Problem Types
What type of problem are you solving?
What type of decisions do need to make to solve your problem?
Categorisation
NP Hard Problems are particularly challenging because they cannot be solved in polynomial time, but a proposed solution can be quickly verified in polynomial time. Examples of NP-hard problems include the Traveling Salesman Problem, the Knapsack Problem, and the Integer Programming Problem.
Chaotic problems are difficult to understand the relation between cause and effect. No obvious pattern to follow. Financial markets, highly dynamic and personal, results reflect changes in time and complex data structures. Ask what type of black swan events your systems could be exposed to.
Complex problems require analysis and reflection, ad-hoc problem solving with workflows to help solve the problem. Resolution is not a predictor of the future. Experts don't exist Experimentation and outcomes prove what works.
Complicated problmes require domain expertise/experience to understand the problem and how to fix with decision tree in the workflow map. Best practice analysis
Simple: The impact of cause and effect are well-defined. Simple data analysis to monitor and easily understood workflows to prevent or fix problems without much experience. Best practice exists