Venture capital is a “hit business.” The relatively few hits pay for the flops. And it’s the tantalizing possibility of a mega-hit that animates the industry, that keeps investors dreaming, prospecting and writing checks. For venture capitalists, it’s the hits and the mega-hits that make the high flop rate tolerable.
But is frequent venture failure inescapable? Could a probabilistic approach based on big data, machine learning and advanced computing do better?
Thomas Thurston, a data scientist and CTO of venture firm W.R. Hambrecht, is someone who “look(s) at things the way they are, and asks(s) why?”* Speaking in New York recently at Tabor Communications’ HPC & AI on Wall Street conference, Thurston discussed his data-driven, decade-plus quest to take on the venture industry’s immutable laws – not only its high flop rate but also its approach to investment discovery and assessment.