Inter-Operator Variability Effects on Quality and Productivity
Authors: Johnson Steven L. 
Published: July 2017

The paper discusses the magnitude of differences among individual operators and the effect of those differences on two areas of particular interest today: productivity and product quality. The focus of the paper is on the impact of individual differences on paced (i.e. machine-paced) operations. There has been an extensive amount of work conducted on individual differences, particularly within the psychological literature. However, most of this work has been conducted in laboratories using well controlled (i.e. often simplified) tasks, rather than the generally more complex tasks representative of industrial operations. In addition, the subjects in these studies have often been college students that are not representative of the industrial workforce. The studies that have been conducted on actual manufacturing or assembly operations with industrial operators have exhibited interesting results. The differences among operators that are of particular importance to the present paper are the differences in the time required to complete a task. That is, for a given manufacturing or assembly operation, there is a distribution of times necessary to complete the task by different operators. The dispersion of this type of distribution has been specified in many ways (e.g. standard deviation, coefficeint of variation, range, etc.) The measure that most authors have used, and one that is readily interpretable, is the ratio of the fastest to the slowest operator in terms of the time required. The conclusions of many different studies in many different environments are very similar. The ratio of the fastest (shortest time) to the slowest (longest time) is generally between 1:2.0 and 1:2.5. The problem, therefore, is that if the slowest individual performing an operation (e.g. assembly line) takes twice as long as the fastest, how long should be allotted to perform the job if it is a paced operation? The standard answer provided by Time Study Engineers (and textbooks) is “pick the normal operator.” When asked to define “normal” the usual response refers to the “average” operator. However, if a paced operation is set for the average (i.e. mean) operator, then 50 percent of the workforce would be unable to perform the task. This is not desirable and is, in fact, not the case. Pursuing the issue further, the question could be asked, “What proportion of the workforce can not perform the task in the allotted time?” To this question, the answer is essentially always less than ten percent and is often less than five percent. The implications of the distribution among operators in a paced operation are neither subtle nor inconsequential. The operators who are slower than the fixed pace have one or more of the following alternatives. One alternative is attrition by moving to a different job. A problem with this, however, is that many of the paced operations today are entry level jobs and movement requires seniority. A second alternative is to compromise safety precautions, such as removing guards or taking shortcuts that are considered to be unsafe, although they might take less time. A third alternative is to not complete the task (five screws instead of six), thus reducing the quality of the product and/or increasing repair costs. The alternatives listed above are some of those possible for the slower operator. However, for a fixed paced line (e.g. set so that only 10 percent are not able to complete the task), what are the implications for the group of operators who could perform the operation faster. That is, if only 10 percent can not accomplish the task, then 90 percent could perform it faster but are not allowed to in a paced operation. This obviously has severe implications for the productivity of an operation. If the ratio of the fastest to the slowest operator is 1:2.0 (a conservative estimate according to the literature) and the allowed time is set for the tenth-percentile operator, then productivity could be improved by approximately 17 percent by using a self paced operation. Although self-paced (actually non-machine paced) systems have additional costs (e.g. more costly conveyance, more in-process material, etc.), the benefits derived from the potential productivity improvement are considerable. The purpose of the present paper is threefold. First, it is to reiterate the fact that inter-operator differences (as well as intra-operator differences) do exist in industry, as well as in laboratories. Second, the differences that exist in industry today are not small (e.g. in the range of 1:2.0 to 1:2.5). Third, there are serious implications resulting from operators who can not perform their job in the allotted time (e.g. attrition, safety, and quality). Fourth, the resultant loss in productivity due to paced operations that do not accommodate individual differences among operators is not trivial (e.g. 17 percent or greater). The area of inter-operator variability is an area that needs more investigation. However, even with the present limited information on the topic, there are important improvements that are possible in industry today by utilizing difference in capabilities instead of ignoring them.