Trying Out That Fancy Network Stuff
So, I bumped into this name, daniel olguin, a while back. Seen him mentioned here and there, connected to using data to figure out how teams actually work together. You know, mapping out who talks to who, who the real go-to people are, that kind of thing. Sounded pretty cool, like some secret sauce for fixing collaboration problems.
I got this idea in my head, maybe I could do something similar, just on a small scale, you know? See what’s really going on in my own little corner. Thought it might show us where communication gets stuck or who we should really be listening to more. Seemed straightforward enough when you read about it.
So, I decided to give it a shot. Nothing too fancy, mind you. Didn’t have access to company-wide email logs or anything like that, obviously. I basically tried two things:
- First, I put together a simple, anonymous survey. Asked folks who they worked with most often on different types of tasks. Who they went to for advice, who they found helpful for getting things unstuck.
- Second, I tried looking at publicly shared calendars – just seeing who was in meetings together often. Thought maybe that would show some collaboration patterns.
Man, what a hassle that turned out to be. Getting people to actually fill out the survey? Tough. Even when it’s anonymous, people get weird about this stuff. They worry it’s some kind of management trick or they just don’t have the time. So the response rate was pretty low.
And the calendar thing? Mostly useless. Just showed the usual suspects meeting all the time, didn’t really tell me anything deep about informal help or real influence. Plus, trying to make sense of the patchy data I did get? Gave me a headache. Drawing lines between names on a paper didn’t suddenly reveal profound truths, you know?
Here’s the deal: Reading about guys like Daniel Olguin and the smart ways they use data at big companies or in research labs is one thing. Trying to actually do it yourself, even a super basic version, is a whole different ballgame. It takes serious tools, serious data access, and probably a Ph.D. to make real sense of it all.
For me? It was mostly just a time sink. Didn’t really uncover any secrets. Made me appreciate that this stuff is way harder than it looks from the outside. Maybe useful for the big guys, but for us regular folks just trying to get work done, probably not the magic bullet I was hoping for. Just another reminder that fancy ideas often bump hard against messy reality.
