Workplace Persona #2 - Maniacal Metrics Manny
You may know a Manny.
Manny obsesses about data.
Manny believes you can measure anything.
Manny compulsively computes metrics.
Manny can barely contain himself when a sexy number catches his eye.
Manny is maniacal about metrics.
You know Maniacal Metrics Manny.
Meet MMM.
My first set of Observations on MMM
Observation 1: MMM loves data too much. For MMM the world is a fascinating place, swirling and twirling with numbers. He can see them move like Neo in the matrix. Only problem is no one else sees the world the way he does.
Observation 2: MMM’s spend much of their day in Excel, SQL or Python. They worry about statistical significance as much as you worry about the value of your home or Restricted Stock Unit’s. They talk about p-values as if everyone knows what they’re talking about. But we know that at best people know that lower is better, like golf. MMM’s are blissfully unaware that others don’t really understand.
Observation 3: MMM’s can be very helpful. But you can’t give them a problem that’s too big, or too small. A problem that’s too big will cause their brains to collapse under the weight of the TerraByte’s of data they need to compute. A problem that’s too small causes their instinctual recommendation to check a “self-serve dashboard”. I am a self-serving a-hole, but not in the case. Nice try Manny.
Observation 4: MMM’s most likely have the answer to your medium sized problem. The bigger issue is whether they can communicate this in a way that makes sense. Unfortunately the key design flaw with a big brain to compute metrics, is small resources dedicated to communication. Trade-offs are a bitch.
Observation 5: MMM’s really like to complain about something called telemetry. If you’re not careful, you’ll get caught in an epic rant about boring shit like event tracking, click events and the importance of QA. Don’t even get them started on compute, tables, joins and window functions. Snooze fest. Let me cut this short MMM, I don’t care. This is your job, that you’re good at. Own it. Shut up.
Observation 6: MMM’s often get very worked up about simple asks. Like what’s so complicated about getting three years of data, by platform and page? Or tracking a user across different platforms? All I know is that they sweat, bite their tongue, grab their ear, or grind their teeth when these types of questions come up.
Observation 7: MMM’s are real sticklers for definitions. Be prepared to use the most precise words known to man so they can understand what you’re talking about. I think they like being pedantic to show off their power. Try not to get into a conversation about retention rates, and don’t ever switch up the term visitor or distinct user when reviewing metrics. Or do it just to fuck with them.
Observation 8: MMM’s rarely, if ever, get to the point quickly. They’d rather talk about methodology, their battle with the mythical telemetry monster, t-tails and z-tails. Telling you exactly what you want to hear is not possible. Be prepared to remind them that they get points for simplicity, not complexity. So stick the landing already buddy.
Make it stand out
Whatever it is, the way you tell your story online can make all the difference.
Observation 9: MMM’s often overlook painfully obvious discrepancies in their carefully crated metrics. For as smart as they are, they can be extremely obtuse. You might have to say something like, “Manny. There areb’t 10 Billion people on the planet. So there’s no way 10 billion people visited our barely workin’ app last month”. Breathe. They mean well.
Observation 10: MMM’s often create absurd hypotheses to explain human behavior, instead of correcting their metrics. Be careful if you hear it’s possible that users might open a video, close it, open it again, then complete the video! Humans are lazy and Occam says no.
Observation 11: MMM’s often get frustrated at your stupidity and having to repeat themselves. The brilliant don’t pity fools. To get the best out of MMM play the jester not the fool. There’s a playful way to get to the right answer.
Observation 12: MMM’s often gloss over the most critical part of their whole analysis. If you’re not listening intently you might miss it. Be prepared to snatch a fly out of the air, or else you’ll miss understanding what really is valuable from their hours of toil.
Observation 13: MMM’s will on occasion deliver the data point you need to look smart. THIS IS THE LONE REASON why you put up with observations one through twelve. If you can suffer, you can get the gold. Be sure to tell them that it’s the data point that will turn the leadership team’s opinion from no to yes. This really gets their juices flowing. Do not, under any circumstances tell them you didn’t use the data. You might need them in the future.