The most common failure in problem-solving is rushing past defining ("State") and structuring the problem to get to the more gratifying "Solution" phase. A disciplined, multi-stage process forces a shift from instinctive (System 1) to deliberative (System 2) thinking, preventing premature and often flawed solutions.
Structured analysis works when you can theorize potential causes and test them. However, for problems where the causes are "unknown unknowns," design thinking is superior. It starts with user empathy and observation to build a theory from the ground up, rather than imposing one prematurely.
Experts often view problems through the narrow lens of their own discipline, a cognitive bias known as the "expertise trap" or Maslow's Law. This limits the tools and perspectives applied, leading to suboptimal solutions. The remedy is intentional collaboration with individuals who possess different functional toolkits.
Relying on previously successful solutions without deeply analyzing the new problem's context is a cognitive trap. Ron Johnson's attempt to apply Apple's retail strategy to JCPenney failed because he overlooked fundamental differences in their customer bases, demonstrating the danger of surface-level analogical reasoning.
When hiring, top firms like McKinsey value a candidate's ability to articulate a deliberate, logical problem-solving process as much as their past successes. Having a structured method shows you can reliably tackle novel challenges, whereas simply pointing to past wins might suggest luck or context-specific success.