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Tag: Tech

Lyft vs Uber: A Tale of Two S-1’s

You can learn a great deal from reading and comparing the financial filings of two close competitors. Tech-finance nerd that I am, you can imagine how excited I was to see Lyft’s and Uber’s respective S-1’s become public within mere weeks of each other.

While the general financial press has covered a lot of the top-level figures on profitability (or lack thereof) and revenue growth, I was more interested in understanding the unit economics — what is the individual “unit” (i.e. a user, a sale, a machine, etc.) of the business and what does the history of associated costs and revenues say about how the business will (or will not) create durable value over time.

For two-sided regional marketplaces like Lyft and Uber, an investor should understand the full economic picture for (1) the users/riders, (2) the drivers, and (3) the regional markets. Sadly, their S-1’s don’t make it easy to get much on (2) or (3) — probably because the companies consider the pertinent data to be highly sensitive information. They did, however, provide a fair amount of information on users/riders and rides and, after doing some simple calculations, a couple of interesting things emerged

Uber’s Users Spend More, Despite Cheaper Rides

As someone who first knew of Uber as the UberCab “black-car” service, and who first heard of Lyft as the Zimride ridesharing platform, I was surprised to discover that Lyft’s average ride price is significantly more expensive than Uber’s and the gap is growing! In Q1 2017, Lyft’s average bookings per ride was $11.74 and Uber’s was $8.41, a difference of $3.33. But, in Q4 2018, Lyft’s average bookings per ride had gone up to $13.09 while Uber’s had declined to $7.69, increasing the gap to $5.40.

Average Bookings $/Ride
Sources: Lyft S-1; Uber S-1

Note: the numbers presented above for Uber are for Uber ridesharing bookings divided by total Uber rides, which includes rides for Uber Eats — this was done because we don’t have great data on rides for Uber Eats and because I suspected that Uber Eats trips represent a small minority of trips — something borne out by the fact that the trend / numbers I arrived at roughly matches the Ridesharing Gross Bookings per Trip chart in the Uber S-1

This is especially striking considering the different definitions that Lyft and Uber have for “bookings” — Lyft excludes “pass-through amounts paid to drivers and regulatory agencies, including sales tax and other fees such as airport and city fees, as well as tips, tolls, cancellation, and additional fees” whereas Uber’s includes “applicable taxes, tolls, and fees“. This gap is likely also due to Uber’s heavier international presence (where they now generate 52% of their bookings). It would be interesting to see this data on a country-by-country basis (or, more importantly, a market-by-market one as well).

Interestingly, an average Uber rider appears to also take ~2.3 more rides per month than an average Lyft rider, a gap which has persisted fairly stably over the past 3 years even as both platforms have boosted the number of rides an average rider takes. While its hard to say for sure, this suggests Uber is either having more luck in markets that favor frequent use (like dense cities), with its lower priced Pool product vs Lyft’s Line product (where multiple users can share a ride), or its general pricing is encouraging greater use.

Monthly Rides / Monthly Active Rider

Sources: Lyft S-1; Uber S-1

Note: the “~monthly” that you’ll see used throughout the charts in this post are because the aggregate data — rides, bookings, revenue, etc — given in the regulatory filings is quarterly, but the rider/user count provided is monthly. As a result, the figures here are approximations based on available data, i.e. by dividing quarterly data by 3

What does that translate to in terms of how much an average rider is spending on each platform? Perhaps not surprisingly, Lyft’s average rider spend has been growing and has almost caught up to Uber’s which is slightly down.

Monthly Bookings $ / Monthly Active User

Sources: Lyft S-1; Uber S-1

However, Uber’s new businesses like UberEats are meaningfully growing its share of wallet with users (and nearly perfectly dollar for dollar re-opens the gap on spend per user that Lyft narrowed over the past few years). In 2018 Q4, the gap between the yellow line (total bookings per user, including new businesses) and the red line (total bookings per user just for rides) is almost $10 / user / month! Its no wonder that in its filings, Lyft calls its users “riders”, but Uber calls them “Active Platform Consumers”.

Despite Pocketing More per Ride, Lyft Loses More per User

Long-term unit profitability is more than just how much an average user is spending, its also how much of that spend hits a company’s bottom line. Perhaps not surprisingly, because they have more expensive rides, a larger percent of Lyft bookings ends up as gross profit (revenue less direct costs to serve it, like insurance costs) — ~13% in Q4 2018 compared with ~9% for Uber. While Uber’s has bounced up and down, Lyft’s has steadily increased (up nearly 2x from Q1 2017). I would hazard a guess that Uber’s has also increased in its more established markets but that their expansion efforts into new markets (here and abroad) and new service categories (UberEats, etc) has kept the overall level lower.

Gross Margin as % of Bookings
Sources: Lyft S-1; Uber S-1

Note: the gross margin I’m using for Uber adds back a depreciation and amortization line which were separated to keep the Lyft and Uber numbers more directly comparable. There may be other variations in definitions at work here, including the fact that Uber includes taxes, tolls, and fees in bookings that Lyft does not. In its filings, Lyft also calls out an analogous “Contribution Margin” which is useful but I chose to use this gross margin definition to try to make the numbers more directly comparable.

The main driver of this seems to be higher take rate (% of bookings that a company keeps as revenue) — nearly 30% in the case of Lyft in Q4 2018 but only 20% for Uber (and under 10% for UberEats)

Revenue as % of Bookings
Sources: Lyft S-1; Uber S-1

Note: Uber uses a different definition of take rate in their filings based on a separate cut of “Core Platform Revenue” which excludes certain items around referral fees and driver incentives. I’ve chosen to use the full revenue to be more directly comparable

The higher take rate and higher bookings per user has translated into an impressive increase in gross profit per user. Whereas Lyft once lagged Uber by almost 50% on gross profit per user at the beginning of 2017, Lyft has now surpassed Uber even after adding UberEats and other new business revenue to the mix.

Monthly Gross Profit $ per Monthly Active User
Sources: Lyft S-1; Uber S-1

All of this data begs the question, given Lyft’s growth and lead on gross profit per user, can it grow its way into greater profitability than Uber? Or, to put it more precisely, are Lyft’s other costs per user declining as it grows? Sadly, the data does not seem to pan out that way

Monthly OPEX $ per Monthly Active User
Sources: Lyft S-1; Uber S-1

While Uber had significantly higher OPEX (expenditures on sales & marketing, engineering, overhead, and operations) per user at the start of 2017, the two companies have since reversed positions, with Uber making significant changes in 2018 which lowered its OPEX per user spend to under $9 whereas Lyft’s has been above $10 for the past two quarters. The result is Uber has lost less money per user than Lyft since the end of 2017

Monthly Profit $ per Monthly Active User
Sources: Lyft S-1; Uber S-1

The story is similar for profit per ride. Uber has consistently been more profitable since 2017, and they’ve only increased that lead since. This is despite the fact that I’ve included the costs of Uber’s other businesses in their cost per ride.

Profit $ per Ride
Sources: Lyft S-1; Uber S-1

Does Lyft’s Growth Justify Its Higher Spend?

One possible interpretation of Lyft’s higher OPEX spend per user is that Lyft is simply investing in operations and sales and engineering to open up new markets and create new products for growth. To see if this strategy has paid off, I took a look at the Lyft and Uber’s respective user growth during this period of time.

Sources: Lyft S-1; Uber S-1

The data shows that Lyft’s compounded quarterly growth rate (CQGR) from Q1 2016 to Q4 2018 of 16.4% is only barely higher than Uber’s at 15.3% which makes it hard to justify spending nearly $2 more per user on OPEX in the last two quarters.

Interestingly, despite all the press and commentary about #deleteUber, it doesn’st seem to have really made a difference in their overall user growth (its actually pretty hard to tell from the chart above that the whole thing happened around mid-Q1 2017).

How are Drivers Doing?

While there is much less data available on driver economics in the filings, this is a vital piece of the unit economics story for a two-sided marketplace. Luckily, Uber and Lyft both provide some information in their S-1’s on the number of drivers on each platform in Q4 2018 which are illuminating.

Q4 2018LyftUberComparison
Drivers1.1 million 3.9 million
Rides / Driver162.18382.82Uber is higher by 136%
Rides Bookings
$ / Driver
$2,123$2,943Uber higher by 39%
because Uber bookings
per ride lower by 41%
Total Bookings
$ / Driver
$2,123$3,63319% of Uber bookings
are non-ride
Take Home
$ / Driver
$1,514$2,982 (total)
$2,350 (rides)
Uber higher by 97%
because drivers take
home 15% more per $
If only rides, Uber
higher by 55%

Sources: Lyft S-1; Uber S-1

The average Uber driver on the platform in Q4 2018 took home nearly double what the average Lyft driver did! They were also more likely to be “utilized” given that they handled 136% more rides than the average Lyft driver and, despite Uber’s lower price per ride, saw more total bookings.

