Work sampling is the statistical technique used for determining the proportion of time spent by workers in various defined categories of activity (e.g. setting up a machine, assembling two parts, idle...etc.). [1] It is as important as all other statistical techniques because it permits quick analysis, recognition, and enhancement of job responsibilities, tasks, performance competencies, and organizational work flows. Other names used for it are 'activity sampling', 'occurrence sampling', and 'ratio delay study'. [2]
In a work sampling study, a large number of observations are made of the workers over an extended period of time. For statistical accuracy, the observations must be taken at random times during the period of study, and the period must be representative of the types of activities performed by the subjects.
One important usage of the work sampling technique is the determination of the standard time for a manual manufacturing task. Similar techniques for calculating the standard time are time study, standard data, and predetermined motion time systems.
The study of work sampling has some general characteristics related to the work condition:
There are several recommended steps when starting to prepare a work sampling study: [1]
After the work elements are defined, the number of observations for the desired accuracy at the desired confidence level must be determined. The formula used in this method is:
standard error of proportion
percentage of working time
percentage of idle time
number of observations
Work sampling was initially developed for determining time allocation among workers' tasks in manufacturing environments. [3] However, the technique has also been applied more broadly to examine work in a number of different environments, such as healthcare [4] and construction. [5] More recently, in the academic fields of organizational psychology and organizational behaviour, the basic technique has been developed into a detailed job analysis method for examining a range of different research questions. [6]
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