From 4de1436ade9dc3aedfc5ef49319610a71b6a00c8 Mon Sep 17 00:00:00 2001 From: counterweight Date: Mon, 3 Feb 2025 16:22:51 +0100 Subject: [PATCH] draft --- .../writings/valuing-data-teams-output.html | 132 ++++++++++++++++++ 1 file changed, 132 insertions(+) create mode 100644 public/writings/valuing-data-teams-output.html diff --git a/public/writings/valuing-data-teams-output.html b/public/writings/valuing-data-teams-output.html new file mode 100644 index 0000000..0cdcdd9 --- /dev/null +++ b/public/writings/valuing-data-teams-output.html @@ -0,0 +1,132 @@ + + + + + Pablo here + + + + + + + +
+

+ Hi, Pablo here +

+

back to home

+
+
+

Valuating data teams output

+

+ - Freedom and fucking up + - How work looks like + - This is an economics problem + - Fairy tail organizational designs +

+

+ In 2023, I had the chance to do something not a lot of people get to do: I started a Data team in a + startup (Truvi, formerly Superhog) from scratch. +

+

+ Being in a greenfield situation, both in organization and technical terms, was equally challenging and + rewarding. It gave me the right space and craving to spend time thinking on stuff I hadn't before. This + included very foundational questions such as... what should the Data team do? The kind of stuff you + don't think about much when you land in a cruise ship that's already been rolling for a while, and you + get told your job is to pull that lever up and down when the light tells you to. Ever since, I've had + the + chance to learn and think a lot about embedding a Data team in a small SaaS company. +

+

+ One of the hard and interesting topics is how do you measure the success of the team. How do you look at + what the team has done and answer the following questions: +

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  • How valuable is this thing we delivered?
    • +
  • Was it the most valuable think we could have done?
    • +
+

+ These are not trivial questions. Because it's easy to fuck up. Being a nimble team in a small company, + the amount of flexibility you enjoy is ecstatic. You can (and usually need to) pivot a lot, very fast. + But with freedom comes responsibility, and the pleasure of having many choices comes with the pain of + wondering if you're screwing up in what you choose. +

+

+ How work looks like +

+

+ I find experience and real situations make abstract rants like this one much more interesting, so let me + explain a bit what the Data team at Truvi faces on a daily basis to give some context. +

+

+ Truvi is a SaaS company that services short-term rentals (STR) hosts and guests. Our goal is to help + both parties reduce and manage risk in their bookings. Risk here means, for the other part, the other + party doing something nasty to you (e.g. your guest burns down your BnBs kitchen, or your host let's you + know the property you booked is flooded right when you show up at the door on a Monday night at + 11:30PM). We offer multiple services, like screening and protection, to help both parties manage this, + and we charge fees for it. +

+

+ We deliver our services through a couple of in-house developed applications and some API integrations + with PMSs, OTAs and other funky acronym-named + types of companies involved in the STR industry. +

+

+ The Data team's main responsibility, as defined by me, is to ensure people in the company know what they + need to know. We deliver this in multiple ways: +

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  • We maintain a lot of reporting. Some of it might be company-wide KPIs all management looks at, + some others are more operational detail that only affect certain teams or functions.
    • +
  • + We keep ourselves available for adhoc, quick and dirty, one off requests. We rotate this through the + different members of the team since it's quite disruptive for one's agenda and focus. +
    • +
  • + We deliver adhoc, slow and steady, brainy reports whenever people not only need Data, but someone + who knows what he's doing because the analysis requires above average data literacy. +
    • +
  • + We support data heavy projects, such as A/B testing or the acquisition of external data sources. +
    • +
+

+ Even if this categorization looks neat, the reality is more of a barrage of a million different things, + coming through the door all at once without any order. +

+

+ Given our humble capacity for delivering and our colleagues heavy appetite for asking, only a sliver + of what gets requested will be done soon. One of my jobs is to decide, together with the company + leadership, what makes it in. It's a tough job at Truvi, and it's been a tough job at previous companies + I've been at. I think that is the case because of poor organizational design. And I think we have a lot + to learn from economics. +

+

Economic calculation

+

+ The situation we have in my team is an economical one. We have lots of needs and we can't satisfy all + of them. +

+

+ This is the same situation society faces at scale: there's plenty of capital and man hours we can put up + to good use, but we have infinite options. What do we do more, hospitals, more schools or more beers? +

+

+ In society, despite what statists and bureacrats would like, these decisions are not made by a bunch of + all knowing intellectuals in their parties office. They are made on the streets, by individuals that + decide how to spend their own money and time. +

+

+ People spend their own very wisely. Even if it might look like they do stupid stuff, they don't. They do + what's good for them, with their resources and preferences. Even if we don't share their choices. Even + if we think we know better than them. +

+ +
+

back to home

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+ + + + \ No newline at end of file