An evaluation of retraining programs for dislocated workers in the airline industry.

Introduction

From 1981 to 1990 nearly two million workers each year became unemployed because of plant closings, workplace restructurings, or production cutbacks (Strawn, 1993). Although the economy was in excellent condition during most of the 1990s, involuntary job loss was a concern for both management and dislocated workers. Job losses were at record numbers (Uchitelle & Kleinfield, 1996), with research indicating that from 1991 through 1995 approximately 3,000 jobs were eliminated each business day (De Meuse & Bergmann, 1997). In Georgia, layoffs since 1999 included over 4,100 apparel and textile workers (Coleman, 1999), and additional layoffs in the Atlanta area alone of 1,200 people by iXL, 600 by CocaCola, 750 by Solectron, 442 by Amazon.com, and 379 by Webvan ("Pink Slip Parade," 2001).

In 1998 the U. S. Department of Labor, which allocates the majority of funding to dislocated worker programs, received approximately $1.2 billion for training (Weinburg, 1999). Equally important, data indicate that in the future eight of every 10 dislocated workers will not return to jobs in their previous area (Strawn, 1993). Even if many employers are actively seeking employees (Goldberg, 1997), management should take steps to insure that dislocated workers are placed back into jobs with a minimum amount of stress, frustration, and loss of income.

In the early 90s there were several major plant closings in the Atlanta, Georgia, metropolitan area. Included were 2,500 layoffs at the Lockheed plant in Marietta, 1,500 layoffs when the second shift of the General Motors' Doraville plant closed, 3,200 layoffs at the General Motors' Lakewood plant, and most significantly, layoffs of over 10,000 when Eastern Airlines ceased operations in January 1991 (Scott, 1992). Employees affected by these layoffs became dislocated workers and were eligible for retraining programs.

This study analyzed entry data on dislocated airline employees in an effort to develop guidelines that would benefit future enrollees in retraining, the retraining organizations, and employers. The study sought to determine if more emphasis should be placed on the Career Ability Placement Survey (CAPS) test as a determinant of success in retraining programs for dislocated airline workers. CAPS tests cognitive ability to provide an effective measure of abilities for retraining programs. The study reviewed four CAPS test areas administered to dislocated airline workers: verbal reasoning, numerical ability, language usage, and word usage. It also evaluated other characteristics as predictors of the ability to complete a retraining program and to obtain employment. These characteristics were gender, age, race, previous educational level, previous salary, and years in previous occupation.

A second purpose of the study was to determine (1) the degree of relationship between certain parts of the CAPS test and final salary, and (2) the degree of relationship between parts of the CAPS test and completion or non-completion of training.

Dislocated worker programs appear to be achieving their goals, but in some programs an initial data analysis indicated that the number of withdrawals and failing grades received by the enrollees in retraining programs was significantly higher than was anticipated at the beginning of the program. Researchers and administrators believed that employees' ability to complete training and to achieve designated standards presented a definite retention problem at retraining centers (Overman, 1992). Many adults seemed to lack an appropriate foundation for completing retraining programs. It is important, therefore, that research be undertaken examining variables such as age, ethnicity, and cognitive ability and their relationships to success in retraining programs. Some companies are concerned that workers lack the aptitude or motivation to learn new skills.

Gowan and Gatewood (1997) discussed forms of cognitive abilities, and Gowan, Riordan, and Gatewood (1999) tested models of response to involuntary job loss. Gatewood and Feud (1990) gave the history of ability tests and concluded that cognitive abilities, as measured by ability tests, have proved to be a valid selection device. Warr (1987) discussed why few studies use cognitive abilities as a variable in determining performance in retraining programs. He concluded that the lack of studies might be related to the difficulty of collecting data, or, since the data had apparently not been used as a measure of success, there was no rationale for obtaining the data.

