It was a little past 11pm as the doors parted at 66th Street and Lincoln Center and a gaggle of people poured on. Riding down the Upper West Side on the 1 train with two friends Friday night, “Ah,” one knowingly smiled at the crowd. “The opera’s let out.”
It was an aha moment. How do you get to Carnegie Hall? Forget practice--take an N, Q, or R to 57th Street and Seventh Avenue!
I ended up staying the length of the rest of the ride, bidding friends goodnight and immersing myself in strategizing a plan: (1) Aggregate humanistic-cultural event schedules, (2) merge with MTA turnstile datasets on dates for given stations adjacent to event locations, (3) calculate alternative-hypothetical differences in turnstile entry counts for stations after adjacent events versus not after events at null-hypothetically analogous times to arrive at a sense of about how much additional foot traffic an event generates with regards to a given station, (4) calculate the margin of error for these estimations, (5) thus use subway data to scale observations of post-event timing….I was beginning to think like a data scientist.
I was also thinking like a Metis student. Last Monday I and 22 others commenced a 12-week deepest of dives into the wide world of Python programming for data science, and Friday’d marked our first group presentations. We had four days to complete a consulting project for a mock-client seeking strategic insight about street team placement. Instrumentally, the client wanted to accrue emails in order to send invites for and fill up an upcoming gala event. At the same time, the client wanted to utilize street teams to target potential donors and enthusiasts.
After the opera, after the play or the concert or even the ballgame...these were the moments to be by the subway, and timing was everything. People’d be milling about, making their ways slowly to their trains, not wanting to get on and leave the magic, the milieu, the ur-ness of profound collective experience. As fellow humans standing by the subway, street team members would be uniquely primed to be people who people actually wanted to talk to.
This was not the sort of recommendation my or any other group had made. Oh well. I was learning. Humans are compelled to prolong social interaction following a humanistic event, I scribbled along as the train, too, clamored away. We were nearly as unselfconscious as each other.
Over my first week at Metis I earned an incredible number of valuable lessons--lessons from talented classmates, from thoughtful and patient instructors, and, most of all, from my own experiences wrestling with new and newly complex material. There have been abundant not-sure-which-but-feels-like-both-little-and-big challenges and realizations--even a napkin drawing along the way. It’s been a constant mental workout, which I love. I wouldn’t have it any way else. I’ll cherish that first napkin drawing.
I’ve learned some invaluable lessons, as well, including but not limited to ready maxims like Live with Thy Data, Peruseth Before Thou Useth Thy Data, Learn from Thy Data, Love Thy Data. Friday’s realization taught me big-time how much stories owe to anomalies.
Yet my biggest takeaway of the week has to do with the role insight can play in informing decisions, and with the consequent role data analysis can play in deriving insight.
Insight is like a toy. A really good toy sustains focused interaction, supports a diverse array of uses, engenders multiple interpretations, and even drives new ways of thinking and problem-solving. It shifts discourse. Consider how many uses there are for a set of Legos, and how Legos change what it means to play with blocks. Bad toys don't play well and break. The worst toys take themselves to be totally smart and super way cool and beat you over the head with the thought that they’re edifying you. There is a simplicity and subtlety to insight that edification lacks. Insight encapsulates itself.
Strategic decisions are the deeply-informed products of intuitions infused with insight (toys). Bring on the toys! Consultants are Santas. The point is to gift flexible tools, clear and compelling light between overall strategies and particular tactics, that clients can take up on their own so as to reach well-formed decisions. The point is to impel decision-making.
Analysis doesn’t output answers. What it can do is make lucid representations possible. Insight lies in its potential. It travels well.
Eagerly do I await what these next weeks and months and years have up their sleeves. I’ll try to check in as I can.