Twitter, Valuation and Venture Capital

Read Write analyzes the recent investment in Twitter at a valuation of USD 1 Billion valuation. They write:

These high-profile deals have "optics" (i.e. the PR or headline story for public consumption) and fundamentals (i.e. how the investors actually make money). They are very different.

The key to the fundamentals is the Liquidation Preference. We touched on this in one of our "Startup 101" chapters: How to Scale Without Losing Your Shirt. Basically, upon exit, the investors get their money out before the entrepreneurs do. That's reasonable. For example, the Twitter team has not actually built a business worth $1 billion; it is only saying it can do so (with some credibility).

So, the investors putting in $100 million have their risk (or downside) covered. The only way they can lose money is if Twitter sells for less than $100 million, which is pretty unlikely... not impossible, but unlikely. But if it sells for $100 million, then all of the other investors lose everything. The exit valuation has to be higher than $157.97 million (total money invested) for the founders and management team to see a dime.

So, with their downside covered, investors can focus on the upside. This is where optics matter. With this deal, the entrepreneurs can say the following to any potential acquirers:

• "Negotiations have to start at $1 billion. It clearly cannot be lower than that," and
• "We have a long runway. If you don't do this deal now, the price will only be higher later."

In this case, the optics are critical. Although the investors in this latest round have protected their downside, they won't see any upside unless the exit valuation is greater than $1 billion. By putting in a large amount (which they cannot really lose), the investors help to ensure that the exit valuation is high.

Ideally, Twitter will exit before revenue, when revenue potential is unlimited. As soon as actual revenue comes in, three bad things happen:

1. Acquirers say, "Let's wait and see how this pans out."
2. Costs go up: you have paying customers who demand real service.
3. Revenue targets may go south. Exponential hockey-stick growth is hard enough for a free service (kudos to Twitter for doing that brilliantly) but way, way harder when money changes hands. Real money (not investment money) paid by someone to Twitter becomes friction. Twitter ceases to be a friction-less flywheel.

Twitter does have enough cash now to execute on a revenue plan and outlast acquirers who like to sit on the fence. So any way you look at it, this is a smart deal. It is not "evil": this is all business between consenting adults. Evil would be selling stock to "widows and orphans" in the public market who (A) don't have Preference and (B) don't have the means to evaluate the risk on a deal like this. That was Bubble 1.0, and it won't happen again. This is not Bubble 2.0. This is fundamentally different, even if the optics may look similar.

Last week we discussed Netflix and their Netflix Prize. An interesting story about them (especially love his vacation policy) in Wired--as they write in a very interesting read:

It had taken the better part of a decade, but Reed Hastings was finally ready to unveil the device he thought would upend the entertainment industry. The gadget looked as unassuming as the original iPod—a sleek black box, about the size of a paperback novel, with a few jacks in back—and Hastings, CEO of Netflix, believed its impact would be just as massive. Called the Netflix Player, it would allow most of his company's regular DVD-by-mail subscribers to stream unlimited movies and TV shows from Netflix's library directly to their television—at no extra charge.

The potential was enormous: Although Netflix initially could offer only about 10,000 titles, Hastings planned to one day deliver the entire recorded output of Hollywood, instantly and in high definition, to any screen, anywhere. Like many tech romantics, he had harbored visions of using the Internet to rout around cable companies and network programmers for years. Even back when he formed Netflix in 1997, Hastings predicted a day when he would deliver video over the Net rather than through the mail. (There was a reason he called the company Netflix and not, say, DVDs by Mail.) Now, in mid-December 2007, the launch of the player was just weeks away. Promotional ads were being shot, and internal beta testers were thrilled.

But Hastings wasn't celebrating. Instead, he felt queasy. For weeks, he had tried to ignore the nagging doubts he had about the Netflix Player. Consumers' living rooms were already full of gadgets—from DVD players to set-top boxes. Was a dedicated Netflix device really the best way to bring about his video-on-demand revolution? So on a Friday morning, he asked the six members of his senior management team to meet him in the amphitheater in Netflix's Los Gatos offices, near San Jose. He leaned up against the stage and asked the unthinkable: Should he kill the player?

Three days later, at an all-company meeting in the same amphitheater, Hastings announced that there would be no Netflix Player. Instead, he would spin off the device, letting developer Anthony Wood take the technology and his 19-person team to a small company Wood had founded years earlier called Roku. But Netflix, which had already begun streaming movies to users' PCs, was hardly giving up on the idea of streaming them to televisions as well. Instead, the company would take a more stealthy—and potentially even more ambitious—approach. Rather than design its own product, it would embed its streaming-video service into existing devices: TVs, DVD players, game consoles, laptops, even smartphones. Netflix wouldn't be aPublish Post hardware company; it would be a services firm. The crowd was stunned. In half an hour, Hastings had completely reinvented Netflix's strategy

So how does Reed Hastings manage?

