Skip to content →

47 search results for "startup"

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!

Leave a Comment

Advice VCs Want to Give but Rarely Do to Entrepreneurs Pitching Their Startups

I thought I’d re-post a response I wrote a while ago to a question on Quora as someone recently asked me the question: “What advice do you wish you could give but usually don’t to a startup pitching you?”

  • Person X on your team reflects poorly on your company – This is tough advice to give as its virtually impossible during the course of a pitch to build enough rapport and get a deep enough understanding of the inter-personal dynamics of the team to give that advice without it unnecessarily hurting feelings or sounding incredibly arrogant / meddlesome.
  • Your slides look awful – This is difficult to say in a pitch because it just sounds petty for an investor to complain about the packaging rather than the substance.
  • Be careful when using my portfolio companies as examples – While its good to build rapport / common ground with your VC audience, using their portfolio companies as examples has an unnecessarily high chance of backfiring. It is highly unlikely that you will know more than an inside investor who is attending board meetings and in direct contact with management, so any errors you make (i.e., assuming a company is doing well when it isn’t or assuming a company is doing poorly when it is doing well / is about to turn the corner) are readily caught and immediately make you seem foolish.
  • You should pitch someone who’s more passionate about what you’re doing – Because VCs have to risk their reputation within their firms / to the outside world for the deals they sign up to do, they have to be very selective about which companies they choose to get involved with. As a result, even if there’s nothing wrong with a business model / idea, some VCs will choose not to invest due simply to lack of passion. As the entrepreneur is probably deeply passionate about and personally invested in the market / problem, giving this advice can feel tantamount to insulting the entrepreneur’s child or spouse.

Hopefully this gives some of the hard-working entrepreneurs out there some context on why a pitch didn’t go as well as they had hoped and maybe some pointers on who and how to approach an investor for their next pitch.

(Image credit – Someecard)

Leave a Comment

Crowdfunding: Hardware Startups Beware

Hardware startups are one area I spend a fair amount of time with in my life as a VC, and while I love working with hardware companies, it should go without saying that hardware startups are incredibly difficult to do. They require knowhow across multiple disciplines — software, electrical engineering, industrial design, manufacturing, channel, etc. – and, as a result, have challenges and upfront capital needs that most software/web companies lack. This has led many angels and VCs to be wary of investments involving building hardware so its no small wonder, then, that many hardware entrepreneurs have turned to crowdfunding websites like Kickstarter and Indiegogo to try to raise funds for development.

While crowdfunding can be a great fit for certain projects, I think early stage hardware startups should beware. Yes, crowdfunding sites can generate upfront capital that can fund development, but unlike traditional equity/debt investments (like the kind an angel or VC or bank will give you), “crowdfunding capital” has a particularly onerous type of “string attached”: it’s a presale.

Obviously, the entrepreneurs trying to raise crowdfunding capital want to push their projects towards real sales – so why might a presale be a bad thing? For hardware companies:

  • Raw production costs are a major percentage of sales – so even if you raised $1 million, you probably are going to be able to keep max $500,000 after the cost of materials/manufacturing
  • These pre-sales are oftentimes discounted – so you are generating lower margins on each unit making these particularly painful sales to make
  • Except in a few instances, the number of presales tends to not be high enough to meaningfully change the cost of manufacturing (i.e. upfront tooling costs or supply procurement) – which further eats into the amount of capital you have left to deploy on development since you probably have to pay the low volume price
  • It means you need to keep to some level of deadline. There is a risk that you won’t make your own deadline and there’s also risk that the time pressure might lead to tradeoffs (leave out a certain feature or asset, run fewer tests, etc.) which could hurt your reputation since the public will be getting its first impressions of your company based on that initial launch.
  • It publicly commits you to a particular product even if you learn that your initial idea is wrong or needs tweaking.
  • It tips off the market and potential competition earlier since you likely are doing this at a point before your product is ready and need to provide a fair amount of detail to get supporters.

In the end this “capital” ends up being a very real “liability”, and is a big part of why serious hardware startups that do crowdfunding almost all go back to the traditional VC/Angel community – it is simply not practical to scale up a meaningful hardware business on crowdfunded capital alone.

That said, there are definitely cases where it makes sense for hardware companies to use crowdfunding – and they are cases where the above problems are irrelevant:

  • If your cost of production is tiny relative to the price (think pharmaceuticals, software, music, movie, etc. – trivial cost of production per unit sold)
  • If you’ve already completed the vast majority of development or managed to get capital from another source and are simply using crowdfunding to either gauge customer interest or raise publicity
  • If your intention is to raise money from a VC/angel using a crowdfunding success story (that you’re positive you will get) to show that a large market exists for your product
  • You couldn’t raise money from VCs period and have no other choice

In the first case, a very low cost of production means that more dollars raised can actually go into development, irrespective of volume of production and discounts. In the second case, the pre-sale becomes a good thing: a market signal or a heavily publicized pre-sale for a product which is/is almost done. The third is very risky – because I would maintain its nigh impossible to know if a crowdfunding attempt will “go viral” and even if it does, you are still left with the liability of these presales that you need to fulfill. The last is self-explanatory :-).

