Who would this be of interest to? I would never expect two workplaces to have exactly the same "runstitching time" (or anything else).
Also this is misstated, you would be testing if the two datasets are samples from distributions with the same average. Ie, the actual measured averages are not expected to be the same.
Whether or not that's true, it reminds me of the experiments done near Hawthorne, Illinois around the time of the Great Depression to improve worker productivity by changing their environment. The workers output improved almost regardless of environmental changes. The conclusion was workers output improved because someone was paying attention to them. Henry Landsberger analyzed the experiments in the 1950s and coined the term the Hawthorne Effect.
(Edit for grammar, spelling, and coffee)
How much did it improve? All this test tells you is that there was some difference, it could be minuscule.
I doubt this is really the goal of an experiment like this. The goal would actually be to figure out whether changing their procedures/whatever would make them more money in the future than it would cost to do the change.
If we divide a workplace into two segments, there almost certainly will be some difference in worker productivity between the segments, having nothing to do with implementation of ergonomic practices and just having to do with the inherit variance of individual productivity contributing to the group.
If the difference is productivity is large enough, you start thinking the ergonomic practices might have something to do with it. Statistics makes these principles more precise through concepts like statistical power, significance, and confidence intervals. Proper analysis of such an experiment would allow a company to compare the cost of the ergonomic processes with the benefit of the increased productivity attributable to those processes. This in turn would indeed allow them to make more money!