chapter 5: attracting desired applicants · chapter 5 - 2: recruiting page 5 - 2 lowers turnover...

Chapter 5 - 1: Recruiting

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Chapter 5 Goal: To learn how to

assess the impact of HR policies and

procedures on potential employees’

decisions to become applicants using

business metrics line managers can

understand and relate to important

business decisions.

Good recruiting can lead to low

selection utility. A curious side effect

of good recruiting can be lower

selection utility. Consider “perfect”

recruiting policies that generate only

applicants who are capable of

performing the job adequately, i.e., a

base rate = 100%. We don’t have to

use the Taylor-Russell table from

Chapter 3 to know a selection system

cannot add utility by improving on a

base rate of 100%. This is an extreme

example of a simple fact – selection

systems add value by reducing

uncertainty about who will perform

well in the future. When there is little

or no uncertainty in forecasting which

applicants will perform well in the

future, selection systems add little or

no value. Anything that reduces that

uncertainty, including recruiting

nothing but very good (or very poor)

applicants, reduces the opportunity for

a selection system to add utility.

Uncertainty captured by the Taylor-

Russell model is maximized when base

rates – 50%. Uncertainty in the

Brogdon-Cronbach-Gleser model

occurs when SDy is as large as

possible.

Chapter 5: Attracting Desired Applicants

This chapter describes how to evaluate the impact of HR practices that solicit applicants for

employment from the labor market. Hopefully it is intuitively obvious that quality and quantity of

applicants directly influences downstream business metrics.

Chapter 3 described the Taylor-Russell model of personnel selection

utility, in which base rate and selection ratio influenced whether

new hires were likely to perform adequately. Better recruiting

generates a higher percent of applicants capable of adequate job

performance, or a higher base rate. Better recruiting generates more applicants, increasing the bottom

part of the selection ratio, i.e., number of open positions divided by

number of applicants. Quality and quantity of applicants also

influence the average performance on the selection test of those

selected (𝑧�̅�) and subsequent variation observed in job performance

of those hired (SDy) in Chapter 3’s Brogdon-Cronbach-Gleser

model. Recruiting higher quality applicants increases the average

test score of all applicants, including those selected (𝑧�̅�). Recruiting

more applicants will also lower the selection ratio, causing the cut

score to be higher and thus increasing the average score of those

selected (𝑧�̅�). Recruiting can also affect whether firms meet

affirmative action goals and avoid charges of adverse impact.

Quality and quantity of recruits drive attendance in subsequent

training programs when large numbers of new hires lack needed

skills. Recruiting can also have immediate effects on labor costs

when hiring high vs. low performing recruits into commission-based

sales positions. Recruiting that leads to long job tenure further


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lowers turnover cost as described in Chapter 4. In sum, HR policies and practices attracting desirable

applicants affect the quality and quantity of employees coming into the firm and every down-stream

business metric affected by those new employees.

As in previous chapters, I will first share some “recruiting musings” about unique problems and

opportunities in this area. I then describe a host of business metrics that will be more or less relevant

depending on a firm’s unique strategic needs. The remainder of Chapter 5 explores how to use those

business metrics in various case applications to evaluate how well the organization is attracting

applicants.

Recruiting Musings

I have always found it helpful to view recruiting as the sales and marketing of the company’s job

offerings to “customers” in the labor market. Just like it sells and markets laundry detergent and personal

hygiene products to consumers, Proctor and Gamble also sells and markets job opportunities to

individuals actively seeking employment, or job “consumers,” in the labor market. Proctor and Gamble

can reach labor market “consumers” (applicants) through many channels, just as it manages distribution

of its products through various supply chains.1 Each “recruiting source” applicants are drawn from is the

HR equivalent of labor market supply chain.

Unfortunately, tools used by recruiting professionals are simply not as sophisticated as those used in

marketing. This may be due to HR’s long-time roots in labor economics, with its annoying habit of

assuming “homogeneity of labor units,” i.e., that all applicants in the labor market are equally skilled,

motivated, and decide to apply for and accept job offers in exactly the same way. I believe Henry Ford

was the last successful large manufacturer who made similar marketing assumptions when he said “(a)ny

customer can have a car painted any colour that he wants so long as it is black,” (Ford, 1922). Labor

economists’ assumptions may be appropriate for some types or levels of analysis (e.g., studying market

1 Proctor and Gamble is on the “sending” and “receiving” ends of product market supply chains and on the “receiving” end of labor supply market supply chains.


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behavior as opposed to applicant behavior), though unthinking adoption of labor economists’ assumptions

suggests HR professionals should . . .

1. randomly select new employees, since they are all equally skilled and motivated.

2. use one advertisement or notice of job openings with constant information about job content and employment opportunities, since all applicants decide to accept job offers for the same reasons.

3. use the same employment offer for all new hires, since all applicants are equally skilled and

similarly motivated to accept employment.

It makes me wonder whether university economics departments actually follow such practices when

hiring new faculty members!

Evidence compiled by industrial and organizational psychologists strongly suggests labor

economists’ assumptions are flawed when applied to HR practice. We will assume applicants exhibit job-

related individual differences in knowledge, skills, abilities, personality characteristics, prior work

experience, motivation to accept employment, and motivation to work hard once they are on the job.

Further, if we know what these individual differences are and how they are job-related, communications

about job opportunities can be tailored in ways optimized to attract desirable applicants from each labor

market segment. The question ultimately addressed in this chapter is how knowledge of these individual

differences in recruiting efforts helps obtain desired levels of important business metrics.


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Who is an Applicant? Effective October 6, 2006, the OFCCP implemented a “final rule” for describing who constituted an “internet applicant” for purposes of reporting requirements. The final rule, published in the Federal Register on October 7, 2005, defined “Internet Applicants” as:

Internet Applicant. (1) Internet Applicant means any individual as to whom the following four criteria are satisfied:

(i) The individual submits an expression of interest in employment through the Internet or related electronic data technologies;

(ii) The contractor considers the individual for employment in a particular position;

(iii) The individual’s expression of interest indicates the individual possesses the basic qualifications for the position; and,

(iv) The individual at no point in the contractor’s selection process prior to receiving an offer of employment from the contractor, removes himself or

herself from further consideration or otherwise indicates that he or she is no longer interested in the position.

(2) For purposes of paragraph (1)(i) of this definition, ‘‘submits an expression of interest in employment through the Internet or related electronic data

technologies,’’ includes all expressions of interest, regardless of the means or manner in which the expression of interest is made, if the contractor

considers expressions of interest made through the Internet or related electronic data technologies in the recruiting or selection processes for that

particular position.

(3) For purposes of paragraph (1)(ii) of this definition, ‘‘considers the individual for employment in a particular position,’’ means that the contractor

assesses the substantive information provided in the expression of interest with respect to any qualifications involved with a particular position. A

contractor may establish a protocol under which it refrains from considering expressions of interest that are not submitted in accordance with standard

procedures the contractor establishes. Likewise, a contractor may establish a protocol under which it refrains from considering expressions of interest,

such as unsolicited resumes, that are not submitted with respect to a particular position. If there are a large number of expressions of interest, the

contractor does not ‘‘consider the individual for employment in a particular position’’ by using data management techniques that do not depend on

assessment of qualifications, such as random sampling or absolute numerical limits, to reduce the number of expressions of interest to be considered,

provided that the sample is appropriate in terms of the pool of those submitting expressions of interest.

