Michael Moritz On The Tech Ecosystem | Disrupt SF 2013

TL;DR

A new kind of business, the 'data factory,' now sits closer to consumers than any old factory, runs on unpaid user contributions, and employs far fewer people. It is powered by explosions in bandwidth, storage, computing, and apps: computing power that cost about $33 million in 1973 now fits in a smartphone.

Transcript

uh good morning uh you can tell we're sitting right here in the uh center of the world of technology because this little clicker doesn't work wirelessly it's connected to a bell and then to a light and there's a gentleman that actually moves the slides along so here we are right in the center of the technology Universe um thank you very much for ha... Read More

Key Insights

• The data factory is a new business form that sits in the middle, far more closely connected to consumers than any automobile factory or textile mill, receiving immediate and rich feedback while employing far fewer workers.
• Data factories benefit from unpaid contributions: companies like Google, Amazon, and LinkedIn supply tools that let millions of people enrich the platform for free while the factory pays nothing for that content.
• Computing power that fits in a smartphone would have cost about $33 million in 1973, and those old IBM machines lacked cameras, video, audio, accelerometers, and GPS.
• Storage has transformed dramatically: in 1986 about 14 percent of the world's stored information existed on vinyl records, illustrating how far storage technology has since advanced.
• Applications have exploded over the last 40 years: today millions of apps run on pocket devices, whereas 40 years ago barely 200 computer applications ran on the most popular computers.
• The Industrial Revolution's key change was centralizing tools like the loom into an organized workplace, moving people from self-sustaining farms into factories with suppliers and distribution channels.
• LinkedIn's content strategy shows the model's power: after inviting figures like Bill Gates, the president, and Jamie Dimon to contribute free content, its traffic multiplied eightfold.
• The cost of business tools has collapsed to free or near-free, so functions that were unavailable or cost an arm and a leg a decade ago can now be rented by the sip or obtained at no cost.

Questions & Answers

Q: What is the 'data factory' concept Michael Moritz describes?

The data factory is a new type of business that sits in the middle of an ecosystem, far more closely connected to consumers than any automobile factory or textile mill ever was. It receives immediate and rich feedback, employs far fewer workers than earlier factories, and benefits from unpaid contributions from millions of people who enrich the platform using tools the factory supplies. Examples include Google, Amazon, and LinkedIn.

Q: How much did smartphone-level computing power cost in 1973?

According to Moritz, the equivalent cost of the computing power in a Samsung Android or Apple iPhone would have been about $33 million back in 1973. He emphasizes that those old IBM computers, despite the enormous cost, did not have cameras, video, audio, accelerometers, or GPS. This illustrates how never before have human beings been furnished with tools as powerful as the smartphones people can now buy at the drop of a hat.

Q: How did the Industrial Revolution change the way people worked?

Before the Industrial Revolution, a 1750 farmer worked with his plow aiming for self-sustenance for family and friends, disconnected from consumers, with no concept of an organized workplace. The first phase, beginning in a small part of northwest England, centralized tools like the loom and organized people into factories for the first time. Factories had suppliers, made products for consumers, and installed communication and distribution facilities, but the big change was moving to an organized workplace.

Q: Why do data factories benefit from unpaid contributions?

Data factories supply tools that allow people to contribute and enrich the platform without the factory having to pay for anything. Moritz cites YouTube, Yelp, and especially LinkedIn, which about a year earlier beefed up its content effort and invited notable people to contribute for free. These contributors included Bill Gates, the president, and Jamie Dimon, head of JP Morgan, all providing content at no cost to the platform.

Q: What happened to LinkedIn's traffic after its content strategy?

After LinkedIn beefed up its content effort and invited prominent people like Bill Gates, the president, and JP Morgan's Jamie Dimon to contribute content for free, the result was significant. LinkedIn came to rank among one of the biggest business sites online in the world. Moritz states that LinkedIn's traffic multiplied eightfold thanks to a whole bunch of unpaid contributions, demonstrating the power of the data factory model built on free user-generated content.

Q: What forces enabled the rise of the data factory?

Moritz identifies several powers driving the data factory over the last 10 years. First, an explosion of bandwidth unlike anything seen in any comparable period over 25 years. Second, a transformation in storage, noting 14 percent of stored information in 1986 was on vinyl records. Third, dramatic growth in computing power. Fourth, a massive explosion in applications, from barely 200 computer applications 40 years ago to millions of apps today.

Q: How does the data factory compare to older factories in employment?

The data factory has far fewer employees and workers than earlier examples like textile mills and automobile factories. Moritz presents it as a crude representation where the factory sits in the middle, closely connected to consumers who provide immediate and rich feedback. Unlike blue-collar and white-collar jobs created in and around old factories, the data factory operates with a small workforce while leveraging tools and unpaid contributions from tens or hundreds of millions of people worldwide.

Q: How are digital tools helping individuals and small businesses?