It should be said that this is only a point in time comparison (and its hard to know if Q4 2018 was an odd quarter or if there is odd seasonality here) and it papers over many other important factors (what taxes / fees / tolls are reflected, none of these numbers reflect tips, are some drivers doing shorter shifts, what does this look like specifically in US/Canada vs elsewhere, are all Uber drivers benefiting from doing both UberEats and Uber rideshare, etc). But the comparison is striking and should be alarming for Lyft.

Closing Thoughts

I’d encourage investors thinking about investing in either to do their own deeper research (especially as the competitive dynamic is not over one large market but over many regional ones that each have their own attributes). That being said, there are some interesting takeaways from this initial analysis

  • Lyft has made impressive progress at increasing the value of rides on its platform and increasing the share of transactions it gets. One would guess that, Uber, within established markets in the US has probably made similar progress.
  • Despite the fact that Uber is rapidly expanding overseas into markets that face more price constraints than in the US, it continues to generate significantly better user economics and driver economics (if Q4 2018 is any indication) than Lyft.
  • Something happened at Uber at the end of 2017/start of 2018 (which looks like it coincides nicely with Dara Khosrowshahi’s assumption of CEO role) which led to better spending discipline and, as a result, better unit economics despite falling gross profits per user
  • Uber’s new businesses (in particular UberEats) have had a significant impact on Uber’s share of wallet.
  • Lyft will need to find more cost-effective ways of growing its business and servicing its existing users & drivers if it wishes to achieve long-term sustainability as its current spend is hard to justify relative to its user growth.

Special thanks to Eric Suh for reading and editing an earlier version!

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How to Regulate Big Tech

There’s been a fair amount of talk lately about proactively regulating — and maybe even breaking up — the “Big Tech” companies.

Full disclosure: this post discusses regulating large tech companies. I own shares in several of these both directly (in the case of Facebook and Microsoft) and indirectly (through ETFs that own stakes in large companies)


(Image Credit: MIT Sloan)

†Like many, I have become increasingly uneasy over the fact that a small handful of companies, with few credible competitors, have amassed so much power over our personal data and what information we see. As a startup investor and former product executive at a social media startup, I can especially sympathize with concerns that these large tech companies have created an unfair playing field for smaller companies.

At the same time, though, I’m mindful of all the benefits that the tech industry — including the “tech giants” — have brought: amazing products and services, broader and cheaper access to markets and information, and a tremendous wave of job and wealth creation vital to may local economies. For that reason, despite my concerns of “big tech”‘s growing power, I am wary of reaching for “quick fixes” that might change that.

As a result, I’ve been disappointed that much of the discussion has centered on knee-jerk proposals like imposing blanket stringent privacy regulations and forcefully breaking up large tech companies. These are policies which I fear are not only self-defeating but will potentially put into jeopardy the benefits of having a flourishing tech industry.

The Challenges with Regulating Tech

Technology is hard to regulate. The ability of software developers to collaborate and build on each other’s innovations means the tech industry moves far faster than standard regulatory / legislative cycles. As a result, many of the key laws on the books today that apply to tech date back decades — before Facebook or the iPhone even existed, making it important to remember that even well-intentioned laws and regulations governing tech can cement in place rules which don’t keep up when the companies and the social & technological forces involved change.

Another factor which complicates tech policy is that the traditional “big is bad” mentality ignores the benefits to having large platforms. While Amazon’s growth has hurt many brick & mortar retailers and eCommerce competitors, its extensive reach and infrastructure enabled businesses like Anker and Instant Pot to get to market in a way which would’ve been virtually impossible before. While the dominance of Google’s Android platform in smartphones raised concerns from European regulators, its hard to argue that the companies which built millions of mobile apps and tens of thousands of different types of devices running on Android would have found it much more difficult to build their businesses without such a unified software platform. Policy aimed at “Big Tech” should be wary of dismantling the platforms that so many current and future businesses rely on.

Its also important to remember that poorly crafted regulation in tech can be self-defeating. The most effective way to deal with the excesses of “Big Tech”, historically, has been creating opportunities for new market entrants. After all, many tech companies previously thought to be dominant (like Nokia, IBM, and Microsoft) lost their positions, not because of regulation or antitrust, but because new technology paradigms (i.e. smartphones, cloud), business models (i.e. subscription software, ad-sponsored), and market entrants (i.e. Google, Amazon) had the opportunity to flourish. Because rules (i.e. Article 13/GDPR) aimed at big tech companies generally fall hardest on small companies (who are least able to afford the infrastructure / people to manage it), its important to keep in mind how solutions for “Big Tech” problems affect smaller companies and new concepts as well.

Framework for Regulating “Big Tech”

If only it were so easy… (Image credit: XKCD)

To be 100% clear, I’m not saying that the tech industry and big platforms should be given a pass on rules and regulation. If anything, I believe that laws and regulation play a vital role in creating flourishing markets.

But, instead of treating “Big Tech” as just a problem to kill, I think we’d be better served by laws / regulations that recognize the limits of regulation on tech and, instead, focus on making sure emerging companies / technologies can compete with the tech giants on a level playing field. To that end, I hope to see more ideas that embrace the following four pillars:

I. Tiering regulation based on size of the company

Regulations on tech companies should be tiered based on size with the most stringent rules falling on the largest companies. Size should include traditional metrics like revenue but also, in this age of marketplace platforms and freemium/ad-sponsored business models, account for the number of users (i.e. Monthly Active Users) and third party partners.

In this way, the companies with the greatest potential for harm and the greatest ability to bear the costs face the brunt of regulation, leaving smaller companies & startups with greater flexibility to innovate and iterate.

II. Championing data portability

One of the reasons it’s so difficult for competitors to challenge the tech giants is the user lock-in that comes from their massive data advantage. After all, how does a rival social network compete when a user’s photos and contacts are locked away inside Facebook?

While Facebook (and, to their credit, some of the other tech giants) does offer ways to export user data and to delete user data from their systems, these tend to be unwieldy, manual processes that make it difficult for a user to bring their data to a competing service. Requiring the largest tech platforms to make this functionality easier to use (i.e., letting others import your contact list and photos with the ease in which you can login to many apps today using Facebook) would give users the ability to hold tech companies accountable for bad behavior or not innovating (by being able to walk away) and fosters competition by letting new companies compete not on data lock-in but on features and business model.

III. Preventing platforms from playing unfairly

3rd party platform participants (i.e., websites listed on Google, Android/iOS apps like Spotify, sellers on Amazon) are understandably nervous when the platform owners compete with their own offerings (i.e., Google Places, Apple Music, Amazon first party sales). As a result, some have even called for banning platform owners from offering their own products and services.

I believe that is an overreaction. Platform owners offering attractive products and services (i.e., Google offering turn-by-turn navigation on Android phones) can be a great thing for users (after all, most prominent platforms started by providing compelling first-party offerings) and for 3rd party participants if these offerings improve the attractiveness of the platform overall.

What is hard to justify is when platform owners stack the deck in their favor using anti-competitive moves such as banning or reducing the visibility of competitors, crippling third party offerings, making excessive demands on 3rd parties, etc. Its these sorts of actions by the largest tech platforms that pose a risk to consumer choice and competition and should face regulatory scrutiny. Not just the fact that a large platform exists or that the platform owner chooses to participate in it.

IV. Modernizing how anti-trust thinks about defensive acquisitions

The rise of the tech giants has led to many calls to unwind some of the pivotal mergers and acquisitions in the space. As much as I believe that anti-trust regulators made the wrong calls on some of these transactions, I am not convinced, beyond just wanting to punish “Big Tech” for being big, that the Pandora’s Box of legal and financial issues (for the participants, employees, users, and for the tech industry more broadly) that would be opened would be worthwhile relative to pursuing other paths to regulate bad behavior directly.

That being said, its become clear that anti-trust needs to move beyond narrow revenue share and pricing-based definitions of anti-competitiveness (which do not always apply to freemium/ad-sponsored business models). Anti-trust prosecutors and regulators need to become much more thoughtful and assertive around how some acquisitions are done simply to avoid competition (i.e., Google’s acquisition of Waze and Facebook’s acquisition of WhatsApp are two examples of landmark acquisitions which probably should have been evaluated more closely).

