While entrepreneurship is in the news fairly regularly, I seldom make news myself. Today, however there are two important updates for entrepreneurs everywhere. Let me be brief…
The “Startup Owner’s Manual” goes On Press Tuesday 2/14 Two years in the making and literally ten years in development, I’m proud to announce that my new book, The Startup Owners Manual, goes onto the printing press next Tuesday. This 608-page work is, as its subtitle says, “the step-by-step guide for building a great company.” It’s the result of a decade of me learning from 1,000′s of entrepreneurs, corporate partners, students and scientists the best practices of what wins in startups. I’ve spent the last two years cramming knowledge into this new book.
In brief, the The Startup Owners Manual is far more detailed and more readable than Four Steps to the Epiphany, (most of the sentences are even finished!). In fact, you could say that all that remains from my last book are the four steps of Customer Development. Briefly, the new book:
Integrates Alexander Osterwalders “Business Model Canvas” as the front-end and “scorecard” for the customer discovery process.
Provides separate paths and advice for web/mobile products versus physical products
Offers a ton of detail and great tips on how to get, keep, and grow customers, recognizing that this happens very differently between web and physical channels.
and finally it teaches a “new math” for startups: “metrics that matter.”
While MBA’s have had a stack of texts to help them “execute” a business model, this book joins the growing library of books for practitioners for the “search” for the business model.
The Lean LaunchPad Online Class My online Lean LaunchPad class has created a lot of buzz this week. As you may have heard, I was deep into the production of the lectures when I realized I was producing the wrong class. The online class was originally based on my book The Four Steps to the Epiphany.
Only when I held the draft of my latest book, The Startup Owners Manual, in my hands, did it dawn on me that my online students deserved all the latest best practices of entrepreneurship and Customer Development. Not the stuff I taught a decade ago, but all that I’ve learned teaching the Lean LaunchPad in front of students at Stanford, Berkeley, Columbia and the National Science Foundation in the last year. And I particularly wanted to incorporate everything I’ve spent two years integrating into The Startup Owners Manual into the class.
So apologies to all of you who were expecting the class this month. I hope to get the updated version online in the next 60 days. I’ll keep you updated on this blog as we record our lectures.
In the meantime, if you want to prepare for the class…or get a jump on your startup competition, you can start reading the “recommended text” for the online class right now by ordering my new book. It is recommended—not required—reading for the free online course, and I believe it will be immensely helpful to the startup community at large.
Startups search for business models, exisitng companies execute them
There are tons of texts about execution, but a paucity of practical ones for founders on how to search
Although I typically don’t write about a class while it’s going on, I had to share this extraordinary reflection that Satish Kandlikar, one of the National Science Foundation principal investigators, posted to our Lean LaunchPad class blog.
Satish Kandlikar – The Spirit of Entrepreneurship Satish Kandlikar has been a professor in the mechanical engineering department at the Rochester Institute of Technology for the past twenty-one years. His research is focused in the areas of flow boiling, critical heat flux, contact line heat transfer, and advanced cooling techniques
His team, Akara Lighting, wants to build a device for LED lights that gets rid of heat 50% better than anything on the market. This would result in LED’s having a higher performance at a reduced cost.
Here’s what he had to say about his experience in the Lean LaunchPad class ….
“It is quite an eye-opening experience to transition from an academic “PI” (Principal Investigator) to someone who wants to run a technology start-up. The change in the mindset is perhaps the important factor on the path to success…
The teaching team is simply phenomenal in identifying the pitfalls in our path and guiding us in finding the solutions. They have shown us the other side of the equation from technology to market acceptability. We have been extremely fortunate in having this kind of guidance and support.
A key finding I would like to report is that we just had another “pivot” two days ago when our mentor brought to our attention that we can succeed as a heat pipe company providing thermal solutions to various LED products as well as other applications. I visited two companies, one providing data center cooling solutions, and other providing control panel cooling systems. Key alliances are expected to occur through these initial, very positive, contacts.
One fundamental change that I see in my approach going forward is that I am looking at the research in a totally different way. It is no longer, in my mind, a means to publishing papers and simply graduating students. It means now, to me, how the research can be applied to make products that are accepted in marketplace. Making students understand the entire process, to whatever extent I can influence them, and inspiring them to aspire for transferring their knowledge to products is becoming an important thrust in my classroom interactions.
Another eye-opener was on understanding communications. While making presentations in academic setting, it was more of a paper-based research with extension of knowledge, without too much understanding of its application. Knowing the audience was really not a factor. Now after making “cold-calls”, and seeing that there is a certain way to get them interested in just a few opening sentences, was simply amazing. Knowing what their needs are is a crucial step.
Now it is becoming clear what Steve meant when he said, “get out of the building”. It is clear that the building referred to our mindset more than the physical act of going out or simply contacting someone outside.
The purpose of this posting was to document my beginning of the transformation process from an academician to an entrepreneur. And I am definitely enjoying it.”
Scientists Unleashed Over fifty years ago Silicon Valley was born in an era of applied experimentation driven by scientists and engineers. Fifty years from now, we’ll look back to this current decade as the beginning of another revolution, where scientific discoveries and technological breakthroughs were integrated into the fabric of society faster than they had ever been before, unleashing a new era for a new American economy built on entrepreneurship and innovation.
I was invited to Finland as part of Stanford’s Engineering Technology Venture Program partnership with Aalto University. (Thanks to Kristo Ovaska and team for the fabulous logistics!) I presented to 1,000’s of entrepreneurs, talked to 17 startups, gave 12 lectures, had 9 interviews, chatted with 8 VC’s, sat on 4 panels, talked policy with 2 government ministers, 2 members of parliament, 1 head of a public pension fund and was in 1 TV-documentary. More details can be found at www.steveblank.fi
This is part 2 of 2 of what I found. Part 1 can be found here.
Toxic Business Press and Contradictory Government Incentives Unique to Finland with its strong cultural emphasis on equality and the redistribution of wealth is a business press that doesn’t understand startups and is overtly hostile to their success. When MySQL was sold for $1B and the cleantech company the Switch got acquired for $250M, one would have expected the country to celebrate that they had built these world-class companies. Instead the business press dumped on the founders for “selling out.” In 2010 it got worse with an Act in parliament about the Monitoring of Foreigners’ Corporate Acquisitions. Many founders mentioned this as a reason not to incorporate or grow their companies in Finland.
While the government says they love startups, the first thing they did this year is raise the capital gains tax. While it might have been politically expedient, it was not a welcome sign for long-term investment. I suggested they consider an investment tax credit for pension funds that invest in Finnish based VC firms.
Nokia as “He Who Must Not Be Named” I was in Finland three days before I realized that no one had mentioned the word “Nokia.” After I brought it up in a meeting, you could have heard a pin drop. Nokia was Finland’s symbol of national competence. Most Finns take their failure as a personal embarrassment. (Note to Finland – lighten up. Nokia was blind-sided in a classic disruptive innovation. 50% the fault of a Nokia management that didn’t see it coming, while 50% was due to brilliant Apple execution.) Ultimately, Nokia’s difficulties will turn out to be good news for Finnish entrepreneurs. They’ve stopped hiring the best talent, and startups are not looking so risky compared to large companies.
Nanny-Culture, Lack of Risk Taking, Not Sharing What makes Finland such a wonderful place to live and raise a family may ultimately be what kills it as a startup hub. There’s a safety net in almost every part of one’s public and private life – health insurance, free college tuition, unions, collective bargaining, fixed work hours, etc. And what’s great for the mass of society – a government safety net verging on the ultimate nanny state – makes it impossible to fail. You find early stage employees expecting to work normal hours, to get paid a regular salary, and not asking or expecting equity. There isn’t much of a killer instinct among the masses.
