
Forecasting with uncertainty - Lukas1994
https://www.causal.app/blog/forecasting-with-uncertainty
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refrigerator
Hey folks, I'm one of the authors of the post. Would love to hear people's
thoughts, and happy to answer any questions :)

If you liked this, then I'd definitely recommend reading "The Flaw of
Averages" by Sam Savage. It talks about this stuff in a lot more detail, and
the style is very entertaining — not at all what you'd expect from a
statistics book.

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03199618
Is there anything causal as in Pearl’s graphical models or the potential
outcome framework?

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refrigerator
Afraid not, sorry — right now it's more of a Monte Carlo simulation tool. Can
see how the name might be a bit misleading!

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03199618
If causal.app does not make causal statements of that kind, which kind of
causal statements can it make then?

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_delirium
Not involved with causal.app, but I see it as going the other way as far as
causality goes. Pearl-style models are trying to infer causation from data.
Here, _you_ give it a causal model that encapsulates how you think a scenario
works (which variables affect the outcome, how, and a range of likely values
for them), and it simulates your model to give you ranges of likely outcomes,
plus some other things like sensitivity analysis (which variables impact
likely outcomes the most). I like the comparison they make to spreadsheet
models. It's that style of modeling but with Monte Carlo simulations, so you
can put ranges instead of single numbers in cells, and the ranges propagate
through the model to output ranges.

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refrigerator
Couldn't have put it better myself :)

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jerednel
I like the concept. Who is this targeted at though? Having been an analytics
mgr at couple of ad agencies my common questions were...

Given current impression share for my campaigns, what would incremental spend
do for CPA and position?

What would be the expected CPA to move from avg position of 1.8 to 1.4

Can I tie CRM data to get value of leads/opportunities and optimize for that?

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cpitman
I use these techniques for day-to-day estimation in software development,
usually for things like project timelines, system requirements, etc.

I often run into developers who think "there is no way to estimate when we
will be done". What I think they usually mean is that they cannot estimate a
_single_ time in which it will be done, which is completely fair. However, if
they are being honest with themselves, I think they can often estimate a range
of possible outcomes. Adding a new "Contact Us" form may take a few hours or a
few days, but it isn't going to take 1 year.

One of my bigger successes with this kind of model was sizing the resource
requirements for a brand new high-performance system that was in it's early
stages of development. I created a model that started with what we knew so far
from out performance testing, with uncertainty for everything, and projected
forward to different confidence levels of sizing. We ended up being pretty
having just a little extra, which was perfect considering the multi-month
procurement process.

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refrigerator
Very cool! What tools are you using for this right now?

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cpitman
For my more routine analysis of LOE/budget, where it is mostly a
straightforward summation, I have a template spreadsheet that I just reuse.
For more complex cases, I hand write the equations and error-propagation into
a custom sheet. A little time intensive, but it gives me an excuse to practice
multi-variable calculus.

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clairity
too bad casual.app is so tightly coupled to the google ecosystem, even enough
to say it's optimized for chrome (terrible for privacy/confidentiality). we
really need deeper and wider understanding of decision-making under risk and
uncertainty (see over-reaction to covid by many, under-reaction by some).
tooling like this can help.

it's hard to evaluate the modeling capabilities from a few pages and blog
posts. how does it compare to crystal ball on excel, for example?

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owenshen24
There's also Guesstimate, which I think is similar:
[https://www.getguesstimate.com/?ref=producthunt](https://www.getguesstimate.com/?ref=producthunt)

