2003 IMTA Proceedings - International Military Testing Association

vacancies. In fact, the problem of unfilled vacancies only occurs within the first six
conditions. That is when only a few subsets are processed simultaneously.
Another option we took was not to transfer the applicants that were not assigned to a job
in one classification to the next one. That decision might be a bit more controversial.
Transferring all non-assigned applicants to the next classification increases the number
of degrees of freedom for that classification. In theory, this should result in a better
outcome. The effect of added degrees of freedom may however be tempered by the fact
that the added applicants are expected to be of lesser quality. This is so since the better
applicants were assigned to a job in the previous classification. For our research this
would probably mean that the found differences in recruit quality between the conditions
would be smaller if we had transferred the non-assigned applicants. The main reason
why we decided not to transfer them is that by transferring them, we also increase the
time between their assessment and the moment they learn about the result of their
application. In other words, we would falsify the research design by decreasing the
differences between the different conditions!
An important option relates to the used classification system. As mentioned earlier, the
classification system we used - the Belgian ‘Psychometric Model’ - capitalizes on the
number of degrees of freedom available in the S&C setting to produce a high quality
classification. It is quite obvious that less powerful classification methods will yield less
marked results. The right question here is why S&C managers would prefer to stick to
less powerful methods?
In our setting, we used subsets of equal length. In the first condition each classification
was done for 56 persons at a time, in the second one 112 persons were processed
simultaneously etc. It is however quite unlikely that in practice each selection day or
period would produce exactly the same amount of persons eligible for at least one trade.
It is not clear what the influence of unequal length of subsets would be but it seems
likely that conditions processing larger numbers are less subject to non-representative
variance.
The present research effort only looks at one side of the problem: the influence of waiting
time on recruit quality. There is of course another one: the influence of waiting time on
applicant behavior. Daily practice indicates that when applicants need to wait after their
assessment to know the outcome of their application, some of them loose their interest or
continue their search for a job elsewhere. This is bad news for the organization. It is
therefore important to study the interaction between both sides: the increased recruit
quality obtained when postponing batch classification and the loss of applicants when
doing so. As was mentioned earlier, the complexity of most S&C systems makes it quite
impossible to give general advice. However, given the importance of recruit quality for
the Military, this should be studied! Another aspect that needs to be looked closer at is
related to the fact that smart batch classification systems are able to respect the
applicants’ preferences better when processing larger groups. This means that by waiting
some time longer, the applicants that are assigned to jobs are more likely to get a trade
they like 28 . This might have a positive influence on early turnover and other relevant
aspects of training.
Further research should also have a closer look at the left end of the graphs we presented.
In the first condition of our research design, we classified subsets one at a time. Each
subset represented 56 persons. Given the quasi-logarithmic shape of the curve it would be
28 On the obvious condition that the classification system includes applicant preferences.
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45 th Annual Conference of the International Military Testing Association
Pensacola, Florida, 3-6 November 2003