The new algorithm can predict the success of a start-up company?

Ancient men sought alchemy, and modern investors wanted them to find a way to accurately predict the success or failure of start-ups. Now, a company called substituting science has invented a new algorithm that can make investors dream come true.

The new algorithm does not rely on guesswork, advice, or advice based on years of experience. It tries to extend the "Subversion theory" (disruption germ) to a whole new level. "As far as I know, no one in the world can predict the success or failure of a start-up." Thomas Thurston, CEO of substituting Science, said, "at least there is no quantitative way to predict, all by guessing and inspiration." Thomas Sotton ”

"Business model Emulation" (Business model simulation) as a service without industry-recognized acronyms. Because few people do it. "There are a few people who use simulation software to simulate money flow and supply chains, but it's totally different from us," Sugden said. "Previously, the company did simulations for large, Intel-level companies. But as the simulation process automates the cost, start-up-level companies become its customers.

Substituting science currently 80% of the prediction process is automated. "There is a data that is very valuable in predicting the success or failure of a business model." We used to collect this information by hand. Not only slow, costly and difficult. Sugden explained. "Similarly, we find that 80% of startups ' forecasts are related to external information such as markets, customers, competitors, and only 20% of the data is relevant to itself, which is surprising to most people." Similarly, the team accounts for only 12% of our equation, and the algorithm 88% has nothing to do with who the team is. The reality is that the majority of venture capital VCs are the team's primary factor. ”

This new algorithm is Sugden and "Subversion theory" founder Clayton Christensen (Clayton http://www.aliyun.com/zixun/aggregation/16434.html ">christensen) A joint study at Harvard Business School. Christensen's "Subversive theory" explains why some new companies can disrupt the industry. Substituting science uses this data-scientific theory to study three areas: the probability of business success or failure, growth expectations, and how to change when failures can increase the odds of success.

Although the specific algorithm is highly confidential, Sugden does find some of his favorite companies, such as Dropbox, Tango, Indow Window, Practice Fusion and CloudFlare, and so on.

In fact, some data as a predictive tool is not to throw the decision-making process to the machine, but to expand our way of thinking. It also affects start-ups ' scrutiny of their business models.

Wouldn't it be a bit scary if you knew that there was a company in the world that knew the odds before the product was released? But Sugden said: "It should be so--before you create real products, everyone uses CAD software to simulate new products, and so does business." In other words, it is also a predictive project. ”

(Responsible editor: The good of the Legacy)