It’s the rare region where risk equals experience. By nature Finns are not good at tolerating risk. This gets compounded by the cultural tendency not to share or talk in meetings, sometimes to the point of silence. This is a fundamental challenge in creating an entrepreneurial culture. This extends to sharing among startups. The insular nature of the culture hasn’t yet created a “pay it forward” culture.
The young entrepreneurs I met are bringing impressive energy and intelligence to their goal of building one of Europe’s leading technology hubs in Helsinki. Finland itself has significant engineering talent, and is also attracting entrepreneurs from Russia and the former USSR. It will be fascinating to see if they can lead the cultural change and secure the political support (in a government run by an older generation) to support their vision.
Finland is trying to engineer an entrepreneurial cluster as a National policy to drive economic growth through entrepreneurial ventures
They’ve gotten off to a good start with a start around Aalto University with passionate students
Startup incubators, business angels and VCs are starting to emerge
The country needs to figure out a long term privatization strategy for Venture investing
Finnish culture makes risk-taking and sharing hard
I spent the month of September lecturing, and interacting with (literally) thousands of entrepreneurs in two emerging startup markets, Finland and Russia. This is the first of two posts about Finland and entrepreneurship.
I was invited to Finland as part of Stanford’s Engineering Technology Venture Program partnership with Aalto University. (Thanks to Kristo Ovaska and team for the fabulous logistics!) I presented to 1,000’s of entrepreneurs, talked to 17 startups, gave 12 lectures, had 9 interviews, chatted with 8 VC’s, sat on 4 panels, talked policy with 2 government ministers, 2 members of parliament, 1 head of a public pension fund and was in 1 TV-documentary.
What I found in Finland was:
a whole lot of smart, passionate entrepreneurs who want to build a startup hub in Helsinki
a government that’s trying to help, but gets in the way
a number of exciting startups, but most with a narrow, too-local view of the world
and the sense that, before too long, they may well get it right!
While a week is not enough time to understand a country this post – the first of two – looks at the Finnish entrepreneurial ecosystem and its strengths and weaknesses.
The Helsinki Spring Entrepreneurship and innovation are bubbling around Helsinki and Aalto University. There are thousands of excited students, and Aalto university is working hard to become an outward facing institution. Having a critical mass of people who think startups are cool in the same location is a key indicator of whether a cluster can catch fire. Finnish startup successes on a global stage include MySQL, F-Secure, Rovio, Habbo, Playfish, The Switch, Tectia, Trulia and Linux. While it’s not clear yet whether the numbers of startups in Helsinki are sufficient to ignite, it feels like it’s getting there, (and given the risk-averse and paternal nature of Finland that by itself is a miracle.)
The good news is that for a 5 million person country, there’s an emerging entrepreneurialecosystem that looks like something this:
9-to-5 Venture Capital Ironically one of the things that’s holding back the Finnish cluster is Tekes, the government organization for financing research, development and innovation in Finland. It’s hard enough to pick which existing companies with known business models to aid. Yet Tekes does that and is trying to act like a government-run Venture Capital firm. At Tekes, government employees (and their hired consultants) – with no equity, no risk or reward, no startup or venture capital experience – try to pick startup winners and losers.
Tekes has ended up competing with and stifling the nascent VC industry, indiscriminately handing out checks to entrepreneurs like an entitlement. (To be fair this is an extension of the government’s role in almost all parts of Finnish life.)
In addition to Tekes, Vigo, the government’s attempt at funding private business accelerators, started with good intentions and got hijacked by government bureaucrats. The accelerators I met with (the ones the government pointed to as their success stories) said they were leaving the program.
Tekes lacks a long-term plan of what the Finnish government’s role should be in funding startups. I suggested that they might want to consider putting themselves out of the public funding business byusing public capital to kick-start private venture capital firms, incubators and accelerators. And they should give themselves a 5-10 year plan to do so. Instead they seem to be stuck in the twilight zone of not having a long-term vision of their role. (There has been tons of reports on what to do, all seemingly ignored by an entrenched bureaucracy.)
Lack of Business Experience Direct government funding of startups has also delayed the maturation of business experience of local angels and VC’s. Finnish private investors don’t yet have enough time-in-grade to have developed good pattern recognition skills, and most lack operating backgrounds. I have no doubt they’ll get there by themselves, but in wouldn’t take much imagination to attempt to recruit some seasoned overseas investors to add to the mix.
Even a more serious challenge is the lack of global business competence. The number of serial entrepreneurs is very low and until recently most of the talented sales and marketing professionals choose to work for Nokia.
Part 2 with more observations about Finland and the Lessons Learned is here.
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If you’re an experienced coder and user interface designer you think nothing is easier than diving into Ruby on Rails, Node.js and Balsamiq and throwing together a web site. (Heck, in Silicon Valley even the waiters can do it.)
But for the rest of us mortals whose eyes glaze over at the buzzwords, the questions are, “How do I get my great idea on the web? What are the steps in building a web site?” And the most important question is, “How do I use the business model canvas and Customer Development to test whether this is a real business?”
My first attempt at helping students answer these questions was by putting together the Startup Tools Page - a compilation of available web development tools. While it was a handy reference, it still didn’t help the novice.
So today, I offer my next attempt.
How To Build a Web Startup – The Lean LaunchPad Edition
Then use godaddy or namecheap to register the name. (RetailMeNot usually has ~ $8/year discount coupons for Godaddy You may want to register many different domains (different possible brand names, or different misspellings and variations of a brand name.)
Once you have a domain, set up Google Apps on that domain (for free!) to host your company name, email, calendar, etc
Use your network to find target customers – ask your contacts, “Do you know someone with problem X? If so, can you forward this message on to them?” and provide a 2-3 sentence description
For B2B products, Twitter, Quora, and industry mailing lists are a good place to find target customers. Don’t spam these areas, but if you’re already an active participant you can sprinkle in some references to your site or you can ask a contact who is already an active participant to do outreach for you.
Step 8: Test the “Customer Problem” by collecting Customer Data
Use Web Analytics to track hits, time on site, source. For your initial site, Google Analytics provides adequate information with the fastest setup. Once you’ve moved beyond your initial MVP, you’ll want to consider a more advanced analytic platform (Kissmetrics, Mixpanel, Kontagent, etc)
Create an account to measure user satisfaction (GetSatisfaction, UserVoice, etc.) from your product and get feedback and suggestions on new features
Specific questions, such as “Is there anything preventing you from signing up?” or “What else would you need to know to consider this solution?” tend to yield richer customer feedback than generic feedback requests.
If possible, collect email addresses so that you have a way to contact individuals for more in-depth conversations.
Step 9: Test the “Customer Solution” by building a full featured High Fidelity version of your website
Update the Website with information learned in Step 5-8
Remember that “High Fidelity” still does not mean “complete product”. You need to look professional and credible, while building the smallest possible product in order to continue to validate.
Keep collecting customer analytics
Hearing “This is great, but when are you going to add X?” is your goal!
Step 10: Ask for money
Put a “pre-order” form in place (collecting billing information) even before you’re ready to collect money or have a full product.
When you’re ready to start charging – which is probably earlier than you think – find a billing provider such as Recurly, Chargify, or PayPal to collect fees and subscriptions.
For all Steps: Monitor and record changes week by week using the Lean LaunchLab
For Class: Use the Lean LaunchLab to produce a 7-minute weekly progress presentation
Start by putting up your business model canvas
Changes from the prior week should be highlighted in red
Lessons Learned. This informs the group of what you learned and changed week by week – Slides should describe:
Here’s what we thought (going into the week)
Here’s what we found (Customer Discovery during the week)
Here’s what we’re going to do (for next week)
Emphasis should be on the discovery done for that weeks assigned canvas component (channel, customer, revenue model) but include other things you learned about the business model.
