Last October, shortly after being named CFO of machine learning start-up Moloco, Brandon Maultasch decided to forgo yet another welcome coffee to instead engage with a wide flock of Moloco employees on the virtues of discounted cash analysis.
“The last thing you want a new people leader talking to the entire company about,” confesses Maultasch, before launching a stirring defense of the fall discussion that he refers to as a “teach-in.”
Read More“We have 65 data scientists and machine learning engineers at the company. If they can build the things that they build, they are smart enough to understand finance, which isn’t all that complicated,” remarks Maultasch, whose approach is notable as much for what it does focus on as for what it doesn’t.
By exploring a framework for discounted cash analysis, Maultasch rejected the more traditional point of engagement for incoming CFOs: the company’s future IPO.
“The IPO is an important milestone, but it’s not the destination,” notes Maultasch. “The destination is building a generationally important company that adds value in the long run. I want to help our people understand that the durability of cash flows is what drives long-term value creation.”
Once armed with a deeper understanding of discounted cash flows, Maultasch says, employees at large can bring forth more of the insights, processes, and technical solutions that are needed to move the levers of value creation.
“I want to align our conversations around durability and long-term margins. These are the levers that move our revenue, move our profitability, and move our position in the value chain,” he adds.
According to Maultasch, an added benefit from “teach-in” discussions is that they sometimes expose what the finance team has gotten wrong.
“Some of the things that we thought were inputs turn out to be outputs,” he observes, “so it’s this process of discussion, argument, and learning that aligns everyone toward building a great company.” –Jack Sweeney
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CFOTL: Tell us about MOLOCO … what does this company do, and what are its offerings today?
Maultasch: MOLOCO is a machine learning company in the ad tech or advertising tech space. Our founder, Ikkjin Ahn, is a machine learning pioneer. He was one of the earliest machine learning engineers at YouTube shortly after it was acquired by Google. He built the first machine learning products at YouTube and then created the monetization stack, which was the way in which they sold and optimized ads via machine learning. Then he was an early employee at Android, at Google Shift over there, where he built their entire data infrastructure. So, he really had an early view on the power of machine learning to drive digital advertising.
Read MoreFast-forward, and the reality is that Google and Facebook won digital advertising. Those two companies combined take more than 50% of the digital ad dollars, and part of this is the wonderful owned and operated properties they have. But this explains only about half of their scale. The machine learning optimization that they built to target the right customers—to put products in front of people that turn into transactions—that’s the difference. If you look at Facebook’s RPU—revenue per user, or the revenue that they’re getting from each customer on their platform—you see that it is about five times higher than that of Pinterest and three times higher than Snap’s. This differential on a per-user basis comes from the power of machine learning.
Ikkjin founded this business to take this wonderful technology that nobody else was going to have the skills or the capital to build and put it in the public cloud so that other businesses could build on top of it and use their first-party data to optimize their ad buys and ultimately their ad businesses. So, in the reductive form that I sometimes use to explain it to investment bankers, we’re like The Trade Desk for performance advertisers, and our long-term vision is to be more like a Twilio for machine learning–based ad optimization.
jb
Moloco | www.moloco.com | Redwood City, CA