Labor productivity and work sampling: The bottom line

This paper describes the relationship between labor productivity and direct work as reported in work-sampling studies. Seven data bases, collected primarily from nuclear-power-plant construction projects, are used. Investigations of a 30-project data base show that direct work is better in the winter than during the rest of the year, is best during the start-up and testing phase, and has improved since the Three Mile Island accident. It is concluded that these results are illogical. Using linear regression models, the paper shows that direct work is not related to productivity. This conclusion is based on three assumptions: Reducing wait time leads to increased direct-work time, increased direct-work time leads to better productivity, and better productivity is accompanied by less time spent waiting. Each assumption is tested, and the model statistics show very poor correlations and predictive capabilities. The most reliable data base, consisting of 46 data points, yielded an [equation found] value of 0.00 and a standard error of the estimate that is equal to the standard deviation of the performance measure. The conclusion is that work-sampling studies show how busy the crafts are, and the results cannot be used to predict labor productivity or to quantify inefficient work hours.