Wrap-Up

(Image Credit: OECD Forum Network)

This is hardly a complete set of rules and policies needed to approach growing concerns about “Big Tech”. Even within this framework, there are many details (i.e., who the specific regulators are, what specific auditing powers they have, the details of their mandate, the specific thresholds and number of tiers to be set, whether pre-installing an app counts as unfair, etc.) that need to be defined which could make or break the effort. But, I believe this is a good set of principles that balances both the need to foster a tech industry that will continue to grow and drive innovation as well as the need to respond to growing concerns about “Big Tech”.

Special thanks to Derek Yang and Anthony Phan for reading earlier versions and giving me helpful feedback!

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Different Paths to Success for Tech vs Hardtech Startups

Having been lucky enough to invest in both tech (cloud, mobile, software) and “hardtech” (materials, cleantech, energy, life science) startups (and having also ran product at a mobile app startup), it has been striking to see how fundamentally different the paradigms that drive success in each are.

Whether knowingly or not, most successful tech startups over the last decade have followed a basic playbook:

  1. Take advantage of rising smartphone penetration and improvements in cloud technology to build digital products that solve challenges in big markets pertaining to access (e.g., to suppliers, to customers, to friends, to content, to information, etc.)
  2. Build a solid team of engineers, designers, growth, sales, marketing, and product people to execute on lean software development and growth methodologies
  3. Hire the right executives to carry out the right mix of tried-and-true as well as “out of the box” channel and business development strategies to scale bigger and faster

This playbook appears deceptively simple but is very difficult to execute well. It works because for markets where “software is eating the world”:

  • There is relatively little technology risk: With the exception of some of the most challenging AI, infrastructure, and security challenges, most tech startups are primarily dealing with engineering and product execution challenges — what is the right thing to build and how do I build it on time, under budget? — rather than fundamental technology discovery and feasibility challenges
  • Skills & knowledge are broadly transferable: Modern software development and growth methodologies work across a wide range of tech products and markets. This means that effective engineers, salespeople, marketers, product people, designers, etc. at one company will generally be effective at another. As a result, its a lot easier for investors/executives to both gauge the caliber of a team (by looking at their experience) and augment a team when problems arise (by recruiting the right people with the right backgrounds).
  • Distribution is cheap and fast: Cloud/mobile technology means that a new product/update is a server upgrade/browser refresh/app store download away. This has three important effects:
    1. The first is that startups can launch with incomplete or buggy solutions because they can readily provide hotfixes and upgrades.
    2. The second is that startups can quickly release new product features and designs to respond to new information and changing market conditions.
    3. The third is that adoption is relatively straightforward. While there may be some integration and qualification challenges, in general, the product is accessible via a quick download/browser refresh, and the core challenge is in getting enough people to use a product in the right way.

In contrast, if you look at hardtech companies, a very different set of rules apply:

  • Technology risk/uncertainty is inherent: One of the defining hallmarks of a hardtech company is dealing with uncertainty from constraints imposed by reality (i.e. the laws of physics, the underlying biology, the limits of current technology, etc.). As a result, hardtech startups regularly face feasibility challenges — what is even possible to build? — and uncertainty around the R&D cycles to get to a good outcome — how long will it take / how much will it cost to figure this all out?
  • Skills & knowledge are not easily transferable: Because the technical and business talent needed in hardtech is usually specific to the field, talent and skills are not necessarily transferable from sector to sector or even company to company. The result is that it is much harder for investors/executives to evaluate team caliber (whether on technical merits or judging past experience) or to simply put the right people into place if there are problems that come up.
  • Product iteration is slow and costly: The tech startup ethos of “move fast and break things” is just harder to do with hardtech.
    1. At the most basic level, it just costs a lot more and takes a lot more time to iterate on a physical product than a software one. It’s not just that physical products require physical materials and processing, but the availability of low cost technology platforms like Amazon Web Services and open source software dramatically lower the amount of time / cash needed to make something testable in tech than in hardtech.
    2. Furthermore, because hardtech innovations tend to have real-world physical impacts (to health, to safety, to a supply chain/manufacturing line, etc.), hardtech companies generally face far more regulatory and commercial scrutiny. These groups are generally less forgiving of incomplete/buggy offerings and their assessments can lengthen development cycles. Hardtech companies generally can’t take the “ask for forgiveness later” approaches that some tech companies (i.e. Uber and AirBnb) have been able to get away with (exhibit 1: Theranos).

As a result, while there is no single playbook that works across all hardtech categories, the most successful hardtech startups tend to embody a few basic principles:

  1. Go after markets where there is a very clear, unmet need: The best hardtech entrepreneurs tend to take very few chances with market risk and only pursue challenges where a very well-defined unmet need (i.e., there are no treatments for Alzheimer’s, this industry needs a battery that can last at least 1000 cycles, etc) blocks a significant market opportunity. This reduces the risk that a (likely long and costly) development effort achieves technical/scientific success without also achieving business success. This is in contrast with tech where creating or iterating on poorly defined markets (i.e., Uber and Airbnb) is oftentimes at the heart of what makes a company successful.
  2. Focus on “one miracle” problems: Its tempting to fantasize about what could happen if you could completely re-write every aspect of an industry or problem but the best hardtech startups focus on innovating where they won’t need the rest of the world to change dramatically in order to have an impact (e.g., compatible with existing channels, business models, standard interfaces, manufacturing equipment, etc). Its challenging enough to advance the state of the art of technology — why make it even harder?
  3. Pursue technologies that can significantly over-deliver on what the market needs: Because of the risks involved with developing advanced technologies, the best hardtech entrepreneurs work in technologies where even a partial success can clear the bar for what is needed to go to market. At the minimum, this reduces the risk of failure. But, hopefully, it gives the company the chance to fundamentally transform the market it plays in by being 10x better than the alternatives. This is in contrast to many tech markets where market success often comes less from technical performance and more from identifying the right growth channels and product features to serve market needs (i.e., Facebook, Twitter, and Snapchat vs. MySpace, Orkut, and Friendster; Amazon vs. brick & mortar bookstores and electronics stores)

All of this isn’t to say that there aren’t similarities between successful startups in both categories — strong vision, thoughtful leadership, and success-oriented cultures are just some examples of common traits in both. Nor is it to denigrate one versus the other. But, practically speaking, investing or operating successfully in both requires very different guiding principles and speaks to the heart of why its relatively rare to see individuals and organizations who can cross over to do both.

Special thanks to Sophia Wang, Ryan Gilliam, and Kevin Lin Lee for reading an earlier draft and making this better!

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The Four Types of M&A

I’m oftentimes asked what determines the prices that companies get bought for: after all, why does one app company get bought for $19 billion and a similar app get bought at a discount to the amount of investor capital that was raised?

While specific transaction values depend a lot on the specific acquirer (i.e. how much cash on hand they have, how big they are, etc.), I’m going to share a framework that has been very helpful to me in thinking about acquisition valuations and how startups can position themselves to get more attractive offers. The key is understanding that, all things being equal, why you’re being acquired determines the buyer’s willingness to pay. These motivations fall on a spectrum dividing acquisitions into four types:

four

  • Talent Acquisitions: These are commonly referred to in the tech press as “acquihires”. In these acquisitions, the buyer has determined that it makes more sense to buy a team than to spend the money, time, and effort needed to recruit a comparable one. In these acquisitions, the size and caliber of the team determine the purchase price.
  • Asset / Capability Acquisitions: In these acquisitions, the buyer is in need of a particular asset or capability of the target: it could be a portfolio of patents, a particular customer relationship, a particular facility, or even a particular product or technology that helps complete the buyer’s product portfolio. In these acquisitions, the uniqueness and potential business value of the assets determine the purchase price.
  • Business Acquisitions: These are acquisitions where the buyer values the target for the success of its business and for the possible synergies that could come about from merging the two. In these acquisitions, the financials of the target (revenues, profitability, growth rate) as well as the benefits that the investment bankers and buyer’s corporate development teams estimate from combining the two businesses (cost savings, ability to easily cross-sell, new business won because of a more complete offering, etc) determine the purchase price.
  • Strategic Gamechangers: These are acquisitions where the buyer believes the target gives them an ability to transform their business and is also a critical threat if acquired by a competitor. These tend to be acquisitions which are priced by the buyer’s full ability to pay as they represent bets on a future.

