Conyac で依頼された翻訳結果を公開

A much larger ecosystem will mean nodes of social proof will be overflooded and investors will have difficulty sorting through the noise causing many good startups to fall through the cracks.
Increased startup capital efficiency amplifies this problem by enlarging the investment funnel, with a fixed amount of capital needing to be allocated across many more startups. Additionally many of these new startup investors don’t have very good intuition about what a good startup looks like. Benchmarks of the right metrics and automated due diligence tests can allow inexperienced investors to approximate the intuition of of more experienced investors, and can save precious time for the more experienced. A data driven approach looks to be a piece of the puzzle to handling increasing deal volume and establish scalable standards. One distinguishing characteristic of data applications is they get more useful the more they are used. The Investor Compass relies on benchmarks from the Startup Compass, and since we launched it a few months ago data the product has been used by over 17,000 businesses. We believe this shift to a quantitative alternative with the Investor Compass is a major step towards opening up the data driven business frontier. Considering this frontier is fast approaching we should put into perspective some of the limits of data tools, especially when applied to the innovation space. First of all, since startups evolve along developmental stages where the fight for a startup is mostly against itself, then predicting success in the early stages is not a goal worth aiming for. Each stage presents its own new set of challenges, and success in one stage rarely makes a company any more likely to succeed in the next. For instance, just because a product has strong uptake with early adopters, doesn’t mean they are going to be able to successfully scale the company from a marketing or organizational perspective.