It’s rational to expect a solution to be big if the problem is big, right?
Sound rationale but inherrently flawed. Big things are simply a collection of little things working together. If one little thing stops working as expected, it could bring down the whole thing with it.
You would expect that someone who makes a living assembling little things together to make big things to understand this intuitively, but you would be wrong. So very wrong.
I wrote about a problem I was facing with an app I built. I didn’t have much time to dedicate to investigating and debugging the issue, and since it was non-critical I decided to ignore it til I had time to dedicate to the matter.
When I finally got around to tackling the problem, I was amazed to find out the solution was literally one line of code.
I’ve been getting emails about the server timing out on some requests for months, and the simple fix was one line of code to implement?!? I’ve probably spent more time deleting emails from the server than it took to implement the solution! I was on the right track in my last post, so why didn’t I see it through to the end?
I assumed the solution would be big because the problem looks big.
Problems have a way of puffing themselves up, persuading you to give up simply because they appear to be very large. This isn’t to say that problems can’t appear deceptively small and turn out to be much bigger than you expect. The real issue is that you can’t gauge the size of the solution by the size of the problem. The best way to know is to face the problem head on and deal with it.
Reminds me of when 4 high school kids built a cheap robot that beat MIT’s.
“How’d you make the laser range finder work?” Swean growled. MIT had admitted earlier that a laser would have been the most accurate way to measure distance underwater, but they’d concluded that it would have been difficult to implement.
“We used a helium neon laser, captured its phase shift with a photo sensor, and manually corrected by 30 percent to account for the index of refraction”
What appeared to be a difficult problem for MIT students was implemented by high school students on a very tight budget.
Don’t worry about the size of the problem. Deal with it.