What’s useful about this framework is that it gives guidance to companies who are contemplating acquisitions as exit opportunities:

  • If your company is being considered for a talent acquisition, then it is your job to convince the acquirer that you have built assets and capabilities above and beyond what your team alone is worth. Emphasize patents, communities, developer ecosystems, corporate relationships, how your product fills a distinct gap in their product portfolio, a sexy domain name, anything that might be valuable beyond just the team that has attracted their interest.
  • If a company is being considered for an asset / capability acquisition, then the key is to emphasize the potential financial trajectory of the business and the synergies that can be realized after a merger. Emphasize how current revenues and contracts will grow and develop, how a combined sales and marketing effort will be more effective than the sum of the parts, and how the current businesses are complementary in a real way that impacts the bottom line, and not just as an interesting “thing” to buy.
  • If a company is being evaluated as a business acquisition, then the key is to emphasize how pivotal a role it can play in defining the future of the acquirer in a way that goes beyond just what the numbers say about the business. This is what drives valuations like GM’s acquisition of Cruise (which was a leader in driverless vehicle technology) for up to $1B, or Facebook’s acquisition of WhatsApp (messenger app with over 600 million users when it was acquired, many in strategic regions for Facebook) for $19B, or Walmart’s acquisition of Jet.com (an innovator in eCommerce that Walmart needs to help in its war for retail marketshare with Amazon.com).

The framework works for two reasons: (1) companies are bought, not sold, and the price is usually determined by the party that is most willing to walk away from a deal (that’s usually the buyer) and (2) it generally reflects how most startups tend to create value over time: they start by hiring a great team, who proceed to build compelling capabilities / assets, which materialize as interesting businesses, which can represent the future direction of an industry.

Hopefully, this framework helps any tech industry onlooker wondering why acquisition valuations end up at a certain level or any startup evaluating how best to court an acquisition offer.

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Henry Ford

This weekend, I paid a visit to The Henry Ford. Its a combination of multiple venues — a museum, an outdoor “innovation village”, a Ford Motors factory tour — which collectively celebrate America’s rich history of innovation and manufacturing and, in particular, the legacy of Henry Ford and the Ford Motors company he built.

While ambitious super-CEOs like Larry Page (Google), Elon Musk (Tesla), and Jeff Bezos (Amazon) with their tentacles in everything sometimes seem like a modern phenomena, The Henry Ford shows that they are just a modern-day reincarnations of the super-CEOs of yesteryear. Except, instead of pioneering software at scale, electric vehicles, and AI assistants, Ford was instrumental in the creation of assembly line mass production, the automotive industry (Ford developed the first car that the middle class could actually afford), the aerospace industry (Ford helped develop some of America’s first successful passenger planes), the forty hour workweek, and even the charcoal briquet (part of a drive to figure out what to do with the lumber waste that came from procuring the wood needed to build Model T’s).

In the same way that the tech giants of today pursue “moonshots” like drone delivery and self-driving cars, Ford pushed the frontier with its own moonshots: creating cars out of bioplastic, developing biofuels, and even an early collaboration with Thomas Edison to build an electric car.

It was a striking parallel, and also an instructional one for any company that believes they can stay on top forever: despite the moonshots and the technology advantages, new technologies, market forces, and global shifts come one after the other and yesterday’s Ford (eventually) gets supplanted by tomorrow’s Tesla.

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Snap Inc by the Numbers

If you follow the tech industry at all, you will have heard that consumer app darling Snap Inc. (makers of the app Snapchat) has filed to go public. The ensuing Form S-1 that has recently been made available has left tech-finance nerds like yours truly drooling over the until-recently-super-secretive numbers behind their business.

snapchatnyse.jpg
Oddly apt banner (Image Credit: Business Insider)

Much of the commentary in the press to date has been about how unprofitable the company is (having lost over $500M in 2016 alone). I have been unimpressed with that line of thinking — as what the bottom line is in a given year is hardly the right measure for assessing a young, high-growth company.

While full-time Wall Street analysts will pour over the figures and comparables in much greater detail than I can, I decided to take a quick peek at the numbers to gauge for myself how the business is doing as a growth investment, looking at:

  • What does the growth story look like for the business?
  • Do the unit economics allow for a path to profitability?

What does the growth story look like for the business?

As I noted before, consumer media businesses like Snap have two options available to grow: (1) increase the number of users / amount of time spent and/or (2) better monetize users over time

A quick peek at the DAU (Daily Active Users) counts of Snap reveal that path (1) is troubled for them. Using Facebook as a comparable (and using the midpoint of Facebook’s quarter-end DAU counts to line up with Snap’s average DAU over a quarter) reveals not only that Snap’s DAU numbers aren’t growing so much, their growth outside of North America (where they should have more room to grow) isn’t doing that great either (which is especially alarming as the S-1 admits Q4 is usually seasonally high for them).

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Last 3 Quarters of DAU growth, by region

A quick look at the data also reveals why Facebook prioritizes Android development and low-bandwidth-friendly experiences — international remains an area of rapid growth which is especially astonishing considering how over 1 billion Facebook users are from outside of North America. This contrasts with Snap which, in addition to needing a huge amount of bandwidth (as a photo and video intensive platform) also (as they admitted in their S-1) de-emphasizes Android development. Couple that with Snap’s core demographic (read: old people can’t figure out how to use the app), reveals a challenge to where quick short-term user growth can come from.

As a result, Snap’s growth in the near term will have to be driven more by path (2). Here, there is a lot more good news. Snap’s quarterly revenue per user more than doubled over the last 3 quarters to $1.029/DAU. While its a long way off from Facebook’s whopping $7.323/DAU (and over $25 if you’re just looking at North American users), it suggests that there is plenty of opportunity for Snap to increase monetization, especially overseas where its currently able to only monetize about 1/10 as effectively as they are in North America (compared to Facebook which is able to do so 1/5 to 1/6 of North America depending on the quarter).

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2016 and 2015 Q2-Q4 Quarterly Revenue per DAU, by region

Considering Snap has just started with its advertising business and has already convinced major advertisers to build custom content that isn’t readily reusable on other platforms and Snap’s low revenue per user compared even to Facebook’s overseas numbers, I think its a relatively safe bet that there is a lot of potential for the number to go up.

Do the unit economics allow for a path to profitability?

While most folks have been (rightfully) stunned by the (staggering) amount of money Snap lost in 2016, to me the more pertinent question (considering the over $1 billion Snap still has in its coffers to weather losses) is whether or not there is a path to sustainable unit economics. Or, put more simply, can Snap grow its way out of unprofitability?

Because neither Facebook nor Snap provide regional breakdowns of their cost structure, I’ve focused on global unit economics, summarized below:

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2016 and 2015 Q2-Q4 Quarterly Financials per DAU

What’s astonishing here is that neither Snap nor Facebook seem to be gaining much from scale. Not only are their costs of sales per user (cost of hosting infrastructure and advertising infrastructure) increasing each quarter, but the operating expenses per user (what they spend on R&D, sales & marketing, and overhead — so not directly tied to any particular user or dollar of revenue) don’t seem to be shrinking either. In fact, Facebook’s is over twice as large as Snap’s — suggesting that its not just a simple question of Snap growing a bit further to begin to experience returns to scale here.

What makes the Facebook economic machine go, though, is despite the increase in costs per user, their revenue per user grows even faster. The result is profit per user is growing quarter to quarter! In fact, on a per user basis, Q4 2016 operating profit exceeded Q2 2015 gross profit (revenue less cost of sales, so not counting operating expenses)! No wonder Facebook’s stock price has been on a tear!

While Snap has also been growing its revenue per user faster than its cost of sales (turning a gross profit per user in Q4 2016 for the first time), the overall trendlines aren’t great, as illustrated by the fact that its operating profit per user has gotten steadily worse over the last 3 quarters. The rapid growth in Snap’s costs per user and the fact that Facebook’s costs are larger and still growing suggests that there are no simple scale-based reasons that Snap will achieve profitability on a per user basis. As a result, the only path for Snap to achieve sustainability on unit economics will be to pursue huge growth in user monetization.

Tying it Together

The case for Snap as a good investment really boils down to how quickly and to what extent one believes that the company can increase their monetization per user. While the potential is certainly there (as is being realized as the rapid growth in revenue per user numbers show), what’s less clear is whether or not the company has the technology or the talent (none of the key executives named in the S-1 have a particular background building advertising infrastructure or ecosystems that Google, Facebook, and even Twitter did to dominate the online advertising businesses) to do it quickly enough to justify the rumored $25 billion valuation they are striving for (a whopping 38x sales multiple using 2016 Q4 revenue as a run-rate [which the S-1 admits is a seasonally high quarter]).

What is striking to me, though, is that Snap would even attempt an IPO at this stage. In my mind, Snap has a very real shot at being a great digital media company of the same importance as Google and Facebook and, while I can appreciate the hunger from Wall Street to invest in a high-growth consumer tech company, not having a great deal of visibility / certainty around unit economics and having only barely begun monetization (with your first quarter where revenue exceeds cost of sales is a holiday quarter) poses challenges for a management team that will need to manage public market expectations around forecasts and capitalization.

