Performance sensitive code is often overlooked in business apps. This is because high-performance code might not affect outcomes. Concerns with execution times are ignorable if the code finishes in a reasonable time. Apps either meet expectations or not, and performance issues can go undetected. Devs, for the most part, care about business outcomes and performance is the outlier. When response times cross an arbitrary line, everything flips to less than desirable or unacceptable.
Luckily, the Big-O notation attempts to approach this problem in a general way. This focuses both on outcomes and the algorithm. Big-O notation attempts to conceptualize algorithm complexity without laborious performance tuning.
This is a rather high-level take on the idea, as it doesn’t cover any of the O(NlogN) or O(logN) algorithms out there. But if you are not familiar with the concept, it is good to know.