In any event, frustrations over utilization of unscheduled intermittent leaves have reached a point where FMLA has been interpreted as the “Friday and Monday Leave Act” (Shopes, 2008).
SUMMARY
Transit providers maintain a reserve pool of operators, known as extraboards, to fill work
assignments when regular-duty operators are absent. The extraboard planning process (or
“sizing the extraboard”) must anticipate the amount of open work that will need to be
filled. Sizing the extraboard is thus an exercise in predicting absences among regularduty
operators. Important consequences follow when the size of the extraboard does not
match the amount of work that needs to be filled. Missed pull-outs occur when the open
work exceeds the available extraboard. Alternatively, when the available extraboard
exceeds the amount of open work, surplus operators must be paid for services that
customers never see. In either case, a cost is imposed, borne either by customers or the
service provider.
Short-duration absences, extending from one to three days, account for most of the dayto-
day variation in the amount of open work that must be filled by extraboard operators.
Both the general incidence and the variability of short-duration operator absences have
increased since the implementation of the Family and Medical Leave Act (FMLA) of
1993. The U.S. Department of Labor has identified the transit industry as being among
the most affected by FMLA regulations on unscheduled intermittent leaves associated
with serious medical conditions. FMLA regulations currently allow workers to notify
their employer of such leaves up to two days after their occurrence.
Given the increasing frequency and daily volatility of short-duration absences, there is a
need to gain a better understanding of their systematic occurrence in order to support
extraboard planning efforts. Apart from facilitating the planning process, improving our
understanding of factors that contribute to short-duration absences may also help in
identifying changes in policies or practices that would reduce their incidence. Beyond
our direct interest in extraboard planning, research indicates that short-term absences
represent an early indicator of more serious subsequent conditions, such as medical
disabilities, and can also lead to premature resignations.
This report examines patterns of short-duration absences at TriMet, the transit provider
for the Portland, OR, metropolitan area. It is distinguished from previous absence studies
in the transit industry by its use of operator-specific information recovered from ITS
technologies that have become widely deployed in the transit industry. The analysis
integrates ITS data with information from TriMet’s human resource, scheduling, incident,
and customer relations databases.
A statistical model is estimated, relating daily attendance or absence to operators’
personal characteristics, employment status, characteristics of assigned work, indicators
associated with the delivery of service, and customer comments related to operators and
service delivery. The sample analyzed covers 1,362 bus and 175 light-rail regular-duty
operators and their daily work in 2006 and 2007.
Findings from the statistical analysis show the influence of a variety of factors
contributing to absence patterns among operators. Regarding personal characteristics,
absence likelihoods are highest among Caucasian operators and decline progressively for
African-Americans, Asians, and Hispanics. Absence likelihoods are estimated to be
higher for women than for men. Regarding employment status, full-time operators are
estimated to have a higher absence likelihood than part-time and probationary operators.
Absence likelihoods are estimated to increase with seniority, but this is more than offset
by estimated declines with respect to operator age.
Among the assigned work characteristics, operators on regular-relief and straight-run
assignments are estimated to have the lowest absence likelihood, while the absence
likelihoods of those with split shifts (both full- and part-time) are the highest. Assigned
runs that conclude before 5 p.m. have lower estimated absence likelihoods than runs that
conclude in the evening or nighttime hours. Estimated absence likelihoods vary by day
of the week, with Thursdays, Fridays, and Saturdays being the highest. Absence
likelihoods also are estimated to jump on the day before an operator’s regular day off.
Seasonality is apparent, with absence likelihoods estimated to reach a peak in December,
January, and February, and a trough in the April-to-September period.
Among the service delivery variables, on-time performance is found to be an important
absence indicator. Operators who are consistently late in departures from time points
compared to their peers are estimated to have a higher absence likelihood. Other factors
contributing positively to absence likelihoods are speeding and higher volumes of
passenger movements and lift operations. The recent occurrence of selected events was
also found to have positive effects on absence likelihoods. Such events included security
response requests, having to take evasive action, vehicle malfunctions, and lost service.
In the area of customer relations, a pattern of recent complaints related to the safe
operation of a vehicle, the timeliness or availability of service, or customers’ treatment by
the operator each were estimated to have a positive effect on absence likelihoods. A
recent incident involving a question of an operator’s fitness for duty, whether initiated
from a customer contact or other source, also was estimated to positively affect the
estimated absence likelihood.
The statistical model provides a basis for estimating short-duration absences in support of
the extraboard planning process. Findings from the analysis also indicate the possible
attendance benefits that would follow from several policy changes. First, allowing
operators to switch from full-time to part-time status without losing their seniority rights
would be beneficial to several operator groups. These groups include senior operators,
who might be induced to return to service on a part-time basis after retirement, and
women operators, who may find the option of part-time service to be a better fit in
balancing their work and non-work responsibilities.
READ FULL REPORT HERE!
1 comment:
Interesting but not surprising correlations. The data was gathered in 2006-7 which is prior to Depression 2.0. So, the factors affecting absence occurred in good economic times.
Anyone who's driven for Trimet could group the absence factors into two groups. The smaller group would be factors where the reader might be surprised. The much larger group of factors are where almost anyone would say, "Yeah, that work condition makes it harder to drag one's butt down to the garage some days."
"Mental health days" are more common occurances for certain obvious working conditions. (Duh!)
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