The study by Gatewood and Feild (1990) suggested a possible correlation between cognitive ability tests and basic academic ability levels and between cognitive abilities and other variables related to the educational area. Education and cognitive abilities appraisal as variables in the context of unemployment were further discussed in a study by Harris, Heller, and Braddock (1988). General cognitive knowledge was believed to be a predictor of training success by Hunter (1986), who found that organizations using general cognitive ability measures for selection and promotion would more likely hire individuals with higher cognitive abilities.

Method

* Subjects: Subjects for the study were participants enrolled in retraining programs through the Career Center for Dislocated Airline Workers in Jonesboro, Georgia. The subjects were 190 of the 1,664 individuals who became dislocated workers when Eastern Airlines ceased operations on January 18, 1991, and for whom complete data records were available. The subjects had previously participated in retraining programs but had not attended any programs for up to 90 days. Those subjects who found employment within 90 days of last attending a retraining program, regardless of whether or not they had completed the retraining program, are designated as positive terminations in this study. The 90-day figure was based on government regulations for this retraining program. Those who did not find employment within 90 days after last attending training are designated as negative terminations.

Ninety-one (48%) of the subjects were male and 99 (52%) were female. One hundred sixteen (61%) were white and 74 (39%) were nonwhite. The average age of the subject was 41 years with an average of 12.5 years of employment with the airline. The subjects had an average of 13.76 years of education with a range of 10 to 17 years of schooling. Their average hourly salary earned as employees of Eastern Airlines was $13.78.

Instruments: Data was obtained on four cognitive ability areas of the Career Ability Placement Survey (CAPS) (Knapp et al, 1987).

These areas are:

1. Verbal reasoning (VR) -- measures how well a person can reason with words and the person's aptitude for understanding and using concepts expressed in words.

2. Numerical ability (NA) -- measures aptitude for reasoning with and using numbers and for working with quantitative materials and ideas.

3. Language usage (LU) -- measures aptitude for recognizing and using grammar, punctuation, and capitalization.

4. Word knowledge (WK) -- measures how well a person understands the meaning and precise use of words.

Data on the other individual characteristics of gender, race, previous educational level, previous salary, years in previous occupation, and final salary (after training) was taken from the files of participants in the retraining programs. Individual names, social security numbers, or any other identifying information were not retained.

* Data Analysis: Descriptive statistics and correlations were obtained for all variables included in the study. Comparisons were also made by groupings of positive and negative terminations and by completion and non-completion of retraining programs. Descriptive statistics for the different groups are shown in

Tables 1 and 2. A multivariate analysis of variance (MANOVA) (Pedhazur, 1982) was used to determine whether there was a significant difference between groups for the variables of gender, race, previous educational level, previous salary, years in previous occupation, final salary (after training), and the cognitive abilities tests. Multiple regression analysis (Chetterjee, 1991) was used to examine the efficacy of predicting final salary (after training) from the available variables.

Results

Descriptive statistics for the groups are shown in Tables 1 and 2. Table 1 gives the statistics on positive and negative terminations, as well as for the total group. The following differences can be seen.

1. The mean age for positive terminations was 40.4 years, whereas the mean age for negative terminations was 45.5 years. Age discrimination, or the unwillingness to relocate or accept lower paying positions probably affected these statistics.

2. The mean "years in previous occupation" was 14.3 years for negative terminations and 12.0 years for positive terminations.

1. The mean age for individuals who found employment after completing training was 42.5 years whereas the mean age for those who found employment but did not complete training was 39.41 years. This would indicate that older individuals were more likely to complete training, but, as shown in Table 1, they were less likely to find employment.

An examination of Table 2 also shows the following differences between those who did and did not complete the retraining program.

2. The mean previous salary (PVSAL) was higher for individuals who did not complete training, indicating that dislocated workers with higher predislocation salaries were less likely to complete training.

3. The mean stanine scores on both the numerical (NA) and the word knowledge (WK) sections of the CAPS test were higher for individuals who found employment and completed training than were the mean stanine scores in areas for individuals who found employment but did not complete training.