A quiet, hands-off leader, he sets the tone and objectives and lets his employees figure out how to execute them. His main directive is that everyone act like an adult: Netflix has no vacation policy (take as much as you need, when you need it), pay is flexible (stock or cash, your choice), and though firings are unusually common, severance checks are unusually generous. Hastings is comfortable creating his own rules for how to run a business; you don't see any management tomes in his office. In fact, he doesn't even have an office. The CEO prefers to stroll around, a ThinkPad in hand, pitching camp in an empty conference room or huddling in an engineer's cubicle to whiteboard some formula.

Intel

As noted earlier, Intel held their Developer's Conference last week. Paul Otellini, CEO, noted the following:

“The world of computing is expanding beyond the personal computer, We’re building out a spectrum of computing devices … all the way down to handheld. For consumers we want to deliver the same experience across any device.”

The New York Times, then noted the following implications:

At the chip level, this means building most of a device’s functions into just one or two chips. The largest integration leap was a chip for digital televisions, introduced Thursday. The CE 4100 chip packs an Intel Atom processor, a graphics processor, and silicon for handling video, networking and many of the typical PC connection technologies — like the Universal Serial Bus, or USB — all into one chip.

“The CE 4100 portends our future,” said Bill Leszinske, general manager of Intel’s Digital Home Group.

The design, referred to generally as system-on-a-chip, is crucial because it’s a template for Intel’s push into mobile phones and small Internet devices in 2010 and 2011 — two markets that are currently dominated by other chipmakers like Texas Instruments and Samsung. A version of this design will be used next year in a high-end smartphone from LG Electronics.

Google and M&A

Complements of Tech Crunch, see the below map--it looks like a subway map, but it is all of the acquisitions made by Google of young, start-up companies.

The Technology behind Facebook

Facebook--how it works. that is the subject of an interview with the CTO of the Company by the Technology Review. How do you scale a system that is so personalized--300MN users, 1.2MN photos per second.

He notes of the internally developed system that can serve up in near real time customized information:

Your best weapon in most computer science problems is caching. But if, like the Facebook home page, it's basically updating every minute or less than a minute, then pretty much every time I load it, it's a new page, or at least has new content. That kind of throws the whole caching idea out the window. Doing things in or near real time puts a lot of pressure on the system because the live-ness or freshness of the data requires you to query more in real time.

We've built a couple systems behind that. One of them is a custom in-memory database that keeps track of what's happening in your friends network and is able to return the core set of results very quickly, much more quickly than having to go and touch a database, for example. And then we have a lot of novel system architecture around how to shard and split out all of this data. There's too much data updated too fast to stick it in a big central database. That doesn't work. So we have to separate it out, split it out, to thousands of databases, and then be able to query those databases at high speed.

Netflix Prize

The Netflix prize was given this week--the $1MN award is for the team that was able to improve the algorithm for movie recommendations by 10%---it represents a landmark way (and I do not use the word "landmark" lightly) of how development works. Also please note the "human engineering"--understanding how people think and behave when devising systems. Wired Magazine writes:

the Netflix Prize competition has proffered hard proof of a basic crowdsourcing concept: Better solutions come from unorganized people who are allowed to organize organically. But something else happened that wasn’t entirely expected: Teams that had it basically wrong — but for a few good ideas — made the difference when combined with teams which had it basically right, but couldn’t close the deal on their own.

Ironically, the most outlying approaches — the ones farthest away from the mainstream way to solve a given problem — proved most helpful towards the end of the contest, as the teams neared the summit.

For instance, BellKor’s Pragmatic Chaos (methodology here) credits some of its success to slicing the data by what they called “frequency.” As it turns out, people who rate a whole slew of movies at one time tend to be rating movies they saw a long time ago. The data showed that people employ different criteria to rate movies they saw a long time ago, as opposed to ones they saw recently — and that in addition, some movies age better than others, skewing either up or down over time. (Finally, someone has explained whySnakes On A Plane seemed more fun at the time than it does now.)

By tracking the number of movies rated on a given day as an indicator of how long it had been since a given viewer had seen a movie, and by tracking how memory affected particular movie ratings, Pragmatic Theory (later part of the winning team) was able to gain a slight edge, even though this particular algorithm isn’t particularly good at predicting which movies people will like when run on its own.

Another example: According to Joe Sill of The Ensemble, Big Chaos (the Austrians who also became part of the winning team) discovered that viewers in general tend to rate movies differently on Fridays versus Mondays, and certain users are in good moods on Sundays, and so on. The team essentially devised a three-dimensional model that incorporated time into the relationship between people and movies.