(4) For purposes of paragraph (1)(iii) of this definition, ‘‘basic qualifications’’ means qualifications—

(i)(A) That the contractor advertises (e.g., posts on its web site a description of the job and the qualifications involved) to potential applicants that they

must possess in order to be considered for the position, or

(B) For which the contractor establishes criteria in advance by making and maintaining a record of such qualifications for the position prior to

considering any expression of interest for that particular position if the contractor does not advertise for the position but instead uses an alternative

device to find individuals for consideration (e.g., through an external resume database), and

(ii) That meet all of the following three conditions:

(A) The qualifications must be noncomparative features of a job seeker. For example, a qualification of three years’ experience in a particular position is

a noncomparative qualification; a qualification that an individual have one of the top five number of years’ experience among a pool of job seekers is a

comparative qualification.

(B) The qualifications must be objective; they do not depend on the contractor’s subjective judgment. For example, ‘‘a Bachelor’s degree in

Accounting’’ is objective, while ‘‘a technical degree from a good school’’ is not. A basic qualification is objective if a third-party, with the contractor’s

technical knowledge, would be able to evaluate whether the job seeker possesses the qualification without more information about the contractor’s

judgment.

(C) The qualifications must be relevant to performance of the particular position and enable the contractor to accomplish business-related goals.

(5) For purposes of paragraph (1)(iv) of this definition, a contractor may conclude that an individual has removed himself or herself from further

consideration, or has otherwise indicated that he or she is no longer interested in the position for which the contractor has considered the individual,

based on the individual’s express statement that he or she is no longer interested in the position, or on the individual’s passive demonstration of

disinterest shown through repeated non-responsiveness to inquiries from the contractor about interest in the position. A contractor also may determine

that an individual has removed himself or herself from further consideration or otherwise indicated that he or she is no longer interested in the position

for which the contractor has considered the individual based on information the individual provided in the expression of interest, such as salary

requirements or preferences as to type of work or location of work, provided that the contractor has a uniformly and consistently applied policy or

procedure of not considering similarly situated job seekers. If a large number of individuals meet the basic qualifications for the position, a contractor

may also use data management techniques, such as random sampling or absolute numerical limits, to limit the number of individuals who must be

contacted to determine their interest in the position, provided that the sample is appropriate in terms of the pool of those meeting the basic qualifications.

Who is in the labor market and who is an applicant? Before we do that, however, we must revisit when an

individual is a member of the relevant labor market (i.e., a “potential” applicant) and when an individual

actually becomes an applicant. I think it is safe to assume anyone actively looking for employment or willing

to consider the “right” job offer is a “potential” applicant – s/he is part of the target labor market population.

Regardless of where they currently live, as long as these individuals are willing to consider moving to the

employment location for the “right” job, they are part of the relevant labor market. This would include happily

employed individuals who are not currently looking for alternative employment, but might be enticed back into

the market if the right opportunity came along.


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Regardless of how broadly we define “potential” applicants, most HR policies and practices are at

least partially aimed at attracting qualified individuals willing to consider employment opportunities with

the firm.2 Actual applicants are the most immediate result of HR policies and practices aimed at potential

applicants. The side bar contains the Labor Department’s Office of Federal Contract Compliance

Programs (OFCCP) “final rule” defining what constitutes an “internet applicant” for federal contractors.

It suggests an individual becomes an “applicant” if s/he expressed an interest in being considered an

applicant, the employer considers her/him an applicant, the individual’s expression of interest suggests

s/he possesses basic qualifications for the position, and the individual does not remove him/herself from

consideration as an applicant. Simply browsing through an employer’s web site or electronic job postings

does not make someone an applicant. Importantly, someone who applies without possessing the most

basic knowledge, skills, abilities, or competencies needed for the job is not considered an applicant.

Who is an applicant becomes critically important when determining whether an HR system has

adverse impact against a protected group. Recall the 4/5ths rule described in Chapter 2 compared

utilization ratios such as

applied

hired

applied

hired

whites

whites

blacks

blacks

N

N

N

N. If 𝑁𝑏𝑙𝑎𝑐𝑘𝑠𝑎𝑝𝑝𝑙𝑖𝑒𝑑

contained a large number of

unqualified applicants and 𝑁𝑤ℎ𝑖𝑡𝑒𝑠𝑎𝑝𝑝𝑙𝑖𝑒𝑑 contained only individuals with at least basic qualifications for

the position, subsequent selection systems are likely to “adversely impact” black applicants only because

good selection systems will reject black applicants without basic qualifications more frequently.

Why would a higher frequency of poorly qualified black applicants apply for a job? An example

might be found in the various times the State of Alabama Department of Transportation agreed to send

post cards announcing job openings to every black adult in Alabama (see Reynolds v. Alabama

Department of Transportation, 1998). Nonblack Alabama residents did not receive special notifications

of job openings. The goal of these special job notifications was to generate a greater number of black

applicants. One might also expect more marginally qualified black applicants (i.e., those who are just

2 Some HR policies and practices supporting local schools may broadly develop future members of the labor market without specifically targeting individual students as future recruits.


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Table 5-1: Recruiting-related Business Metrics

Business Metric Measure 1. Time to fill. Average number of days a position is unfilled.

2. Loss while empty. Average loss (sales, production, etc.) due to average days a position goes unfilled.

3. Cost while empty Average increase in overtime costs due to average days a position goes unfilled.

4. Time to applicant. Average time between announcement and first applicant.

5. Time to interview (sourcing).

Average time between announcement and presentation of first interview candidates.

6. Interviews/opening. Number of interviews ÷ number of openings. 7. Time to job offer. Average time between first interviews and job offer.

8. Time to acceptance. Average time between job offer and acceptance.

9. Acceptance rate. % offers accepted.

10. Rejection rate. % offers rejected listed by reason for rejection.

11. Time to start. Average time between job offer acceptance and start date.

12. Advertising cost. Average cost of job advertising per position filled. 13. HR recruiting cost. Average cost HR labor and operations costs per position

filled.

14. Job tenure. Average job tenure by . . . i. Voluntary turnover

ii. Reason for involuntary turnover. 15. Performance. Average job performance (any and all measures).

16. Tenure/performance profiles

See Figure 5-1.

17. Hires/recruiter. Number of hires ÷ number of recruiters.

18. Diversity and/or AI goals.

% of 𝑁𝑚𝑖𝑛𝑜𝑟𝑖𝑡𝑦need to meet utilization or diversity goal

achieved.

short of or barely exceed minimum basic qualifications) to apply simply because of the low personal cost

of applying and high possible reward. Top down selection of applicants based on scores from tests of

job-related knowledge, skills, and abilities is likely to appear to have adverse impact against black

applicants. However, in fact recruiting efforts that generated disproportionately higher numbers of poorly

qualified black applicants may be the root cause, not the selection system, of any subsequent adverse

impact. Basing the “Internet Applicant” definition on applicant expressions of interest and possession of

basic or minimum qualifications for

the job helps ensure an “apples to

apples” comparison of how well an

employer markets job opportunities to

blacks versus whites. Heroic or

unusual recruiting efforts that cause

dissimilar minority versus majority

qualification distributions may make

subsequent selection systems appear

to cause adverse impact that would

not have occurred if minority and

majority qualification distributions

were the same. The Uniform

Guidelines state “differences in

selection rate may not constitute

adverse impact where the differences are based on small numbers and are not statistically significant, or

where special recruiting or other programs cause the pool of minority or female candidates to be atypical

of the normal pool of applicants from that group.” Unfortunately, it is impossible for the state of

Alabama to know what the “normal pool of applicants” might have been had the race conscious post card

recruiting campaign not been implemented.


