One of established-company Facebook's many offices.

Curators often ask if established companies should be included in their communities' dataset.

The short answer: yes.

What is an established company?

For the purposes of this post, “established companies” are companies that are simply no longer a startup. They’ve successfully transcended that stage of their growth. If you subscribe to Steve Blank's definition of a startup, established companies have found their repeatable business model and how to scale it. If you subscribe to Eric Ries's definition of a startup, an established company is no longer operating under conditions of extreme uncertainty, has found its product/market fit and knows how to mitigate risk. An established company is likely to have hundreds of employees. A company's transition from startup to established company may have happened within the last few years (Facebook) or more than a hundred years ago (John Deere).

Why should we include them?

Startup Genome is a set of tools for understanding your entire startup ecosystem. Established companies are part of that ecosystem in several ways:

1. They were once startups themselves. We’re tracking startup communities as they grow and recede over time and these companies are a key element of that history.


2. They invest in and acquire startups. We don’t often think of companies as “investors” but many invest in startups via their corporate venture funds. Also, tracking acquisitions is an important part of the aforementioned history.


3. Established companies hire talent from startups and startups hire from established companies. The talent pipeline goes both ways and talent is the heart of any startup community.


4. Established companies make for great sponsors, judges and mentors at startup events.

NOTE: We’re working on a company genealogy tool that will help track these relationships in your community and elsewhere. Look for that down the road.

There’s a lot of established companies, are we mapping them all?

It would obviously be impossible to map them all, so start with those that participate in your community in ways similar to the four points above. We seeded the maps with data from CrunchBase which includes a lot of established companies who hit points 1 and 2. Others get added when someone who worked for one of these companies imports their LinkedIn work history and that represents point 3.

Categorization is important.

While its hopefully clear by now that we want to recognize the participation of established companies in your startup community by including them in the map, we want to make sure they categorized appropriately. The same is true for small businesses. This allows anyone working with the dataset to simply filter them out if they truly only want to look at startups.

Also, just a heads up that the community statistics page only takes into account  organizations classified as startups. Keeping every record classified correctly goes a long way in making sure that data isn’t skewed.

Photo Credit: eston on Flickr