Why The Future Of Venture Capital Is Quantitative
Ismael Hishon-Rezaizadeh is the Head of Data at Renegade Partners. He architects and leads data-driven investment strategies.
In an industry predicated on backing the boldest entrepreneurs and the biggest ideas, there has paradoxically been a stagnation in the adoption of new technologies and data strategies by venture capital firms. Today, most venture capital firms operate the same way they did 10 years ago. Also, 58% of deals are still sourced through professional networks and references, and so due diligence is done devoid of competitive benchmarks, and many of the top partners still defer to their “Midas touch” as the rationale for their decisions. In fact, according to PitchBook’s 2019 survey, only 38% of firms currently use data as part of evaluating all of their investment decisions.
While no one doubts the historical efficacy of these approaches, their staying power in a world where decisions are increasingly made through data has been called into question. For firms relying on traditional approaches, their success is predicated on information about hot deals propagating to their partnership before any data reaches one of their competitors.
The industry is bifurcating into the firms built to leverage data-driven insights and those that aren’t. To data-aware firms, every credit card transaction, every app download and every social follower is a signal they can analyze to better understand markets and maximize returns for their limited partners (LPs). To most firms, though, these signals go unnoticed.
Many of the largest firms have already begun building out engineering teams and hiring top data scientists to operationalize their treasure troves of decades-old portfolio company financial statements and KPIs. Still, most of the boutique firms and angel syndicates that make up the majority of the early-stage venture ecosystem have yet to catch on.
A Centralized Data Advantage
The explosion in recent years of companies selling new forms of alternative data directly to private market investors has driven the early adoption of data by many firms. The most valuable data sets, though, are the proprietary growth data and KPIs that are being collected from across the portfolio of top firms.
Firms investing in capturing and structuring this proprietary data today are building out a defensible moat for the future. When they assess investments 10 years from now, they will have a decade of longitudinal KPIs to benchmark them against. Boutique firms will soon not only have to compete with larger and better resourced competitors but also with an insurmountable data advantage that is already accruing to forward-thinking firms.
As the gap in analytics materializes into a gap in LP returns, institutional capital will become increasingly centralized in the hands of firms that have preemptively built their data moat. The flywheel this process creates may slowly squeeze boutique firms that are unable to adapt out of the industry.
How Firms Are Building For The Future
Firms building around data-centric strategies today are structured very differently than traditional firms. A savvy firm can hire a team of data scientists, software engineers and ML practitioners for a fraction of the cost of hiring the armies of pre-MBA analysts and post-MBA associates traditionally responsible for sourcing deals.
By driving down the per unit cost of making an investment, firms can redeploy resources into supporting their portfolio companies. For entrepreneurs, the equation is simple, the more resources a firm is spending on finding and making investments, the less resources it has available to support those investments. As firms automate aspects of their deal process, they can scale out their portfolio support teams and networks of advisors.
Preparing your firm for the future doesn’t require a large upfront investment. Hiring a single data scientist and implementing simple practices to organize your data is enough to put most firms on the right track. Firms should start by looking closely at their current processes to identify areas of inefficiency where data can help. Common areas where firms leverage data include generating deal flow, benchmarking company performance and sourcing talent for their portfolio.
The most difficult part of transitioning a firm to leverage data-driven practices is implementing a culture that supports effective use of data. If the data suggests a potential investment is performing below industry standards but a partner likes the company, should the firm make the investment? Is the partner wrong or is the data wrong?
In a healthy culture, the partnership group is willing to discuss discrepancies between their view and what the data shows. The question of who is wrong is moot, so long as a discussion takes place and both perspectives factor into the decision. A word of caution, though: If your interest in data is as a tool to provide you reassurance in making the decisions you were already intending to make, the value of a quantitative approach to your firm will always be inherently limited.
Venture capital firms building themselves for the future see analytics and automation as an addition to their talented investment teams, rather than as a threat. There will always be a need for great investors who make bold bets on ambitious entrepreneurs, but top-tier returns will go to individuals who find a balance between their instincts and data. While the industry as a whole will never be automated, data and analytics are poised to play an increasingly essential role in how decisions are made by top firms.
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