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Figure 5-1a: Job Tenure by Recruiting Source

Figure 5-1b: Mortgages Closed (in millions) by Recruiting Source

Figure 5-1c: Average Days to Fill by Recruiting Source

Figure 5-1d: Average Recruiting Cost

0

50

100

Mo

nth

1

Mo

nth

4

Mo

nth

7

Mo

nth

10

Mo

nth

13

Mo

nth

16

Mo

nth

19

Mo

nth

22

On-line RecruitsRemaining

Print Ad RecruitsRemaining

Employee ReferralRecruits Remaining

$0.00

$20.00

$40.00

Mo

nth

1

Mo

nth

5

Mo

nth

9

Mo

nth

13

Mo

nth

17

Mo

nth

21

On-line Recruits

Print Ad Recruits

Employee Referrals

0

10

20

30

40

50

60

70

On-lineRecruits

Print AdRecruits

EmployeeReferrals

Ave. Days to Fill

$0$200$400$600$800

$1,000

Ave. RecruitingCost

Business Metrics

The number of possible business metrics

reflecting how well HR policies and practices meet

recruiting needs is mind boggling. Table 5-1 contains

a short list of possible business metrics, which become

particularly instructive when compared across sources.

For example, Figure 5-1 compares job tenure,

sales volume, and average days to fill vacancies for

new mortgage brokers recruited from on-line, print

media, and current employee referrals by existing

Countryside Mortgage Inc. employees, a large national

home mortgage company.3 Figure 5-1a and Figure 5-

1b show how dynamic business outcomes, i.e.,

outcomes that change over time, differ across three

applicant sources (on-line, print media, and current

employee referrals). Figure 5-1c shows how a static

business metric – average number of days needed to

fill an open position – differs by applicant source.

Figure 5-1d plots the average recruiting cost per

applicant hired from on-line, print media, and

employee referral sources, while Figure 5-1c shows it

takes over 66 days to fill positions through current

employee referrals compared to 22 and 45 days for on-

line and print media, respectively. These figures

3 The “Countryside Mortgage” case discussed in this chapter is an amalgam of real data and examples taken from approximately one dozen mortgage companies I have worked with over the last 20 years.


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strongly suggest applicants referred by current employees stay longer, perform better, and cost less to

recruit. Cost differences would be much larger if they included the cost of downstream voluntary

turnover (Figure 5-1a). The only “downside” to current employee referrals is the two months it typically

takes to fill an opening through current employee referrals.

These statistics are fairly compelling until one realizes that referrals from current employees

filled only 9% of all mortgage broker vacancies! While encouraging current employee referrals might

cause some increase, I doubt Countryside Mortgage will ever be able to rely on it alone. Regardless, one

could conceivably tabulate 17 of Figure 5-1’s business metrics for purposes of comparing recruiting

sources. I routinely group business metrics coarsely into three categories:

1. Costs and measures reflecting speed of recruiting process up to new hire start date (metrics 1-13 & 17).

2. Business metrics 14, 15, & 16 taken during employees “newcomer” periods, i.e., the time it takes

for someone to move out of “newcomer” status and be expected to perform at steady state levels associated with “seasoned” (i.e., non-newcomer) employees.

3. Business metrics 14, 15, & 16 taken after employees move out of “newcomer” status, i.e., where

they are expected to perform at steady state levels associated with “seasoned” employees.

Note, I rarely find anything “interpretable” when examining business metrics for newcomers obtained

in the first few months on the job. Between learning unique aspects of the job they may have never seen

before and learning the shared beliefs, values, and attitudes of their new coworkers (i.e., the firm’s

culture), there are a lot of things influencing early job performance besides qualities newcomers bring

with them. At best I might find patterns in early termination codes for newcomers turning over in their

first 6 months on the job. Early on- and off-the-job training as well as pay systems may also cause early

job tenure performance swings. For example, mortgage brokerage firms often pay brokers a straight

salary of about $1500 per month for their first three months on the job, after which all income comes from

commissions on mortgages sold. At the height of the infamous sub-prime lending boom, brokers

typically generated ~$1500 in commissions for every $8M in new mortgages sold. Brokers who did not

achieve $8M in mortgage sales in their third month typically quit before the end of the fourth month (with

minor exceptions, average total mortgages sold was > $8M for all applicant sources by the 4th month).

Hence, examination of Countrywide mortgage brokers’ four month survival rate and 3rd month mortgage


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sales would be particularly relevant, even though “steady state” mortgage sales performance did not occur

until about month 7 regardless of applicant source.4

As I have said before, the number of business metrics available is solely a function of the type of HR

policy or practice examined and the HR professional’s creative use of her/his business knowledge.

Knowing how mortgage brokers were paid suggests ways to capture key recruiting outcomes (e.g., four

month survival rate) that were uniquely valuable to this mortgage company. We will now examine how

to evaluate evidence bearing on how alternate HR recruiting policies and practices influence relevant

business metrics in two real business settings. Case I uses the Countryside mortgage broker example to

evaluate how well a realistic job preview (RJP) recruiting effort helps the firm attain a strategic goal –

weathering change in housing and mortgage markets while establishing a unique mortgage “brand.” Case

II extends the Countryside Mortgage Co. example to examine how well recruiting efforts aimed at

increasing diversity among mortgage brokers accomplished its goals and affected key business metrics.

Case I: Mortgage “Branding” and Brokers for the Long Haul

Anyone who owns a home in the United States is aware of recent events influencing the housing

market. When hurricane Katrina devastated gulf coast natural gas facilities, home heating prices

drastically increased. As cost of home ownership goes up, growth in home prices slows. Changes in

monetary policy by the Federal Reserve Board caused a decrease in the cost of money from ~ 2001-2005,

resulting in a huge increase in mortgage refinancing, subprime mortgage lending, and increases in average

home sale price (as mortgage rates go down, home prices go up). The subsequent “sub-prime lending

crisis” caused a drastic increase in number of mortgage defaults, and consequently had a chilling effect on

interest rates, number of new mortgages, and mortgage refinancing. The commission-based mortgage

broker labor market experienced a number of recent “boom and bust” income cycles as a result of these

and other market forces.

4 Steady state employment occurred somewhere between months 13 & 17, when percent still employed seemed to level off for all applicant sources.


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Countryside Mortgage wanted to create a national mortgage “brand” that provides consumers with

“continuity of home financial care,” i.e., consistent long term service of consumers’ life time home

financing needs. According to Countryside’s records, the average U.S. home owner changes jobs and

homes about every five years. Further, changes in interest rates and life circumstances may encourage

mortgage refinancing to extract equity or lower monthly payments. After considering all influences on

home financing needs, Countryside estimated typical homeowners would need mortgage services at least

seven times after age 30. Countryside’s new 5-year strategic plan described three goals related to these

seven financing/refinancing opportunities. First, increase market share of mortgage services provided to

first time homeowners in their late 20’s and early 30’s. Second, increase market share of mortgages

provided to non-first time homeowners who are changing homes or seeking alternate financing of current

homes. Third, to drastically increase retention of current and new mortgage customers by making

Countryside “the” preferred brand for mortgage services (like Kleenex or Xerox in the nasal tissue and

photocopy markets, respectively). While the first two goals will impact near and medium term financial

performance, “continuity of home financial care” through retention of current mortgagee business (the 3rd

strategic goal) will yield long term financial performance for both Countryside and its mortgage brokers.

