The Types of Network Effects Explained

What do Apple, Alibaba, and Visa have in common? All American companies? Nope. All tech companies? Not really. All three have a lot of cash? Yeah, but c'mon, that does not count. These companies have all leveraged network effects to become what they are today now, consistently ranking high in the list of the most valuable companies in the world year in and year out.

What network effects unlock for us

Network effects refer to a phenomenon whereby the value of a good, a service, or a platform increases as the number of users grows. Before diving deep into what these forces are, it is essential to understand the two types of value we derive from goods and services with network effects.

Inherent value

This corresponds to the kind of value an individual derives from using a good or a service. This is the value we enjoy from just solving a pain by using a product for the job it was designed for. Think about your favorite video game. It's a source of entertainment for you, giving you a much-needed distraction from life, even when you play in the single-player mode all by yourself.

Network value

This is the compounded overall value derived from a good or a service when it is used by a community. To continue with the video game example, platforms like Steam help you unlock the network value hidden in your favorite game. You can tap into the game modes developed by your fellow gamers, exchange in-game items with them, and form online tribes you can take to other games. Network value builds upon the inherent value and enriches it to such an extent that the product feels transformed.

Tech companies have become particularly good at combining these two. They first develop killer products that deliver users instant value from usage. Then, they layer the network value on top of that, revealing a new set of benefits once the product becomes popular in a community of users.

A good example would be Twitter. You could use Twitter as a microblogging service if you had no other contacts on the network. However, the presence of a network, the likes, retweets, and the embedding function completely transform the Twitter experience, turning it into a habit-forming product. The network effects are the difference between an isolated personal microblog and an addictive social media app.

Types of network effects

Although sometimes grouped into two categories (direct and indirect), network effects make better sense when they are classified into three types:

Direct network effects

Direct network effects describe the increase in value users get to enjoy thanks to the growth of a network. For example, the bigger your LinkedIn network is, the more valuable it becomes for you with regard to accessing knowledge or becoming aware of job opportunities.

These effects are particularly prominent in communication networks and let you see Metcalfe's law at work. Metcalfe's law states that the value generated by a network is proportional to the square of the number of nodes in that network. Therefore, as the number of users with a phone line, fax machine, or WhatsApp on their phones increases, the network comes to generate increasingly more value for the existing users.

Indirect network effects

Some network effects are more subtle and operate in more mysterious ways than direct network effects do. However, despite not being out in the open, their impact can be astonishingly significant. Indirect network effects occur when increased usage of a product or a service creates value for another product, which, in turn, adds to the value of the first product. Andrew Cheng provides an inspirational example to this phenomenon in his book The Cold Start Problem.

IBM struck a deal with Microsoft in the 1980s for a partnership that would change the tech industry forever. According to the deal, IBM's hardware components and applications would work on the MS-DOS operating system. The deal required Microsoft to develop a custom operating system for IBM PCs. An underestimated clause in the agreement gave Microsoft the right to sell the operating system it would build for IBM to other brands (The Cold Start Problem, pp.120-22).

This clause triggered a chain reaction.

• Manufacturers copying IBM's proven formula also inadvertently started developing products compatible with MS-DOS.
• Users appreciated the wide range of applications on PCs that came with MS-DOS.
• With more people using PCs running on MS-DOS, developers were incentivized to prioritize developing applications for this particular operating system.
• Of course, manufacturers would not be indifferent to this sea change. They licensed MS-DOS because products running on MS-DOS were what customers demanded.

Microsoft had successfully built an ecosystem around MS-DOS, with users, developers, and PC manufacturers deriving value from it. This clever game plan created a sustainable, lucrative business on top of indirect network effects. Using this blueprint, Google and Apple were able to leverage Android and iPhone, respectively, to tap into the app store business.

Two-sided network effects

Two-sided network effects exist in platforms that bring together two distinct groups of users, like buyers and sellers, or drivers and riders. The increase in the number of one group creates more value for the other.

Ride-sharing platforms provide a good case in point. When more drivers join these networks, it becomes easier for customers to find a driver nearby, bringing down the estimated time of arrival (ETA). The same phenomenon applies to marketplaces like Amazon and eBay as well. As the number of sellers on these platforms increases, buyers enjoy a wider range of options and lower prices.

However, the value resulting from two-sided network effects tends to be asymptotic, that is, the growth in the supply side (sellers or drivers) results in diminishing returns. Having 200 different options, though, is not necessarily better as it will lead to confusion. Likewise, an Uber driver showing up at your door in 5 minutes is ace. But an ETA of one minute will not generate extra value as you will still take a few minutes getting prepared before going out.

Final thoughts

Analysts at the venture capital firm NfX conducted a study of digital companies from 1994 to 2017. They concluded that companies relying on network effects were responsible for 70 percent of the value created in the last 25 years. From American and Chinese social media platforms to Google and Tesla, it is difficult to think of a company that has dominated its respective industry without taking advantage of network effects in the last quarter century.

But what exactly do these forces do for companies? What do they bring to the table that catapults its practitioners into industry leadership? The answers to these questions justify another blog post. Stay tuned.