This was something I read in a book called The Art of Scalability, something I believe I’d always intuitively known but never had spelt out explicitly: that having additional hands (or brains) does not necessarily equate to a proportional increase of output – it is often less, especially at the start.
The problem is relatively new. In the old industrial economy where work was relatively simple or specialised, it was possible to have somebody come in and make widgets at almost the same productivity level as someone who had been there for a far longer time.
If one widget-maker can make 100 widgets in a day, two should be able to make 200, or maybe 150 if one of them is new.
But in the knowledge economy where work involves far greater scope and interdependencies, with steeper learning curves, this model doesn’t necessarily replicate very well.
If one analyst can create a spreadsheet model within a day, can two create the model within half a day? Or three quarters of a day? Probably not. And if the second analyst is new, it’d actually probably take two days. Throw in a third analyst and you’d probably get that model done in a week.
There is often a learning curve on the part of new joiners; and though we often take note of the the learning of process and technical skills, we often forget there’s also cultural and general adaptation, which can take far longer.
And if the new hire has had plenty of prior experience, there’s also the time needed to spend unlearning old behaviours if they are incompatible with current ones.
There’s also somebody who’s got to give the training, often a senior team member or manager, whose productivity would likely decrease during this period as the new joiner’s increases; and this increase/decrease is often disproportionate, with the drop of productivity in the trainer being far worse than the increase of productivity of the one being trained.
If the new joiner leaves just as he or she gets up to speed, which could be a year into the role, then there’s simply no justification for bringing him or her into the team in the first place.
I love to read and write. Professionally, data science, technology, and sales ops are my thing. In my non-professional life, I aspire quite simply to be a good person, and encourage others to do the same. For those who care, I test as INFJ in the MBTI.