If you are an aspiring hardware entrepreneur, in almost all cases your best bet will be to go with traditional equity/debt financing first. Obviously, I am in part biased by my current choice of profession but while VCs and angels can be annoying to deal with and raise money from, the lack of the pre-sale liability and their potential for connecting you with potential hires and partners makes them a much better fit.

Got any questions? Disagree? I want to hear from you!

2 Comments

Stuck between a big company and a startup place

imageI sometimes feel like I’m caught between two worlds.

On the one hand, I feel a strong tug towards the “Silicon Valley dream” of entrepreneurship. Friends of mine like Charles Ju, Founder and CEO of PlayMesh, the maker of one of the top iPhone games out there (iMafia) are living that dream – driven by one’s passions and one’s desire to engineer a product/service/technology to change the world – and heck, maybe get wealthy while you’re at it. It’s that drive which has pushed me to work with my buddies on projects like Xhibitr and Benchside.

On the other hand, I also feel a strong pull towards the corporate strategy world which I currently am involved in at my day job. The work is more stable (in the sense that I’m usually not dependent on the next round of funding for my livelihood), and the issues one explores are more strategic. It’s not desperately asking “will someone PLEASE buy my product?” or “how do I improve my product without spending any money because I’m out of cash?”. It’s literally answering “how do I shape an industry?” and “how do I change our business processes to be more responsive to customer needs?”

What makes the soul-searching all the more difficult is how different the two things are, and how different the people who work in each are. It makes it hard to just take the advice of friends like Charles or Serena who tell me to jump ship and head for startup-infested waters.

image For starters, I’ve noticed that there are very different skills involved in the two groups. Big corporate strategy guys are more likely to value things like analysis (e.g., do the models support the proposed strategy? do we have the right numbers? what does that do to our cash and margin position?) and gameboarding (e.g., how will Microsoft or Google or Intel or Cisco react? how do the tech trends affect us/get shaped by us? who are the strategic partners/enemies who will care most about this?). I’ve found startup guys to more value execution over strategy (e.g., can we ship on time? can we get it done?) and boldness over analysis (e.g. is our product cool enough? will people care?)

This is not to say that big business guys don’t value execution or boldness, or that startup guys have no sense for analysis or gameboarding. And this is not even to say that either side is unreasonable. After all, startups need to execute before they worry about a perfect strategy, and big companies need to defend their sizable profit pool before they bet on a new one.

But that dynamic oftentimes frustrates me. When I’m doing the corporate strategy stuff, I grow frustrated at the conservatism and lack of boldness and progress. I am bothered by the bureaucracy and the lack of value placed on my scientific/technical knowledge.

And yet, when I talk with startup guys, I am troubled by what I see as a lack of emphasis on analysis and strategic thinking. I’m concerned that the heavy focus on execution and boldness traps them into bad decision cycles. I see an almost callous disregard of things which all big companies do as a matter-of-practice (e.g. legal, business development, and HR issues). And, to be perfectly honest, the lack of resources to fund anything (let alone the pretty decent salary I’ve come to expect) is not an exciting proposition either.

And so here I am. Stuck between a big company and a startup place, and not quite sure how much longer before I get crushed.

(Image credit) (Image Credit)

One Comment

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!

Leave a Comment

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.

Leave a Comment

Dr. Machine Learning

doctor_s4a.jpg
Not going to happen anytime soon, sadly: the Doctor from Star Trek: Voyager; Image Credit: TrekCore

Despite the hype, it’ll likely be quite some time before human physicians will be replaced with machines (sorry, Star Trek: Voyager fans).

While “smart” technology like IBM’s Watson and Alphabet’s AlphaGo can solve incredibly complex problems, they are probably not quite ready to handle the messiness of qualitative unstructured information from patients and caretakers (“it kind of hurts sometimes”) that sometimes lie (“I swear I’m still a virgin!”) or withhold information (“what does me smoking pot have to do with this?”) or have their own agendas and concerns (“I just need some painkillers and this will all go away”).

Instead, machine learning startups and entrepreneurs interested in medicine should focus on areas where they can augment the efforts of physicians rather than replace them.

One great example of this is in diagnostic interpretation. Today, doctors manually process countless X-rays, pathology slides, drug adherence records, and other feeds of data (EKGs, blood chemistries, etc) to find clues as to what ails their patients. What gets me excited is that these tasks are exactly the type of well-defined “pattern recognition” problems that are tractable for an AI / machine learning approach.

If done right, software can not only handle basic diagnostic tasks, but to dramatically improve accuracy and speed. This would let healthcare systems see more patients, make more money, improve the quality of care, and let medical professionals focus on managing other messier data and on treating patients.

