Venture capital is often lightheartedly referred to as an art, not a science. It is extremely hard to quantify the ideal investment because startups operate in emerging markets with very few concrete and calculable insights. Oftentimes this difficulty leads venture capitalists to work on gut-instinct, not data-driven insights. However, to succeed in an ever-competitive market, it is necessary for businesses to find meaningful and data-driven insights, thus giving them a competitive advantage. This intersection is where business intelligence can play a key role in venture finance.

Business intelligence, in an ideal implementation, should allow a business vertical to interact, understand, and create actionable insights from collected data, Insights should drive business objectives by finding inefficiencies, growing opportunities, and creating a consistent decision-making process. As I have stated, one industry in need of a business analytics revamp is venture capital. Nevertheless, the headwinds when applying business intelligence to venture finance are innumerable – private investments details cause insufficient data sets, unstructured data needs complex text mining, emerging markets lead to difficult market analysis, and the companies probably haven’t even collected revenue.

However, these headwinds do not stop innovation in the space. There are segments of venture capital that are very suitable for immediate application of machine learning algorithms and BI insights. A recent article from TechCrunch highlights a new venture capital fund in Berlin, Fly Ventures, that is utilizing machine learning to deal source new companies. Typically, deal sourcing is a very labor-intensive process. A venture capital fund relies on network connections to source deals or waits for entrepreneurs to seek out funding. Fly Ventures turns this paradigm around – rather than relying on this manual process, they have a machine learning algorithm scrape blogs, accelerators, and other internet resources to proactively find deals. Then, as TechCrunch describes, the program presents the results, “in a Tinder like interface that lets [Fly Ventures] quickly decide whether [they] want to speak to a company.” The article does not clarify, but optimally the machine learning algorithm would learn from their choices to tune its ranking operation. This is just one example of business intelligence allowing for a competitive advantage in venture finance. By using this business intelligence approach, they are now on the hunt, actively seeking out and investing in companies before other funds can find the startups. Without competition from other funds, Fly Ventures can lead the investments and invest at a lower price because there is no competition from other funds.

Business intelligence plays a key role in almost every industry. The insights that are derived from these analytical approaches can give a company the competitive advantage that allows them to beat out competition. I believe that in the future, we will see more and more data-driven venture capital funds that are advantaged because of business intelligence. It will lead to more consistent investments, earlier connections to startups, and allow entrepreneurship to thrive.

Article Citation:

O’Hear, Steve. “Fly Ventures, a Berlin-based VC using machine learning to find its next deal, closes $41M fund.” TechCrunch. December 21, 2017. Accessed January 16, 2018.