Taken on its own, the fact that a viewer rated a given movie on a Monday is a horrible indicator of what other movies they’ll want to rent — a crucial part of Netflix’ business (it says its recommendations are better indicators of what people will rent than their “most popular” lists). But combined with hundreds of other algorithms from other minds, each weighted with precision, and combined and recombined, that otherwise inconsequential fact takes on huge importance.

Globalization and Industry Transformation

Michael Moe, a noted global technology analyst, writes of the effect of globalization on industries (note global vs. local in looking at business models). His point:

While many new leaders still originate in the United States, increasingly emerging stars such as Baidu, Alibaba, MercadoLibre, Ctrip, Research in Motion, and Vestas are conceived outside the U.S. Moreover, even new leaders such as Google and First

Solar are generating approximately 50% of their revenues outside of the United States

and 50% of the S&P 500 earnings come from abroad.

On specific industries that benefit from globalization:

Despite the airline business having been a notoriously horrible industry with the

cumulative loss by all US airlines being approximately $25 billion since Orville and

Wilbur Wright took wings, globalization and the demographic of aging populations

retiring and having more time to travel makes it impossible not to be bullish on the

travel industry.

As English is the global business language, another pure play on globalization is

English Language training. China, always looking ahead, has made English classes

mandatory starting in the 2nd grade. Berlitz is an idea with that theme. Pearson and

Thomson are two terrific global media companies that have sizable English Language

businesses. Rosetta Stone, which is a recent IPO but has stumbled lately, is another

terrific play for this theme. Livemocha, which is a private company in the social

language learning space, has tremendous potential in my view.

Identification technology such as biometrics is an obvious benefactor of a global world.While for now a driver’s license is generally sufficient identification in the United States,

and a passport is acceptable abroad, in a global world where people are traveling in

multiple countries frequently and commerce is conducted without geographic

boundaries, physical and virtual security will be enhanced by more infallible

identification.

Of course, driving so much of this globalization has been the internet of late.

Industry that Benefit from Globalization

Medicine

Airlines

Language Training

Identification Technology

Security Companies

Education

Financial Services

Consumer Brands

Entertainment

Green Technology/Water

Internet/Media

Social Learning/Social Media

A.T Kearney Global Services Location Index 2009

Rank Country

1 India

2 China

3 Malaysia

4 Thailand

5 Indonesia(6)

6 Egypt

7 Philippines

8 Chile

9 Jordan

10 Vietnam

11 Mexico

12 Brazil

13 Bulgaria

14 United States

15 Ghana

16 Sri Lanka

17 Tunisia

18 Estonia

19 Romania

20 Pakistan

Source: AT Kearney

For the full reading of the report:

http://www.nextupresearch.com/Site/NEXT_up!_files/NeXt%20Up!%2009.20.09.pdf

You Scream I Scream....

This sounds too good to be true...an ice cream machine that makes homemade ice cream in 40 seconds! What is the business model?

How to Start-up a Company

Advice on how to start a company abounds, particularly in the internet space. This excerpt is from Tech Crunch, quoting Meebo CEO and Founder. Meebo is a high profile, start-up company focused on Instant Messaging.

At the exact moment you had your idea, ten other people had the exact same idea. There was just something in the environment that made it the right time for folks to think that one up. The race has already begun! Who’s going to execute first? Who’s going to execute best? If you want to waste nine months trying to raise VC money for that idea, great. But six months in, you’re gonna cry when you see someone else put out that same product you’re pitching me right now. Like I said, forget everything else and just get your product out the door. Now.

Inevitably, the excuses begin: I need to hire people to build the product. I don’t know any developers. I need money for the servers. I want to get that last promotion at my current company first!

Here’s the rub: in consumer internet (and often enterprise), if your founding team doesn’t have the chops to get a prototype of your product out and in the hands of a blogger to test and write about, you might as well save yourself a lot of pain – you’re not going anywhere. Need proof? Just look at some of the most successful tech companies in the last decade: eBay, YouTube, Sun, Oracle, Apple, Cisco, Facebook, Yahoo!, and Google. All of them share a couple common traits: they launched before taking outside investment, and they were able to do it because they had a set of founders with the skills to build the initial version of the product themselves. Only eBay was founded by a single individual – the rest were team efforts

For the full article, go here.

Semiconductor Industry: New Kid in Town.

NY Times notes the following:

Forget the $64,000 question. For the chip industry, we’re up to the $10 billion question.

That’s just about how much money the government of Abu Dhabi has thrown at the ultracompetitive, often volatile chip-making business. Last year, Abu Dhabi pledged to spend at least $6 billion to create a new chip-making venture in partnership withAdvanced Micro Devices.

This week, the government committed an additional $3.9 billion, in cash and the assumption of debt, toward the purchase of a Singaporean contract chip maker, Chartered Semiconductor.

For further details, go here.