| SELECTING TOP PERFORMERS—BE CAREFUL WHAT YOU
WISH FOR |
| When using job match assessments to improve the
selection and promotion process, success may depend
largely upon how top performers are identified. Since
the process is designed to help a business select
candidates who share the job-related characteristics of
top performers, misidentification of those
characteristics by misidentifying members of that group
can lead to poor results and selection of candidates who
do not perform well. Ask a manager who his or her top
performers are and you will usually get a quick answer.
Ask for the basis of that selection, however, and you
may be surprised how fuzzy or imprecise the criteria
are. It is not unusual to discover that managers have no
measurable, repeatable criteria for identifying this
most important group of employees!
In some jobs, measurable and objective criteria are
relatively easy to identify. A salesperson, for example,
may be measured on sales production (units, dollars,
profit, etc.). Appropriate measures for sales
performance may also include calls made per unit of
time, customer service measures or revenue growth.
Performance in other jobs may not be as easy to measure.
- What are the metrics for a top performing social
worker?
- How do we measure performance of a researcher in a
pharmaceutical company where 20 years of research by
50 people may go into the development of a single new
drug?
Often, faced with the task of identifying performance
measures in a field with soft outputs or very long-term
outputs, managers fall back on personal likes and
dislikes, personality conflicts/lack of conflicts or
other measures with little relationship to their
company’s goals, profitability or long-term success.
In some settings, recognition of these challenges
result in attempts to make evaluation more objective. A
favorite tactic in these settings is supervisory rating
scales, where supervisors rate incumbents on one or more
dimensions thought critical to performance on a
numerical scale that may run from three to 10 points.
The outcome of such ratings may look objective, as we
tend to associate decimal numbers with objectivity: “She
scored a 2.7 of a possible three!” Unfortunately,
analysis of range compression (where everyone scores in
a one-point range of a possible three) and interrater
reliability raises serious questions about the validity
and utility of these procedures.
If the procedures are flawed, the outcomes will be
equally flawed, with serious consequences for the
business and the employees affected.
What can a manager do to avoid these pitfalls and
select top performers on the basis of objective,
repeatable and predictive criteria? Fortunately, since
the issues in selecting top performers for job fit
assessment are essentially the same as those surrounding
the entire topic of performance appraisal, the
literature is rich with sources offering guidance.

Interested readers might start with these
titles:
- The Complete Idiot’s Guide to Performance
Appraisals, Adele Margrave and Robert Gorden, 2001.
- Performance Management, Robert Bacal, 1998.
- The Performance Management Activity Pack, Terry
Gillen, 2001
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| CREDIT UNION CUTS TURNOVER WITH ASSESSMENT
PROGRAM |
| In last month’s edition of Employer’s Advantage, the
case study demonstrated how a bank used a strategic
assessment program to cut turnover, improve customer
service and bring more profit to the bottom line.
As the current data set demonstrates, similar savings
and improved performance can apply to credit unions as
well. Volume two, Issue two, featured a mid-sized credit
union whose preliminary data illustrated that their
strategic assessment program was achieving desired
results. After a full year, the early indications are
confirmed.
The
credit union adopted a funnel model of selection. At the
wide end of the funnel, applicants are screened for
suitability on the basis of their application documents.
Those chosen to enter the interview process first
complete an honesty-integrity assessment, the Step One
Survey II™ (SOS2). With a strong applicant pool, the
credit union applies a relatively high criterion to the
scores on that instrument. The criterion, combined with
an initial interview (using the assessment’s interview
guide) selects approximately 40 percent of the pool to
continue the process. At this point, candidates
remaining in the pool complete a job match assessment
specific to customer service jobs, the Customer Service
Perspective™ (CSP). If their match to the success
pattern for the job under consideration is favorable,
they also complete a job match assessment specific to
sales, the Profile Sales Indicator™ (PSI). A final
interview is conducted considering the complete file of
information available (assessments, employment history,
reference checks and interview results) and a job offer
decision is reached.
After a full year of this effort, the evidence is
clear: the program works as designed. Results of the
turnover reduction are illustrated in the graph below.
More importantly to the credit union and its
owner-members, return on their investment is
exceptional, and will allow them to continue pursuit of
improved customer service.
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| The focus of this case study is a gaming operation
owned and operated by a Native American Tribe. The
operation includes a large casino with restaurant and
entertainment venues, a substantial hotel and an
adjacent RV park and has expectations of future growth.
Located on a major Interstate Highway, the development
is in a rural environment with a very limited employment
pool. For years, the area’s economy rested on the
timber, mill, and mining industries; the collapse of
those industries resulted in outmigration and further
shrinking of the population of available workers. The
challenge for the HR team includes recruiting an
adequate supply of workers and finding workers with the
qualities required to succeed in the 24-hour,
seven-day-week environment of gaming. In addition,
integrity of workers is essential in a cash-rich
environment.
The baseline group for this case study consisted of
the last 100 employees hired prior to the beginning of
the assessment program. In this group, failure rates
were compiled for 30, 60, and 90-day cumulative failure
rates, as well as total failures over the study period.
Failure was defined as leaving employment with the
operation for any reason.
Beginning with the study period, every applicant
selected as eligible for an interview completed the Step
One Survey II™, an honesty-integrity assessment which
measures attitudes on four scales:
Integrity, Substance Abuse, Reliability, and Work
Ethic. The SOS2 also includes a measure of
distortion—exaggeration in the positive direction.
Hiring procedures were modified and a criterion level
was adopted, based on research using the SOS2 assessment
in similar employment settings. A distortion score of
one or two, or any two scale scores of three or less,
were considered a negative factor in the total
employment decision, much as a negative reference or
unexplained gap in work history would be. Managers who
chose to consider a candidate who scored below criterion
level could do so and could hire, but were required to
provide reasons for their decision. The interview guide
produced by the assessment was used in the interview to
investigate any negative indications in the results.
Over the six-month study period, 302 assessments were
administered and 155 hires were completed. The
relatively high 50 percent ratio reflects the shallow
nature of the applicant pool in this setting.
Presumably, managers were forced to balance the
desirability of individual candidates with the
necessities of the operation and the reality of the
pool.
Further indication of the dilemma managers faced is
provided by the nature of the failures—less than 10
percent of the people who left were under involuntary
terms.
Results of the study are summarized in the table
below. Surprisingly, 30-day failure rates nearly doubled
with use of the assessments, but overall hire failures
dropped in every other category and were reduced by 33
percent overall.
Based on a cost-per-hire of $3,000 (frequently used
in the hospitality industry), this represents an 855
percent return on investment.
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"Success is
not so much what we have as it is what we are."
~ Jim Rohn
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