As an investor, I’m very excited about the new businesses that can be built here and put together the following “wish list” of what companies setting out to apply machine learning to healthcare should strive for:

  • Excellent training data and data pipeline: Having access to large, well-annotated datasets today and the infrastructure and processes in place to build and annotate larger datasets tomorrow is probably the main defining . While its tempting for startups to cut corners here, that would be short-sighted as the long-term success of any machine learning company ultimately depends on this being a core competency.
  • Low (ideally zero) clinical tradeoffs: Medical professionals tend to be very skeptical of new technologies. While its possible to have great product-market fit with a technology being much better on just one dimension, in practice, to get over the innate skepticism of the field, the best companies will be able to show great data that makes few clinical compromises (if any). For a diagnostic company, that means having better sensitivty and selectivity at the same stage in disease progression (ideally prospectively and not just retrospectively).
  • Not a pure black box: AI-based approaches too often work like a black box: you have no idea why it gave a certain answer. While this is perfectly acceptable when it comes to recommending a book to buy or a video to watch, it is less so in medicine where expensive, potentially life-altering decisions are being made. The best companies will figure out how to make aspects of their algorithms more transparent to practitioners, calling out, for example, the critical features or data points that led the algorithm to make its call. This will let physicians build confidence in their ability to weigh the algorithm against other messier factors and diagnostic explanations.
  • Solve a burning need for the market as it is today: Companies don’t earn the right to change or disrupt anything until they’ve established a foothold into an existing market. This can be extremely frustrating, especially in medicine given how conservative the field is and the drive in many entrepreneurs to shake up a healthcare system that has many flaws. But, the practical reality is that all the participants in the system (payers, physicians, administrators, etc) are too busy with their own issues (i.e. patient care, finding a way to get everything paid for) to just embrace a new technology, no matter how awesome it is. To succeed, machine diagnostic technologies should start, not by upending everything with a radical solution, but by solving a clear pain point (that hopefully has a lot of big dollar signs attached to it!) for a clear customer in mind.

Its reasons like this that I eagerly follow the development of companies with initiatives in applying machine learning to healthcare like Google’s DeepMind, Zebra Medical, and many more.

Leave a Comment

Laszlo Bock on Building Google’s Culture

Much has been written about what makes Google work so well: their ridiculously profitable advertising business model, the technology behind their search engine and data centers, and the amazing pay and perks they offer.

My experiences investing in and working with startups, however, has taught me that building a great company is usually less about a specific technical or business model innovation than about building a culture of continuous improvement and innovation. To try to get some insight into how Google does things, I picked up Google SVP of People Operations Laszlo Bock’s book Work Rules!

Bock describes a Google culture rooted in principles that came from founders Larry Page and Sergey Brin when they started the company: get the best people to work for you, make them want to stay and contribute, and remove barriers to their creativity. What’s great (to those interested in company building) is that Bock goes on to detail the practices Google has put in place to try to live up to these principles even as their headcount has expanded.

The core of Google’s culture boils down to four basic principles and much of the book is focused on how companies should act if they want to live up to them:

  1. Presume trust: Many of Google’s cultural norms stem from a view that people are well-intentioned and trustworthy. While that may not seem so radical, this manifested at Google as a level of transparency with employees and a bias to say yes to employee suggestions that most companies are uncomfortable with. It raises interesting questions about why companies that say their talent is the most important thing treat them in ways that suggest a lack of trust.
  2. Recruit the best: Many an exec pays lip service to this, but what Google has done is institute policies that run counter to standard recruiting practices to try to actually achieve this at scale: templatized interviews / forms (to make the review process more objective and standardized), hiring decisions made by cross-org committees (to insure a consistently high bar is set), and heavy use of data to track the effectiveness of different interviewers and interview tactics. While there’s room to disagree if these are the best policies (I can imagine hating this as a hiring manager trying to staff up a team quickly), what I admired is that they set a goal (to hire the best at scale) and have actually thought through the recruiting practices they need to do so.
  3. Pay fairly [means pay unequally]: While many executives would agree with the notion that superstar employees can be 2-10x more productive, few companies actually compensate their superstars 2-10x more. While its unclear to me how effective Google is at rewarding superstars, the fact that they’ve tried to align their pay policies with their beliefs on how people perform is another great example of deviating from the norm (this time in terms of compensation) to follow through on their desire to pay fairly.
  4. Be data-driven: Another “in vogue” platitude amongst executives, but one that very few companies live up to, is around being data-driven. In reading Bock’s book, I was constantly drawing parallels between the experimentation, data collection, and analyses his People Operations team carried out and the types of experiments, data collection, and analyses you would expect a consumer internet/mobile company to do with their users. Case in point: Bock’s team experimented with different performance review approaches and even cafeteria food offerings in the same way you would expect Facebook to experiment with different news feed algorithms and notification strategies. It underscores the principle that, if you’re truly data-driven, you don’t just selectively apply it to how you conduct business, you apply it everywhere.

Of course, not every company is Google, and not every company should have the same set of guiding principles or will come to same conclusions. Some of the processes that Google practices are impractical (i.e., experimentation is harder to set up / draw conclusions from with much smaller companies, not all professions have such wide variations in output as to drive such wide variations in pay, etc).