4. The mean final salary, after entering a retraining program, was $9.02 per hour for individuals who completed training, $0.43 higher than the mean final salary of $8.59 for individuals who did not complete training.

5. The mean final salaries after training and the mean salaries employees earned prior to dislocation were quite different. The subjects who completed training earned $9.02 per hour after retraining compared with $13.57 prior to being dislocated. Retraining subjects who found employment, but who had not completed their retraining programs, had a mean final salary of $8.59 compared with a previous mean salary of $14.12.

The interrelationships among the variables were studied through the use of correlations, shown in Table 3. The cognitive ability tests are highly interrelated. The numerical ability and word knowledge scales of the CAPS show a high degree of correlation with a number of other variables. The final salary after retraining shows significant correlation with race, previous salary, and numerical ability. Results of the MANOVA indicated that there was no significant difference (Wilks' lambda = 0.91, [F.sub.11.178] = 1.70, p = .08) between the positive and negative terminations with a combination of gender, age, race, previous education, previous salary, years in previous job, completion/noncompletion of training, and the CAPS used as predictor variables.

There was, however, a significant difference between those who completed or did not complete the retraining program (Wilks' lambda = .90, [F.sub.10.179] = 1.91, p = .047) using the same variables.

Implications

Throughout the study there was a great deal of discussion about the variables. In actuality, these variables represented actual circumstances and real challenges faced by anyone who hopes to positively affect the retraining of dislocated airline workers. Future models must consider all issues. Quotas, learning abilities, genderbased roles, downsizing, multi-culturalism and standard testing inequities are just some of the areas that must be struggled with on a daily basis. Future retraining models should also consider the interpretation of the data in this study in an effort to make employment-related final decisions more beneficial. The concerns presented by the study's implications and conclusions are seen as a challenge to the administration of retraining programs as they are today. Age was an important predictor variable in the study. The requirements of older airline workers seeking to salvage careers are far different from those of individuals, usually younger adults, striving to develop them. Retrainin g models must consider that the curriculum and content delivery best suited for the enhancement of one group may, in all likelihood, fail to be the most beneficial for the other. Since basic skills are essential to the learning process, they should continue to be included in any retraining effort. However, the definition of basic skills should be expanded to include those needed (1) by dislocated airline workers, and (2) for future employment for all individuals. Transferable skills such as communication, team building, problem-solving, and people skills should be emphasized. Some airline workers began their careers before the exponential growth of technology in the workplace. For those employees, functional skills such as those involving computer literacy must be stressed.

Steps must be taken to facilitate equal access to technological development by older displaced workers, females, and heretofore circumstantially excluded minority groups. In addition, future retraining models should consider that the actual operation of training centers might need to be altered to better correspond with the needs of the dislocated worker. Location, hours of operation, offerings, and procedures should all be developed with the convenience and well-being of the participant in mind.

One modification for future retraining centers relates directly to the results of this report, which showed that scores on CAPS tests were good predictors of various desirable outcomes such as higher subsequent earnings and program retention rates. The study indicated that some individuals, who possibly had lower educational skills, were unable to obtain higher educational levels because of lower-level basic skills. Since basic skills were evaluated through the use of the CAPS, the acquisition of minimum skill levels, especially for nontraditional students, should serve as a prerequisite to college-level academic training.

When retraining was initiated for the dislocated airline workers, an informal tracking system was devised that allowed participants in longer programs to renew their quarterly vouchers without returning to the center. This needs to be changed for future programs. The staff of the retraining centers must have accurate information about who is still attempting to reach program goals. Participants who refuse to provide information regarding employment, wages, or attendance to a retraining center staff should not be allowed to benefit from the services provided. A formal, accurate tracking system would prevent instances where participants register for school and then withdraw without notifying the center, thus wasting funds and denying assistance to other eligible individuals who would be likely to comply with reporting requirements.

