This Small Business Innovation Research Phase I project is to develop a framework designed to assist high tech entrepreneurs and angel investors in the early formative processes of a venture. The framework combines application software and tools structured and unstructured experimental databases, and a collaborative networking infrastructure - a social network of entrepreneurs and investors. Starting up a rapid growth technology company is a risky proposition. Entrepreneurs jump into a high-pressure, high-stakes realm where decisions are made using dynamic, imperfect information while aiming at a moving target. If a framework could be developed to increase the success rate of such ventures, it may have significant impact. The proposed framework is based on a: 1. software model garnered from observation of thousands of live startups; 2. collaborative network of entrepreneurs and investors who use social networking technologies to distinguish winners from losers; 3. suite of data mining tools to compare one startup?s experience with historical data. The project intends to develop a software implementation of that model, which must be tested and refined using company data.
If high-growth entrepreneurship is an engine of economic growth, the project's immediate aim is to fine-tune that engine's performance, removing friction where it currently exists. The framework seeks to increase startup success rates by empowering the entrepreneur to make informed decisions. The effort also offers investors the power of its framework to select the best projects, and later monitor their progress. The predictive models and collaborative decision making could help savvy investors improve their average ROI significantly.