What Bock’s book highlights, though, is that companies should be thoughtful about what sort of cultural principles they want to follow and what policies and actions that translates into if they truly believe them. I’d highly recommend the book!

Leave a Comment

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%).

Leave a Comment

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.
One Comment

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.

5 Comments

Google Loves to Make Marketers’ Lives Harder

Customer acquisition is oftentimes the key cost for a startup, and hence one of the most important capabilities for a startup to build and a key skillset for a startup to hire for. One reason for that is that Google, while a great tool in many ways for helping companies with customer acquisition, can really make customer acquisition hard to do.

Why? Well, the importance of Google to the internet means its algorithm and policy changes have HUGE impacts on customer acquisition costs and strategies.

Case in point: a little over two years ago, content businesses — like Demand Media which had learned to profit on the difference between the cost of acquiring customers from search engines and the advertisement money they could make on their content — woke up to a sudden shock when Google algorithm changes drastically changed their cost of acquiring web traffic. While this was a conscious effort by Google to improve its search results for its users, the result was like a natural disaster: an unanticipated and massive change in the business environment. Investors dinged Demand Media’s stock price by 50%, Yahoo shuttered its Associated Content business and replaced it with Yahoo Voices, and many of the initial big losers from Google’s algorithm updates continue to lag in search rankings.

Just a few months ago, Google again shook the customer acquisition world by introducing a new tabbed interface in their Gmail web email client. While tabbed interfaces have been around forever, what made Gmail’s special was that these tabs also served to filter email messages so that Facebook/Twitter updates, forum posts, and – drumroll – promotional emails/coupons – weren’t the first thing a user sees when they open up their mail. The result? All those brilliant subject lines and email marketing campaigns that you’ve come up with? There’s a really big chance they got shunted to a tab that the user is predisposed to ignore with impunity. The result?  Companies who rely on email as a customer acquisition channel have to find ways to counteract this — getting users to (1) open up their “Promotions” tab and (2) designate to Gmail that they want those particular promotions to hit the main inbox – or shift to a new way of getting customers to act.

This type of thing is typical in the customer acquisition world: to succeed, you need to not only get really good at today’s modalities of acquiring customers, you also have to be adaptable – and roll with the sudden changes that Google or Facebook or one of any sudden shifts in the digital world can do.

Update at 11AM PST, 8 Oct 2013: As if on cue for my blog post, I received an email from eCommerce jewelry vendor Blue Nile today about moving their promotions into my main email tab 🙂

Leave a Comment

Healthcare Reform is Coming

3v43sn(I couldn’t resist the Game of Thrones meme :D)

No matter how many health technology events I attend or healthtech entrepreneurs/experts I speak with, one thing that has always jumped out to me is just how big of a change the coming healthcare reforms/mandates feel to the hospitals, practices, payers, and technology vendors who are being charged with enacting the proposed changes.

The chart below gives some indication of some of the major changes that hospitals are both in the midst of implementing as well as in the near future that they are (hopefully) planning for (HT: Dr. John D. Halamka, CIO at Beth Israel Deaconess Medical Center). As is probably painfully clear from the alphabet soup of acronyms, the dizzying array of colors, and wonky terms like “Accountable Care Organization”, there is a LOT of complexity here (“Meaningful Use” alone means hundreds of things, divided across multiple stages).

cms

Each box means new technology systems, new ways of doing things, new ways of paying for things, new ways of being paid, new rules, new exceptions … its that complexity and the fact that all of this is intended to shake up “business as usual” which makes the health technology space so interesting and makes it such a vibrant space for new startups. Healthcare reform is coming, people.

Leave a Comment

Tomorrow’s Pets.com

petscomToday, it seems perfectly obvious that building an internet business to sell pet food to customers where shipping and logistic costs (let alone advertising costs, etc.) wiped out any chance of profitability was an idea doomed to fail.

But, was it obvious at the time? While some folks will claim they knew all along, the market evidence suggests that most people had no clue: after all, the company raised over $110M in capital from Hummer Winblad, Comcast, Amazon.com, and others. It went on to successfully IPO in 2000 and at one point employed over 300 people. If it was such a terrible idea, it seems that it took quite a while for people to catch on.

This isn’t to specifically pick on Pets.com – quite the opposite: when you work in technology, there is oftentimes so much change and uncertainty around the future that its not obvious that the “emperor has no clothes” until its too late, oftentimes driven by entrepreneurs, career-seekers, and investors willing to pile on to make sure that they “get in on the action before its too late.”

And therein lies a very interesting question: what are the ideas/companies that have generated a ton of traction today which will become “duh, stupid” Pets.com ideas of tomorrow?

Examples of companies that flew high once and “obviously” crashed afterwards (most of the Dot Com bubble companies, many of the Cleantech bubble companies, some prominent consumer internet companies, etc) suggest that ignoring economic realities is a common refrain. Many of the failed Dot Com bubble companies and many of the challenged consumer internet companies relied primarily on drawing eyeballs to their websites/apps without figuring out how to make money enough on them to recoup their costs of marketing & advertising. The cleantech companies, similarly, gambled wrongly on government support and on their ability to make their technologies competitive with conventional systems.