In any event, I’ll be looking forward to digging in more when Snap reveals future figures around monetization and advertising strategy — and, to be honest, Facebook’s numbers going forward now that I have a better appreciation for their impressive economic model.

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Why VR Could be as Big as the Smartphone Revolution

Technology in the 1990s and early 2000s marched to the beat of an Intel-and-Microsoft-led drum.

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via IT Portal

Intel would release new chips at a regular cadence: each cheaper, faster, and more energy efficient than the last. This would let Microsoft push out new, more performance-hungry software, which would, in turn, get customers to want Intel’s next, more awesome chip. Couple that virtuous cycle with the fact that millions of households were buying their first PCs and getting onto the Internet for the first time – and great opportunities were created to build businesses and products across software and hardware.

But, over time, that cycle broke down. By the mid-2000s, Intel’s technological progress bumped into the limits of what physics would allow with regards to chip performance and cost. Complacency from its enviable market share coupled with software bloat from its Windows and Office franchises had a similar effect on Microsoft. The result was that the Intel and Microsoft drum stopped beating as they became unable to give the mass market a compelling reason to upgrade to each subsequent generation of devices.

The result was a hollowing out of the hardware and semiconductor industries tied to the PC market that was only masked by the innovation stemming from the rise of the Internet and the dawn of a new technology cycle in the late 2000s in the form of Apple’s iPhone and its Android competitors: the smartphone.

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via Mashable

A new, but eerily familiar cycle began: like clockwork, Qualcomm, Samsung, and Apple (playing the part of Intel) would devise new, more awesome chips which would feed the creation of new performance-hungry software from Google and Apple (playing the part of Microsoft) which led to demand for the next generation of hardware. Just as with the PC cycle, new and lucrative software, hardware, and service businesses flourished.

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But, just as with the PC cycle, the smartphone cycle is starting to show signs of maturity. Apple’s recent slower than expected growth has already been blamed on smartphone market saturation. Users are beginning to see each new generation of smartphone as marginal improvements. There are also eery parallels between the growing complaints over Apple software quality from even Apple fans and the position Microsoft was in near the end of the PC cycle.

While its too early to call the end for Apple and Google, history suggests that we will eventually enter a similar phase with smartphones that the PC industry experienced. This begs the question: what’s next? Many of the traditional answers to this question – connected cars, the “Internet of Things”, Wearables, Digital TVs – have not yet proven themselves to be truly mass market, nor have they shown the virtuous technology upgrade cycle that characterized the PC and smartphone industries.

This brings us to Virtual Reality. With VR, we have a new technology paradigm that can (potentially) appeal to the mass market (new types of games, new ways of doing work, new ways of experiencing the world, etc.). It also has a high bar for hardware performance that will benefit dramatically from advances in technology, not dissimilar from what we saw with the PC and smartphone.

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via Forbes

The ultimate proof will be whether or not a compelling ecosystem of VR software and services emerges to make this technology more of a mainstream “must-have” (something that, admittedly, the high price of the first generation Facebook/Oculus, HTC/Valve, and Microsoft products may hinder).

As a tech enthusiast, its easy to get excited. Not only is VR just frickin’ cool (it is!), its probably the first thing since the smartphone with the mass appeal and virtuous upgrade cycle that can bring about the huge flourishing of products and companies that makes tech so dynamic to be involved with.

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How IPOs are Doing in the Public Markets

After reading my last post on what the decline in recently IPO’d startups means for the broader tech industry, a friend of mine encouraged me to look closer at how IPO’s in general have been performing. The answer: badly

Recent IPO performance vs S&P 500 over last year

The chart above shows how Renaissance Capital’s US IPO index (prospectus), which tracks major IPOs in US markets, has performed versus the broader market (represented by the S&P500) over the past year. While the S&P500 hasn’t had a great year (down just over 10%), IPOs have done even worse (down over 30%).

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What Happens After the Tech Bubble Pops

In recent years, it’s been the opposite of controversial to say that the tech industry is in a bubble. The terrible recent stock market performance of once high-flying startups across virtually every industry (see table below) and the turmoil in the stock market stemming from low oil prices and concerns about the economies of countries like China and Brazil have raised fears that the bubble is beginning to pop.

Company Ticker Industry Stock Price Change Since IPO (Feb 5)
GoPro NASDAQ:GPRO Consumer Hardware -72%
FitBit NYSE:FIT Wearable -47%
Hortonworks NASDAQ:HDP Big Data -68%
Teladoc NYSE:TDOC Telemedicine -50%
Evolent Health NYSE:EVH Healthcare -46%
Square NYSE:SQ Payment & POS -34%
Box NYSE:BOX Cloud Storage -42%
Etsy NASDAQ:ETSY eCommerce -77%
Lending Club NYSE:LC Lending Platform -72%

While history will judge when this bubble “officially” bursts, the purpose of this post is to try to make some predictions about what will happen during/after this “correction” and pull together some advice for people in / wanting to get into the tech industry. Starting with the immediate consequences, one can reasonably expect that:

  • Exit pipeline will dry up: When startup valuations are higher than what the company could reasonably get in the stock market, management teams (who need to keep their investors and employees happy) become less willing to go public. And, if public markets are less excited about startups, the price acquirers need to pay to convince a management team to sell goes down. The result is fewer exits and less cash back to investors and employees for the exits that do happen.
  • VCs become less willing to invest: VCs invest in startups on the promise that future IPOs and acquisitions will make them even more money. When the exit pipeline dries up, VCs get cold feet because the ability to get a nice exit seems to fade away. The result is that VCs become a lot more price-sensitive when it comes to investing in later stage companies (where the dried up exit pipeline hurts the most).
  • Later stage companies start cutting costs: Companies in an environment where they can’t sell themselves or easily raise money have no choice but to cut costs. Since the vast majority of later-stage startups run at a loss to increase growth, they will find themselves in the uncomfortable position of slowing down hiring and potentially laying employees off, cutting back on perks, and focusing a lot more on getting their financials in order.

The result of all of this will be interesting for folks used to a tech industry (and a Bay Area) flush with cash and boundlessly optimistic:

  1. Job hopping should slow: “Easy money” to help companies figure out what works or to get an “acquihire” as a soft landing will be harder to get in a challenged financing and exit environment. The result is that the rapid job hopping endemic in the tech industry should slow as potential founders find it harder to raise money for their ideas and as it becomes harder for new startups to get the capital they need to pay top dollar.
  2. Strong companies are here to stay: While there is broad agreement that there are too many startups with higher valuations than reasonable, what’s also become clear is there are a number of mature tech companies that are doing exceptionally well (i.e. Facebook, Amazon, Netflix, and Google) and a number of “hotshots” which have demonstrated enough growth and strong enough unit economics and market position to survive a challenged environment (i.e. Uber, Airbnb). This will let them continue to hire and invest in ways that weaker peers will be unable to match.
  3. Tech “luxury money” will slow but not disappear: Anyone who lives in the Bay Area has a story of the ridiculousness of “tech money” (sky-high rents, gourmet toast, “its like Uber but for X”, etc). This has been fueled by cash from the startup world as well as free flowing VC money subsidizing many of these new services . However, in a world where companies need to cut costs, where exits are harder to come by, and where VCs are less willing to subsidize random on-demand services, a lot of this will diminish. That some of these services are fundamentally better than what came before (i.e. Uber) and that stronger companies will continue to pay top dollar for top talent will prevent all of this from collapsing (and lets not forget San Francisco’s irrational housing supply policies). As a result, people expecting a reversal of gentrification and the excesses of tech wealth will likely be disappointed, but its reasonable to expect a dramatic rationalization of the price and quantity of many “luxuries” that Bay Area inhabitants have become accustomed to soon.

So, what to do if you’re in / trying to get in to / wanting to invest in the tech industry?