If you’re Building a Company Rather Than a Class Project
Not understanding and agreeing what “Entrepreneur” and “Startup” mean can sink an entire country’s entrepreneurial ecosystem.
I’m getting ready to go overseas to teach, and I’ve spent the last week reviewing several countries’ ambitious attempts to kick-start entrepreneurship. After poring through stacks of reports, white papers and position papers, I’ve come to a couple of conclusions.
1) They sure killed a ton of trees
2) With one noticeable exception, governmental entrepreneurship policies and initiatives appear to be less than optimal, with capital deployed inefficiently (read “They would have done better throwing the money in the street.”) Why? Because they haven’t defined the basics:
What’s a startup? Who’s an entrepreneur? How do the ecosystems differ for each one? What’s the role of public versus private funding?
Six Types of Startups – Pick One There are six distinct organizational paths for entrepreneurs: lifestyle business, small business, scalable startup, buyable startup, large company, and social entrepreneur. All of the individuals who start these organizations are “entrepreneurs” yet not understanding their differences screws up public policy because the ecosystem in supporting each type is radically different.
For policy makers, the first order of business is to methodically think through which of these entrepreneurial paths they want to help and grow.
Lifestyle Startups: Work to Live their Passion On the California coast where I live, we see lifestyle entrepreneurs like surfers and divers who own small surf or dive shop or teach surfing and diving lessons to pay the bills so they can surf and dive some more. A lifestyle entrepreneur is living the life they love, works for no one but themselves, while pursuing their personal passion. In Silicon Valley the equivalent is the journeyman coder or web designer who loves the technology, and takes coding and U/I jobs because it’s a passion.
Small Business Startups: Work to Feed the Family Today, the overwhelming number of entrepreneurs and startups in the United States are still small businesses. There are 5.7 million small businesses in the U.S. They make up 99.7% of all companies and employ 50% of all non-governmental workers.
Small businesses are grocery stores, hairdressers, consultants, travel agents, Internet commerce storefronts, carpenters, plumbers, electricians, etc. They are anyone who runs his/her own business.
They work as hard as any Silicon Valley entrepreneur. They hire local employees or family. Most are barely profitable. Small business entrepreneurship is not designed for scale, the owners want to own their own business and “feed the family.” The only capital available to them is their own savings, bank and small business loans and what they can borrow from relatives. Small business entrepreneurs don’t become billionaires and (not coincidentally) don’t make many appearances on magazine covers. But in sheer numbers, they are infinitely more representative of “entrepreneurship” than entrepreneurs in other categories—and their enterprises create local jobs.
Scalable Startups: Born to Be Big Scalable startups are what Silicon Valley entrepreneurs and their venture investors aspire to build. Google, Skype, Facebook, Twitter are just the latest examples. From day one, the founders believe that their vision can change the world. Unlike small business entrepreneurs, their interest is not in earning a living but rather in creating equity in a company that eventually will become publicly traded or acquired, generating a multi-million-dollar payoff.
Scalable startups require risk capital to fund their search for a business model, and they attract investment from equally crazy financial investors – venture capitalists. They hire the best and the brightest. Their job is to search for a repeatable and scalable business model. When they find it, their focus on scale requires even more venture capital to fuel rapid expansion.
Scalable startups tend to group together in innovation clusters (Silicon Valley, Shanghai, New York, Boston, Israel, etc.) They make up a small percentage of the six types of startups, but because of the outsize returns, attract all the risk capital (and press.)
Just in the last few years we’ve come to see that we had been building scalable startups inefficiently. Investors (and educators) treated startups as smaller versions of large companies. We now understand that’s just not true. While large companies execute known business models, startups are temporary organizations designed to search for a scalable and repeatable business model.
This insight has begun to change how we teach entrepreneurship, incubate startups and fund them.
Large Company Startups: Innovate or Evaporate Large companies have finite life cycles. And over the last decade those cycles have grown shorter. Most grow through sustaining innovation, offering new products that are variants around their core products. Changes in customer tastes, new technologies, legislation, new competitors, etc. can create pressure for more disruptive innovation – requiring large companies to create entirely new products sold to new customers in new markets. (i.e. Google and Android.) Existing companies do this by either acquiring innovative companies (see Buyable Startups above) or attempting to build a disruptive product internally. Ironically, large company size and culture make disruptive innovation extremely difficult to execute.
Social Startups: Driven to Make a Difference Social entrepreneurs are no less ambitious, passionate, or driven to make an impact than any other type of founder. But unlike scalable startups, their goal is to make the world a better place, not to take market share or to create to wealth for the founders. They may be organized as a nonprofit, a for-profit, or hybrid.
So What? When I read policy papers by government organizations trying to replicate the lessons from the valley, I’m struck how they seem to miss some basic lessons.
Each of these six very different startups requires very different ecosystems, unique educational tools, economic incentives (tax breaks, paperwork/regulation reduction, incentives), incubators and risk capital.
Regions building a cluster around scalable startups fail to understand that a government agency simply giving money to entrepreneurs who want it is an exercise in failure. It is not a “jobs program” for the local populace. Any attempt to make it so dooms it to failure.
A scalable startup ecosystems is the ultimate capitalist exercise. It is not an exercise in “fairness” or patronage. While it’s a meritocracy, it takes equal parts of risk, greed, vision and obscene financial returns. And those can only thrive in a regional or national culture that supports an equal mix of all those.
Building an scalable startup innovation cluster requires an ecosystem of private not government-run incubators and venture capital firms, outward-facing universities, and a rigorous startup selection process.
Any government that starts public financing entrepreneurship better have a plan to get out of it by building a private VC industry. If they’re still publically funding startups after five to ten years they’ve failed.
To date, Israel is only country that has engineered a successful entrepreneurship cluster from the ground up. It’s Yozma program kick-started a private venture capital industry with government funds, (emulating the U.S. lesson of using SBIC funds.), but then the government got out of the way.
In addition, the Israeli government originally funded 23 early stage incubators but turned them over to the VC’s to own and manage. They’re run by business professionals (not real-estate managers looking to rent out excess office space) and entry is not for life-style entrepreneurs, but is a bootcamp for VC funding.
Unless the people who actually make policy understand the difference between the types of startups and the ecosystem necessary to support their growth, the chance that any government policies will have a substantive effect on innovation, jobs or the gross domestic product is low.
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What makes startups succeed or fail? More than 90% of startups fail, due primarily to self-destruction rather than competition. For the less than 10% of startups that do succeed, most encounter several near death experiences along the way. Simply put, while we now have some good theory, we just are not very good at creating startups yet. After 50 years of technology entrepreneurship it’s still an art.
Three months ago I wrote about my ex-student Max Marmer and the Startup Genome Project. They’ve been attempting to quantify the art. They believe that they can crack the code of innovation and turn entrepreneurship into a science if they had hard data rather than speculation of why startups succeed or fail. Max and his partners had interviewed and analyzed over 650 early-stage Internet startups. In May they released the first Startup Genome Report— an in-depth analysis on what makes early-stageInternet startups successful.
Now 90 days later Max and his team have gathered data on 3200 startups and they believe they’ve discovered the most common reason startups fail.
Benchmarking Your Startup I hadn’t heard from Max for awhile so I thought he took the summer off. I should have known better, it turned out he was hard at work.
Max and his team built a website called the Startup Genome Compass (their benchmarking web site) that allows an Internet startup to evaluate their business performance. The Startup Genome Compass uses a hybrid “Stage and Type” model that describes how startups progress through their business development lifecycle.