Management must present the free retaining services in such a way that the dislocated worker feels it is not only a benefit that has been earned, but also one that carries a heavy responsibility. Whenever possible, short individual sessions should be held with participants. Large group orientations that stress procedural elements plant the thought that a program's services are an entitlement, requiring no commitment from the participant to strive for excellence or complete the training.

One-stop career centers, such as the Career Center for Dislocated Airline Workers, should strive for comprehensive services. The number of individuals who visited the center with noncareer concerns escalated during the duration of the program. Future services might include more bilingual staff, medical and counseling staff (not focused on career services), and other community service providers. Childcare is also a concern that should be addressed if the services are to be fully effective. While no security problems ever arose at the Career Center for Dislocated Airline Workers, the current climate of retribution due to dislocation or other unemployment problems might dictate including some form of security as a matter of course.

The center's location was selected due to its proximity to the area where many of the dislocated workers lived and was considered convenient for that reason. In addition, the state representative responsible for obtaining funding for the center lived in the district. However, both locations in Jonesboro were inaccessible by public transportation. The decision to select sites that could not be visited without personal transportation probably had a measurable impact on the number of eligible employees unable to use the center. Since the ability to obtain and maintain independent transportation is often an extension of a person's general financial status, it is likely that individuals unable to enroll in retraining due to a lack of transportation were also those in serious need of retraining assistance. Future retraining centers should consider locations accessible by public transportation. An additional option might be to offer online courses or other means of distance education for those prevented from visiti ng the center for whatever reason.

The role of the career counselor in retraining programs should also be considered. Some retraining participants reported negative experiences in previous counseling sessions. While little can be done about past counseling services, managers should realize how important it is that career counseling be perceived as worthwhile. One means of maintaining the credibility of career counseling would be by ensuring that vocational advisement take market realities into account. Many dislocated airline workers did not know, or want to accept, the reality that they would probably have to relocate to remain in similar occupations. Retraining administrators should be knowledgeable and concerned with the administration and interpretation of assessment instruments such as the CAPS. Credence should be given to both test results and the participants' retraining desires. Effective counseling should work toward a fine balance by steering clients to opportunities conducive to their personal and professional growth, as indicated by assessments and a knowledge of other individual characteristics, while at the same time meeting the retraining objectives of the participants.

Many participants were able to take advantage of some aspect of the retraining process. However, management should always strive for improvement in the service provider function. A rapport must be built with the participants so they feel in concord with those providing training services. Initial meetings with participants should stress cooperation with the service provider staff, and managers must address the need for the changes in procedures and processes and how changes might affect program participants and staff. Generally, it is difficult to change procedures that are arbitrary. Operational guidelines should be in place before retraining centers open and should ensure that one participant is not asked to do something that another is not asked to do. Once a center opens, the staff structure and work responsibilities should be altered to be responsible to actual challenges and concerns. Factors such as gender, age, previous salary, and other characteristics must be considered as part of job placement efforts.

If possible, problems related to individual characteristics should be forecast in the design of training programs and shared with the staff in the initial stages of any retraining programs. This precaution sets the stage for the type of flexibility needed when changes must be made. Changes should also be made infrequently so that credibility is not threatened and should be implemented in a manner conveying that decisions are not arbitrary. Retraining models must be more flexible than those in the past.

Pragmatic learning applications should be used in the future rather than the rote or memorized methods favored in the past. Wherever possible, training should encompass multiple learning styles such as visual, auditory, experiential, kinesthetic, and spiral. Schools and training organizations should be motivated to experiment with ways to provide training through technology. Distance, independent, selfpaced, and interactive learning modules should be used to prevent any problems with scheduling, finances, and transportation from impeding the retraining process.

When concerns related to the variables of age, race, gender, economic and educational status, and employment security are injected into the model's equation, it becomes apparent that any real solution must be bold or original. For example, one innovative direction currently being tried is the single gender school. A natural extension of that concept to retraining programs would be to isolate and develop materials aimed at a particular generation, such as the older dislocated worker. Designated educational settings would promote greater development for the targeted group because the other group's absence should prevent it (the other group) from serving as a basis for bias, comparison, or inappropriate competition.