But, the danger of generalizing from this type of thinking is that are plenty of examples of huge companies which succeeded despite bleak economic pictures in the early days. Amazon.com is a particularly noteworthy company that aimed to grow first before worrying about profitability (something it continues to do in a number of new businesses), not generating profit until late 2001, 7 years after founding, and over 4 years after it went public. Considering the company is worth over $100B today, compared with roughly $400M when it went public, it would seem blindly paying attention to the immediate economic picture would’ve cheated you out of a very impressive investment.

The truth is that I don’t have a good answer to this question. Studying what led to the failure of past startup models can be very informative in terms of how to think about other businesses, but the truth is that we aren’t likely to know until it hits us. Who knows, maybe in a few years “Big Data” or “Mobile advertising’ might all be revealed to have been terrible businesses…?

I would love to hear any thoughts on the subject in the comments below.

(image credit – Pets.com sock puppet – RightStartups)

One Comment

The Margin Question

While I’ve never been told this directly, I’m sure that a lot of startups I meet are a little put off as to why I oftentimes ask so many questions about their margins. As a brief refresher, margins are the % of sales that a company gets to pocket, after accounting for the cost of production. So, if it costs Acme Co. $5 to make a shirt that it sells for $10, their (in this case gross) margin is 50%.

Generally, the entrepreneurs are miffed at me because – well, they’re working in startups. They’re too busy trying to build out their product to work on financial forecasts which are likely inaccurate. The savvier entrepreneurs will sometimes throw back some variant of the point I made a while back about how the goal (for a venture-backed startup) is not profitability, but growth. The numbers themselves are also kind of a trap: if they are too high, it makes the entrepreneur seem naïve. If they are too low, it makes the business seem uninteresting.

But, the real reason I ask about margins is not necessarily to get at the precise number, but so that I understand how the management team thinks about their business and how it will grow. I’ve been in many meetings where management teams present a fantastic revenue growth story which relies on expanding product lines with lower margins. The idea here is two-fold: first, products with lower margins are easier to sell (since you’re marking them up less) and, second, as long as you are making money on each incremental sale, why not push lower margin products when venture-backed acquisitions and IPOs are oftentimes mainly evaluated on sales growth?

I tend to view that type of reasoning as a poor rationalization of opportunity costs. Whereas an entrepreneur might see “profitable growth opportunity,” my first instinct is that if a business is forced to turn to lower margin products to grow the business, then they should spend more time building a better product (to get those margins back up) or trying to find markets where the company’s innovations are more highly valued. As is oftentimes said, the most important assets that any startup has are time and money – and every second and every dollar spent chasing a lower-margin sale is a second and a dollar that is not being spent improving one’s products or chasing a higher-margin sale. When you combine that with the fact that lower margin businesses tend to be that way because there is more competition, the idea of pursuing lower margin growth opportunities becomes a lot less appealing.

Now, this isn’t to say that pursuing a lower-margin market is fundamentally a bad thing. Companies like Amazon and Samsung have built impressive businesses going after barely profitable markets (i.e., many types of online retail for Amazon and memory chips & TVs for Samsung). But, its only after a careful consideration of opportunity costs and strategy that such a choice should be made.

One Comment

Android Bluetooth (Smart) Blues

Readers of this blog will know that I’m a devout Fandroid, and the past few years of watching Android rise in market share across all segments and geographies and watching the platform go from curiosity for nerds and less-well-off individuals to must-support platform has been very gratifying to see.

Yet despite all that, there is one prominent area in which I find iOS so much better in that even I – a proud Fandroid venture capitalist – have been forced to encourage startups I meet with and work with to develop iOS-first: support for Bluetooth Smart.

LogoBluetoothSmart

In a nutshell, Bluetooth Smart (previously known as Bluetooth Low Energy) is a new kind of wireless technology which lets electronics connect wirelessly to phones, tablets, and computers. As its previous name suggests, the focus is on very low power usage which will let new devices like smart watches and fitness devices and low power sensors go longer without needing to dock or swap batteries – something that I – as a tech geek — am very interested in seeing get built and I – as a venture capitalist — am excited to help fund.

While Bluetooth Smart has made it much easier for new companies to build new connected hardware to the market, the technology needs device endpoints to support it. And therein lies the problem. Apple added support for Bluetooth Smart in the iPhone 4S and 5 – meaning that two generations of iOS products support this new technology. Google, however, has yet to add any such support to the Android operating system – leaving Bluetooth Smart support on the Android side to be shoddy and highly fragmented despite many Android devices possessing the hardware necessary to support it.