The benchmark takes 20 or so minutes to go through as series of questions, and in the end it spits out an analysis of how you are doing.
The benchmark is not perfect, it may even be flawed, but it is head and shoulders above what we have now – which is nothing – for giving Internet startups founders specific advice on best practices. If you have a few world-class VC’s on your board you’re probably getting this advice in person. If you’re like thousands of other startups struggling to get started, it’s worth a look.
It’s Not How Big It Is – It’s How Well It Performs If you’re interested (and you should be) in how you compare to other early stage ventures, they summarized their results in a report “Startup Genome Report Extra: Premature Scaling.”
One of the biggest surprises is that success isn’t about size – of team or funding. It turns out Premature Scaling is the leading cause of hemorrhaging cash in a startup – and death. In fact:
The team size of startups that scale prematurely is 3 times bigger than the consistent startups at the same stage
74% of high growth Internet startups fail due to premature scaling
Startups that scale properly grow about 20 times faster than startups that scale prematurely
93% of startups that scale prematurely never break the $100k revenue per month threshold
The last time I wrote about Max I said, “I can’t wait to see what Max does by the time he’s 21.” Turns out his birthday is in a week, September 7th.
There is nothing more powerful than an idea whose time has come Victor Hugo
When The Boardroom is Bits A revolution has taken hold as customer development and agile engineering reinvent the Startup process. It’s time to ask why startup board governance has failed to keep pace with innovation. Board meetings that guide startups haven’t changed since the early 1900’s.
It’s time for a change.
Reinventing the board meeting may allow venture-backed startups a more efficient, productive way to direct and measure their search for a profitable business model.
Reinventing the board meeting may offer angel-funded startups that don’t have formal boards or directors (because of geography or size of investment) to attract experienced advice and investment outside of technology clusters (i.e. Silicon Valley, New York).
A Hypothesis – The Boardroom As Bits Startups now understand what they should be doing in their early formative days is search for a business model. The process they use to guide their search is customer development. And to track their progress startups now have a scorecard to document their week-by-week changes – the business model canvas.
Yet even with all these tools, early stage startups still need to physically meet with advisors and investors. That’s great if you can get it. But what if you can’t?
What’s missing is a way to communicate all this complex information and get feedback and guidance for startups who cannot get advice in a formal board meeting.
We propose that early stage startups communicate in a way that didn’t exist in the 20th century – online – collaboratively through blogs.
We suggest that the founders/CEO invest 1 hour a week providing advisors and investors with “Continuous Information Access” by blogging and discussing their progress online in their startup’s search for a business model. They would:
Comment/Dialog with advisors and investors on a near-realtime basis
What Does this Change?
1) Structure. Founders operate in a chaotic regime. So it’s helpful to have a structure that helps “search” for a business model. The “boardroom as bits” uses Customer Development as the process for the search, and the business model canvas as the scorecard to keep track of the progress, while providing a common language for the discussion.
This approach offers VC’s and Angels a semi-formal framework for measuring progress and offering their guidance in the “search” for a business model. It turns ad hoc startups into strategy-driven startups.
2) Asynchronous Updates. Interaction with advisors and board members can now be decoupled from the – once every six weeks, “big event” – board meeting. Now, as soon as the founders post an update, everyone is notified. Comments, help, suggestions and conversation can happen 24/7. For startups with formal boards, it makes it easy to implement, track, and follow-up board meeting outcomes.
Monitoring and guiding a small angel investment no longer requires the calculus to decide whether the investment is worth a board commitment. It potentially encourages investors who would invest only if they had more visibility but where the small number of dollars doesn’t justify the time commitment.
A board as bits ends the repetition of multiple investor coffees. It’s highly time-efficient for investor and founder alike.
3) Coaching. This approach allows real-time monitoring of a startup’s progress and zero-lag for coaching and course-correction. It’s not just a way to see how they’re doing. It also provides visibility for a deep look at their data over time and facilitates delivery of feedback and advice.
4) Geography. When the boardroom is bits, angel-funded startups can get experienced advice – independent of geography. An angel investor or VC can multiply their reach and/or depth. In the process it reduces some of the constraints of distance as a barrier to investment.
Imagine if a VC took $4 million (an average Series A investment) and instead spread it across 40 deals at $100K each in a city with a great outward-facing technology university outside of Silicon Valley. In the past they had no way to monitor and manage these investments. Now they can. The result – an instant technology cluster – with equity at a fraction of Silicon Valley prices. It might be possible to create Virtual Valley Ventures.
We Ran the Experiment At Stanford our Lean Launchpad class ran an experiment that showed when “the boardroom is bits” can make a radical difference in the outcome of an early stage startup.
Our students used Customer Development as the process to search for a business model. The used a blog to record their customer learning, and their progress and issues. The blog became a narrative of the search by posting customer interviews, surveys, videos, and prototypes. They used the Business Model Canvas as a scorekeeping device to chart their progress. The result invited comment from their “board” of the teaching team.
Here are some examples of how rich the interaction can become when a management team embraces the approach.
We were able to give them near real-time feedback as they posted their results. If we had been a board rather than a teaching team we would have added physical reality checks with Skype and/or face-to-face meetings.
Show Me the Money While this worked in the classroom, would it work in the real world? I thought this idea was crazy enough to bounce off a five experienced Silicon Valley VC’s. I was surprised at the reaction – all of them want to experiment with it. Jon Feiber at MDV is going to try investing in startups emerging from Universities with great engineering schools outside of Silicon Valley that have entrepreneurship programs, but minimal venture capital infrastructure. (The University of Michigan is a possible first test.) Kathryn Gould of Foundation Capital and Ann Miura-Ko of Floodgate also want to try it.
Summary For startups with traditional boards, I am not suggesting replacing the board meeting – just augmenting it with a more formal, interactive and responsive structure to help guide the search for the business model. There’s immense value in face-to-face interaction. You can’t replace body language.
But for Angel-funded companies I am proposing that a “board meeting in bits” can dramatically change the odds of success. Not only does this approach provide a way for founders to “show your work” to potential and current investors and advisors, but also it helps expand opportunities to attract investors from outside the local area.
Startups are a search for a business model
Startups can share their progress/get feedback in the search
Weekly blog of the customer development narrative
Weekly summary of the business model canvas
Interactive comments and questions
Skype and face-to-face when needed
This may be a way to augment traditional board meetings
This might be a way to rethink our notion of geography as a barrier to investments
There are none so blind as those who will not see. Jonathan Swift
What’s Wrong With Today’s Board Meetings As customer and agile development reinvent the Startup, it’s time to ask why startup board governance has not kept up with the pace of innovation. Board meetings that guide startups haven’t changed since the early 1900’s.
Reinventing the board meeting may offer venture-backed startups a more efficient, productive way to direct and measure their search for a profitable business model.
Reinventing the board meeting may offer angel-funded startups – which because of geography or size of investment typically don’t have formal boards or directors – to attract experienced advice and investment outside of technology clusters (i.e. Silicon Valley, New York).
Because We’ve Always Done It This Way The combination of Venture Capital and technology startups is only about 50 years old. Rather than invent a new form of corporate governance, venture investors adopted the traditional board meeting structure from large corporations. Yet boards of large companies exist to monitor efficient strategy and execution of a known business model. While startups eventually get into execution mode, their initial stages are devoted to a non-linear, chaotic search for a business model: finding product/market fit to identify a product or service people will buy in droves at a sustainable, profitable pace.
In the last few years, our understanding that startups are not smaller versions of large companies, made us recognize that startups need their own tools, different from those used in existing companies: Customer Development – the process to search for a Business Model, the Business Model Canvas – the scorecard to measure progress in the search, and Agile Engineering – the tools to physically construct the product.
