Why Data Is Eating the world

Why Data Is Eating the World

by?Luke M Norris (An Honest Imitation of Marc Andreessen's "Why Software is eating the World)

Data is eating the world.

More than 14 years after the peak of the 2008 housing bubble, a dozen or so new Data First Artificial Intelligent companies like Databricks and Scale AI are sparking controversy in Silicon Valley, due to their rapidly growing private market valuations, and even the occasional successful IPO. With scars from the heyday of Yahoo and Groupon still fresh in the investor psyche, people are asking, “Isn’t this just a dangerous new bubble?”

I, along with others, have been arguing the other side of the case. (I am the founder of Faction, which has invested in technology and services to support the worlds largest data sets in the Multi-Cloud) We believe that many of the prominent Data First companies are building real, high-growth, high-margin, highly defensible businesses.

Today’s stock market actually hates Data Driven AI companies, as shown by all-time low price/earnings ratios for major public Data Driven companies. Starbucks, for example, has a P/E ratio of around 18.9 — about the same as the broader stock market, despite Starbucks’s immense profitability and dominant market position (As of November 2021, the company had 33,833 stores in 80 countries). And, perhaps most telling, you can’t have a bubble when people are constantly screaming “Bubble!”

But too much of the debate is still around financial valuation, as opposed to the underlying intrinsic value of the best of Data First AI companies. My own theory is that we are in the middle of a dramatic and broad technological and economic shift in which Data First companies are poised to take over large swathes of the economy through enhanced decisions and predictive capabilities of Artificial Intelligence.

More and more major businesses and industries are being run on Data First decisions and delivered by Artificial Intelligence — from coffee shops to supply chain logistics to national defense. Many of the winners are first movers, entrepreneurially minded companies taking advantage of the largest data sets that are invading and overturning established industry structures. Over the next 10 years, I expect many more industries to be disrupted by Data First AI Driven companies, with new and old companies doing the disruption in more cases than not.

Why is this happening now?

Eight decades into the computer revolution, six decades since the invention of the microprocessor, and four decades into the rise of the modern Internet, all of the technology required to transform industries through Data First Artificial Intelligence finally works and can be widely delivered at global scale.

Over four billion people now use the broadband Internet, up from perhaps 50 million three decades ago, when I was at Silicon Graphics Inc. In the next 10 years, I expect at least 41 billion Internet of Things devices worldwide by 2025, generating 79 Zettabytes of Data.

On the back end, Data management tools and Cloud-based services make it easy to launch new global Data First start-ups in many industries — without the need to invest in new infrastructure and train new employees. In 2005, when my partner Sean Charnock was co-Founder of the first hyperscale cloud computing company, Softlayer, the cost of a customer running a basic Internet application was approximately $15,000 a month. Running that same application today in Amazon’s cloud costs about $150 a month.

With lower start-up costs and a vastly expanded market for online services, the result is a global economy that for the first time will be fully Data First — the dream of every cyber-visionary of the early 1990s, finally delivered, a full three generations later.

Perhaps the single most dramatic example of this phenomenon of Data eating a traditional business is the suicide of Blockbuster and corresponding rise of Netflix. In 2005, Blockbuster had the opportunity to buy Netflix for 50 million.

Oops.

Today, the world’s largest retailer, Amazon, is a Data First company — its core capability is its amazing Cloud Service AWS, which leads in Data First capabilities S3, Sagemaker and 100s more services. On top of that, while Blockbuster was thrashing in the throes of impending bankruptcy, Netflix rearranged its web site to promote Data First recommendations of DVDs by mail and soon delivered online via Amazon's AWS.

Today’s largest video service by number of subscribers is a Data First AI company: Youtube. How Youtube started is an old story, but now other traditional entertainment providers are facing the same threat. Others are responding by leading Data First AI via extremely effective and tailored algorithms on recommending videos such as TikTok.

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At this point I hope you get the imitation, much as software had done but even more with traditional businesses that are willing to transform to Data First businesses will own their industry through harvesting incredibly large and insightful data moats via Artificial Intelligence. New companies that will implement new processes around Data First AI capabilities will disrupt older ones that don't move fast enough.

But unlike the software revolution, the Data First AI driven revolution will create incredibly large moats of differentiation driven by the asset value of the Data and the insights the AI derives from it. We predict industries will see more winner take all in the Data First AI paradigm, with a significantly harder barrier to over take for the lagger second and third mover companies. First movers succeed in Data First AI will create an even larger intrinsic share of profits, margin and value creation that probably wont be able to be made up by the laggers.

That’s the big opportunity. I know where I’m putting my money.