Rent the Runway: A Rewarding AF Ride
Reflections and advice for fellow ‘data nerds’
After a decade+ journey, Rent the Runway IPO’ed today. And I’m extremely proud to have played a part for 8+ years in this journey as their Chief Analytics Officer. I’m proud not just for the stark fact that very very few companies get to this stage in this punishing and highly variable world of startups but also for the fact that this was a difficult and challenging* journey — and maybe, that’s why for me and a few others who spent the better part of a decade working on this, a life-changing, career-changing experience.
(* I recognize all startups are hard but I could write a book or at least a dozen blog posts about how many things we had to excel at and get right in building Rent the Runway.)
But, I will touch upon one thing which relates to my own career arc. Rent the Runway was born in the “digital era” — we were software-native if you will. But we were also a data-native organization from day one. Even when we had sparse observations, we started building the muscle to instrument sensors — tracking whatever we could, observing the data, hypothesizing, making decisions (often on incomplete observations, under uncertainty), learning, shoring up our instrumentation further, observing, hypothesizing, learning. This scientific method of maximizing the value of our observations was woven into our DNA.
We used early observations of rental timing and inventory queue patterns to engineer the (world’s largest?) reverse logistics machinery. We used observations of inventory consumption to build a highly analytical system for pricing and sourcing. We used observations of user behavior to improve the product and even take big swings with new product bets. Sorry, not used in the past tense, but continue to use, today and will use moving forward. Data-native FTW.
Personally, I was lucky that I had the opportunity to make the transition from a data nerd (ok, will openly admit now) to being a cross-functional leader, a decision-maker. I operated at the Venn diagram intersection of the technical and the business. I see the continued birth and growth of software and data-native startups and my one advice to the technical folks is this: find and spend some time at this intersection — your leverage will feel radically different. You will not just be a “service center”, or a code or data monkey as they say, you will organically impact business outcomes. Huge outcomes.
How do you make this transition? It is impossible to articulate the beautiful messiness in crafting something that starts off looking like a slime mold — you divide it, you shape the different parts, you learn, you understand the connections better, you reshape the pieces, you learn something else, and this goes on — and sometimes, you need the courage to even destroy what you’ve built to rebuild something.
That’s the operator mindset. It’s about understanding the domain, the context, how the pieces connect and drive emergent behavior, and this combined with the engineer ethos, the code or data monkey mindset is a powerful combination. Maybe I’m alluding to something like this — an opinion piece from dbt labs (Rent the Runway is a proud user!) which talks about the powerful intersection of red (business domain) and blue (technical) skills, the purpleness of it all.
And hopefully, all this work is rewarding in the end — that you will look back and feel an intense sense of pride, an indescribable satisfaction in what you were able to contribute to, knowing you gave it your all. I know you will. Just like I do now.