Why Have a Board Meeting? From a VC’s point of view there are two reasons for board meetings.
1) It’s their fiduciary responsibility. Once a startup gets going, it has asymmetric information. Investors get board seats to assure themselves and their limited partners that they are duly informed about their investment.
2) Investors believe that their experience and guidance can maximize their return. Here it’s the board that has asymmetric knowledge. A veteran board can bring 50-100x more experience into a board meeting than a first time founder. (VC’s sit on 6 – 12 boards at a time. Assume an average tenure of 4 years per board. Assume two veteran VC’s per board. = 50-100x more experience.)
From a founder’s point of view there are three reasons for board meetings.
1) It’s an obligation that came with the check.
2) Founders who have a great board do recognize the uncanny pattern recognition skills that good VC’s bring.
3) An experienced board brings an extensive network of customers, partners, help in recruiting, follow-on financing, etc.
What’s Wrong With a Board Meeting? The Wrong Metrics. Traditional startup board meetings spend an insane amount of wasted time using Fortune 100 company metrics like income statements, cash flow, balance sheet, waterfall charts. The only numbers in those documents that are important in the first year of a startup’s life are burn rate and cash balance. Most board meetings never get past big company metrics to focus on the crucial startup numbers. That’s simply a failure of a startup board’s fiduciary responsibility.
The Wrong Discussions. The most important advice/guidance that should come from investors in a board meeting is about a startup’s search for a business model: What are the business model hypotheses? What are the most important hypotheses to test now? How are we progressing validating each hypothesis? What do those numbers/metrics look like? What are the iterations and Pivots – and why?
Not Real-time. Startup board meetings occur every 4-6 weeks. While that’s great when you showed up in your horse and buggy, the strategy-to-tactic-to implementation lag is painful at Internet speeds. And unless there’s rigor in the process, because there is no formal structure for follow up, tracking what happened as a result of meeting recommendations and action items gets lost in the daily demands of everyone’s work. (Of course great VC’s mix in coffees, phone calls, coaching and other non-board meeting interactions but it’s ad hoc and not always done.)
Wastes Founders Time. For the founders, “the get ready for the board meeting” drill is often a performance rather than a snapshot. Powerpoints, spreadsheets and rehearsals consume time for materials that are used once and discarded. There are no standards for what each side (board versus management) does. What is the entrepreneur supposed to be doing? What are the board members supposed to be contributing?
The Wrong Structure. If you read advice on how to run a board meeting you’ll get advice that would have felt comfortable to Andrew Carnegie or John D. Rockefeller.
In the age of the Internet why do we need to get together in one room on a fixed schedule? Why do we need to wait a month to six weeks to see progress? Why don’t we have standards for what metrics VC’s want to see from their early stage startup teams?
Angels In America For angel-funded startups, life is even tougher. Data from the Startup Genome project shows that startups that have helpful mentors, listen to customers, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth. If you’re in a technology cluster like Silicon Valley you may be able to attract ad hoc advice from experienced investors. But very little of it is formal, and almost none of it approaches the 50-100x experience level of professional investors.
As there’s no formal board, most of these angel/investors meetings are over coffees. And lacking a board meeting there’s no formal mechanism to get investor advice. Angel investments in mobile and web apps today are approaching the “throw it against the wall and see if it sticks” strategy.
And for startups outside of technology clusters, there’s almost no chance of attracting Silicon Valley VC’s or angels. Geography is a barrier to investment.
So given all this, the million dollar question is: Why in the age of the Internet haven’t we adopted the tools we build/sell to solve these problems?
In the next post – Reinventing the Board Meeting.
Early stage board meetings are often clones of large company board meetings
That’s very, very wrong
Angel-funded startups have no formal mechanism for experienced advice
The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. This last post – part nine – highlights the final team presentations. Parts one through eight, the class lectures, are here, Guide for our mentors is here. Syllabus is here.
This is the End
Class lectures were over last week, but most teams kept up the mad rush to talk to even more customers and further refine their products. Now they were standing in front of us to give their final presentations. They had all worked hard. Teams spent an average of 50 to 100 hours a week on their companies, interviewed 50+ customers and surveyed hundreds (in some cases thousands) more.
While the slide presentations of each team are interesting to look at, that’s actually the sideshow. What really matters are the business model canvas diagrams in the body and appendix of each presentation. These diagrams are the visual representation of the how and the what a team learned in the class – how they tested their hypotheses by getting out of the building using the Customer Development process and what they learned about each part of their business model.
If you can’t see the Agora slides above, click here.
If you can’t see the Autonomow slides above, click here.
(p.s. they’re going to make a company out of this class project, and they’re hiring engineers.)
Team Blink Traffic
If you can’t see the Blink traffic slides above, click here.
Team D.C. Veritas
If you can’t see the D.C. Veritas slides above, click here.
If you can’t see the Mammoptics slides above, click here.
If you can’t see the OurCrave slides above, click here.
If you can’t see the PersonalLibraries slides above, click here.
If you can’t see the PowerBlocks slides above, click here.
If you can’t see the Voci.us slides above, click here.
Why Did We Teach This Class? Many entrepreneurship courses focus on teaching students “how to write a business plan.” Others emphasize how to build a product. We believe the former is simply wrong and the later insufficient.
Business plans are fine for large companies where there is an existing market, existing product and existing customers, but in a startup all of these elements are unknown and the process of discovering them is filled with rapidly changing assumptions. Experienced entrepreneurs realize that no business plan survives first contact with customers. So our goal was to teach something actually useful in the lives of founders.
Building a product is a critical part of a startup, but just implementing build, measure, learn without a framework to understand customers, channel, pricing, etc. is just another engineering process, not building a business. In the real world a startup is about the search for a business model or more accurately, startups are a temporary organization designed to search for a scalable and repeatable business model. Therefore we developed a class to teach students how to think about all the parts of building a business, not just the product.
There was no single class to teach aspiring entrepreneurs all the skills involved in searching for a business model (business model design, customer and agile development, design thinking, etc.) in one quarter. The Lean LaunchPad was designed to fill that void.
What’s Different About the Class? The Lean LaunchPad class was built around the business model / customer development / agile development solution stack. Students started by mapping their assumptions (their business model) and then each week they tested these hypotheses with customers and partners outside in the field (customer development) and used an iterative and incremental development methodology (agile development) to build the product.
The students were challenged to get users, orders, customers, etc. (and if a web-based product, a minimum feature set) all delivered in 8 weeks. Our goal was to get students out of the building to test each of the nine parts of their business model, understand which of their assumptions were wrong, make adjustments and continue to iterate based on what they learned. They learned first-hand that faulty assumptions were not a crisis, but a learning event called a pivot —an opportunity to change the business model.
What Surprised Us?
The combination of the Business Model Canvas and the Customer Development process was an extremely efficient template for the students to follow – even more than we expected.
It drove a hyper-accelerated learning process which led the students to a “information dense” set of conclusions. (Translation: they learned a lot more, in a shorter period of time than in any other entrepreneurship course we’ve ever taught or seen.)
The process worked for all types of startups – not just web software but from a diverse set of industries – wind turbines, autonomous vehicles and medical devices.
In this first offering of the Lean Launchpad class we let students sign up without being part of a team. In hindsight this wasted at least a week of class time. Next year we’ll have the teams form before class starts. We’ll hold a mixer before the semester starts so students can meet each other and form teams. Then we’ll interview teams for admission to the class.
Make Market Size estimates (TAM, SAM, addressable) part of Week 2 hypotheses
Show examples of a multi-sided market (a la Google) in Week 3 or 4 lectures.
Be more explicit about final deliverables; if you’re a physical product you must show us a costed bill of materials and a prototype. If you’re a web product you need to build it and have customers using it.