  • Understand the business before you get in: Its a shame that market sentiment drives fundraising and exits, because good financial performance is generally a pretty good indicator of the long-term prospects of a business. In an environment where its harder to exit and raise cash, its absolutely critical to make sure there is a solid business footing so the company can keep going or raise money / exit on good terms.
  • Be concerned about companies which have a lot of startup exposure: Even if a company has solid financial performance, if much of that comes from selling to startups (especially services around accounting, recruiting, or sales), then they’re dependent on VCs opening up their own wallets to make money.
  • Have a much higher bar for large, later-stage companies: The companies that will feel the most “pain” the earliest will be those with with high valuations and high costs. Raising money at unicorn valuations can make a sexy press release but it doesn’t amount to anything if you can’t exit or raise money at an even higher valuation.
  • Rationalize exposure to “luxury”: Don’t expect that “Uber but for X” service that you love to stick around (at least not at current prices)…
  • Early stage companies can still be attractive: Companies that are several years from an exit & raising large amounts of cash will be insulated in the near-term from the pain in the later stage, especially if they are committed to staying frugal and building a disruptive business. Since they are already relatively low in valuation and since investors know they are discounting off a valuation in the future (potentially after any current market softness), the downward pressures on valuation are potentially lighter as well.
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Thoughts from Google I/O

A few weeks ago, I had the chance to attend Google I/O — this time, not just as a fan of the Android platform but representing a developer. Below are some of my key takeaways from the event

  • Google‘s strategic direction – there were three big themes that were emphasized
    • Next Billion – a lot of what Google is doing (like making Google Maps / YouTube work without internet) is around making Chrome/Android/Google Search the platforms of choice for the next billion mobile users — many of whom will come from Brazil, India, China, Indonesia, etc. Its important for us to remember that the US/Western Europe is not the totality of the world and that there’s a big chance that future major innovations and platform will come from elsewhere in the world.
    • Machine Learning – I was blown away (and a little creeped out!) by the machine learning tech they showed: Google Now on Tap (you can hold the home button and Android will figure out what’s on your screen/what you’re listening to and give you relevant info), the incredible photo recognition tech in the new Photos app, as well as innovations Android is making in unlocking your phone when it knows its been in your pocket and not your desk. Every company should be thinking about where machine intelligence can be used to enhance their products.
    • Everything Connected – it reminded me of Microsoft’s heyday: except instead of Windows everywhere, its now Android/Chrome everywhere: Android Wear, Chromecast, Android TV, Android Auto, Brillo/Weave, Cardboard for VR, Nest/Dropcam for the home, things like Jacquard & Soli enabling new user interfaces, etc.
  • Marketing enhancements to Google Play: Google has taken steps to make application developers’ lives easier — more details here: http://android-developers.blogspot.com/2015/05/empowering-successful-global-businesses.html, but:
    • I sat through a panel on how Google does personalized recommendations / search on Google Play — long story short: keywords + ratings matter
    • Google will now allow A/B testing of Google Play store listings
    • Google Play console now directly integrates App Install advertising so you can run campaigns on Google Search, AdMob, and YouTube
    • Google Play console will also track how users get to Play Store listing by channel and how many convert to install
  • Android M – a lot of tweaks to the core Android app model for developers to pay attention to
    • Permissions: Android M moves to a very iOS-like model where app permissions aren’t granted when you install the app but when the app first uses them; they’ve also moved to a model where users can go into settings and manually revoke previously granted permissions; all Android developers will need to eventually think about how their apps will work if certain permissions are denied (see: http://developer.android.com/preview/features/runtime-permissions.html)
    • App Links: Android will now let apps handle all links on websites they control by default (see: http://developer.android.com/preview/features/app-linking.html)
    • Doze and App Standby: Applications will now have two additional modes that the OS may enforce — one called Doze that keeps all apps in sleep mode to reduce power drain and Standby where the OS determines an app is “idle” and cuts off network access, syncs, and jobs — apps in both modes can still receive “high priority notifications” (see: http://developer.android.com/preview/behavior-changes.html under Power-Saving Optimizations)
    • Auto Backup: Applications will now backup up to 25MB worth of data to the user’s Google Drive (but won’t count against their quota) once every 24 hours; this can be customized (see: http://developer.android.com/preview/backup/index.html)
    • Fingerprint API, Direct Share, and Voice Interactions: universal fingerprint recognition API, the ability to share specific content with specific favorite users (i.e. send to someone over Facebook Messenger, etc), and a new way to build voice interactions in app (see: http://developer.android.com/preview/api-overview.html, starting from Authentication)
  • Other stuff for developers
    • App InvitesGoogle has built out custom share cards / install flows and deep links to make it easier for users to share apps with their friends: http://googledevelopers.blogspot.com/2015/05/grow-your-app-installs-with-app-invites.html
    • Android Design Library: Google now has libraries to help devs build out Material Design elements — now, you too, can make your own Floating Action Button!: http://android-developers.blogspot.com/2015/05/android-design-support-library.html
    • Chrome Custom Tabs: basically lets you embed Chrome in your app with custom styling (rather than having to embed a vanilla webview and do a lot of work styling it), its apparently already out in beta channels for Chrome: https://developer.chrome.com/multidevice/android/customtabs
    • Google Cloud Testing Lab: This was pretty cool (and a product of Google’s acquisition of Appurify). Now, Google will provide two highly useful testing services for Android developers: (more details: https://developers.google.com/cloud-test-lab/)
      • For free/automatically: pound on every button / interface on your app that they can see after launch for 1 min and see how many crashes they can get on a variety of Android devices (which helps given the sheer number of them that exist)
      • Paid: run custom Espresso or Robotium tests on specific devices (so you can get test coverage on a broader range of devices doing a specific set of things)
    • Places API: a lot of talks promoting their new mobile Places APIs (which will let iOS and Android apps have better mapping and place search capability)
    • Google Cloud Messaging: this is basically Google’s push notification delivery engine and they announced support for iOS as well as “Topics” (so devices don’t have to get every notification, just the ones relevant to them): http://android-developers.blogspot.com/2015/05/a-closer-look-at-googleplay-services-75.html
    • Espresso testing framework: this was a ridiculously packed session — but Google has apparently made numerous refinements to the Espresso UI testing framework
  • A lot of cool announcements about new Android Wear functionality (which my Moto 360 is eagerly awaiting)
  • Just cool stuff from ATAP
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Tesla in Energy Market

One of the most fascinating things about the technology industry is how the lines between markets and competitors can shift all of a sudden. One day, Nokia is mainly thinking about competing with phone makers like RIM and Motorola on getting influence with carriers and upselling text messaging services / ring tones and, the next, they need to deal with players like Apple and Google, fostering a strong app ecosystem, creating intuitive user experiences, and building a brand that resonates with users.

One interesting case that has emerged in the past couple of days is the electric car company Tesla entering the Home and Industrial energy market. In much the same way that software let Apple and Google build operating systems that could double up as phones, the manufacturing prowess and battery technology which let Tesla take on the electric car market also gives them the ability to offer energy storage solutions for the utility market.

When I was a VC looking at energy storage opportunities, there was a fair amount of discussion in the industry about the future potential for electric cars connected to the grid to themselves to operate as energy storage / load balancing. I never expected this to amount to much for at least a decade — when the penetration of electric vehicles would be high enough to make sense for utilities to invest in this capability. Never would I have imagined the path to anything even remotely like this would be through an electric car company directly making and offering electric batteries to supply the market. While history will judge whether or not Tesla is successful at this (a lot of unanswered questions around the durability of their Li-ion batteries for utility purposes and how they will be serviced / maintained), you can’t fault Tesla for lack of boldness!

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A Week with the Moto 360

Its hard for a device to get noticed in a world where new phones and tablets and smartwatches seem to come out every day. But one device unveiled back in March did for me: Motorola’s new smartwatch, the Moto 360 (see Motorola marketing video below).

So, being a true Fandroid, I bought a Moto 360 (clarification: my wonderful wife woke up at an unseemly hour and bought one for each of us) and have been using it for about a week — my take?

While there’s a lot of room for improvement, I like it.