Conclusion

The closure of Eastern Airlines was monumental. The information gained by analyzing the experiences of individuals who tried to minimize damage to the community may, in fact, be the most worthy derivative of the entire episode, because worker dislocation has become common throughout the United States. As was the case with the Career Center for Dislocated Airline Workers, management will increasingly be called upon to anticipate and participate in the creation of programs capable of successfully dealing with dislocation issues. It is for that reason that the results of the data collected in conjunction with the studies of retraining programs should continually be evaluated, with an eye toward reaching conclusions significant to the realization of successful retraining centers.

As long as companies continue to downsize, retraining centers will be essential. While the Career Center for Dislocated Airline Workers is no longer in operation, it served as a rich resource for the development of future retraining programs. More and more companies are likely to need to provide services in light of the expectation of large layoffs.

Hope for retraining efforts, inputs, and endorsements must come from the community at large, not just from those currently affected by dislocation. Retraining administrators should act in partnership with other involved entities, such as government on all levels, private industry, and the dislocated workers. In addition, all levels of organizations, including lower levels, must be empowered to ensure that training agendas correspond to the actual needs of the communities they are developed to serve.

The assimilation, successful reeducation, and ultimate reemployment of the dislocated workers represent a serious challenge for the business community. Analysis is integral to developing strategies that can aid in facilitating the retraining process. Arguably, the success of dislocated workers program retraining goals will have a wide-ranging impact on the ability or inability of the traditional system to meet the needs of dislocated workers. If educational or retraining programs that meet or exceed standards are to be designed, continued examinations of the impact of the variables must be supported.

Establishing a high priority for the review of issues and variables related to the successful retraining of the dislocated airline worker is a natural extension of the desire to improve retraining programs. The realization that establishing the need for analysis is not in and of itself sufficient dictates the necessity of doing the research, and mandates utilizing current information objectively in an attempt to resolve issues related to the dislocated airline worker.

Those requiring educational assistance will usually include individuals with unpredictable combinations of variables, further compounded by possible influences of varied motivations and extenuating internal and external conditions. Therefore, perfecting, as much as possible, the process of obtaining and interpreting data derived from this study is crucial.

The make-up of retraining group demographics presents a challenge. It is hoped that information gained from this study might be used as a model for future retraining programs. In addition, by using these implications and results, retraining organizations should be able to improve the quality and success of their programs.

The goal of the study was to use the information gained from the research to determine the effect cognitive ability tests and other variables can have when used as a measure of success in retraining programs. The results indicated that it might not be possible to predict very well whether or not dislocated airline workers would complete a retraining program or find subsequent employment. There were, however, some lessons that employers should remember when downsizing. Older people are less likely to find jobs if they are laid off, and people who have been at their jobs for longer periods of time have a hard time finding employment. Older dislocated workers, however, are much more likely to complete retraining programs. In addition, the relationship of the numerical ability scale of the CAPS with final salary indicates the possible usefulness of cognitive ability in the prediction of success in retraining of the airline dislocated workers.

Although this study involved dislocated airline workers, airline employees typically have skills that would benefit other industries. For instance, many ramp workers have college degrees in various fields and work on the ramp in an "entrance position" to gain the experience and knowledge to advance to higher positions related to their degrees. The majority of airline employees have management, accounting, clerical, safety, security, information technology, and various engineering and technical skills they could use elsewhere; i.e., draftsmen, architects, industrial and mechanical engineers.

The implications of the relationships found among the variables will be studied further in the future. The guidelines might also serve as a motivational tool to develop new and more effective retraining methods and to acknowledge the need for more counseling and support for students enrolled in retraining programs, especially during early transitional periods.