Teach the channel lecture (currently week 5) before the demand creation lecture (currently week 4.)
Find a way to grade team dynamics – so we can really tell who works well together and who doesn’t.
Video final presentations and post to the web. (We couldn’t get someone in time this year)
It Takes a Village While I authored these blog posts, the class was truly a team project. Jon Feiber of Mohr Davidow Ventures and Ann Miura-Ko of Floodgate co-taught the class with me (with Alexander Osterwalder as a guest lecturer.) Thomas Haymore was our great teaching assistant. We were lucky to get a team of 25 mentors (VC’s and entrepreneurs) who selflessly volunteered their time to help coach the teams. Of course, a huge thanks to the 39 Stanford students who suffered through the 1.0 version of the class. And finally special thanks to the Stanford Technology Ventures Program; Tom Byers, Kathy Eisenhardt, Tina Selig for giving us the opportunity to experiment in course design.
E245, the Lean LaunchPad will be offered again next Winter. See you there!
Listen to the post here:
The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. This post – part eight – was the last formal lecture. Parts one through seven of the lectures are here, Syllabus is here.
While this is the last lecture, the teams still have one more week to work on their companies, and then they have their final presentations – for 30% of their grade. All the teams have crossed the Rubicon.
Week 8 of the class.
Last week the teams tested their Revenue Models hypotheses: what are customers willing to pay for? This week they were testing their hypotheses about Partners. Partners are the external companies whose product or service combines with your Value Proposition to create a complete customer solution or “whole product” to satisfy customers. For example, Apple needed music from their record label partners to make the original iPod and iTunes experience complete. (The concept of Partners, took some explanation as some teams confused partners with the Distribution Channel.)
The Nine Teams Present PersonalLibraries was now an on-line “social shopping system.” After a week of hectic customer discovery, the team further refined their new business model. Their minimum viable product would be “Trusted Advice on products tailored to your needs by people and groups relevant to you.” Their initial customer segment were upwardly mobile professionals with $2-10K discretionary purchases/year (excluding travel,) and their revenue model was affiliate program fees.
With the clock ticking down to the end of the class the team appeared to give up sleep for the remainder of the quarter. They contacted a dozen admissions consulting firms, ran three Usertesting.com video interviews on a social shopping tool, surveyed 40 Stanford students on their on-line shopping habits, and then did another survey of 700 Stanford MBA students (!) to find out what books they’d recommend for prospective students. They used that data as their first “trusted advice” for the new website they built in a week. http://insidely.com/books/
Within the week they were #6 in Google search results for “Stanford Admission Books.”
Amazingly it looked like the PersonalLibraries team had restarted the company and found a segment where customers wanted their product. They had another week to go until their final presentations. This looks like a race to the wire.
On the technology front, last week they tested whether their Carrotbot (their research platform they built to gather data for machine vision/machine learning) could tell the difference between a carrot and a weed in a farm field versus the lab. This week the team started investigating whether the spectral reflectance curves of healthy green plants are different from weeds, and if so could an infrared Hyperspectral imaging camera be better suited than their current visible light camera for weed/plant recognition.
But what got our attention was when they told us they were investigating what it takes to kill a weed in the field. Their answer? With a laser. Way cool.
sharks with laser beams
They spent the week sorting through some basic laser technical questions. How much energy does it take to kill a weed? Answer: About 5 Joules of energy. Next question: How much energy will the laser require? Answer: If the robotic weeder is traveling at 1.5 mph, the laser needs to kill the weed in about 10 milliseconds; therefore the laser needs to put out no more than 500 watts of energy. What wavelength of laser? Answer: The most cost effective wavelength is 800-900nm ~ $20/watt. But water (the main ingredient in a weed) best absorbs light at higher frequencies – think microwaves. Final question: Is the improved absorption efficiency worth the extra cost? Testing for all of these is required.
The next team was D.C. Veritas, building a low cost wind turbine for cities. Last week the team did mass interviews of city officials across the United States to understand the project approval process inside a city. This week they broadened the discussion with interviews with the city planner in Mariposa, Texas and the city engineer from Rapid City, South Dakota.
They worked on understanding their partners. D.C. Veritas needs three types of partners: installers (to reduce their overhead,) certification authorities (who would provide credibility) and government and research labs (for testing facilities).
Of real interest was their evolving view of their revenue model. Instead of selling a city the wind turbine hardware, their revenue model moved to a Wind Power Purchase Agreement, a long term contract with a city to buy the electricity generated by the D.C. Veritas turbines.
The Agora Cloud Services team was now making a tool set for managing Amazon Web Services cloud compute usage. They believed their tools could save customers 30% of their Amazon bill. Their value proposition was to provide service matching, capacity planning and usage monitoring & control. They had another 3 interviews, this time with potential partners and integrators.
The Week 8 Lecture: Q&A and Summing Up Our lecture covered Key Resources and Cost Structure. The textbooks for this class were Alexander Osterwalder’s Business Model Generation (along with the Four Steps to the Epiphany). So who better to have as a surprise guest lecturer for our last class than Alexander Osterwalder himself.
His lecture covered: What resources do you need to build your business? How many people? What kind? Any hardware or software you need to buy? Any IP you need to license? How much money do you need to raise? When? Why? Importance of cash flows? When do you get paid vs. when do you pay others?
Our assignment for the teams during their final week: What’s your expense model? What are the key financials metrics for costs in your business model? Costs vs. ramp vs. product iteration? Access to resources. Where is the best place for your business? Where is your cash flow break-even point? Assemble a resources assumptions spreadsheet. Include people, hardware, software, prototypes, financing, etc. When will you need these resources? Roll up all the costs from partners, resources and activities in a spreadsheet by time.
The last part of their assignment is their final presentation – a “Lessons Learned” summary of their work over the entire quarter – which will count for 30% of their grade. To help them get ready for their final, one of our mentors plans to hold a mandatory “story-telling” workshop, to assist them in assembling their final presentation.
Over the last few weeks as our students presented, we had a growing feeling that we were seeing something extraordinary. Our teaching objective was to take engineers (with a smattering of MBA’s) and give them an immersive hands-on experience of how an idea becomes a profitable business. We taught them theory, methodology, and practice using Customer Development and business model design.
Watching them we realized that we had found a way to increase the information density a student team could acquire in eight short weeks. But what was truly awe-inspiring was the breathtaking speed and tempo of the teams’ Pivots.
All teams had all accomplished something remarkable, but it won’t be clear what a singular achievement this was until we see their final presentations.
The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. With one week and one more updates to go, this post is part seven. Parts one through six are here, Syllabus is here.
With a week to go the teams are starting to look like opening night before the big play. Teams are iterating and pivoting right and left, one team threw their entire business model out the window and did a complete restart, and another team was having a meltdown over personalities.
Week 7 of the class.
Last week the teams were testing their hypotheses about their Channel (how a company delivers its value proposition (i.e. its product or service) to its customers. This week they were testing their hypotheses about Revenue Models: what are customers really willing to pay for? How? Are you generating transactional or recurring revenues? Is it a multi-sided market, and if so who’s the user versus who’s the payer.
The Nine Teams Present The first team up was PersonalLibraries the team making a reference management system for discovering, organizing and citing researchers’ readings. Oops. No more. The team looked at the potential revenue and concluded that the outlook for this business with this customer segment was dismal. They decided to do something more dramatic than just a Pivot. They did a restart. They moved from “Reference Libraries” to “Product Libraries”— an on-line social shopping system. (If this had been a real startup rather than a class we would have had the team test many more variants on customer segment, revenue models, channels, etc before such an extreme move.)
They quickly came up with a new business model canvas, value proposition and customer segment.
