May 112013
 

Yesterday I was in a meeting with some people. I’m in meetings with people a lot, so this wasn’t that special. We (my team) wanted something from the other people (nothing stranger there either so far). Specifically we wanted some data. That’s not true, we didn’t want some data, we wanted a lot. In fact, we wanted more data than has been produced in written form in all of human history before 1900. This had to come from different sources. Mixed and matched together so that we could play around with it.

But if you're all out, money will do

But if you’re all out, money will do

So we discussed data-fields, servers, creating joins, SQL queries and what-not.

The whole process took about an hour. And in the end it seemed that everybody was happy with what was going to be provided and how and where.

This meeting made me realize two things.

First, I was so glad that there was someone else doing this work. I couldn’t think of anything more tedious than running around in large databases, grabbing data, checking it, etc. and then packaging it nicely so that someone else can do the cool work with it.

But these people seemed happy, intrigued even! They were looking forward to this very specific challenge. And I’m sure that they would’ve hated to do my job, which was to produce a nice model to run with the data.

So my first insight: No matter how shitty you think a job is, there is someone who actually enjoys doing it!

The second was that I recognized a lot of myself in these people. Not the specifics, but more on a general level. They were throwing around a lot of terms that I only half understood (and can’t remember right now). They were talking about processes of which I had no knowledge whatsoever.

I wrote again! Yesterday morning in the train, just for 20 minutes, but I did. And it felt wonderful! Maybe my train-time will be a bit happier / more productive in the future as well…
And I could see myself, perhaps a few years younger (perhaps not), enthusiastically blabbering about statistical distributions, goodness-of-fit-tests, fourth moments, etc. And I could see the people (mostly from slightly higher up in the tree) sitting opposite me, their eyes glazed over, staring off into space.

They didn’t care about my wonderful distributions. They needed to understand just enough to make sure that the job actually was getting done. The hows and wheres were something for me (and the rest of the team) to figure out. Just give us the results already!

So second insight: No matter how important you think what you’re doing is, there will be people who really couldn’t care less.

Conclusions: Find the people who enjoy the work you hate and don’t bother me with the details, just give me the data already!

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