Current mortgagees constitute a reliable source of business for mortgage brokers, helping them survive

tough market conditions that decrease the number of first time home buyers.

The impact on mortgage brokers becomes clear when looking at some simple descriptive statistics.

For example, much of the refinance business in the 2001-2005 time range came from “cold calls,” i.e.,

call center telephone operators randomly calling home owners in hopes of obtaining “leads” a mortgage

broker could be follow up. When interest rates were low, this sales tactic generated a lot of mortgage

refinancing because many homeowners did not know interest rates had become so attractive.

Commissions were the sole source of Countryside mortgage broker income after three months on the job,

and many applicants were attracted to open mortgage broker positions due to the healthy commissions

generated from the 2001-2005 increase in mortgage refinance business – they made a lot of money simply

completing application forms for clients attracted by cold call sales efforts. Many mortgage brokers hired


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in this period did not provide services needed to ensure these homeowners stayed with Countryside for

future home financing needs.

As interest rates rose throughout 2005, call center sales efforts generated substantially fewer

mortgage refinancing business. Countryside’s mortgage broker ranks swelled by 70% (+1600) during

2001-2005, only to fall back to 85% of its original size (~800) when many mortgage brokers left due to

the severe drop in commission income after 2006. Research by Countryside’s HR vice president

identified a “core” group of current career mortgage brokers who had survived multiple environmental

changes for at least an 8 year period (N = 390), including the recent drought resulting from the subprime

lending fiasco. One-on-one and small group interviews with a select group of CMBs (CMB) resulted in a

job analysis questionnaire, which all 390 core and a sample of 120 “non-core” mortgage brokers

subsequently completed. Analyses comparing core vs. non-core broker responses suggested:

Approximately 97% of non-core broker and 25% of CMB mortgages came from call center leads.

Evening call center efforts resulted in “lead sheets” passed electronically to brokers the next day

based on each broker’s current work load. CMBs were called “short sheeters” because their daily

cold-call lists were about 25% as long as non-core broker lists. Most CMB mortgage activity came from sources other than daily lead sheets. Non-core broker’s rarely obtained less than 95%

of their commissions from mortgages initiated through cold call leads.

Approximately 25% of CMB mortgages were “repeat” business, i.e., new mortgages issued to prior customers.

Approximately 25% of CMB mortgages involved current customers refinancing existing

mortgages.

CMBs developed and maintained a network of professional relationships or colleagues in the real estate business or the larger community.

o 35% of core brokers did their own local advertising (e.g., billboards, public transit signage,

etc., subject to approval by Countryside district marketing managers). Approximately 20% of CMB mortgages came from referrals through contacts in the real estate

business and larger community. This figure varied widely from year to year depending on

interest rates and local housing conditions. o This percentage was low in years with low interest rates or high local population growth.

o This percentage ranged up to 40% in years with high interest rates or low demand (e.g.,

when a large local employer closed operations or had a large lay off).

Approximately 5% of CMB mortgages went to new customers referred by past or existing customers.

Non-core brokers focused most of their non-customer contact time on streamlining form

completion processes expediting other professional’s services (e.g., title and abstracting work, title insurance, inspections, appraisals, etc.). CMBs enjoyed the benefits of this streamlining, but

devoted none of their own time to achieving it.

CMBs spent most of their non-customer contact time developing and maintaining relationships with real estate professionals and others in the local community.


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Average job tenure of core brokers was 5+ years. Initial core broker income came primarily from

cold call follow-ups. Percent of commissions received from referrals typically increased to about 20% within the first year, with percent of commissions coming from servicing existing customer

mortgage needs (i.e., financing new homes or refinancing existing mortgages) slowly growing

over the second and third years.

In sum, CMBs were successful regardless of economic conditions because of careful cultivation of future

business from current customers and professionals elsewhere in the local community. In contrast, “non-

core” brokers were only successful in periods of high mortgage demand (i.e., when mortgage demand

exceeded the capacity of existing “core” brokers to service it). During periods of “normal” or low

customer demand for mortgage products, “non-core” brokers were “pursuing other career opportunities”

outside the mortgage industry.

In light of the job analysis survey and Countryside’s new strategic goals, Ms. Blandine Cortez,

Countryside’s V.P. of HRs, decided to implement a new “strategic staffing goal” of selecting/developing

CMBs who can 1) survive and thrive regardless of housing market conditions and 2) help Countryside

reach its strategic mortgage brand goal. Ms. Cortez was considering committing to a specific goal of

doubling the number of “core” brokers at Countryside by +400 by the end of the 5-year strategic plan

based on the following facts:

1. Less than 50% of mortgage brokers on staff before the last “boom-bust” cycle were “core”

brokers (390 of 900). Seasoned “core” brokers made up about 50% or less of employees at

competing mortgage financing firms. 2. Strategic Goals 1 & 2 involved increasing the size of Countryside’s market. Tactics adopted to

achieve these goals included expanding existing banks of call center operators doing cold-call

sales and new internet-based advertising aimed at retaining current mortgage customers. 3. Countryside HR training professionals developed a systematic CMB training program aimed at

developing skills needed to obtain, grow, and nurture local contacts and current mortgage

customers. 4. Countryside staffing HR professionals developed a realistic job preview that highlighted the

following negatives and positives of being a Countryside mortgage broker:

a. Negatives: cold call sales are basis of early commission income, boom and bust nature of

home financing markets. b. Positives: Countryside “core” broker training program, strategic commitment to grow

Countryside “brand” and percentage of repeat customer home financing needs,

advertising aimed at retaining future business of existing mortgage customers.

Adding 400 CMBs over the next five years involved extensive commitments of time and resources by

Countryside HR professionals and line mangers, though current levels of mortgage broker turnover


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Table 5-2: Realistic Job Preview Content

Glossy pamphlet developed containing brief description of Countryside’s core mortgage broker job, Countryside’s strategic goals, and what those goals mean for career CMBs. Pamphlet was distributed to business school finance departments and other historic sources of mortgage broker applicants.

Print media advertisements paralleling pamphlet content run in select “state” newspapers (e.g., the Des Moines Register) and regional editions of national magazines (e.g., Time, Newsweek, etc.).

Multi-media web site version of pamphlet linked to existing job postings on Monster.com (only for central district job listings).

Office manager training on standardized job “sales pitch” containing both negative and positive aspects of mortgage broker positions and how the job contributes to Countryside’s strategic goals and objectives.

Focus on initiating communications and building networks of relationships with community stakeholders in Countryside CMB training program, emphasizing on how this ensures long term viability of a mortgage broker career path.

Development of “business tracking forecast” software so new brokers can track mortgages generated by customer type and compare it to “target” performance trajectories of those who go on to become CMBs.

suggested it might be completed in as little as three years. Before making such a commitment, Ms.

Cortez wanted to be confident the goal was attainable. Her HR team suggested a 24 month “pilot” study

in which one district used the new realistic job preview recruiting campaign and the core broker training

program. Comparison with results obtained from “status quo” districts using existing recruiting and

training systems should yield clear evidence on how the new HR system might increase the number of

core brokers. If the pilot program achieves its goal of attracting applicants likely to become CMBs, the

three years remaining ought to be enough time to recruit, select, and train 400 new CMBs before

completion of the five year strategic plan.

