Network effect is “a phenomenon whereby a product or service gains additional value as more people use it”. That is the elemental construct that drives great platforms like Facebook, LinkedIn, and Twitter: if your friends and families are in Facebook, the more valuable it will be to you. Indeed, the population of the users is the most important feature in the platforms, far ahead of any tool. That explains why cloning a product that mirrors Facebook, but without the users, does not offer any value.
The network effect is a phenomenon where increased numbers of people or participants improves the value of a good or service. The internet is a good example. Initially, there were few users of the internet, and it was of relatively little value to anyone outside of the military and a few research scientists. As more users gained access to the internet, adding more content, information, and services, however, there were more and more websites to visit and more people to communicate with. The internet became extremely valuable to its users.
Types of Platforms
I identify two types of platforms based on the relationships among consumers, advertisers, and publishers/producers. They include the following:
- Platform, Unbounded by Geography: In this type of platform, the relationship between the consumers and the producer is not bounded by any geography. This means that as the product scales, there is no inherent limitation on the physical availability of users and producers. Facebook belongs to this group. Its scalability is not affected by the physical location of its users (the consumers) and the producers (the users, also). Also, the advertisers can be from any location. Nothing is bounded by physical geography. This type of platform is very difficult to challenge in local markets as they have moats which no local company can exploit. (Let me call this Category 1).
- Platform, Bounded by Geography: In this type of platform, there is network effect, but the relationship between the producer and the consumer is bounded by geography. There is a limitation on how the platform can scale as it has to deal with the physical-induced marginal cost, and other issues. Uber, the ride-hailing app, is a good example. Also, AirBnB is another example. Uber depends on the availability of riders and drivers to have a business in any city. That is why Uber goes to big cities when it comes to any country (contrast that with Facebook which does not care about your location, to a great extent). Uber wants to have supply of riders and also drivers. You find the mix easily in big cities. The same applies to AirBnB which also needs to have available apartments for its renters. So, that city must have landlords even as it provides a good source of potential renters. That is why AirBnB looks at big cities as it moves into Africa. (Let me call this Category 2).
Local Competition Impacts
The Category 1 platforms are very difficult to challenge locally because they have moats which are not limited by geography. There is nothing a local company can do locally to have an advantage over them. So, most times, you do not have any local competitor to them as everyone has moved to the main (global) platforms.
But Category 2 platforms are very vulnerable. They can be easily dislocalized by geography. In other words, you can have many ride-hailing companies in Africa even when you have no one competing against LinkedIn and Facebook. So, in Kenya, we have Little Cab and in Nigeria, Taxify is challenging Uber. Across the Asian world, Uber has many competitors. It gave up in China when it sold its assets to Didi Chuxing.
Simply, Uber is vulnerable to competition because its business has bounded participants defined by geography. That reduces its scalable advantage to a little below one, even though it is asset-light. On the other hand, Facebook has little to worry when it comes to geography, pushing its scalable advantage to 1 as I noted in the video below.
Any startup needs to model its scalable advantage (SA) to ascertain its capacity to scale and win in the market place. There are many factors which determine a company’s scalable advantage. Some are external like regulation, industry of operation and size of the market. Others are internal and they include marginal cost, supply pipeline, among others. In this video, I explain how to model that advantage by looking at the core transaction frictions between selling and buying. The more the business eliminates the friction, the more scalable it becomes.
As noted for Category 2, the business has impacts associated with geography. They have two sides: Uber with the riders and the drivers; AirBnB with the landlords and the renters. There are many other examples in this category: China’s Mobike, a motorcycle sharing startup is a good example. Even Etsy, the handcrafting retailer qualifies. There are many elements associated with geography, in these firms, either access to the network or the logistics for distribution. I will use Uber and AirBnB as they are more popular in Africa.
To compete against Uber and AirBnB, a local entrepreneur can build a better product because the global network effect of Uber and AirBnB while partially relevant is not absolutely dominating, locally. Uber can have millions of riders in Europe and US but it has none in my village. So, if I go to Ovim (Abia State) and start one, I will be the leader in that locality. Sure, Uber has the brand equity which is huge, but the very fact that it has no driver, I am on top in my village. (That depends if there is a business for that in the village, I hope you get the point.) For AirBnB, where it has no listing, it does not exist and any entrepreneur can build a business therein.
In summary, dislocalization of network effect, i.e. making the localized network effect of global platforms irrelevant, is the way local companies can win. But you need to understand the type of platforms you can technically have any advantage to use local knowledge and expertise to win. There will always be many Ubers around the world, but we will not have many Facebooks.
Uber can lose drivers and riders easily to local competitors because its demand and supply pool are all localized. Unlike AirBnB which has a local supply but globalized demand, challenging AirBnB may be more difficult. Why? You can book your AirBnB short stay, in any city, from any location on earth, while you can only order Uber rider when you are local (i.e. where you need to be picked-up).
That means that Uber demand (i.e. riders) is bounded locally by geography making it easier to compete against Uber, unlike AirBnB which has a global platform that makes it easier for renters, who may not be local, to book. (Africa has many Uber competitors like Taxify, Little Cab etc while AirBnB has few. Sure, AirBnB itself is not even doing well.) That asymmetry in demand access makes a challenge against AirBnB to be tougher while Uber is a fair game. Indeed, the dislocalization of Uber is possible unlike AirBnB.