rgw@icdattcwsm:~/Blog$ cat 2024-11-04-Solve-For-X.md

There is a poetic elegance in mathematical challenges to "solve for X."

Firstly, X has a definite value. The objective is not to solve for "A AND B," "A OR B," or more complex formulations, but simply for X.

Secondly, clues for X's value can be ascertained by looking at how X impacts other components of the system.

Thirdly, both deductive and inductive approaches to solve for X may be, depending on the context, valid.

For instance, a business may, deductively, set prices based on known industry standards and market research data. Likewise, a business may notice that a certain feature of their product generates customer enthusiasm and, inductively, hypothesize that expanding this feature would lead to greater success.

The pursuit of deductive approaches, is a symptom of framing a low risk problem statement. 

When a restaurant decides how much to charge for a meal, they might use a deductive approach. This involves looking at how much the ingredients cost and checking what other restaurants charge for similar meals. This is inherently low risk, and will inevitably yield low/ temperate returns.

On the flip side, if they notice that a new dish is a hit and keeps selling out, they might decide to add more dishes like it, figuring people will love them too. This is the space where start ups differentiate themselves from old school risk-averse behemoth businesses.

Inevitably, the value generated by "solving for X" has little to do with proof/disproof of the problem statement. It does, however, have everything to do with the quality of the proposition.

Competitive success, thus, can be attained simply by a relentless pursuit of a superior "solve for X" proposition—irrespective of the actual outcome of attempts. In football, the side that scores the most goals wins the match, but the side that concedes the least goals has better odds of winning the league.

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