One class of predictors that has been shown to yield positive relationships with job performance and less disparate impact than General Mental Ability Tests is Biodata. The concept underlying Biodata is appealing. Few doubt that there is consistency in the manner in which people behave. If a person has a history of approaching significant events in his or her life in a positive and adaptive manner, such behavior should carry over to the job currently being sought. Success in school, including extracurricular activities, success in community activities, and success in previous jobs should predict success in future jobs. Further, such prediction should be enhanced if, by a careful job analysis, one discovers the particular types of behaviors that maximize success on the job being sought. For example, if teamwork is important for success on this job, inquire about life experiences involving teamwork.
Biodata scales typically consist of multiple-choice or true-false items. The content of Biodata items may include:
ü Life history
“Did you ever hold an elective office in a community, social, or religious organization?”
ü Work history
“How many days were you absent from work in the past year?”
ü Self-assessment
“Compared to your co-workers, do you accomplish more work in a typical work day? About the same amount of work? Less work?”
ü Work environment
“Which of the following do you prefer: To work alone? To work as part of a small group? To work as part of a large group?”
Biodata works, but not as well as tests of GMA or Work Sample Simulations. That is, Biodata scales predict training and job performance for a variety of jobs, including clerical, sales, management, and scientific/engineering. In addition, Biodata scales can be developed which exhibit little or no disparate impact. So far so good.
If Biodata predicts job performance and exhibits minimal disparate impact, why is there any controversy? Why not just use Biodata scales to select for most or all of your jobs? There are several reasons.
1. Validity coefficients tend to be 10-20 points lower than GMA tests and Work Sample Simulations. Validity coefficients are a direct reflection of the utility of a test. Tests exhibiting higher validity coefficients will result in a more productive work force. This means that for most jobs Biodata will not be the best predictor of job performance.
2. The content of some Biodata items, particularly life history items, has been the subject of criticism. Early Biodata scales often included items about your participation in extracurricular activities in school, or leadership positions you may have held in community, social, or religious organizations. However, not everybody has an equal opportunity for such activities. If you needed to work while in school, you could hardly be expected to have time for extracurricular activities.
3. Some types of Biodata items, such as work history, self-assessment, and work environment items, are often transparent. That is, the favored answer seems obvious. As a result, such Biodata items may be subject to faking.
4. Applicant reactions to Biodata scales have been mixed. Some have expressed concerns about invasion of privacy. That is, "What right does an employer have to ask us about our personal lives?" Also, the apparent relevance of Biodata items to the job they are seeking ("face validity") is not often obvious to applicants.
5. There are questions concerning what Biodata scales measure. Is it learned work habits? An indirect measurement of GMA? Or do Biodata scales primarily measure personality traits such as conscientiousness?
To summarize, Biodata scales work well, but not as well as GMA or Work Sample Simulation tests. Disparate impact is minimal which is a strong plus. However some Biodata items may seem inappropriate to applicants, while others may be subject to faking.