Countryside Pilot Study Design

Countryside has ~250 mortgage offices in 4 districts nationwide, with a median of 4 brokers per

office (typically a little less than 2 core

and a little more than 2 non-core

brokers). Districts roughly correspond

with the eastern, central, mountain, and

Pacific time zones, with regional

offices in New York, Chicago, Denver,

and Seattle. After considering things

like average job tenure, current broker

job tenure, and existing training

facilities, the HR staff decided to

perform the pilot study on brokers

recruited to fill vacant or new broker

positions in the 60 central district

mortgage offices. The central district

currently employed 100 core and 150 non-core brokers.


Page 5 - 14

Realistic job preview (RJP) material was carefully prepared. Table 5-2 describes the various HR

efforts contributing to the RJP. The common theme underlying all of these components was emphasis on

both the pleasant and unpleasant aspects of CMB careers. Simultaneously, Countryside HR developed a

CMB training program at the central Chicago district office. CMBs in the greater Chicago area

participated in developing the one week program and sat through a “dry run” before pronouncing it ready

to go. Training program content focused on both the pleasant and unpleasant aspects of prospecting for

future home financing needs among existing mortgagees and developing relationships with real estate

brokers and builders in the local community. Training content focused on specific tactics for addressing

unpleasant aspects and overcoming difficulties encountered.

Existing turnover rates, current central district mortgage broker job tenure, and business growth

projections all indicated approximately 150 mortgage broker openings would occur in the next 12 months

(90% would come from the ranks of current non-core brokers). Sources of applicants for these positions

historically included print media job advertisements (30%), on-line recruiting through Monster.com

(45%), college campus business school interviews (20%), and current employee referrals (5%).

Countryside HR professionals gathered a variety of monthly business metrics from Table 5-1on new

mortgage brokers hired across all districts for 12 months after the start of the study. New Business

Tracking Software installed in each Countryside office gathered and summarized information on

mortgage origination (e.g., cold-call list, referral from contacts in local community, refinance of existing

mortgage, new mortgage for an existing customer, etc.), monthly commissions, percent of monthly

commission by mortgage origination, and job tenure for all Countryside mortgage brokers.

Comparisons of Results

Countryside HR professionals pooled information across the eastern, mountain, and Pacific

districts for all subsequent analyses. The central district had 152 openings filled after implementing the

pilot JCP training and recruiting program, with 109 (72%) of the initial job offers accepted. The

remaining 43 openings had offers accepted after the most preferred candidate declined the first job offer.

The remaining districts had 499 openings filled, with 339 (68%) of the initial job offers accepted and the


Page 5 - 15

Table 5-3: Comparison of Business Metrics Resulting for RJP versus Non-RJP Districts

Business Metrics Central District

N = 152

Eastern, Mountain, &

Pacific Districts N = 499

�̅� SD �̅� SD z*

Time to fill 59.5 11.3 34.1 7.4 26.1***

Time to applicant 8.2 2.7 4.9 2.1 13.8***

Time to interview 24.2 5.3 14.2 5.9 19.8***

Interviews/opening 5.1 1.1 2.9 3.7 11.7***

Time to job offer 18.2 2.0 6.8 1.8 62.9***

Time to acceptance 4.1 1.0 4.1 .9 0

1st offer acceptance rate

109 (72%) 6.45

339 (68%) 10.42 .93

Time to start 4.8 9.0 4.1 3.3 2.73***

Hires/recruiter 5.6 1.8 7.2 3.9 11.13*** Ave. Advertising Cost per Position $602 $69 $519 $56 13.5***

Ave. Dollar Mortgages Sold:

Central District Eastern,

Mountain, & Pacific Districts

1st 3 months $8.6M (N = 132) $1.4M

$6.0M (N=412) $3.8M 13.7***

1st 6 months $9.9M (N=125) $1.6M

$6.9M (N=334) $2.9M 6.2***

1st 12 months $13.2M (N=119) $1.9M

$8.8M (N=287) $4.0M 14.8***

Hires/recruiter 5.6 1.8 7.2 3.9 11.13***

Month 4 Turnover .15 (N=129) 4.4

.40 (N=359) 10.9 5.69***

Month 12 Turnover .22 (N=119) 5.1

.42 (N=287) 11.0 4.47***

*Equation 1, except for the last 2 rows, which come from Equation 2

presented in Chapter 5. ** p < .01,*** p < .001

remaining 160 filled after the most preferred candidate declined the first job offer. We want to know

whether differences exist in cost, time to fill open positions, and proportion of commissions coming from

non-cold call (referral) mortgages that can be attributed to the RJP efforts. Specifically, did the pilot RJP

recruiting and training efforts in Chicago result in more CMB performance trajectories?

Table 5-3 reports business metric averages and standard deviations for the central versus

combined eastern, mountain, and Pacific districts.

Table 5-3’s last column contains the z statistic test

of whether average business metrics were

significantly different between the central district

and combined eastern, mountain, and pacific

districts, or Ho: 𝜇𝑅𝐽𝑃 − 𝜇𝑜𝑙𝑑 = 0 vs. HA: 𝜇𝑅𝐽𝑃 −

𝜇𝑜𝑙𝑑 ≠ 0 (remember “𝜇” is the Greek lower case

letter used to represent the population average).

Note, the null and alternative hypotheses for

Table 5-3’s rows 7, 15, & 16 are Ho: 𝑝𝑅𝐽𝑃 −

𝑝𝑜𝑙𝑑 = 0 vs. HA: 𝑝𝑅𝐽𝑃 − 𝑝𝑜𝑙𝑑 ≠ 0, since these

rows deal with differences in proportions

(Equation 2 below contains the formula for that

statistic). Recall the z statistic tells us how likely

it is that a difference between any two values of

�̅�𝑅𝐽𝑃 or �̅�𝑜𝑙𝑑 happened by random chance (i.e.,

due to random sampling error) when 𝜇𝑅𝐽𝑃 = 𝜇𝑜𝑙𝑑 .

The formula for the z statistic (from Chapter 2’s

Equation 1) is:


Page 5 - 16

2 2

1 1

( ) ( )

1 1

RJP old

RJP old

N N

RJP oldi i

i i

RJP old

RJP old

x xz

x x x x

N N

N N

Equation 1

The z statistic will be 0 when �̅�𝑅𝐽𝑃 = �̅�𝑜𝑙𝑑, as it was for average Time to Acceptance in Table 5-3. Recall

also from Chapter 2 that the Central Limit Theorem tells us z is normally distributed. If we use a normal

probability table from the back of a statistics textbook, we see z > 1.65 occurs only 5% of the time by

random chance when 𝜇𝑅𝐽𝑃 = 𝜇𝑜𝑙𝑑 . The first result from the z column in Table 5-3 suggests the average

time required to fill open mortgage broker positions was “statistically significantly” longer for the new

RJP recruiting process (60 vs. 34 days). In other words, in light of the variability in average number of

days to fill an open position, averages of 60 and 34 days are expected to be found less than 5% of the time

by random chance when the population these two samples of 152 and 499 were drawn from actually did

not differ in average number of days to fill.

The next six results from the z column suggest the RJP recruiting system had significantly longer

lags at every recruiting stage except Time to Accept, which was not surprising given “offer letters” placed

a ceiling on response time by asking for an answer within 5 days. The new RJP recruiting method also

cost significantly more per position filled in advertising costs ($83), and college recruiters generated 1.6

fewer applicants for each open mortgage broker position in the Central District. Results clearly indicate

the new RJP recruiting effort cost more and was slower to fill open mortgage broker positions.