To be fair, part of this is probably due to the differences in how Apple and Google approached Bluetooth. While Android has fantastic support for Bluetooth 4.0 (what is called “Bluetooth Classic”) and has done a great job of making that open and easy to access for hardware makers, Apple made it much more difficult for hardware makers to do novel things with Bluetooth 4.0 (requiring an expensive and time-consuming MFi license – two things which will trip up any startup). Possibly in response to complaints about that, Apple had the vision to make their Bluetooth Smart implementation much more startup-friendly and, given the advantages of using Bluetooth Smart over Bluetooth Classic, many startups have opted to go in that direction.

The result is that for many new connected hardware startups I meet, the only sensible course of action for them is to build for iOS first, or else face the crippling need to either support Android devices one at a time (due to the immaturity and fragmentation in Bluetooth Smart support) or get an MFi license and work with technology that is not as well suited for low power applications. Consequently, I am forced to watch my chosen ecosystem become a second-class citizen for a very exciting new class of startups and products.

I’m hoping that at Google I/O this year (something I thankfully snagged a ticket for :-)), in addition to exciting announcements of new devices and services and software, Google will make time to announce support for Bluetooth Smart in the Android operating system and help this Fandroid VC not have to tell the startups he meets to build iOS-first.

One Comment

Thompson-gate

If you’ve been following the major tech trades, you’ll know that Scott Thompson, former head of eBay’s PayPal unit and CEO of internet giant Yahoo, has been embroiled in an embarrassing scandal about a misrepresentation on his resume. It turns out that Mr. Thompson’s resume specifically says that he had a degree in computer science from Stonehill College – something that turned out to be flat-out false, and which ultimately led to Thompson stepping down as CEO.

I may be in the minority here, but I feel that Thompson lying on his resume was probably not the biggest deal, especially since I doubt that degree made any real difference to why Yahoo hired him. But what was a heck of a lot worse was that the misrepresentation made its way into Yahoo’s 10K  — “Mr. Thompson holds a Bachelor’s degree in accounting and computer science from Stonehill College” — a filing to the SEC that Thompson signed, certifying that:

I, Scott Thompson, certify that:

1. I have reviewed this Amendment No. 1 to the Annual Report on Form 10-K of Yahoo! Inc. for the year ended December 31, 2011; and

2. Based on my knowledge, this report does not contain any untrue statement of a material fact or omit to state a material fact necessary to make the statements made, in light of the circumstances under which such statements were made, not misleading with respect to the period covered by this report.

(bolding mine)

This changed Thompson’s sin from one of “just” padding a resume to one of either (1) not carefully reading one of the most important documents a company can issue and/or (2) outright lying to the government and to Yahoo’s investors – not a good sign for a new (and now ex-) CEO. And, also seriously calls into question the Yahoo board of directors’ judgment in that they failed to do a very simple thing such as running a basic background check on a key hire.

As someone who is an investor (both in my job in venture capital investing in startups and outside of my work in the public market) and has been lucky enough to participate in board meetings for some of our portfolio companies, these are particularly alarming signs. While the underlying lie is not really that big a deal, being able to trust the executives and the board members who are supposed to have your best interests at heart is – and misrepresentations in a regulatory filing speak very poorly to a person’s thoroughness, competence, and/or credibility.

The next Yahoo CEO has a difficult job ahead – not only will he/she need to address the underlying problem of Yahoo not having a coherent vision/strategy and having demoralized workers, he/she will likely need to manage the construction of a better board of directors and the implementation of new policies and procedures to prevent this type of thing from happening again.

Leave a Comment

3D Printing as Disruptive Innovation

Last week, I attended a MIT/Stanford VLAB event on 3D printing technologies. While I had previously been aware of 3D printing (which works basically the way it sounds) as a way of helping companies and startups do quick prototypes or letting geeks of the “maker” persuasion make random knickknacks, it was at the event that I started to recognize the technology’s disruptive potential in manufacturing. While the conference itself was actually more about personal use for 3D printing, when I thought about the applications in the industrial/business world, it was literally like seeing the first part/introduction of a new chapter or case study from Clayton Christensen, author of The Innovator’s Dilemma (and inspiration for one of the more popular blog posts here :-)) play out right in front of me:

