Save money by overpaying for elite talent
A group of scientists studied variation in individual programming output. In short, the study found that there are huge variations in productive capacity among programmers.
These scientists studied professional programmers with an average of 7 years' experience and found that the ratio of initial coding time between the best and worst programmers was about 20 to 1; the ratio of debugging times over 25 to 1; of program size 5 to 1; and of program execution speed about 10 to 1.
Why the huge difference?
Programming is like any other creative pursuit, where there's a huge difference in productive output between really good talent and merely okay talent.
A 10x developer (one that is 10 times better than an average one) will find solutions that would never occur to an average programmer. 10 engineers writing the wrong code can often be out-performed by a single engineer writing the right code. In fact, that's really what drives the possibility of a a tiny software startup unseating existing industry titans
10x engineers are at the heart of it all.
What does this mean for you, as an employer?
One great programmer whose hourly rate is $200/hour is cheaper than than an average or below-average programmer who charges $50/hour.
What takes the second programmer 100 hours might only take the first programmer 10, saving you money in the short-term.
The 10x developer will likely build a product that's better and more maintainable over the long-term, as well, saving you money for a re-write in the medium-term.
And finally, elite developers only work with elite developers. If you aspire to build a business around your project, you risk sending your organization's future technical quality into a downward spiral with merely a single poor hire, which may doom your company in the long-term.
At gun.io, we live by the motto: if you think hiring a professional is expensive, wait until you've hired an amateur.
Sackman, H., W.J. Erikson, and E. E. Grant. 1968. "Exploratory Experimental Studies Comparing Online and Offline Programming Performance." Communications of the ACM 11, no. 1 (January): 3-11.