✍️Takeaways from SuperReturn, SuperVenture & DDVC Breakfast
TL;DR From a Week Full of "Tech in VC"
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Hi there!
I just got back from a crazy week at SuperReturn & SuperVenture in Berlin. It was great to see so many of you at the conference and our fully booked DDVC community breakfast that we co-hosted with Affinity on Wednesday. The next one is already scheduled alongside our Investor Summit at Bits & Pretzels in Munich. Sign up for our breakfast on 30th September here.
But before we jump into future events, I wanted to share with you a TL;DR of the valuable learnings from the week, including takeaways from my two panels and discussions at our DDVC breakfast.
1. Data as a Driver for Smarter Investments in Private Equity
From Dashboards to Decisions: Operationalizing Data in PE
Too often, data ends up as a static artifact—sitting in dashboards, disconnected from the rhythm of real decision-making. But in today’s competitive landscape, data has to shape actions, not just reports. The firms that outperform aren't necessarily the ones with the most data, but the ones that embed data into every critical decision, from sourcing to term sheets to portfolio support.
Seeing What Others Miss: The Power of Unconventional Signals
The strongest signals aren’t found in pitch decks or traditional KPIs—they're hidden in places most overlook. Traffic surges before funding rounds, hiring velocity as a proxy for product-market fit, founder sentiment during moments of stress, even nuanced aspects of founder backgrounds.
When structured and triangulated properly, these unconventional signals offer asymmetric insights that help investors spot breakout potential ahead of the market.
Speed and Feedback: Iteration Over Intuition
In top-performing firms, theory gives way to tight feedback loops. Data teams don’t just hand off insights—they work hand-in-hand with deal and ops teams, testing hypotheses, refining sourcing models, and adjusting theses based on real-world outcomes. This iterative learning system creates compounding advantages: every deal improves the model, every miss sharpens the filter.
The Talent Shift: From Pedigree to Practicality
The talent equation is evolving. Success in data-driven VC doesn’t require a fancy degree or brand-name resume—it requires people who can operate in ambiguity, adapt as new insights emerge, and apply what works with urgency and creativity. The most valuable team members are part strategist, part builder, part detective—people who turn signals into systems and insight into impact.
2. Technology for Your Firm: Using Software to Achieve Better Results
Beyond the Tool Stack: Building a Real Data Advantage in VC
The notion of “proprietary” has evolved.
Five years ago, having your own crawler (see episode “how to scrape alternative data”) or scoring tool (see episode “how to automate startup screening”) might have given you an edge.
Today, those tools are common across DDVC firms. The real differentiation no longer lies in what you use, but how you integrate, orchestrate, and extend these tools into something uniquely powerful.