The Success of Startups
It is widely accepted that we are in a “golden age” of information and technology. With access to so many services at our fingertips, it is no surprise that each new entrepreneur seeks to establish their permanent position in today’s society. Startups and the business of creating startups has snowballed in the last decade or so as people strive to come up with the next Facebook or Twitter and “get rich quick”. Erin Griffith writes an article named “Why startups fail, according to their founders” on Fortune.com that discusses the often short lifespans of such startups and, as the title suggests, why they fail. Generally speaking, nine out of ten startups will fail. To the average consumer that may seem like a large percentage, but in light of the number of startups that are created on a yearly basis it is not surprising that so many fail. Griffith quoted a study done by CB Insights that processed 101 startup failures and determined that the largest reason for failure was that there simply wasn’t a market for the product. While this may seem like a trivial reason that most startups would consider before even venturing forth on their product/service, often it is not as easy to predict or companies may rely too much on their ability to market their idea.
The initial growth or lack thereof of startups has direct applications from the study of networks. The second biggest reason cited by founders for their failure was running out of cash. In reality, its not necessarily that there wasn’t enough capital, but more that the company did not grow quickly enough to gain more capital or start turning a profit. This is paralleled in our study of network dynamics and tipping points in relation to network effects. Prior to the first equilibrium point, there was generally a downwards pressure that forced demand to decrease. In comparison, the success of a startup depends entirely then on if it is able to grow quick enough to overcome the hump that is the first equilibrium point.
Finally, there is always the factor of luck in the success of a startup which is embodied wholly by the rich-get-richer process. If somehow a startup gains enough traction to be recognized by a significant portion of consumers, its consumer base will grow as it will have the advantage of being referred to by its already established consumers.
Thus, a modeling startups under the influence of network effects subject to network dynamics allows for a reasonable prediction of whether startups will succeed.
http://fortune.com/2014/09/25/why-startups-fail-according-to-their-founders/