Re:The Truth About Linear Regression (2015)
by wiz21c on Wednesday July 31, 2024 @02:53AM
(#41116925)
> Often people demand more decisive decisions, of 'yes'/'no' or concrete action, not shades of grey and fiddling at the margins.
And working with these people is so painful.
Yes. I also found that in many cases being able to turn problems that require discrete decisions into problems that admit continuous decisions, eg by re-arranging how the business works etc, can unlock a lot of business value.
In my concrete cases I mostly saw that in the direct sense of being able to deploy more mathematics and operations research, eg for netting out (partially) offsetting financial instruments for a bank.
But by introspection you can come up with more example. Eg that's a common selling point for running your servers on AWS instead of building your own hardware.
Re:The Truth About Linear Regression (2015)
by harperlee on Wednesday July 31, 2024 @09:50AM
(#41119159)
I often make fun of McKinsey- style four quadrants when overused, but they really boil down to something that makes a lot of sense in communicating a problem space:
a) carefully choose the two most important dimensions of concern (as Alan Kay said: the correct point of view is worth 80 Iq points)
b) make them binary: are we happy here or do we need to change?
In a way similar to the pareto ratio, you keep a surprising amount of value in something “so simple it cant be possibly so useful”.
Of course, you can also weaponise the choice of axes for your (office) politics: pick the two axes right, and the policy outcome you want to pick might already be baked into the whole process from the start.
No, that's not true. Human groups are very able to make discrete decisions. Actually, often they tend to go for discrete decisions, when something continuous (and perhaps linear) would be a lot better.
(Just to be clear: if you force your linear models to make discrete predictions, they are no longer linear in any sense of the word. That's why linear optimisation is a problem that can be solved in polynomial time, and integer linear optimisation is NP complete.
Even convex optimisation, which is no longer linear but still continuous, can be solved in roughly polynomial time.)
Often people demand more decisive decisions, of 'yes'/'no' or concrete action, not shades of grey and fiddling at the margins.
Getting people to even appreciate linear models is already a step forward. Like it or not, your business strategy meetings are already a step ahead of what most people would naturally be inclined to.