  • This is by far the best looking smartwatch out there. Given how important appearance is for a watch, this is by far the most important positive that can be said of the Moto 360 — it just looks good. I was a little worried that the marketing materials wouldn’t accurately represent reality, but that fear turned out to be unfounded. The device not only looks nice up close, especially since its round design just looks so much better than pretty much every other smartwatch’s blocky rectangular designs, it also feels good: stainless steel body, a solid-feeling glass surface, and a very nice-feeling leather strap.
  • The battery life is nothing to brag about but will last you a full day. The key here is that the watch display can be used in two modes: (1) where the display is always on (and, from what I’ve read, will get something like 12 hours of battery life which won’t last you a whole day) and (2) where the display only turns on when you’ve triggered it which, in my experience, will get you something more like 20 hours of battery life — enough to get through a typical day. Obviously, I use (2) and what makes this possible is that turning on the screen is quite easy: you can do it by tapping on the touch-sensitive screen, by pushing the side button, or (although this only works 80% of the time) by moving your arm to be in a position where you can look at it. Now, I’d love a watch that could last at least months with the screen on before needing a charge but since I’m already charging my phone every night and since the wireless charging dock makes it easy to charge the device, this is an annoyance but hardly a dealbreaker.
  • The out-of-the-box experience needs some work. While the packaging is beautiful and fits well with how nice the watch itself looks, the Moto 360 unfortunately ships needing to be charged up to 80% before it can be used. Unfortunately this is not clear anywhere on the packaging or in the Android Wear smartphone app that you’re supposed to use to pair with the device or on the watch display so let me be explicit: if you buy the Moto 360, charge the device up before you download the Android Wear app or try to use it. Otherwise, nothing will happen — something which very much freaked out yours truly when I thought I had gotten a defective unit. Also, while I haven’t heard about this from anyone else, the Moto Connect app that Motorola wanted me to install also failed to provision an account for me correctly, leaving me unable to customize the finer details on the watchface designs that come with the watch. Not the end of the world, but definitely a set of problems a company like Motorola shouldn’t be facing.
  • I’m not sure the pedometer or heart rate sensor are super-accurate, but they’ve pretty much killed any need/desire on my part for a fitness wearable. The fitness functionality on the watch isn’t anything to write home about (its a simple step counter and heart rate sensor with basic history and heart-rate goal tracking). I’m also not entirely convinced that the heart rate sensor or the pedometer are particularly accurate (although its not like the competition is that great either), but their availability on a device I’m always going to be wearing because of its other functionality may pose a serious risk to fitness wearable companies which only do step tracking or heart rate detection.
  • Voice recognition is still not quite where it needs to be for me to make heavier use of the voice commands functionality.
  • The software doesn’t do a ton but that’s the way it should be. When I first started using Android Wear, I was a little bummed that it didn’t seem to have a ton of functionality: I couldn’t play games on it or browse maps or edit photos (or send my heartbeat or a random doodle to a random person…). But, after a day or two of wearing the device to social gatherings, I came to realize you really don’t want to do everything on your watch. Complicated tasks should be done on your phone or tablet or PC. They not only have larger screens but they are used in social contexts where that type of activity makes sense. Spending your time trying to do something on your smartwatch looks far more awkward (and probably looks far more rude) than doing the same thing on your phone or other device. Instead, I’ve come to rely on the Moto 360 as a way of supplementing my phone by letting me know (by vibrating and quickly lighting up the screen) about incoming notifications (like from an email or text or Facebook message), new alerts from Google Now (like access to the local weather or finding out about sudden traffic on the road to/from work), and by letting me deal with notifications the way I would if they were on my phone (like the ability to play and pause music or a podcast, or the ability to reply using voice commands to an email or text). This helps me be more present in social settings as I feel much less anxiety around needing to constantly check my phone for new updates (something I’ve been suffering from ever since my Crackberry days)
  • Android Wear’s approach makes it easy to claim support for many apps (simply by supporting notifications), but there needs to be more interesting apps and watchfaces for the platform to truly get mainstream appeal

All in all, I think the Moto 360 is hands down, the best smartwatch available right now (I’ll reserve my judgement when I get a chance to play with the Apple Watch). Its a great indicator of what Google’s Android Wear platform can achieve when done well and I’ve found its meaningfully changed how I’ve used my phone and eliminated my use of other fitness tracking devices. That being said, there’s definitely a lot of room for improvement: on battery life (especially in a world where the Pebble smartwatch can achieve nearly a week of battery life between charges), on voice recognition accuracy, on out-of-the-box setup experience, and on getting more apps and watchfaces on board. So, if you’re an early adopter type who’s comfortable with some of these rough edges and with waiting to see what apps/watchfaces come out and who is interested in some of the software value I described, this would be a great purchase. If not, you may want to wait for the hardware and software to improve another iteration or two before diving in.

I think the industry still needs a good answer to the average person around “why should I buy a smartwatch?” But, in any event, I’ll be very curious to see how this space evolves as more smartwatches come to market and especially how they change people’s relationships with their other devices.

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Minecraft for Education

I’ve always been blown away by the richness of the Minecraft “game engine”. While ostensibly a game about breaking and placing blocks (while potentially surviving against monsters and other players depending on the server and the game mode), its “creative mode” as well as widespread user modifications to the game have unleashed an amazing amount of creativity resulting in people building amazing worlds including (but not limited to, HT: Mashable for a lot of these)

What blew my mind recently, though, was discovering that people have even used the Minecraft game engine to serve as simulations for things as sophisticated as a computer processor:

and a 1 kilobyte hard drive!

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Knowing how much kids enjoy Minecraft made me wonder if it would be possible to use the game and these sorts of rich models as an education tool to complement the traditional “blackboard lecture” model of teaching which does a very poor job of imparting intuition and understanding. The beauty of something like Minecraft is that it can be used to produce a visual, modifiable simulation in a format that students are probably already consuming (or can probably learn how in a short amount of time), and as a result, it lends itself to exploration and to students making or modifying things to demonstrate and improve their understanding.

Building a microprocessor or digital storage system may be too difficult for a class assignment (although at a reduced level of complexity, they could become very useful teaching aids), but a digital tour of ancient Rome or an assignment to build an Egyptian pyramid or a basic AND or OR circuit? I think that type of learning could benefit a great deal from some Minecraft-ification :-).

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Tech Should be More Than Just Dollar Signs and Deals

#sentimental

Much of the talk recently about the company Oculus Rift has been around the notion that it’s recent $1B purchase by Facebook is a sign of a tech bubble: that companies without clear traction or business plans are being valued for outrageous sums of money.

Without commenting on that particular transaction or idea, I will say that while things like financials and valuations are important (I am a VC after all :-D), those of us in the tech industry oftentimes forget the reason that we’re all here: to help create things which improve people’s lives in transformative ways.

Seeing this article/video on Engadget earlier today about how Oculus Rift helped a terminally ill woman get to virtually walk outside reminded me that there is more to the tech industry than dollar signs and deals: the reason we’re here is to make people’s lives better and that we should never lose sight of that.

This won’t (nor should it) resolve any debate or concerns over the technical and financial merits of Oculus Rift. But my point is there is more to tech than just making money and driving up valuations, and if we want the future of the tech industry to be more than just bubbles and crashes, we should keep that in mind.

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Pace of Mobile

Two slides from NVIDIA’s presentation at CES (captured by the excellent Anandtech team) were particularly stunning to me in terms of illustrating how quickly the mobile revolution is advancing.

This first slide highlights the main NVIDIA product announcement/claim: that starting with their current-generation product, Tegra K1 (cue NVIDIA PR: it was so advanced that they couldn’t just call the successor Tegra 5 :-)), their mobile graphics architecture would be the same as what they are currently selling for their PC products (Kepler).

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That’s not really a new claim — after all, it had been announced previously that Logan (the comic book inspired codename for Tegra K1) was supposed to have Kepler technology inside. What is interesting is when its presented in the following way:

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According to NVIDIA, it took 8 years for the PC technology that supported the Unreal Engine 3 game engine to make it to smartphones (in and of itself an impressive feat if you think about it), but only two years for Unreal Engine 4.

Obviously, there are a lot of caveats here (this is, after all, a press announcement to drum up excitement) – even if the GPU architecture is 100% the same we have no idea what kind of real-world performance or power consumption we’ll get out of this (so word to the wise: ignore a lot of the “core count” crap, its not really apples-to-apples with anything). But it’s a great indicator of how quickly the smartphone/tablet are usurping the role as the primary computing device for the world and how hard that is pushing the broader technology industry to keep up.

More great content on this (and more) at Anandtech

(Images captured by Anandtech team during NVIDIA CES press conference liveblog)

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The Facebook Hamster Wheel

With a $1 billion price tag for Instagram, a $1.1 billion valuation for Tumblr, and a rumored $3 billion bid for Snapchat, many observers are probably scratching their heads, wondering: why are companies like Facebook and Yahoo willing to shell out this kind of cash for barely-in-revenue-if-at-all consumer startups?While I can’t pretend that all these valuations are “rational” in a traditional sense, I can say that it becomes more understandable if you think about Facebook’s business model. Plain and simple, Facebook’s business model revolves around taking the total amount of time users spend on Facebook and making money against it, whether its through ads or charging a “tax” on virtual goods (think Farmville items) or gifts bought on the platform.

As a result, for Facebook to grow its core business, it really has two options:

  1. Increase the total amount of time users are spending on Facebook
  2. Increase how effectively you are monetizing existing time spent on Facebook

The challenge with #2 is that there really is an upper limit to how much money you can make on a minute of user eyeball-time before you start annoying the user base (either because there are too many ads or because the ads get kind of creepy). So, what most internet media companies strive for is #1 – increase the total amount of time users spend on their websites/apps.

