🦉 10x curiosity — Issue #34
starting a series over the next couple of weeks on problem finding, problem solving and solution implementation. I think often individually looked at but rarely pulled together coherently. First to problem finding — how clearly can you articulate the issue? “A problem well stated is a problem half-solved.” This advice was presented by Charles F. Kettering, over 100 years ago.
But how to do to this?
It all starts getting good data, which in turn comes from asking good questions to get to the heart of the problem — questions posed to stakeholders, or yourself as you look at what insights you can gleam. Initially you are aiming to cast a broad net, now is not the time to limit your scope of investigation — As Henry Ford highlights “If I’d asked the customer what they wanted they would have said faster horses…”. Be careful you are not looking for faster horses when you really should be making car.
- Who needs to benefit from our decision? How?
- How can you go 10x rather than 10%
- What else would we need to know to be more confident of this decision?
- Who are the people affected by this decision; who have the least power to influence it?
- How much of this decision must we make today?
- Why is this important? and whats important about that?
- If we have had infinite resources — time, money, people — what would we do? what would be do if we had none?
- what are all the reasons this is the right decision? what are all the reasons it is the wrong decision?
Asking these question will help create a list of options to investigate.
Next week we will look more into some design tools to assist further with understanding and defining the problem.
If you missed last week newsletter you can check it out here
More to keep you interested….
Often we discuss the value of taking the time to write a memo or a detailed response to a technical problem. This article articulates the benefits of doing this. Also compare with the Amazon policy of the 6 page memo
Also see this related article in the Atlantic on how suberbugs actually can be resistant to antibiotics before they are even exposed to it
A great guide on deep learning for you to reference.
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