The Data Network Effect for Crimefighting

Think of what it would have been like to be the first person with a telephone. It probably wouldn’t have been that useful without anyone else to talk to. But if you were the one millionth person with a telephone, it was a lot more useful. The telephony network is a simple example of a point-to-point network effect, where the value it provides increases as more people join it. You will be familiar this with other services you use in your life like Facebook and LinkedIn.

Another type of network effect is a double-sided marketplace where there are typically buyers and sellers like eBay, AirBnB, and Uber. If we take Uber as an example, there are people who need a ride somewhere (buyers of a service) connected with people who will drive passengers somewhere for money (sellers providing the service). This type of network effect can be more challenging to build as you need to bring on both buyers and sellers, but as users can attest, they are incredibly useful when achieved.

Data network effects go one step further where a shared pool of data increases in utility as more people add data to that pool. Take Google search as example. Chances are when you search for something, it returns what you want within the top three search results. But there are literally millions of web pages out there, so how does Google do it? One method Google uses is to rate search relevancy. For example, as each person performs a Google search and clicks on a result, Google tracks how long the person visits that web page for. If the person stays on the web page for a long period of time, the relevancy rating goes up against the keywords in the search term. As more people perform more searches, Google gets more data points to continue to improve the usefulness of their search results.

Danny Gilligan and Rohen Sood from Reinventure

In our very first podcast, Reinventure’s Managing Partner specialising in data investments, Danny Gilligan, discuss these concepts in more detail with Rohen Sood and explores the power of data network effects and their application to crimefighting.