On the positive side, mortgage brokers recruited using the new RJP procedure accepted job offers

significantly more frequently (though only slightly), consistent with the RJP findings reported elsewhere

(Premack &Wanous, 1985). Importantly, mortgage brokers recruited using the new RJP procedure and

subsequently trained with the new CMB training program generated significantly higher mortgage

volume and significantly higher likelihood of lasting 3, 6, and 12 months on the job. The bottom half of

Table 5-3 reports RJP recruits in the central district generated average mortgage volumes that were


Page 5 - 17

Figure 5-2: Central District Mortgages by Source

Figure 5-3: Combined Eastern, Mountain, & Pacific Mortgages by Source

$-

$5,000,000.00

$10,000,000.00

$15,000,000.00

$20,000,000.00

Referral

Cold Call

Total

$-

$5,000,000.00

$10,000,000.00

$15,000,000.00

Referral

Cold Call

Total

$2.6M, $3M, and $3.4M higher during their first 3, 6, and 12 months on the job. The 112 mortgage

brokers who survived 12 months in the central district (78%) generated $1570.8M. If the eastern,

mountain, and Pacific districts had used RJP recruiting with similar success, 359 brokers are predicted to

have survived 12 months on the job (as opposed to the 287 who actually did survive). These 359 brokers

would also generate average monthly mortgage volumes of $13.2M and a total expected mortgage

volume of $5148M, or $2622.2M more than what was actually generated by the 287 brokers recruited and

trained existing methods in the eastern, mountain, and Pacific districts. The new RJP system is expected

to more than double 12 month mortgage volumes in

the eastern, mountain, and Pacific districts by

retaining more brokers who generate higher

mortgage volumes.

Recall Countryside’s new strategic goals

targeted development of CMBs, i.e., brokers who

generated most of their mortgage volume from

existing customers, referrals from existing customers,

and contacts in the local community. Further,

existing CMBs generated ~ 20% of mortgage

commissions from sources other than cold calls by

their 12th month on the job. Figure 5-2 and

Figure 5-3 plot the amount of mortgages sold

$-

$5,000,000.00

$10,000,000.00

$15,000,000.00

$20,000,000.00

Referral

Cold Call

Total


Page 5 - 18

monthly originating from referrals versus cold call sales (repeat business from existing customers were

not measured in the first year of job tenure, though it was in subsequent years). Figure 5-2 shows RJP

recruited brokers generated about 25% of mortgage volume from referrals after 12 months on the job.

Figure Figure 5-3 shows brokers recruited and

trained using existing methods generated a little more than 4% of mortgage volume from referrals.

Virtually all RJP-recruited brokers surviving 12 months on the job appeared well on their way to attaining

CMB status, while less than 5% of brokers recruited using existing methods earned > 20% of

commissions from non-cold call sources after 12 months on the job. Tests of whether the percent of

commissions based on non-cold call mortgage business were equal, i.e., H0: pRJP = pold, using the special

version of the z statistic used for proportions when the sample size is greater than 30 in Equation 2 below:

1 1(1 )

RJP old

total total

RJP old

p pz

p pN N

Equation 2

. . . where pRJP = .25, or the proportion of commissions earned from referral sources for brokers recruited

using the RJP procedure, pold = .04, or the proportion of commissions earned from referral sources for

brokers recruited using the old recruiting procedure, and ptotal = .09, the proportion of commissions earned

by all N = 651 brokers regardless of how they were recruited. Plugging in the values pRJP = .25, pold = .04,

ptotal = .09, NRJP = 152, and Nold = 499, we find z = 7.92, which occurs less than .1% of the time by chance

when two samples of N = 152 and N = 499 are randomly drawn from a population in which pRJP = pold.

So, the proportion of commissions generated from referrals is “statistically significantly higher” for

$-

$5,000,000.00

$10,000,000.00

$15,000,000.00

$20,000,000.00

Referral

Cold Call

Total


Page 5 - 19

Compelling Comparisons. There are

lots of ways of contrasting expected

differences in mortgage sales volumes.

For example, given that 78% (119/152)

of brokers remain after 12 months and

earn an average of $13.2M per month

in mortgage sales, hiring one broker

using the RJP-training procedure is

expected to yield .78 x $13.2M =

$10.33M in monthly mortgage sales.

In contrast, the existing

recruiting/training procedures yield

57.5% (287/499) brokers remaining

after 12 months, each of which

generated a average of $8.8M in

monthly mortgage sales. Hiring one

broker using the existing recruiting-

training procedures is expected to

generate .575 x $8.8M = $5.1M in

monthly mortgage sales, less than half

the expected monthly mortgage sales

volume generated by brokers brought

to Countryside by the pairing of RJP &

training procedures pilot tested in the

central district. Listening to executives

talk about key business metrics is

perhaps the best way of determining

how to communicate results that have

the most impact.

brokers recruited and trained using new HR procedures in the central district relative to the “control”

districts. Virtually all brokers recruited and trained with the new HR procedures in the central district

were on trajectory to achieve CMB profiles within 4-5 years.

So, what conclusion should Ms. Cortez take away from these results? She should see the new

RJP recruiting procedure-training program pairing is likely to yield

slightly higher first offer acceptance rates, meaningfully higher

mortgage volumes, and a mortgage “mix” profile trajectory

suggesting new hires will achieve CMB status and Countryside will

achieve its strategic “branding’ goal. Ms. Cortez now has to decide

whether all of these expected outcomes are worth the extra $83 cost

to fill and 26 days each opening stays vacant (on average). I

personally would judge the extra $83 per opening filled as a trivial

cost relative to the expected increase of between $4.5M per month in

mortgages written after 12 months – how often can you spend $83

per employee to get an extra $4.5M per month in business? The

extra 26 days positions remained open under the RJP-training

procedures is less than one month, which I again would not see as

too high a price for the extra $4.5M in monthly mortgages issued.

Again, if I were Ms. Cortez, I would order immediate

implementation of the new RJP recruiting practices and training

program nationwide. I would also ask for the data in Table 5-3 to be broken out by recruiting source

(print media, Monstor.com, college recruiting, and employee referral) to see whether one or more sources

of applicants cost less and/or filled openings faster with the same level of subsequent performance.

The next case extends the Countryside example to examine how different recruiting practices

influence the presence or absence of adverse impact.

Case II: Recruiting Effects on Adverse Impact and Affirmative Action


Page 5 - 20

Countryside recently geographically expanded its offices into 12 large regional markets

surrounding 12 urban centers in southern and western states. Initial plans were for approximately 70% of

each office’s staff at time of start-up to come from existing Countryside employees who wanted to

transfer, usually relocating from some northern state. Unfortunately, initial information available on

regional mortgage broker labor market racial composition surrounding Miami, Atlanta, Birmingham, New

Orleans, Houston, Dallas, San Antonio, Austin, Phoenix, San Diego, Orange County (CA), and Los

Angles suggested a much higher percentage of Hispanics relative to their presence in labor markets in

Countryside’s other regions and relative to their presence among Countryside’s existing mortgage

brokers.