Moritz explains that the price of tools needed to operate a business has collapsed, with most functions now free, close to free, or rentable by the sip, compared to costing an arm and a leg a decade ago. For individuals, tools placed in their hands help people who would otherwise be lost in the low-paid part of the American service economy. He points to examples like Uber, Lyft, and Instacart as services empowering individual workers.

Summary

In this video, the speaker discusses the rise of the data factory and how it is changing the way people work and make money. He highlights the significant advancements in technology, such as increased bandwidth, storage capabilities, computational power, and the explosion of applications. These advancements have enabled data factories to empower individuals and small businesses, providing them with tools to contribute and thrive in the digital age. The speaker emphasizes the profound implications of this shift and discusses the challenges and opportunities it presents.

Questions & Answers

Q: How did the Industrial Revolution change the organization of the workplace?

The Industrial Revolution brought about a significant change in the organization of the workplace. Prior to this period, farmers and workers were mainly focused on self-sustenance and had limited interaction with consumers. However, the rise of textile mills and later automobile factories introduced the concept of centralized workplaces. Factories operated with suppliers and produced goods for consumers, leading to the establishment of communication and distribution facilities. The key difference was the shift to an organized workplace, where individuals worked together in a factory setting.

Q: What are the factors that have enabled the rise of the data factory in the last decade?

Several factors have contributed to the rise of the data factory. Firstly, there has been an explosion of bandwidth, allowing for unprecedented connectivity and data transfer speeds. Secondly, advancements in storage technology have ensured that vast amounts of data can be stored and accessed easily. Additionally, the power of computers and computation has grown exponentially, enabling complex data processing and analysis. Lastly, there has been a massive increase in the number of applications available, providing users with a wide range of tools and services. These factors have laid the foundation for the emergence of data factories.

Q: How have tools and computing power become more accessible and affordable?

The cost and distribution of tools and computing power have undergone a dramatic transformation in recent years. In the past, the computing power equivalent to today's smartphones would have cost millions of dollars. However, with technological advancements, smartphones now provide powerful tools at a fraction of the cost. Furthermore, the size and scope of tools have significantly increased. In the past, industries like automotive and textile production had peak productions in the millions, but now, data factories distribute billions of dollars worth of tools to individuals worldwide. Additionally, the cost of other essential tools for operating a business, such as software and services, has significantly decreased, making them more accessible to small businesses and individuals.

Q: How do data factories benefit from unpaid contributions?

Data factories benefit from unpaid contributions from numerous individuals. Many platforms, like YouTube, Yelp, and LinkedIn, encourage users to contribute content for free. These contributions enrich the data factory's services and content, attracting more users and driving traffic. For example, LinkedIn's invitation to influential figures like Bill Gates and the President to contribute content has significantly boosted its traffic and made it one of the largest business sites online. These unpaid contributions help data factories expand their offerings and increase their user base.

Q: Can you provide examples of individuals and small businesses benefiting from data factory tools?

Many individuals and small businesses have thrived thanks to the tools provided by data factories. For instance, platforms like eBay and Google AdWords have enabled millions of sellers to run successful businesses, generating significant income. YouTube has launched numerous individuals into successful careers, such as Michelle Phan, who has built a thriving business and following. Amazon has transformed small enterprises, like a sled business and independent authors, enabling them to reach a global audience and achieve considerable success. Other services, such as Airbnb, Etsy, and Square, have empowered individuals to generate income and grow their businesses. These examples demonstrate the impactful role of data factory tools in supporting entrepreneurship and economic growth.

Takeaways

The rise of data factories has ushered in a new era of work and opportunity. With the advancements in technology and the accessibility of powerful tools, individuals and small businesses can now thrive in the digital economy. These data factories provide platforms for unpaid contributions, enabling individuals to contribute their expertise and content. Additionally, data factory tools have empowered entrepreneurs, transforming average individuals into successful business owners. However, despite these advancements, significant challenges remain, including income inequality and the struggle to attract and retain talent in the competitive global landscape. Nonetheless, the emergence of data factories signifies a monumental shift in the organization of work and presents new possibilities for individuals and societies worldwide.

Summary & Key Takeaways

• Michael Moritz of Sequoia frames technology through history, starting with a 1750 farmer whose plow-based, self-sustaining life differed little from farmers 2,000 years earlier. The first Industrial Revolution began in a small part of northwest England, centralizing tools like the loom into organized factory workplaces with suppliers and consumers.

• The second industrial phase concentrated around Detroit and Pittsburgh in steel mills and automobile factories, yet workplaces stayed isolated from consumers with lengthy feedback. Four forces then enabled the 'data factory': exploding bandwidth over 25 years, transformed storage, vastly cheaper computing, and an explosion of applications from barely 200 to millions.

• The data factory sits close to consumers, employs few workers, and thrives on unpaid contributions from platforms like Google, Amazon, and LinkedIn. Categories include labor matching (LinkedIn), money raising (Kickstarter, Indiegogo, Stripe), and global data factories. Tools placed in individuals' hands power services like Uber, Lyft, and Instacart.