With Zomato’s listing, Indian investors are required to get their head around how to value businesses which don’t yet make money yet are being sold the long term story around ‘winner takes all’, thanks to network effects. Whilst it is increasingly clear that in the digital age, network effect is perhaps one of the stronger sources of sustainable competitive advantage, it is often very loosely used. A venture capital firm in California whose investing philosophy is based on network effects (they even call themselves NFX) has attempted to build and share a better understanding of network effects. This long read as is titled is more like a manual for network effects and as the author humbly submits is still evolving. But it does give a neat framework with lots of examples for all of us to think about and build our own understanding of this powerful force in an increasingly digital world.
“Our three-year study, which we released recently, shows that [Network Effects] nfx are responsible for 70% of the value created by tech companies since the Internet became a thing in 1994. Even though they are only a minority of companies, companies with nfx end up creating the lion’s share of the value…
…the simplified definition of network effects is that they occur when a company’s product or service becomes more valuable as usage increases.”
The manual makes a clarification upfront:
“Network effects are not viral effects. Network effects are about creating defensibility, and viral effects are about getting new users for free. They have totally different objectives and playbooks.”
The manual identifies 13 different types of network under five broader categories –
- Direct Network Effects
- Physical (Eg: Infrastructure such as road, rail, telecom)
- Protocol (Eg: Fax, VHS, Ethernet, Bitcoin)
- Personal Utility (Eg: Instant messaging such as Whatsapp, SMS)
- Personal (Eg: Facebook, Instagram, LinkedIn)
- Market network (Eg: Honeybook, Angellist)
- 2-sided Network Effects
- Marketplace (Eg: eBay, Alibaba, Visa, Mastercard, Wikipedia)
- Platform (Eg: Android, Microsoft OS, Nintendo)
- Asymptotic marketplace (Eg: Uber, Lyft)
- Data Network Effects (Eg: Google, Amazon)
- Tech Performance Network Effects (Eg: BitTorrent, Hola)
- “Social” Network Effects
- Language (Google, Uber, Netflix, Bitcoin)
- Belief (Religions, Idealogies, Currencies)
- Bandwagon (Apple, Google, Stripe)
The manual elaborates on each of these and is well laid out with visuals and a summary table at the end listing the properties of each network effect, which makes for good reading.
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