  • Like many other disruptive innovations when they began, 3D printing today is unable to serve the broader manufacturing “market”. Generally speaking, the time needed per unit output, the poor “print resolution”, the upfront capital costs, and some of the limitations in terms of materials are among the reasons that the technology as it stands today is uncompetitive with traditional mass manufacturing.
  • Even if 3D printing were competitive today, there are big internal and external stumbling blocks which would probably make it very difficult for existing large companies to embrace it. Today’s heavyweight manufacturers are organized and incentivized internally along the lines of traditional assembly line manufacturing. They also lack the partners, channels, and supply chain relationships (among others) externally that they would need to succeed.
  • While 3D printing today is very disadvantaged relative to traditional manufacturing technologies (most notably in speed and upfront cost), it is extremely good at certain things which make it a phenomenal technology for certain use cases:
    • Rapid design to production: Unlike traditional manufacturing techniques which take significant initial tooling and setup, once you have a 3D printer and an idea, all you need to do is print the darn thing! At the conference, one of the panelists gave a great example: a designer bought an Apple iPad on a Friday, decided he wanted to make his own iPad case, and despite not getting any help from Apple or prior knowledge of the specs, was able by Monday to be producing and selling the case he had designed that weekend. Idea to production in three days. Is it any wonder that so many of the new hardware startups are using 3D printing to do quick prototyping?
    • Short runs/lots of customization: Chances are most of the things you use in your life are not one of a kind (i.e. pencils, clothes, utensils, dishware, furniture, cars, etc). The reason for this is that mass production make it extremely cheap to produce many copies of the same thing. The flip side of this is that short production runs (where you’re not producing thousands or millions of the same thing) and production where each item has a fair amount of customization or uniqueness is really expensive. With 3D printing, however, because each item being produced is produced in the same way (by the printer), you can produce one item at close to the same per unit price as producing a million – this makes 3D printing a very interesting technology for markets where customization & short runs are extremely valuable.
    • Shapes/structures that injection molding and machining find difficult: There are many shapes where traditional machining (taking a big block of material and whittling it down to the desired shape) and injection molding (building a mold and then filling it with molten material to get the desired shape) are not ideal: things like producing precision products that go into airplanes and racecars or printing the scaffolds with which bioengineers hope to build artificial organs are uniquely addressable by 3D printing technologies.
    • Low labor: The printer takes care of all of it – thus letting companies cut costs in manufacturing and/or refocus their people to steps in the process which do require direct human intervention.
  • And, of course, with the new markets which are opening up for 3D printing, its certainly helpful that the size, cost, and performance of 3D printers has improved dramatically and is continuing to improve – to the point where the panelists were very serious when they articulated a vision of the future where 3D printers could be as widespread as typical inkjet/laser printers!

Ok, so why do we care? While its difficult to predict precisely what this technology could bring (it is disruptive after all!), I think there are a few tantalizing possibilities of how the manufacturing game might change to consider:

  • The ability to do rapid design to production means you could do fast fashion for everything – in the same way that companies like Zara can produce thousands of different products in a season (and quickly change them to meet new trends/styles), broader adoption of 3D printing could lead to the rise of new companies where design/operational flexibility and speed are king, as the companies best able to fit their products to the flavor-of-the-month gain more traction.
  • The ability to do customization means you can manufacture custom parts/products cost-effectively and without holding as much inventory; production only needs to begin after an order is on hand (no reason to hold extra “copies” of something that may go out of fashion/go bad in storage when you can print stuff on the fly) and the lack of retooling means companies can be a lot more flexible in terms of using customization to get more customers.
  • I’m not sure how all the second/third-order effects play out, but this could also put a damper on outsourced manufacturing to countries like China/India – who cares about cheaper manufacturing labor overseas when 3D printing makes it possible to manufacture locally without much labor and avoid import duties, shipping delays, and the need to hold on to parts/inventory?

I think there’s a ton of potential for the technology itself and its applications, and the possible consequences for how manufacturing will evolve are staggering. Yes, we are probably a long way off from seeing this, but I think we are on the verge of seeing a disruptive innovation take place, and if you’re anything like me, you’re excited to see it play out.

7 Comments

Mr. Tseng Goes to SXSW

Apologies for the lack of blogging these past few weeks. Part of that (although I really have no excuse) is because I got to attend famed tech, music, and film convention South-by-Southwest (aka SXSW).

It was my very first time in Austin, and I had a blast hanging out at the various booths/panels during the day and on Austin’s famous 6th Street in the evening. Granted, I just barely missed the torrential rain of the first half of the conference (and, sadly, also had to miss out on the music and film part of the festivals), but I got to see a fair amount of the tech conference, and had a few observations I thought I’d share