The team hasn’t been getting much sleep as they have a week and a half to make meaningful progress. Lets see what they can pull off.
Autonomow, the robotic farm weeder had a busy week. In talking to their sales channel (farm equipment dealers) and customers (organic farmers) they realize they have an opportunity to come up with a unique revenue stream. Instead of selling or leasing the equipment they are going to charge for leasing according to weed density in the farm fields. The denser the weeds the higher the rental price per day. Customers and dealers agree that it’s a fair deal. Wow.
On the way to the WorldAg Expo their Carrotbot (their research platform they built to gather data for machine vision/machine learning) hit the farm fields near Avenal, California.
The videos of the robot in the field were priceless.
CarrotBot hits the Ground
Where are we?
At the World Ag Expo in Tulare the team encounters its first potential competitor – “Robocrop.” (No kidding, I couldn’t make this up.) The Robocrop Precision Guidance System for row crop cultivators uses a camera to shift a hitch so cultivators can cut very close to the plant rows and the Robocrop InRow is a robotic weeder.
The next team was D.C. Veritas, the team building a low cost residential wind turbine wind turbine for cities and utilities.Last week the team pivoted and their wind turbine is now embedded into street and highway light poles.
This week the D.C. Veritas team put it into overdrive and did mass interviews of city officials across the United States. In Palo Alto they talked to the financial and utilities mangers. In Williamstown, West Virginia they spoke to the city planner and a member of the budget committee. In Oklahoma City, Oklahoma it was the city engineer and director of public works. In Amarillo, Texas they had interviews with the head of the bidding process, the Street light manager, Director of Public Works and the utilities engineer.
They quickly got a good handle on the canonical project approval process inside a city.
They combined their understanding of the city approval process with the data they gleaned from customer interviews and developed preliminary archetypes. These represented the different customers in the approval cycle inside a city.
The Agora team, a marketplace for cloud computing, (a relative island of calm in a turbulent sea of other teams) now believed their business was providing a tool set for managing Amazon Web Services cloud compute usage. They believed they could build tools that would save customers 30% of their Amazon bill by provide service matching, capacity planning and usage monitoring & control. The team was a paragon of steady and relentless progress. They had another 4 interviews with potential customers and consultants.
Our lecture this week covered Partners. Which partners and suppliers leverage your model? Who do you need to rely on?
Our assignment for the teams for next week: What partners will you need? Why do you need them and what are risks? Why will they partner with you? What’s the cost of the partnership? What are the benefits for an exclusive partnership? What are the incentives and impediments for the partners?
The pressure was on. The other five teams were also furiously iterating and pivoting. The JointBuy team (the one that sent out 16,000 emails last week) realized that their low-fidelity website they used to test key concepts needed to get real to attract buyers and sellers in volume. The team pulled a week of all nighters and turned the wireframe prototype into a fully functioning site.
In almost every entrepreneurship class with a team project there’s a team that can’t figure out how to work together. These are the same problems one sees in real startups (disagreements over who controls the vision, team members not pulling their weight, disillusionment with the team direction, individuals uncomfortable in rapid decision making with less than perfect data, etc.) We give the students an escalation path if they’re having interpersonal problems (mentors – to Teaching Assistant – to Professors) to see if they can first worth through the issues without our intervention. While these are always painful we try to teach that they are part of the learning process. Better you encounter the problems in a classroom than after you raised a venture round.
At this point in the class almost all the teams are in a full sprint to the finish line. Next week, the last lecture.
The Stanford Lean LaunchPad class was an experiment with a new model of teaching startup entrepreneurship. With two weeks and two more updates to go, this post is part six. Parts one through five are here, Syllabus is here.
While we’ve been pushing hard on the teams, this week the teaching team was about to get its socks blown off. All the teams were showing us what agile looked like, but this week several would remind us what focused and relentless really meant.
Week 6 of the class.
Last week the teams tested their hypotheses about Customer Relationships (how do they get, keep and grow customers.) This week they were testing their hypotheses about the sales “Channel” – how a company delivers its value proposition (i.e. its product or service) to its customers. There are two major channels: physical channels and virtual (web/mobile) channels. Physical channels include Direct Sales, Rep Firms, Systems Integrators, Value-added Resellers, Distributors, Dealers, Mass Merchandisers, and Original Equipment Manufacturers. Virtual channels include Dedicated e-commerce, Two-step e-distribution and Aggregators.
The Nine Teams Present The first team up was Autonomow, the robotic mower farm weeder. They believed tthey would sell their robotic weeder to farm equipment dealers and distributors so they interviewed 9 more of them this week. They found that sales to this channel would require a demonstration, and that dealers would have to demo the robotic weeders to the customers. They learned that farmers expect personal and timely service/support. Relationships and trust are important.
Their week 6 business model now looked like this:
All that we expected. But what they showed us next astonished all of us.
Last week we challenged the team that unless they developed hardware which could tell the difference between a weed and a plant, their business model would be just another set of PowerPoint slides. We expected that at best in the final 3 weeks of class they might build prototype hardware on a lab bench. Instead they built the prototype of an entire weeding robot – in one week. They called it the CarrotBot.
CarrotBot was their research platform to gather data for machine vision/machine learning. They wanted to test: can a machine tell the difference between a weed and a plant in the field? What about under different lighting and soil conditions? Could they train a machine to do this automatically?
The CarrotBot had a high-speed machine vision camera and a high-resolution camera for visual data as well as a panning LIDAR system for sub-millimeter depth measurement. Encoders on the drive motors and RTK-GPS measured precision position and velocity. After they validated the weed detection system, the next step was to arm the CarrotBot with a weed kill system (clove oil, high pressure steam/water, or lasers).
The Autonomow team worked 20-hour days, Wednesday – Monday. (On Wednesday night they got the idea to build a robot. On Thursday they ordered the parts, received them Friday, then built the robot over the next three days. (They got help from another student researcher in robotics and machine learning in the Stanford Artificial Intelligence Lab.)
Their goal is to deploy CarrotBot this week in the farm fields in Avenal, California, on the way to the World Ag Expo.
I’m sure the teaching team gave them some advice, but we were so busy trying to hide our jaws hitting the floor I can’t remember what it was..
Next was D.C. Veritas, the team building a low cost residential wind turbine. This week the team got religion and decided that a major pivot was in order. They ditched the residential market as they realized that a more accessible and profitable customer segment(s) were cities, lighting companies and utilities.
In talking to customers, the team found that cities are actively trying to reduce street lighting costs (retrofitting with LEDs, turning off lights, and charging streetlight fees.) If they redesigned their the wind turbine, it could be embedded into street and highway light poles. Not only could the turbine power the street lights, but it would make excess energy that could be sold back into the grid. Their value proposition had now changed from a wind turbine supplier to homes, to a distributed power supplier to cities and utilities.
Their channel was still direct sales, but now selling to cities allowed them to sell multiple turbines with a larger order size.
D.C. Veritas estimated that their new total available market was 13 million city street lights in the U.S., plus an unknown number of highway lights.
The feedback from the teaching team was that with a new customer segment identified the team was now in a race against time to provide a meaningful business model before the class ended.
PersonalLibraries was focused on creating a reference management system for discovering, organizing and citing researchers’ readings. Last week the teaching team had suggested that they ought to “run away from the academic researcher market as fast as possible.” Yet like passionate entrepreneurs, the team ignored our advice and pressed on. (To be fair, one of their team members had built the software and worked on it for awhile.)
This team spoke with 10 more customers and potential channel partners. They heard: “the academic market is terribly small, charging $1 a user for a high volume academic site license is unrealistic, the cost of reaching lab managers is prohibitive, despite poor economics there are many niche competitors, and academic software is a “dinosaur” business with lots of competitors in the space because they started there years ago and aren’t able to pivot out.” Ouch!
