The idea
Technical sophistication and problem-solving value are different. A simple model can isolate assumptions, create a baseline and expose where complexity is actually needed.
Worked example · illustrative
Trying a meal plan before paying for an app
Situation. You keep throwing away groceries that never get used. You’re thinking about paying for an app that tracks what’s in the kitchen and plans your meals, but you’re not sure why so much food is going to waste.
The tempting conclusion. An app that organizes everything should help us waste less.
What changes the view. You could try planning three dinners on paper and checking the fridge before shopping for a couple of weeks. If less food ends up in the bin, planning meals around what you buy seems to help. If plans keep falling apart because everyone gets home at different times, tracking more ingredients might not be what you need.
What this supports. The app might still be useful, but you’d have a better idea of what you want it to help with. Maybe the paper plan is enough, or maybe it’s hard to keep everyone’s plans in one place. A couple of weeks won’t tell you how this works through every busy spell, but it could give you a useful start before paying for more features.
Useful when
Watch for
Simplicity is a starting strategy, not a belief that simple solutions are always sufficient.
Where this came from
Quantitative research, Machine learning