301 karma · joined December 20, 2010
http://blog.harterrt.com/pages/about.html#about
Mostly data science - been slow lately, but I’m working on a couple pieces again.
Some markets run a separate capacity market that rewards power generators explicitly for their capacity - independently of whether they actually generate any electricity. (California's market (CAISO) doesn't do this)
A long time ago I was involved in setting capacity market prices if y'all have follow up questions.
I wrote for the void for a long time. At the time, some folks on my immediate team found it useful. Now, a few years later, I'm still referencing those posts.
The important hard work was actually writing and polishing the idea until it was good enough to publish.
In OP's situation, it sounds like their counterpart is trying to argue that this project is a "good thing to do" for the user/system. In reality, it's a bit of code hygiene that makes it more fun to do work (still important [1]).
That dissonance hides the true value of the work and makes it difficult to reason about.
I just wrote a piece on how to break down corporate goals into something that's meaningful for you and your team [1]. If you're having a hard time figuring out what your goals should be it might be that your company's goals are too broad and need to be broken down more.
That's a great breakdown. I hadn't put my finger on stakeholder or customer empathy before, but I agree they're critical skills.
> Unfortunately these three areas are soft skills and you won't know you've improved until you find yourself reciting a fact. Usually you'll think "well duh, because the customer thinks this." It'll seem obvious, but it is only because you went through the trenches to learn that fact.
Definitely. This reminds me of Siver's "Obvious to you, Amazing to others" (https://sive.rs/obvious).
I'm trying to spend the rest of the year documenting as much of this soft-knowledge as I can. A lot of the data science hype over-focuses on hard skills and misses these soft skills.
[1] https://www.sciencedirect.com/science/article/pii/S096007602...
[1] https://www.sciencedirect.com/science/article/pii/S096007602...
That said, I don't think it's fair to characterize the COVID study as low-quality. It's worth mentioning contrary results, even if it's an exception that proves the rule.
It's unlikely that the strongly significant result we're seeing in the study is due to sampling error.