The 1978 EEOC Uniform Guidelines on Employee Selection Procedures defined adverse impact

as “(a) substantially different rate of selection in hiring, promotion, or other employment decision which

works to the disadvantage of members of a race, sex, or ethnic group.” The Guidelines go on to state that

a “selection rate for any race, sex, or ethnic group which is less than four-fifths (4/5) (or eighty percent)

of the rate for the group with the highest rate will generally be regarded by the Federal enforcement

agencies as evidence of adverse impact, while a greater than four-fifths rate will generally not be regarded

by Federal enforcement agencies as evidence of adverse impact. Smaller differences in selection rate may

nevertheless constitute adverse impact, where they are significant in both statistical and practical terms or

where a user's actions have discouraged applicants disproportionately on grounds of race, sex, or ethnic

group. Greater differences in selection rate may not constitute adverse impact where the differences are

based on small numbers and are not statistically significant, or where special recruiting or other programs

cause the pool of minority or female candidates to be atypical of the normal pool of applicants from that

group.” While not explicitly defined as “illegal” in any federal legislation, the Guidelines go on to say

“(t)he use of any selection procedure which has an adverse impact on the hiring, promotion, or other

employment or membership opportunities of members of any race, sex, or ethnic group will be considered

to be discriminatory and inconsistent with these guidelines, unless the procedure has been validated in

accordance with these guidelines, or the provisions of section 6 of this part are satisfied.”


Page 5 - 21

The U.S. Supreme Court gave the Guidelines “great deference” in arriving two precedent setting

decisions (i.e., Griggs v. Duke Power, 1971, and Albemarle v. Moody, 1975), effectively giving the 4/5ths

rule the power of law. In order to stay consistent with the Guidelines, an employer found to be adversely

impacting some protected group must provide validity information described in Section 6 of the

Guidelines. Conservative estimates of costs associated with such validity evidence routinely run well

over $250k for each HR policy or practice in question (Cascio, 1999).

Clearly it is in the best interests of firms covered by Title VII of the 1964 Civil Right Act to

monitor staffing efforts for possible violation of the 4/5ths rule applied to “utilization ratios.” Utilization

ratios compare the relative “use” or employment of one protected subgroup to whatever protected

subgroup has the highest representation. A utilization ratio comparing Countryside’s existing workforce

representation to workforce representation in the 12 new south and southwestern regional labor markets

becomes ker ker

labor marketCountryside

labor market

HispanicsHispanics

All Countryside Bro s All Bro Applicants

NN

N N. This ratio is commonly referred to as a “pool”

ratio, since it compares racial representation in a firm’s internal labor pool to racial representation in some

relevant external labor pool. Countryside HR professionals estimated this ratio to be 58% when

examining racial make-up of the new offices if 70% of the new mortgage broker positions filled via

transfer. Unless the remaining 30% of all new mortgage broker positions created in the 12 new regions

contain disproportionately high numbers of Hispanics, the pool utilization ratio for all new mortgage

brokers is not likely to meet or exceed 80%.


Page 5 - 22

Affirmative Action Planning. If Countryside held

federal contracts worth at least $10,000 annually, it

would be subject to addition requirement imposed by

President Johnson’s Executive Orders 11246 and

11375. Order 11246, Subpart B, Sec. 202(1) from

1965 says “The contractor will not discriminate

against any employee or applicant for employment

because of race, color, religion, sex, or national origin.

The contractor will take affirmative action to ensure

that applicants are employed, and that employees are

treated during employment, without regard to their

race, color, religion, sex or national origin.” The

Office of Federal Contract Compliance Programs

(OFCCP) enforces Executive Orders. The OFCCP

requires contractors to file quarterly utilization reports,

which are periodically audited for compliance. If

utilization ratios are not above 80%, contractors must

develop an “affirmative action plan” outlining actions

or steps the firm plans to take in order to get a

deficient utilization ratio above 4/5. Note, these steps

cannot involve reverse discrimination, i.e., firing a

bunch of white mortgage brokers and hiring a bunch of

new Hispanic mortgage brokers. Since the utilization

ratio indicates Hispanics were underrepresented in the

12 new regional labor markets, Countryside would

need to develop a plan detailing what it intended to do

to change (i.e., increase) the flow of Hispanic

applicants. The plan would include goals (not quotas)

and time tables, which the OFCCP auditors would

monitor for progress on a quarterly basis. The only

sanction imposed on contractors that consistently fail

to comply with these Executive Orders is loss of the

federal contract.

The utilization ratio hired hired

applied applied

Hispanics whites

Hispanics whites

N N

N N captures any differences in rates at which

applicants “flow” into an organization. If

Countryside continues to exhibit ~ 25-30%

annual mortgage broker turnover, the “pool”

utilization ratio will slowly move toward 4/5

if the flow utilization ratio is 80% or higher.

Given the costs and negative publicity

associated with adverse impact charges,

Countryside HR professionals developed real

time information management systems to

monitor key utilization ratios. This is not

difficult to do - I have undergraduates

develop Excel spread sheets to do this in

class! To avoid fines, legal fees, and court

costs, I have developed spreadsheets for

companies under close Justice Department

scrutiny that track key ratios in real time,

generating green, yellow, and red Windows

“tray” icons (like the lower right battery icon

on laptops) to show when ratios are above

(green), hovering close to (yellow), or below

(red) 80%. Updating ratio numerators and denominators for each job every time employees start,

terminate, retire, or quit will alert HR professionals the moment adverse impact becomes a problem.

Countryside’s system for monitoring both pool and flow utilization ratios alerted Ms. Cortez to

the possibility of severe underutilization of Hispanics in each of the 12 new urban areas when doors were


Page 5 - 23

first opened for business. Like any good executive, Ms. Cortez asked her staff for alternative HR

practices that would eliminate underutilization without meaningfully increasing recruiting costs as

quickly as possible. A number of alternatives were discussed, including:

Option 1. Not approving transfers of a disproportionately high number of current Countryside

mortgage brokers who are white while simultaneously approving a disproportionately high

number of transfer requests made by current Countryside mortgage brokers who are Hispanic. Transfer approval rates by race are managed to ensure the utilization ratio meets or exceeds the

4/5ths standard.

Option 2. Recruiting more than 66% of mortgage brokers for the 12 new regions from local labor markets. Corporate strategic goals include opening all new offices for these regions within a 1

year period. Recruiting the majority of mortgage brokers from the local labor market would

delay opening of all offices for an additional 18 months.

Option 3. Recruiting 30% of mortgage brokers for the new offices from the 12 regional labor markets as originally planned. Proactively encourage Hispanic applicants from the 12 regional

labor markets as needed to fill openings created by future turnover, with the expectation that

utilization ratios will initially fail to meet the 80% standard, though they will slowly surpass it as turnover occurs and local applicants are recruited for new positions. If audited by the OFCCP

before then, Countryside will be found to be underutilizing Hispanics – fines and negative

publicity will follow. Option 4. Adopt the position that transfers from existing Countryside offices constitute applicants

from a relevant “internal” labor market and should be counted in “labor market” portions of the

ratioker ker


labor market

HispanicsHispanics


NN

N N. In this instance,

𝑁𝐴𝑙𝑙 𝐵𝑟𝑜𝑘𝑒𝑟 𝐴𝑝𝑝𝑙𝑖𝑐𝑎𝑛𝑡𝑠𝑙𝑎𝑏𝑜𝑟 𝑚𝑎𝑟𝑘𝑒𝑡 becomes the weighted combination Hispanic proportions in both

the 12 regional external labor markets and Countryside internal labor market.

Option 4 above is not really an option unless consideration of Countryside internal labor market make up

affects whether ker ker


labor market

HispanicsHispanics


NN

N Nis greater or less than 4/5. This could only

occur if the number of existing Countryside offices was so large that the number of mortgage broker

applicants for transfer was equal to or larger than the number of mortgage broker applicants available in

the 12 new regions in which office are to be opened (highly unlikely).

