sales activities.
Hiring managers and recruiters need admit if effective pre-screening was so easy to do, why wasn’t it done before? Testing methodology cannot be learned by reading short articles like this. It takes professional skills and experience. If testing seems too easy, it probably won’t work.
Calculate how much it costs to hire and train low producing salespeople. Then ask yourself why they weren’t identified by an interview.

Do the numbers. The difference between a 50% accuracy rate and a 90% accuracy rate is an 80% improvement! (90% – 50% = 40%, and 40% / 50% = 80%). Could your organization use an 80% improvement in sales?