You either win or you lose (learning optional)
"I never lose; I either win or I learn." - cliché alert.
More often than not, you plainly lose, and you learn precisely nothing. Nada. Null.
Winning is excellent. It is the validation that your cognitive model maps nicely onto the world, it increases our dopamine and, as such, it feels good. Actually, winning is designed to feel good since the winning posture constituted a major evolutionary advantage.
Losing, conversely, is plain painful. The corporate reflex to a loss is the post-mortem. A small army of managers trying to magically transform losing into some kind of golden knowledge for the future, a lesson learned. The hidden ultra-powerful hypothesis here is that business is a clean laboratory where "root cause" exists and can be found. This silently assumes a linear causality where action A causes disaster B. Nonlinear dynamics have shown that this is fantasy: all interesting nonlinear systems (which pretty much include all human-touched systems) are deeply geared towards multi-causality, where multiple different causes trigger multiple different effects, sometimes with interesting feedback loops between causes and effects. Essentially reality, or at least any meaningfully juicy part of reality, is kind of resistant to simple root cause analysis.
Therefore, humans being the relentless pattern-seeking engines that we are, we are seeing patterns even when there are none. And the lesson you extract is many times the wrong one: you decide you lost the bid because the presentation lacked technical depth while, sometimes, you actually lost because the buyer plays paddle with your competitor. So you over-complicate the next pitch for no reason.
Some reflection after a small or big loss is by all means necessary, as well as processing the sheer pain (and ego slap) of loss. However, over-analyzing, or even worse, romanticizing loss, is plain useless. And, sometimes, it leads to over-correcting on fully inconsequential variables, throwing good money after bad money.
We either win or we lose, and sometimes we get useful lessons out of both. Sometimes not.