With the evidence piling up, the team is now starting to think about pivoting to other customer segments and/or other pricing models. Should they create a freemium version of their current product? Should they look at the Document Management market?
Time is running out for the PersonalLibraries team. Two more weeks of the class to go. Take a look at their presentations and you decide – what should they do?
The Agora Cloud Services team, (a marketplace for cloud computing) spent the week testing their channel hypotheses and further refined their business model canvas. They believed they were going to have inside sales reps, third party cloud computing consultants and their own web channel sales.
The team interviewed another 9 customers and industry experts and attended the Amazon Web Services meetup in San Francisco.
This week’s lecture covered the Revenue Model including questions like these: How does your company make money? What are your customers going to pay for? What types of revenue streams are there? How does the web differ from other channels?
Our assignment for the teams for next week: What are the key financials metrics for your business model? If you have more than one product, how will you package it into various offerings? How will you price the offerings? What is the customer lifetime value? How are your competitors pricing? Each team has to test their pricing in front of 100 customers on the web or 10-15 customers non-web. And they had to assemble an income statement for the their business model.
Most of the teams were doing great. A few were doing spectacularly well. One other team in the class, Jointbuy (an online platform allowing buyers to purchase products in bulk) turned in an equally extraordinary effort. When testing demand creation in their multi-sided business model, they couldn’t get enough sellers to their site. So they sent out mass emails to create demand. They certainly got noticed – as they had hijacked the Stanford email system to send 16,000 emails before they got shut down.
Much like startups in the real world, team performance in entrepreneurship classes seems to follow a Pareto distribution.
Two weeks to go. Let’s see how tenacity, sleepless nights, customer feedback and agile iteration change the final outcome.
The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. This post is part five. Parts one through four are here, Syllabus is here.
Week 5 of the class.
Last week the teams were testing their hypotheses about their Customers (who are the users, payers, buyers, etc.) This week they were testing one of the most confusing sections of a company’s business model – Customer Relationships - the activities used to “Get, Keep and Grow” customers in a physical or virtual (web or mobile) channel. (Internet investor Dave McClure coined the acronym ”AARRR,” to remember the parts of Customer Relationships on the web.)
Many of the students had heard phrases that fall under Customer Relationships before; “customer acquisition, SEO/SEM, public relations, Social Network, Advertising, Loyalty programs, cross-sell and up-sell” etc., but now they were actually trying to implement it. (If their team was a web or mobile app they actually had to buy Google or Facebook ads and create demand.)
For some of the teams their expectation was if they built the product customers will come. Filing into the classroom I could tell that for some reality had just come crashing down on them. Seeing the lack of customer interest for the first time is always depressing. (The goal of the class was to get them to understand that in a startup, that was the norm not the exception. And to teach them a methodology of what to do about it.) It was making some of the teams question other parts of their business model (did they have the right customer, did they have the right product features to meet customer needs, etc.)
The Nine Teams Present The first team to present was D.C. Veritas, the team building a low cost, residential wind turbine. During the week they interviewed 7 more companies and consultants, developed case studies for 20 different cities in 5 states, and finalized the bill of materials for the wind turbine. But the big project for the week was testing and analyzing Customer Acquisition Costs. The team put together their sales funnel and started testing demand.
The results were disappointing. The most optimistic estimates showed that the residential wind turbine market was less than $20m in year 5 and the costs to acquire the customers made this a money-losing business.
After regrouping the team decided that a major pivot was in order. Perhaps residential customers were the wrong target? Maybe the wind turbine they were building was better suited to a different customer segment? They had gotten feedback from consultants and industry experts that cities and utilities might be a more receptive audience. What if they redesigned the wind turbine to be embedded into street and highway light poles? Then they could serve cities, lighting companies and utilities. Using the business model canvas, the changes to their business were obvious.
(BTW, our definition of a Pivot: it’s when you significantly modify one or more of the business model building blocks.)
Three more weeks to go. Can the D.C. Veritas team discover whether there’s a real opportunity for their wind turbine in cities? The teaching team observed that the next few weeks are going to be interesting. Time to dig in and find out.
Our next team up was Autonomow, the robot lawn mower farm weeder. Last week they had pivoted from customers who needed large areas mowed, to organic farmers who needed lower costs for weeding. In this weeks foray into farm country they spoke to five farm implement dealers and interviewed yet another farmer. However, their primary focus was thinking through how they would “get” their initial customers. In talking to farmers and farm equipment dealers they learned the farm-specific places to create demand; trade shows like the World Ag Expo and magazines such as Vegetable Grower, Ag Source, Farm Equipment and Tractor House. The team then put together a specific budget for initial demand creation.
The teaching team suggested that was the research to date was great, but until they built a robot that could actual tell the difference between a weed and a plant, this would just be a paper exercise. They were engineers, certainly they could do better than that? The Autonomow team started thinking how they could prove that their paper business model was real.
PersonalLibraries Last week we asked the PersonalLibraries team: are there enough customers to make this a business? So during the week they ran more hands-on user testing, A/B tests, landing page conversion tests, and bought Google Adwords.
The results were not impressive. The feedback they were getting was that the product was a “nice to have” but not a “hair-on-fire” product.
Our feedback was, that their data seemed to say that their current users don’t want to spend money and will incur infinite support and infinite cost. Our suggestion was, “run away from the academic researcher market as fast as possible.” We offered that the team might want to expand their user research to think about new features and verticals (document management, law firms, lab managers with discretionary budget, etc.)
Agora Cloud Services The Agora team ended last week wondering whether they were 1) a true marketplace for cloud computing, where they provide both matching and exchange capabilities for real-time trading. Or were they 2) an information exchange, providing matching services for cloud computing buyers and sellers, providing matching services. This week they answered the question by “punting.” They decided they were going to start as a information services, move to brokering, then prediction and finally evolve into a true market. They interviewed another 8 buyers/sellers/industry experts.
Their results on whether they could acquire with Google Adwords was a bit sobering. Their first effort didn’t get much traffic: 6 clicks out of ~2000 impressions. Worse yet, each of these clicks cost about a $1.00. Reason? They had been bidding on keywords that are too generic (e.g. cloud, ec2, Amazon Web Services, etc.)
Their ads of “Cloud Demand Prediction” hadn’t been catching the eyes of people searching for these keywords. So they picked more specific keywords such as, (cloud comparison, best cloud providers, etc). And they created ads with specific headlines, such as “Too many cloud providers?”, “Reduce your cloud spend”, etc). They also increased their daily campaign budget to $20.00. What they found was that the keywords that did have traffic volume are extremely expensive. Depending on the keyword, the first page bids were between $5.00 to $25.00 per click! Ouch.
The team concluded that AdWords may not be the best channel to create demand.
The Week 5 Lecture: Channel Channels are how a company delivers its value proposition (i.e. its product or service) to its customers. There are two major channels – virtual (web/mobile) and physical channels – and the difference is dramatic. In one, physical goods move from a loading dock to a customer or a retail outlet. In another the product is offered and sold online. (If the product is itself bits, it may not only be sold online but is often also delivered or used on-line.)
Our lecture talked out how to choose the right sales channel, how the channel makes money, how they’re motivated, and the economics of a sales channel.
The lesson for the students this week was failure. What we wanted to teach them wasn’t how to fail fast – any idiot can do that. We wanted to teach them how to recognize failure, learn from it, and pivot. It’s not about failing fast – it’s about learning faster. That’s the lesson at the heart of the search for a repeatable and scalable business model.
Now deep into the class most of the teams are starting to rethink their initial assumptions. Which teams will continue to Pivot? Will any completely abandon their current business and pick a new one?