Table 1

Comparisons of Termination Data

   Variable   N    Mean  Std Dev  Minimum  Maximum

     SEX--P  156   1.53   0.50       1        2
        --N  34    1.47   0.50       1        2
     AGE--P  156  40.37   8.64      19       60
        --N  34   45.47   8.52      24       64
    RACE--P  156   1.40   0.49       1        2
        --N  34    1.32   0.47       1        2
   PRVED--P  156  13.67   1.55      10       17
        --N  34   14.17   1.26      12       16
   PVSAL--P  156  12.98   7.15       4       65
        --N  34   17.48  15.35       5       78
     YRS--P  156  12.04   9.39       1       34
        --N  34   14.32   9.96       2       32
COMPTRNG--P  156   0.61   0.48       0        1
        --N  34    0.55   0.50       0        1
      VR--P  156   3.60   1.83       1        9
        --N  34    3.52   1.95       1        9
      NA--P  156   4.01   1.94       1        9
        --N  34    4.26   1.69       1        8
      LU--P  156   4.62   2.17       1        9
        --N  34    4.58   2.21       1        9
      WK--P  156   5.82   2.36       1        9
        --N  34    6.14   2.67       1        9

P = Positive terminations;

N = Negative terminations;

2 = Female (SEX), nonwhite (RACE)
Table 2

Comparisons of Completion and Noncompletion of Training

Variable   N    Mean  Std Dev  Minimum  Maximum

  SEX--C  115   1.52     0.50     1        2
     --N  75    1.52     0.50     1        2
  AGE--C  115  42.50     8.83    20       64
     --N  75   39.41     8.15    19       55
 RACE--C  115   1.39     0.49     1        2
     --N  75    1.39     0.49     1        2
PRVED--C  115  13.83     1.58    10       17
     --N  75   13.65     1.43    11       16
PVSAL--C  115  13.57     8.14     5       65
     --N  75   14.12    10.86     5       78
  YRS--C  115  12.17     9.57     1       34
     --N  75   12.88     9.48     1       34
   VR--C  115   3.53     1.82     1        9
     --N  75    3.68     1.90     1        9
   NA--C  115   4.19     1.93     1        9
     --N  75    3.85     1.86     1        8
   LU--C  115   4.69     4.69     1        9
     --N  75    4.52     4.52     1        9
   WK--C  115   6.07     6.07     1        9
     --N  75    5.58     5.58     1        9
 FSAL--C  96    9.02     4.28   4.25     31.25
     --N  60    8.59     3.02   4.30     16.60

C = Completed training;

N = Did not complete training;

2 = Female (SEX), nonwhite (RACE)
Table 3

Correlations Among All Variables

            AGE    RACE    PRV    PV     YRS   COMP    VR     NA     LU
                            ED    SAL          TRNG

   GENDER  -0.24   0.10  -0.09  -0.35  -0.04   0.00  -0.10  -0.20  -0.11
      AGE         -0.16   0.12   0.33   0.60   0.17  -0.06   0.16   0.14
     RACE                 0.00  -0.31  -0.20   0.00  -0.35  -0.46  -0.37
    PRVED                        0.24   0.05   0.06   0.14   0.31   0.27
    PVSAL                               0.33  -0.03   0.14   0.31   0.11
      YRS                                     -0.04   0.03   0.18   0.18
COMP TRNG                                            -0.04   0.09   0.04
       VR                                                    0.50   0.44
       NA                                                           0.55
       LU
       WK

             WK    FSAL


   GENDER  -0.11  -0.15
      AGE   0.27   0.00
     RACE  -0.40  -0.20
    PRVED   0.22   0.15
    PVSAL   0.35   0.23
      YRS   0.26  -0.06
COMP TRNG   0.10   0.05
       VR   0.49   0.01
       NA   0.56   0.24
       LU   0.68   0.04
       WK          0.12

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Dr. Deis teaches performance/quality management and also has extensive experience in government and industry; Dr. Scott is Research Coordinator for the Southeastern Center for the Enhancement of Learning, which provides training in cognitive enrichment.