The challenge with #1, though, is that every additional user-minute a company gets is an incremental minute of some other activity that the user needs to give up. And, since we all only have 24 hours a day (and need to sleep), that’s a limited number of minutes to go around, especially for a company like Facebook, where its users are already pretty addicted.

This means that Facebook (and other digital media companies like Yahoo and Twitter) is in a horrifying never-ending race not only to get more precious user-minutes but just to hold on to what they already have. Any time a shiny new startup takes off which seems to suck up user-time — especially if its amongst teens/adolescents who, because they don’t have tons of friends on Facebook already, don’t have any strong reason to be on Facebook — Facebook needs to find a way to grab that time back just to stay even. It’s a hamster wheel that Facebook can never get off of short of changing its underlying business model.

It’s this attention economy that drives digital media companies to pay up for startups like Instagram or Tumblr or Snapchat — they’re new threats to Facebook’s growth and business model, as well as new opportunities to get new user-minutes. That’s why these companies are so prized – for digital media companies in the attention economy, it’s the user-minutes, stupid.

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Disruptive Innovation in one Chart

There are few examples of disruptive innovation as clear as what happened to Research in Motion/Blackberry, the former giant when it came to smart mobile devices for businesspeople (and a device which was previously super-important to me). Despite a seemingly unassailable market position and huge profits, they were caught off-guard by the more software-and-consumer centric smartphone wave that followed, the result being an astonishing 94% loss in company value in 5 years (HT: Quartz):

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Only the paranoid survive indeed…

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What Accel Thinks About Big Data

Capitalizing on widespread interest in companies built around “Big Data”, VC firm Accel yesterday unveiled its “Big Data Fund 2”, a $100M fund aiming to make investments in technology companies which help their customers make sense of the massive volumes of data that they are now able to gather and generate.

While I personally have gotten a little sick of the “Big Data” moniker (its become like “cloud computing” – just one of many buzzwords that companies slap on their websites and press releases), what jumped out to me in reading the press release and the tech blog coverage was the emphasis of the fund away from companies commercializing Big Data infrastructure technology and towards companies building “data driven software”.

Now, no VC’s “rules” about a fund are ever absolute – they will find ways to put money into (what they perceive as) good investments, regardless of what they’ve said in press releases – but the message shift jumped out to me as potentially a very bold statement by Accel on how they perceive the state of the “Big Data” industry.

All industries go through phases – in the early days, the focus is around laying the infrastructure and foundation, and the best tech investments tend to be companies working on infrastructure which ultimately serves as a platform for others (for example: Intel [computing] and Cisco [internet] and Qualcomm [mobile]). Eventually, the industry moves on to the next phase – where the infrastructure layer becomes extremely difficult for small companies to compete in and the best tech investments tend to be in companies which take advantage of the platform to build new and interesting applications (for example: Adobe or VMWare [computing] and Amazon.com [internet] and Rovio [mobile]).

Of course, its hard to know when that transition happens and, as often happens with tech, the “applications” phase of one industry (e.g., Facebook, Salesforce.com, etc.) can oftentimes serve as the infrastructure phase for another (e.g., social applications, CRM-driven applications, etc.). But, what Accel’s “Big Data Fund 2”’s mission suggests is that Accel believes the “Big Data industry” has moved beyond infrastructure and is on towards the second phase where the most promising early-stage investments are no longer in infrastructure to help companies manage/make use of Big Data, but in applications that generate the value directly.

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No Digital Skyscrapers

A colleague of mine shared an interesting article by Sarah Lacy from tech site Pando Daily about the power of technology building the next set of “digital skyscrapers” – Lacy’s term for enduring, 100-year brands in/made possible by technology. On the one hand, I wholeheartedly agree with one of the big takeaways Lacy wants the reader to walk away with: that more entrepreneurs need to strive to make a big impact on the world and not settle for quick-and-easy payouts. That is, after all, why venture capitalists exist: to fund transformative ideas.

But, the premise of the article that I fundamentally disagreed with – and in fact, the very reason I’m interested in technology is that the ability to make transformative ideas means that I don’t think its possible to make “100-year digital skyscrapers”.

In fact, I genuinely hope its not possible. Frankly, if I felt it were, I wouldn’t be in technology, and certainly not in venture capital. To me, technology is exciting and disruptive because you can’t create long-standing skyscrapers. Sure, IBM and Intel have been around a while — but what they as companies do, what their brands mean, and their relative positions in the industry have radically changed. I just don’t believe the products we will care about or the companies we think are shaping the future ten years from now will be the same as the ones we are talking about today, nor were they the ones we talked about ten years ago, and they won’t be the same as the ones we talk about twenty years from now. I’ve done the 10 year comparison before to illustrate the rapid pace of Moore’s Law, but just to be illustrative again: remember, 10 years ago:

    • the iPhone (and Android) did not exist
    • Facebook did not exist (Zuckerberg had just started at Harvard)
    • Amazon had yet to make a single cent of profit
    • Intel thought Itanium was its future (something its basically given up on now)
    • Yahoo had just launched a dialup internet service (seriously)
    • The Human Genome Project had yet to be completed
    • Illumina (posterchild for next-generation DNA sequencing today) had just launched its first system product

And, you know what, I bet 10 years from now, I’ll be able to make a similar list. Technology is a brutal industry and it succeeds by continuously making itself obsolete. It’s why its exciting, and it’s why I don’t think and, in fact, I hope that no long-lasting digital skyscrapers emerge.

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Why Comparing Google Drive to Dropbox is Missing the Point

Last week, Google unveiled its long-rumored Google Drive product with great fanfare. While the gaggle of tech journalists/bloggers issued predictable comparisons of Google’s new service with online storage/syncing services like Dropbox, I couldn’t help but think that most of the coverage missed the point on why Google Drive was interesting. Yes, its another consumer-facing cloud storage service – but the really interesting aspect of it is not whether or not it’ll “kill Dropbox/Box.net/iCloud/[insert your favorite consumer cloud service here]”, but the fact that this could be the beginning of a true web “file system”.

I’ve blogged before about the strengths of the web as a software development platform and the extent to which web apps are now practically the same thing as the apps that we run on our computers and phones. But, frankly, one of the biggest things holding back the vision of the web as a full-fledged “operating system” is the lack of a web-centric “file system”. I use the quotes because I’m not referring to the underlying NTFS/ExtX/HFS/etc technology that most people think of when they hear “file system”: I’m referring to basic functionalities that we expect in our operating systems and file systems:

  • a place to reliably create, read, and edit data
  • the ability to search through stored information based on metadata
  • a way to associate data with specific applications and services that can operate on them (i.e. opening Photoshop files in Adobe Photoshop, MP3s in iTunes, etc)
  • a way to let any application with the right permissions and capabilities to act on that data

Now, a skeptic might point out that the HTML5 specification actually has a lot of local storage/file handling capabilities and that services like Dropbox already provide some of this functionality in the form of APIs that third party apps and services can use – but in both cases, the emphasis is first and foremost on local storage – putting stuff onto or syncing with the storage on your physical machine. As long as that’s true, the web won’t be a fully functioning operating system. Web services will routinely have to rely on local storage (which, by the way, reduces the portability of these apps between different machines), and applications will have to be more silo’d as they each need to manage their own storage (whether its stored on their servers or stored locally on a physical device).

What a vision of the web as operating system needs is a cloud-first storage service (where files are meant to reside on the cloud and where local storage is secondary) which is searchable, editable, and supports file type associations and allows web apps and services to have direct access to that data without having to go through a local client device like a computer or a phone/tablet. And, I think we are beginning to see that with Google Drive.

  • The local interface is pretty kludgy: the folder is really just a bunch of bookmark links, emphasizing that this is a web-centric product first and foremost
  • It offers many useful operating system-like functionality (like search and revision history) directly on the web where the files are resident
  • Google Drive greatly emphasizes how files stored on it have associated viewers and can be accessed by a wide range of apps, including some by Google (i.e. attachments on Gmail, opening/editing on Google Docs, and sharing with Google+) and some by third parties like HelloFax, WeVideo, and LucidChart

Whether or not Google succeeds longer-term at turning Google Drive into a true cloud “file system” will depend greatly on their ability to continue to develop the product and manage the potential conflicts involved with providing storage to web application competitors, but suffice to say, I think we’re at what could be the dawn of the transition from web as a software platform to web as an operating system. This is why I feel the companies that should pay more close attention to this development aren’t necessarily the storage/sync providers like Dropbox and Box.net – at least not for now – but companies like Microsoft and Apple which have a very different vision of how the future of computing should look (much more local software/hardware-centric) and who might not be in as good a position if the web-centric view that Google embodies takes off (as I think and hope it will).

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