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Where's the part where the welders start doing needless welding to satisfy the helper's target? Or is the point that a good consultant knows to leave before that happens?
More likely the consultant helped them learn that now that they're so efficient, they can downsize the welding team.
Where's the part where the welders start doing needless welding to satisfy the helper's target? Or is the point that a good consultant knows to leave before that happens?
In this story, the consultant found a way to remove stupid/low-skilled work from the welders' todo. They no longer have to lift shit, take off their gear, and peel plastic off parts. None of that sounds fun and presumably welders are happy not to be doing that.
I suspect a welder prefers to weld. The consultant found a way to let welders do what they chose/are trained to do, which is weld. I don't see any sort of bullshit metric/target imposed on them.
Where's the part where the welders start doing needless welding to satisfy the helper's target? Or is the point that a good consultant knows to leave before that happens?
Many humans avoid malicious compliance, because they want to keep their job.
I imagine the blue light applied to programming would be a crude tool. I want to hear keys clacking? See issues closed, pull requests? But we can ask what are the things developers are doing which interrupt them from coding and could there be a benefit to someone employed to handle those distractions?
Recall that data science itself is 80-90% data cleaning and basic exploratory analysis, so that means no more than 1-4% of their overall time is spent doing the work that they're actually trained to do, and that you are actually paying them to do.
They look productive because they are always busy. But really they need helpers (data engineers and dev/data ops people) to do all the random software work, so the data scientists can actually build models, meet with senior leadership, and all the other actually value-generating work that justifies their high price tag, and moreover keeps them happy with the work so they are more likely to actually stay at your company.
This all can be learned from The Goal by Goldgratt which is a story about theory of constraints.
Where's the part where the welders start doing needless welding to satisfy the helper's target? Or is the point that a good consultant knows to leave before that happens?
More likely the consultant helped them learn that now that they're so efficient, they can downsize the welding team.
This is a great story because it's not just about welding. I have seen many data science teams working under similar conditions: spending 90% of their time doing miscellaneous bullshit and 10% doing data science at best . Recall that data science itself is 80-90% data cleaning and basic exploratory analysis, so that means no more than 1-4% of their overall time is spent doing the work that they're actually trained to…
For example, Newton / Leibnitz's invention of calculus created much more than enough value to pay for every single mathematician ever since, and that wasn't even all they did.
It's incredible that one person was able to handle all the work that took up 90% of the welders time. Lots of time must have been spent getting in and out of gear. I’d expect that one guy to end up the bottleneck and the welders to be waiting for him to bring them parts, but it says he even as time to peel the plastic! I imagine the blue light applied to programming would be a crude tool. I want to hear keys clacking…
The article's story anecdote of "blue light" is about finding the true value in a process. Blue light means the welder is actually creating value in the product. Anything else in the process does not help build value to the product. It is all non-value added activities. The non-value added activities might be necessary such as setup, delivery, reposition or what not but it doesn't drive value. By maximizing the blue…