What to do, what to do? Hopefully Ms. Cortez and other Countryside HR professionals

reconsider Option 1. Specifically, it is one thing to encourage existing Countryside Hispanic mortgage

brokers to consider transfers (while not providing similar encouragement to current non-Hispanic

brokers). A policy of permitting lower numbers of non-Hispanic transfers, or setting lower non-Hispanic


Page 5 - 24

When is it Disparate Impact or

Treatment? Ultimately, nothing

constitutes disparate treatment,

disparate impact, or a violation of Title

VII of the 1964 Civil Rights Act until a

judge say so. Many attorneys take

exception with “experts” expressing

opinions about what might or might not

constitute violation of Title VII, as

these “experts” typically do not have

formal legal educations (e.g.,

industrial/organizational psychologists,

labor economists, etc.). While this

position may have merit in some

instances, EEO legislation is not the

same as the IRS tax code. Simple

understanding of verbs and nouns in the

English language is usually enough to

understand whether a policy or practice

treats people differently on the basis of

race, sex, creed, color, religion, etc.

When in doubt, I find a good test is to

simply restate the policy or practice

while substituting or changing

protected subgroup labels. For

example, the annual performance

review summary stating “you

performed your responsibilities well for

a man your age” may not immediately

be seen as evidence of disparate

treatment. Substituting in the phrase

“black man” for “man your age” yields

“you performed your responsibilities

well for a black man.” This should

clearly be seen as an example of

disparate treatment, which makes the

original phrasing disparate treatment

too.

quotas, may constitute disparate treatment where current Countryside mortgage brokers are “treated”

differently by the transfer policy according to race.

So, Ms. Cortez and her HR team quickly focused on Options

2 & 3. Option 3 involves opening all planed offices in the 12 new

regions immediately at a 70% staffing level, with all initial mortgage

broker positions filled by transfers from existing Countryside offices.

Given 15% of Countryside’s mortgage brokers were Hispanic and

Department of Labor surveys indicated Hispanics constituted 40% of

the 12 new regional labor markets, expected initial pool utilization

ratio would be ~ 15/40 ≈ 38%, well below the 80% or 4/5ths

standard.5 As Countryside hired new mortgage brokers from the 12

regional labor markets to 1) attain a 100% staffing level and 2) fill

openings due to turnover, the utilization ratio should slowly move

toward 4/5. Once 100% staffing levels were achieved, expected pool

utilization ratio is

.15+.15+.40

3

.40= 58%. If Countryside aggressively

recruits Hispanic applicants from the 12 local labor markets so that

60% of locally hired mortgage brokers were Hispanic, expected pool

utilization ratio will be

.15+.15+.60

3

.40= 75%. Option 3 is not expected to

utilization goals alone.

Option 2 is a little more complicated. Each new Countryside

office will contain 2-3 mortgage brokers, though office overhead and

operational costs require at least two mortgage brokers per office, as

one broker can never generate enough business alone. So, Option 2 involves filling at least one open

5 This assumes the racial proportions of current Countryside mortgage brokers choosing to transfer mirrored the existing 15% Hispanics


Page 5 - 25

broker position per office by transfer. Once a current Countryside mortgage broker accepts a transfer to

one of the 12 new regions, her/his new office cannot open until a local applicant fills at least one other

mortgage broker position. Option 3 permits the opening of virtually all new offices immediately, as two

current Countryside mortgage brokers would transfer into each office. Option 2 involves opening new

Countryside offices in the 12 new regions only as fast as at least one new mortgage broker can be

recruited, selected, and hired from the local labor markets. The pool utilization ratio for offices initially

opening with one transferred mortgage broker and one locally recruited mortgage broker is initially

expected to be

.15+.40

2

.40= 69%, were

.15+.40

2 is the weighted combination of Hispanic proportions expected

among transfers (15%) and new hires (40%). When a third mortgage broker recruited from the 12

regional labor markets is added to each office, the final expected pool utilization ratio is expected to be

.15+.40+.40

3

.40= 79%. However, recruiting and selecting 70% of new mortgage brokers from the local labor

market, training them, and getting them up to “steady state” performance levels is forecast to take 18-30

months. So, Option 2 opens all the offices immediately with a mortgage broker workforce that severely

under represents Hispanics (utilization ratio = .38), though under representation is lessened as the offices

add at least one additional broker from the local labor market (full staffing level utilization ratio = .58). If

efforts to attract qualified Hispanic applicants from the local labor market yield 50% more Hispanic

applicants than expected (i.e., 60% is 50% larger than 40%), the utilization ratio should approach 75%.

Option 3 opens the first office 18 months later, with an initial utilization ratio of .69. Full staffing

jumps the utilization ratio to .79, and I would expect that minimally aggressive recruiting of qualified

Hispanics would yield a utilization ratio above 80%. “Aggressive” recruiting of qualified Hispanic

applicants using Options 2 & 3 would involve advertisements placed in newsletters and annual

publications of the National Hispanic Mortgage Bankers and Brokers Association (NHMBBA), the

Hispanic National Mortgage Association, the National Association of Hispanic Real Estate Professionals,

and The National Association of Real Estate Professionals. Countryside also planned to rent booths to

promote mortgage broker career opportunities at these associations’ national and regional conferences.


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Directed mailings of informational brochures will also be sent to membership mailing lists purchased

from these associations, with special emphasis on student affiliate chapters at business schools located in

the 12 target regions. Finally, Countryside planned on immediately asking Hispanic mortgage brokers

hired from the local labor markets for referrals of friends or acquaintances who might be qualified and

interested in a mortgage broker career path. “Non-aggressive” recruiting would expect to yield Hispanic

applicants from the 12 regional labor markets at or around the 40% participation rate identified by the

Department of Labor. Countryside will know if these “aggressive” recruiting efforts targeting Hispanic

members of the 12 regional labor markets were effective if the proportion of qualified Hispanic applicants

is meaningfully higher than 40% Hispanic participation base rate.

So, the choices between Options 2 & 3 boil down to a trade-off between speed with which new

Countryside offices open and generate new business in the 12 new urban regions versus risk of EEO

litigation. Option 3 maximizes both outcomes, though aggressive recruiting of Hispanic applicants might

mitigate risk of EEO litigation within 18+ months. Option 2 minimizes risk of EEO litigation with an

initial expected utilization ratio of 69%. With normal (i.e., non-aggressive) recruiting, utilization ratio

should be very close to 80% (i.e., 79%) within 18 months, and well over 80% if Hispanic applicants are

aggressively recruited from the local labor markets. Ms. Cortez would like to know if the planned

“aggressive” Hispanic recruiting effort will increase the flow of Hispanic applicants from the regional

labor markets enough to eliminate risk of EEO litigation. How can she find out? Of course! A pilot

study!

Summary

This chapter described a number of ways one might generate and interpret evidence evaluating

the impact of HR recruiting efforts. Of the chapter topics present so far, recruiting presents perhaps the

richest source of business outcome metrics.


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References

Albemarle Paper Co. v. Moody, 422 U.S. 405, 431 (1975)

Cascio, W.F. (1999). Costing human resources: The financial impact of behavior in

organizations (4th edition). Kent Publishing: Boston, MA.

Ford, H. (1922). My life and work. Double Day: Garden City, N.Y.

Griggs v. Duke Power Co., 401 U.S. 424, 433-34 (1971)

Premack, S.L. & Wanous, J.P. 1985. A meta-analysis of realistic job preview experiments.

Journal of Applied Psychology, 70, 706-720.

Johnny Reynolds et al. v. Alabama State Department of Transportation et al. (1998). Civil Action

No. 85-T-665-N.

http://lw.bna.com/lw/19980623/665.htm

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