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On September 5, 2024, the Dutch VC community VEECEE held an event on data-driven venture capital at Google Cloud Amsterdam that kicked of with a roundtable, exclusively for the partners of the region’s most successful funds. During the roundtable discussion led by Lisa Brouwer, investment manager at Curiosity VC, the focus was primarily on the tools VCs can use to gain insights and make data-driven decisions. Not all tools seem to be equally satisfactory. “You’re better off using LinkedIn.”
Nearly every sector is undergoing a digital transformation, and the venture capital sector is no exception. More and more VC firms are embracing advanced analytical tools and techniques to support investment decisions, optimize portfolio management, and improve other VC operations. This is no surprise, as the potential benefits are substantial.
To begin with, a data-driven approach ideally leads to more efficient and effective investing. Data-driven tools help VCs – still ideally – identify promising startups by using advanced search platforms that employ AI and machine learning. These tools can find potential investment opportunities based on specific criteria. Additionally, repetitive tasks, such as screening pitch decks, can be automated. The data-driven approach also leads to better decision-making. By analyzing data on factors such as market growth, team development, and funding rounds, VCs can spot opportunities earlier. Moreover, data analysis can help reduce subjectivity in investment decisions by focusing on measurable criteria and trends.
More efficient portfolio management is another advantage. Data-driven tools support VCs in monitoring their portfolio companies, analyzing performance, and identifying potential risks or growth areas. Fundraising and relationship management also benefit from a data-driven approach. Data can be used to improve the targeting of potential investors, for example, by employing a chatbot on the site to gather information about potential investors. Furthermore, data analysis can provide insight into the interests and priorities of existing LPs, which can contribute to building stronger relationships. Tools can streamline communication with investors through automated reports and updates on portfolio performance.
Popular Tools
It’s no wonder that data-driven tools are widely used. Not only the well-known PitchBook (for financial analysis), but also lesser-known tools such as Specter, Venturelytic, Rundit (platforms for portfolio management, analysis, and reporting), and Bunch (an all-in-one platform for fund managers) or Pipedrive (a relationship management tool, not specifically developed for the sector, but usable for establishing and maintaining relationships with – for example – co-financiers). In theory, these tools can be useful in all phases of the investment process, from initial market exploration to the portfolio management phase.
Unfortunately, practice often lags behind theory, mainly because the tools are not always equally powerful. Often, their developers are startups themselves, and their software is simply not mature enough. And when the software does come from an experienced supplier, it’s often a general tool that has been tweaked for VCs, and doesn’t fully meet the customer’s needs. An example is Specter, a tool that, according to the provider, ‘offers real-time insights and trends in private markets’ and ‘provides VC firms with actionable information about private companies’. Sounds good, but according to one of the participants, Specter’s information is often one or two weeks behind current events. “You’re better off using LinkedIn.” There’s also criticism of the costs, which smaller VCs particularly struggle with. One participant notes: “We see that large VCs are gaining an advantage through their investments in technology. It threatens to become an uneven playing field.” The solution? “Maybe we should take out joint subscriptions,” is suggested.
Nevertheless, the data-driven venture capital firm is the future. Mainly because in a data-driven venture capital firm, there is more time and attention for the human aspects of the work. And this is still a ‘people’s business’, as one of the participants says: “I don’t think I’ve ever scored a deal because I was the first. It’s because it was a good match with me and my knowledge and the rest of the team.” And the less time you as a fund manager spend collecting and plowing through data, the more time you can allocate for contact with others. “I see it as a way to gain time that I can spend building and maintaining a personal network.”
Fully Data-Driven VC?
Still, some attendees think that in the future, venture capital firms may emerge that become fully data-driven, just as there are now credit institutions that decide whether to honor a credit application based on data – in their case, mainly payment data. Why, analogously, couldn’t a venture capital firm also fully automatically handle investment applications? “I think some venture capital firms could even make this their USP.”
It seems more likely that the advance of applications to process data will continue – what about tools to analyze the character traits of entrepreneurs looking for investors, for example? – but that this will not displace the human aspects of the work. That the importance of empathy, analytical ability, and social intelligence will not disappear as venture capital firms become more data-driven. On the contrary, one of the participants thinks: “Rather, the firms that increasingly benefit from this in dealing with others will have an advantage. Because being data-driven will become a given for every venture capital firm in the future, not a distinguishing feature. That distinction lies in the people who work there. The people who, thanks to the data-driven nature of the venture capital firm where they work, have all the space to display their humanity.”
Viewed this way, the future is likely to belong to the venture capital firms that know how to combine the best of both worlds – the power of data and the irreplaceable human touch that makes venture capital so unique. And as the sector evolves, the ability to find this balance will likely make the difference between successful and less successful venture capital firms in the data-driven era.