It's still early... very early
Five indicators that we are early in the technical transformation
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Investment in technology companies, as well as liquidity events (e.g., IPOs) have hit all-time highs. As a result, it is easy for people to scream “it’s a bubble”.
Asset prices may very well be over-extended, but it is a mistake to use historical performance as the sole indicator. In reality, we are in the midst of many digital transformations at once, and when you zoom out, there are many reasons to actually believe we are still very early. Consider these five indicators:
Internet access
Affordable technology
Coding literacy
Concentration
Scale
Let's walk through them one-by-one and talk through the data.
First, let's consider the most basic stepping stone: an internet connection.
Notice how much of the world still lacks internet access. China has <60% of the population online. India has <40%. Most of Africa has <30%. It is estimated in January 2021 only ~60% of the world had internet connections.
When you look at the locations with low adoption, like Africa, you realize it is a coverage issue. In many parts of Africa, there is no internet coverage, and there are very few countries with +50% coverage. This is why technology like Starlink is so critical. There are still billions of people waiting to come online and contribute.
Even if you do have access to internet, can you afford the hardware? What about software required to build products? Compute?
For basic smartphones, some countries, particularly in Africa, can be 10+ days of wages. In India, it is 63 days of wages. That requires setting aside 100% of your wages for at least two months!! Imagine how expensive it gets if you want a computer or additional add-ons.
Thankfully, we know this trend is headed in the right direction. For years (and decades), the cost of a computer has been decreasing. If we use TVs and software as a proxy in Exhibit 3, we know the cost of technology will continue to become orders of magnitude more affordable, unlocking opportunity for emerging countries. We are already seeing this end of the curve with computers like the Chromebook.
And if we consider Moore's law, we know the cost of compute continues to decrease over time. Exhibit 4 may seem complicated, but the point is quite simple.
X-axis = Time
Y-axis = Cost per MSOPS (Million standard operations per second)
Basically, we are plotting how expensive is it to run a preset number of computations. The key takeaway is the slope of the plot. Over time, the cost for that much computational power is decreasing significantly.
Reducing the cost of hardware, software, and compute are critical to getting more people online. One of the great examples of lowering the hurdle to get people online is JIO.
Exhibit 6: A thread on the JIO effect
JIO gave Indians 4G internet access… for free. Within four years, they gained 400 million customers! Within that same time, the total number of internet users in India doubled!
In the next few years, let's say Starlink gives you internet access, and the cost of technology drops. The next step is being to build. This (barring some no-code tools) requires coding literacy.
Daxx estimates the number of software developers globally is only ~27M (left-hand side). There are of course people with the ability to code that are not full-time software developers.
Let's say for every software developer, there are 10 people that know how to code (maybe a slight overestimate). By these estimates, <5% of the population is programming literate. Likely even significantly less.
Will coding literacy ever hit 100%? No. But even if it hits 20%, then we could see a +7x jump in creators (millions of programmers) enter the ecosystem.
The fourth indicator is the concentration of capital investment. Everyone knows the Bay Area has been traditionally an absolute juggernaut.
California (and the Bay Area specifically) dwarf other states in venture investment. But lately (with Covid as a catalyst), the share of total capital is shifting to other places.
Additional states like Michigan, North Carolina, Florida, Texas, and others continue to see increasing growth in capital. The opportunity is spreading.
This is playing at a global scale. Similar to California, the United States as a whole dominates the global venture market.
We have spoken at length at the opportunity for growth in users in both India and countries within Africa, but from exhibit 8, you can see the capital is still overly concentrated in the US.
There are, however, indicators that the balance is shifting, with recent reports suggesting +50% of total deals were executed outside of the US.
Exhibit 11: Over half of venture funding outside of the US
These are already big numbers. The scale overwhelms people. Did other countries already miss the wave? This leads us to our final indicator: scale.
David Friedberg gave the best example on the All-In Pod that I have heard. The global equities market reached $95T roughly a year ago. The Dow Jones is up ~15% since then. So let's assume the number is +$100T just to be safe.
If the capital above (~$600B) makes a ~2.5-3X on average return, then every year ~1-2% of the total market is being disrupted. That's significant value creation, but relative to the overall size of market, it is not as crazy as it may originally sound.
Conclusion
We are undergoing many revolutions at once. Artificial intelligence. Crypto. Web3. It’s crazy.
But there are five key indicators that we are still early in the technical transformation process. The first three indicators are truly focused on adoption. The last two have been capital access constraints.
Building tools and solutions to improve all five will be critical to A) accelerating technical transformation and B) ensuring everyone has participation in the wealth creation (more to come on this).