In the past decade, most global organizations, as well as many government agencies and small business, have been forced to shrink the size of their workforce or restructure their skill composition. Downsizing has become a relevant means of meeting the demands of a dynamic environment.
What are manager’s downsizing options? Obviously, people can be fired, but other choices may be more beneficial to the organization. Exhibit below summarizes a manager’s major downsizing options. Keep in mind that, regardless of the method chosen, employees may suffer.
Exhibit Downsizing Options
1) Firing: Permanent involuntary termination.
2) Layoffs: Temporary involuntary termination may last only a few days or extend to years.
3) Attrition: Not filling openings created by voluntary resignations or normal retirements.
4) Transfers: Moving employees either laterally or downward, usually does not reduce costs but can reduce intra-organizational supply demand imbalances.
5) Reduced workweeks: Having employees work fewer hours per week, share jobs, or perform their jobs on a part time basis.
6) Early retirements: Providing incentives to older and more senior employees for retiring before their normal retirement date.
7) Job sharing: Having employees typically two part timers share one full time position.
What is the basic method of selecting job candidates?
Selection process: The process of screening job applicants to ensure that the most appropriate candidates are hired.
Once the recruiting effort has developed a pool of candidates the next step in the employment process is to determine who is best qualified or the job. In essence, then the selection process is a prediction exercise: It seeks to predict which applicants will be successful if hired that is, which candidates will perform well on the criteria the organization uses to evaluate its employees. In filling a network administrator position for, example, the selection process should be able to predict which applicants will be capable of properly installing, debugging and managing the organization’s computer network. Consider, for a moment that any selection decision can result in four possible outcomes would indicate correct decision, and two would indicate errors.
A decision is correct (1) when the applicant was predicted to be successful (was accepted) and later proved to be successful on the job, or (2) when the applicant was predicted to be unsuccessful (was rejected) and, if hired would have been able to do this job. In the former case, we have successfully accepted in the latter case, we have successfully rejected. Problems occur, however, when we reject candidates who, if hired would have performed successfully on the job (called reject errors) or accept those who subsequently perform poorly (accept errors). These problems are, unfortunately far from insignificant. A generation ago, reject errors meant only that the costs of selection were increased because more candidates would have to be screened. Today, selection techniques that result in reject errors can open the organization to charges of employment discrimination, especially if applicants from protected groups are disproportionately rejected. Accept errors, on the other hand, have obvious costs to the organization including the cost of training the employee the costs generated or profits forgone because of the employee’s incompetence and the cost of severance and the subsequent cost of additional recruiting and selection screening. The major thrust of any selection activity is, therefore to reduce the probability of making errors or accept errors while increasing the probability of making correct decisions. We do this by using selection procedures thata re both reliable and valid.
Reliability addresses whether selection device measures the same characteristics consistently. For example, if a test is reliable, any individual’s score should remain fairly stable over time, assuming that the characteristics it is meaning are also stable. The importance of reliability should be self evident. No selection device can be effective if it is low in reliability. Using such as device would be the equivalent of weighting yourself everyday on an erratic scale. In the scale is unreliable – randomly fluctuating say 10 to 15 pounds every time you step on it the results will not mean much. To be effective predictors, selection devices must pose an acceptable level of consistency.