  • A good majority of the companies paying big bucks to market there should spend their money elsewhere. This is not a ding on the conference. Nor am I even arguing that these companies are wasting time sending representatives to the conference. My two cents is that there were many companies there who were spending their money unwisely at best – whether it be on acts of branding heroism (i.e. paying to rebrand local establishments) or holding massive parties with open bars and no coherent message  conveyed to the attendees about who the company is or why they should use the product. I must’ve attended at least three of the latter – and, truth be told, I can’t even remember the names of the startups that held those parties. Bad way to spend marketing dollars, or terrible way?
  • With that said, there were a number of companies there who definitely spent wisely (although whether or not it works is a question I leave for the marketplace). SXSW is a great venue to try to attract the attention of early adopters of consumer internet/mobile products – and it makes great sense to try to blow out marketing there as part of some major product/marketing push. Here’s two companies that I think were smart to spend a lot of money at SXSW (and, in my humble opinion, executed well):
    • nikefuelI think Nike in pushing its digital initiatives like Nike Fuel (which I plan to write a review of :-)) spent quite wisely building its brand. They had an interesting panel on using the product, an outdoors area that looked like a mini-boot camp (no joke!), a digital billboard which alternated between a appropriately color themed and a room decked out like a club where Nike employees sold the fuel band and helped new users get them set up.
    • ncom-lumia-900-cyan-front-267x500-pngI think Nokia (yes, despite my previous post, I mean Nokia) did a great job as well – they set up a Nokia Labs party area which looked like three giant domes from the outside. Right next to the entrance there was a snow machine (I assume to recreate the Finland snow?). The Nokia folks on the inside were all dressed in labcoats (keeping with the “lab” theme) and, like with Nike, there was crazy club music being played. The bar was offering a drink made with Finnish vodka called “Lumia Liquified” (Lumia is the name of Nokia’s new high-end smartphone line). And with this hip backdrop in place, the Nokia party had multiple exhibits featuring the Lumia’s unique design (there was a great display full of the drab black phones we’re used to seeing and the Lumia’s brightly colored phone standing out), the Lumia’s Carl Zeiss lens/optics, and the Lumia’s Clear Black display technology (basically using layers of polarized glass so that the display looks black and readable under direct light). Enough for me to no longer be a Fandroid? Probably not, but I definitely left the party impressed.
  • Like most tech shows, there was a main exhibition floor which I had a chance to walk through. On these floors, companies assemble at booths attempting to attract customers, business partners, investors, and even just curious passerbys. One of the booths I attended was held by Norton, makers of the Symantec security software that might be running on your computer. The reason I point it out is that, through some marketing deal, they were able to capture the heart of this comic loving blogger by co-opting the branding from the coming Avengers movie. The concept was actually pretty creative, if a bit hokey: participants had to play a handful of Norton security-themed casual games (think quizzes and simple Flash games where you use Norton widgets/tools/powerups to defend a machine from attack) to collect a series of badges. At the end of the sequence, depending on how you did on the games, you are awarded a rank and given a prize. One very fun perk for me is the photo below – guess who’s now a superhero? 🙂

cd8f76d8-greenscreen

    That picture alone made SXSW worth it :-).

(Image credit – Nike fuel band – Linkbuildr)(Image credit – Lumia – Nokia)

One Comment

Pitching a VC is a Romantic Affair

processI swear the title has nothing to do with Valentine’s Day :-).

One question that comes up often when people find out that I work at a venture capital firm is “how do venture capital firms decide what they invest in?” How is it that the same firms that pick wildly successful companies like Google and Facebook can also pick the “what were they thinking” duds?

People are oftentimes surprised to hear my answer. The truth is that while there is a general perception that there is some kind of a secret formula with objective criteria and analysis, the idea that the VC decision process is a purely objective and analytical affair is plain wrong.

The analogy I like to give is that getting an investment from a venture capital firm is a lot like marriage. Yes, there are obviously objective criteria which inform the decision – is the potential spouse/founding team trustworthy? Do we share the same goals in life (i.e. kids vs no-kids or size of outcome/industry)? Are we at the right stage (i.e. ready for commitment or point in lifecycle of the startup)? What do friends/industry experts/customers say? Can both parties add meaningful value to both sides?

But, like with marriage, there is a significant emotional component to the decision as well which can’t be ignored. Things like personal chemistry or whether or not the investors involved are enchanted/charmed by the founding team and the business idea play an enormous role. An investor who doesn’t have a specific qualm about a startup but who just isn’t feeling “the love” will not push a deal forward, no matter how great of a business case is being made. Why? The business model of most venture capital firms forces individual investors to only commit to a handful of companies that they truly can commit to and stick with through thick and through thin (and, rest assured, all companies have bad times they have to survive through).

Of course, let it be clear: any decent investor who “falls in love” with a startup and later uncovers objective reasons to not go forward will fall rapidly out of love with a company – lest someone reading this gets the idea that its all about the emotions. But the lesson to take away here for entrepreneurs is that while its absolutely critical to nail the objective criteria (things like business model, team composition, market size, go-to-market strategy, product/service quality, technology, etc) – that is, after all, the bread and butter of any good startup – don’t forget that, just as with most sales/business deals, the VC process has a huge emotional piece. So:

    • Have high EQ when you approach a conversation with a VC you are interested in: fit the message to the person and if you see the interest/reaction start to go the wrong way, shift gears and adapt the message (although I should remind people to not lie – that never ends well for either party)
    • Know the VCs you are presenting to: its impossible to precisely predict what combination of things will really click with a person, but you can get hints of that by doing your research. At the minimum, it means reading the backgrounds/profiles of the individuals you will be meeting with to understand what they are interested in and what sorts of themes they tend to look for. But, keep in mind to also pay attention to what things might turn them off (i.e. if they were involved with a bad eCommerce deal and you are trying to pitch a eCommerce company, make sure your story/pitch is *very* different).
    • Talk with a lot of VCs and expect to do this for every round of financing: as with romance, you can’t expect to click with everyone, not to mention, as with romance, things can always change the second or third time around. There are definitely cases where entrepreneurs have had very successful relationships with investors they never expected in their first set of pitches as well as VCs who have passed on earlier rounds of investment (no chemistry the first time) only to eagerly participate in follow-on investments.

(Image credit – 3Forward)

2 Comments

Can't find what you're looking for? Try refining your search: