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.”

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.

Lessons Learned

• 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
• The Startup Owners Manual is the definitive reference book for founders, investors and everyone interested in startups
• The Lean Launchpad on-line class will be based on the new book

But the total movie industry revenue was $87 billion. Where did the other $57 billion come from?

From sources that the studios at one time claimed would put them out of business: Pay-per view TV, cable and satellite channels, video rentals, DVD sales, online subscriptions and digital downloads.

The Movie Industry and Technology Progress
The music and movie business has been consistently wrong in its claims that new platforms and channels would be the end of its businesses. In each case, the new technology produced a new market far larger than the impact it had on the existing market.

• 1920’s – the record business complained about radio. The argument was because radio is free, you can’t compete with free. No one was ever going to buy music again.
• 1940’s – movie studios had to divest their distribution channel – they owned over 50% of the movie theaters in the U.S. “It’s all over,” complained the studios. In fact, the number of screens went from 17,000 in 1948 to 38,000 today.
• 1950’s – broadcast television was free; the threat was cable television. Studios argued that their free TV content couldn’t compete with paid.
• 1970’s – Video Cassette Recorders (VCR’s) were going to be the end of the movie business. The movie businesses and its lobbying arm MPAA fought it with “end of the world” hyperbole. The reality? After the VCR was introduced, studio revenues took off like a rocket.  With a new channel of distribution, home movie rentals surpassed movie theater tickets.
• 1998 – the MPAA got congress to pass the Digital Millennium Copyright Act (DMCA), making it illegal for you to make a digital copy of a DVD that you actually purchased.
• 2000 – Digital Video Recorders (DVR) like TiVo allowing consumer to skip commercials was going to be the end of the TV business. DVR’s reignite interest in TV.
• 2006 - broadcasters sued Cablevision (and lost) to prevent the launch of a cloud-based DVR to its customers.
• Today it’s the Internet that’s going to put the studios out of business. Sound familiar?

Technology Innovation
The movie industry was born with a single technical standard – 35mm film, and for decades had a single way to distribute its content – movie theaters (which until 1948 the studios owned.) It was 75 years until studios had to deal with technology changing their platform and distribution channel. And when it happened (cable, VCR’s, DVD’s, DVR’s, the Internet,) it was a relentless onslaught. The studios responded by trying to shut down the new technology and/or distribution channels through legislation and the courts.

Regulation/Legislation
But why does the movie business think their solution is in Washington and legislation?

History and success.

In the 1920’s individual states were beginning to censor movies and the federal government was threatening to do so as well. The studios set up their own self censorship and rating system keeping most sex and politics off the screen for 40 years. Never again wanting to be at the losing side of a political battle they created the movie industry’s lobbying arm, MPAA.

By the 1960’s, the MPPA achieved regulatory capture (where an industry co-opts the very people who are regulating it,) when they hired Jack Valenti, who ran the studios’ lobbying efforts for the next 38-years. Ironically, it was Valenti’s skill in hobbling competitive innovation that negated any need for studios to develop agility, vision and technology leadership.

Management of Innovation
The introduction of new technology is always disruptive to existing markets, particularly to content/copyright owners whose sell through well-established distribution channels. The incumbents tend to have short-sighted goals and often fail to recognize that more money can be made on new platforms and new distribution channels.

In an industry facing constant technology shifts the exec staff and boards of the studios have lawyers, MBAs and financial managers, but no management skill in dealing with disruption. So they rely on lobbying ($110 million a year,) lawsuits, campaign contributions (wonder why the President won’t be vetoing SOPA?) and Public Relations.

Ironically, the six major movie studios have a great technology lab in Silicon Valley with projects in streaming rights, Video On Demand, Ultraviolet, etc. But lacking the support from the studio CEOs or boards, the lab languishes in the backwaters of the studios’ strategy.  Instead of leading with new technology, the studios lead with litigation, legislation and lobbying. (Imagine if the $110 million/year spent on lobbying went to disruptive innovation.)

Piracy
One of the claims that studios make is that they need legislation to stop piracy. The fact is piracy is rampant in all forms of commerce. Video games and software have been targets since their inception. Grocery and retail stores euphemistically call it shrinkage. Credit card companies call it fraud.  But none use regulation as often as the movie studios to solve a business problem. And none are so willing to do collateral damage to other innovative industries (VCRs, DVRs, cloud storage and now the Internet itself.)

The studios don’t even pretend that this legislation benefits consumers. It’s all about protecting short-term profit.

SOPA
When lawyers, MBAs and financial managers run your industry and your lobbyists are ex-Senators, understanding technology and innovation is not one of your core capabilities.

The SOPA bill (and DNS blocking) is what happens when someone with the title of anti-piracy or copyright lawyer has greater clout than your head of new technology. SOPA gives corporations unprecedented power to censor almost any site on the Internet. It’s as if someone shoplifts in your store, SOPA allows the government to shut down your store.

History has shown that time and market forces provide equilibrium in balancing interests, whether the new technology is a video recorder, a personal computer, an MP3 player or now the Net. It’s prudent for courts and congress to exercise caution before restructuring liability theories for the purpose of addressing specific market abuses, despite their apparent present magnitude.

What the music and movie industry should be doing in Washington is promoting legislation to adapt copyright law to new technology — and then leading the transition to the new platforms.

The U.S. State Department has been championing the Internet Freedom initiative across the world. Secretary of State Clinton said, “…when ideas are blocked, information deleted, conversations stifled, and people constrained in their choices, the Internet is diminished for all of us.”

It’s too bad the head of the MPAA – an ex Senator - made a mockery of her words when he wondered “why our online censorship can’t be like China?”

We wonder, “Why can’t the film industry innovate like Silicon Valley?”

Lessons Learned

• Studios are run by financial managers who lack the skills to exploit disruptive innovation
• Studio anti-piracy/copyright lawyers trump their technologists
• Studios have no concern about collateral damage as long as it optimizes their revenue
• Studios $110M/year lobbying and political donations trump consumer objections
• Politicians votes will follow the money unless it will cost them an election

I was lucky enough to get interviewed by Rob Morris of American Entrepreneur Radio.

Ron Morris has a great “radio voice,” and actually seemed to understand what the heck I was talking about.  It made for a fun interview.

Click here to listen to the interview: Steve Blank American Entrepreneur Radio interview

The following week Ron Morris interviewed Regis McKenna, who for decades was the “gold standard” for high tech Public Relations in Silicon Valley. Click here to listen to the Regis interview.

.

Over the last 40 years Technology investors have learned that the success of startups are not just about the technology but “it’s about the team.”

We spent a year screwing it up in our Lean LaunchPad classes until we figured out it was about having the right team.

Startup Team Lessons Learned
During the last 12 months we’ve taught 42 entrepreneurial teams with 147 students at Stanford, Berkeley, Columbia and the National Science Foundation. (As many teams as most startup incubators.)

Get into the Class
When I first started teaching hands-on, project/team entrepreneurship classes we’d take anyone who would apply. After awhile it became clear that by not providing an interview process we were doing these students a disservice. A good number of them just wanted an overview of what a startup was like – an entrepreneurial appreciation class (and we offer some great ones.) But some of our students hadn’t yet developed a passion for entrepreneurship and had no burning idea that they wanted to bring to market. Yet in class they’d be thrown into a “made-up in the first week” startup team and got dragged along as a spear-carrier for someone else’s vision.

Step One – Set a Bar
So as a first step we made students formally apply and  interview for the Lean LaunchPad class. We were looking for entrepreneurs who had great ideas and interest in making those ideas really happen. We’d hold mixers before the first class and the students would form their teams during week one of the class.

But we found we were wasting a week or more as the teams formed and their ideas gelled.

Step Two – Apply As A Team
So next time we taught, we had the students apply to the class as a team. We hold information sessions a month or more before the classes. Here students with preformed teams could come and have an interview with the teaching team and get admitted. Or those looking to find other students to join their team could mix and market their ideas or join others and then interview for a spot. This process moved the team logistics out of class time and provided us with more time for teaching.

But we had been selecting teams for admission on the basis of whether they had the best ideas. We should have known better.  In the classroom, as in startups, the best ideas in the hands of a B team is worse than a B idea in the hands of a world class team.

Here’s why.

Step Three – Hacker/Hardware, Hustler, Designer, Visionary
As we taught our Lean LaunchPad classes we painfully relearned the lesson that team composition matters as much or more than the product idea. And that teams matter as much in entrepreneurial classes as they do in startups.

In a perfect world you build your vision and your customers would run to buy your first product exactly as you spec’d and built it. We now know that this ‘build it and they will come” is a prayer rather than a business strategy.  In reality, a startup is a temporary organization designed to search for a repeatable and scalable business model. This means the brilliant idea you started with will change as you iterate and pivot your business model until you find product/market fit.

The above paragraph is worth reading a few times.

It basically says that a startup team needs to be capable of making sudden and rapid shifts – because it will be wrong a lot. Startups are inherently chaos. Conditions on the ground will change so rapidly that the original well-thought-out business plan becomes irrelevant.

And finding product/market fit in that chaos requires a team with a combination of skills.

What skills? Well it depends on the industry you’re in, but generally great technology skills (hacking/hardware/science) great hustling skills (to search for the business model, customers and market,) great user facing design (if you’re a web/mobile app,) and by having long term vision and product sense. Most people are good at one or maybe two of these, but it’s extremely rare to find someone who can wear all the hats.

It’s this combination of skills is why most startups are founded by a team, not just one person.

University Silos
While building these teams are hard in the real world, imagine how hard it is in a university with classes organized as silos. Business School classes were only open to business school students, Engineering School classes were only open to engineering school students, etc. No classes could be cross-listed. This meant that you couldn’t offer students an accurate simulation of what a startup team would look like. (In our business school classes we had students with great ideas but lacking the technical skills to implement it. And some of our engineering teams could have benefited from a role-model to follow as a hustler.)

So the next time we taught, we managed to ensure that the class was cross-listed and that the student teams had to have a mix of both business and engineering backgrounds.

I think we’ve finally got the team composition right – relearning all the lessons investors already knew.

But now on to the next goal – getting our mentor program correct.

Lessons Learned

• Finding product/market fit in startup chaos requires a team with a combination of skills
• Hacker/Hardware, Hustler, Designer, Visionary
• At times an A+ market (huge demand, unmet need) may trump all
• Getting the Mentors right is the next step

Steve Jobs

Watching an entrepreneur fail is sad, but watching them fail from a lack of nerve is tragic.

Excitement
At the beginning of this year Bob, one of my ex-students was in entrepreneurial heaven. He had an idea for a new class of enterprise software insight-as-a-service based on big data web analytics as a Cloud/SaaS (Software As a Service) application.

Bob had taken to heart the business model canvas and Customer Development lessons. After graduating he put together a prototype and had quickly marched through Customer Discovery, iterating his product with the help of CIOs and Fortune 1000 IT departments.

I had made one of the introductions to a Fortune 100 CIO’s so I got to hear his progress from both him and the CIO.

Takeoff
After 90 days, things seemed to be moving at startup speed. Bob had a backlog of users wanting to try his application, and the corporate IT people who were trying his early prototype said, “It’s crude, we hate the user interface, it’s missing lots of features – but we’ll kill you if you try to take it away from us.”

I pointed a VC who followed the space to the CIO who was testing the prototype. The VC told me the CIO wouldn’t get off the phone. He kept telling him he couldn’t remember when he had seen an enterprise software product with so much promise. The VC checked with other IT users and heard the same reaction. It was a “gotta use it, don’t take it away, we’ll have to buy it” product. After a demo and lunch, the VC (who normally did later stage deals) wrote my ex student a check for a seed round.

Life couldn’t be better.

I followed Bob progress in bits and pieces from updates from the CIO, the VC and his emails and blogs. He seemed to be on the fast track to startup success. But pretty soon a few worrying warning signs appeared.

The first thing that I noticed was that Bob couldn’t seem to find a co-founder. I wasn’t close enough to know if he wasn’t really looking for one, but given the early success he was having, it seemed a bit odd. But the next thing really got me concerned. Bob started hiring second rate developers. At best they were B- players.

Stall
A month went by, and the product stopped getting better. The U/I still sucked, and new features had stopped appearing. The next month, the same thing. I got a call from my CIO friend asking, “what was going on?” He said, “It was a great prototype, we would have loved to deploy it company-wide, and I hate to let it go, but it looks like Bob company just lost interest in developing it. I’m going to dump it and look for a substitute.” So I called Bob and suggested we grab a coffee.

I asked him how things were going and got the update on how the earlyvangelists were using the product. As I had heard, they were ecstatic. But Bob said he was worried he hadn’t found the right customer segment yet. “I’m not sure I can get all of these guys to pay me big bucks,” he said. “That’s why I stopped coding, and I’m spending all my time out in the field still talking to more customers.” “What does your VC’s say you ought to be doing?” I asked.  “Oh, he hasn’t had much time for me, his firm almost never does seed deals. It turns out I was an exception.”  Oh, oh.

The conversation was starting to make the hair on the back of my neck stand up. Bob had gotten to a place most founders never do – his product was a “gotta have it for people with big budgets.” He should have been back rapidly coding, iterating and finding out what feature set would get him to paying customers.

Instead he had produced barely 3 weeks of progress in the last 5 months. His prototype was rapidly wearing out its welcome.

A Lack of Nerve
When I pressed Bob on this he admitted, “No I guess my engineers aren’t very good. But I hired guys who were cheap because I wasn’t sure if my hypotheses were right. Didn’t you tell us to test our hypotheses first?” Now it was my time to be surprised. “Bob, you’ve validated your hypotheses better than any startup I’ve ever seen. You found that out in the first month. You got customers begging you to finish the product so they could buy it. You should have been hiring world-class talent and building something these CIO’s will pay for. It’s not too late. It’s time to grab them by the throat and go for it.”

I wasn’t ready for the answer, “Steve, I’ve been reading all about premature scaling and making sure everything is right before I go for it. I want to be sure I get all of this right. I’m afraid I’ll run out of money.”

I thought I’d make one more run at it. “Bob,” I said, “few entrepreneurs get the first time response you have from an early product. At your rate you’re going to burn through your cash trying to get it perfect. It’s a startup. You’ll never have perfect information. You’re sitting on a gold mine. Grab the opportunity!”

I got a blank stare.

We made some more small talk and shook hands as he left.

Bob was in the wrong business, not the wrong market. He wanted certainty, comfort and security.

I stared at my coffee for a long time.

Carpe Diem – make your lives extraordinary.

Lessons Learned

• Yes, premature scaling is a cause of startup death
• Yes, you need to get out of the building and test your hypotheses
• But, when an opportunity smacks you in the head for gosh sake grab it with both hands and don’t let go
• If you can’t, get out of the startup game

George Bernard Shaw

We’re in the middle of our National Science Foundation Innovation Corps class – taking the most promising research projects in American university laboratories and teaching these scientists the basics of entrepreneurship. Our goal is to accelerate the commercialization of their inventions. Our Lean LaunchPad class teaches scientists and engineers that starting a company is another research project that can be solved by an iterative process of hypotheses testing and experimentation built around the business model / customer development / agile development solution stack. It’s “the scientific method” applied to startups.

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.

And scientists like Satish Kandlikar and the National Science Foundation will lead the way.

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.

Summary
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.

Lessons Learned

• 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 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.

• 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 entrepreneurial ecosystem that looks like something this:

• Aalto University: Aalto Center for Entrepreneurship, Aalto Entrepreneurship Society
• Startup Accelerators: Startup Sauna and Vigo which includes Lifeline Ventures, KoppiCatch, and Veturi
• Startup Blog: Arctic Startup
• Business Angels: FiBAn, Sitra
• Venture Capital: FVCA, NextIt Ventures, Primus Ventures, Open Ocean Capital, Connor VC, and Inventure
• Government Funding: Tekes, Sitra, Finnvera, Finnish Investment Industry

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 by using 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 will follow shortly.

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

Here’s the step-by-step process we suggest our students use in our Lean LaunchPad classes.

1. Set up the logistics to manage your team
2. Craft company hypotheses
3. Write a value proposition statement that other people understand
4. Set up the Website Logistics
5. Build a “low-fidelity” web site
6. Get customers to the site
7. Add the backend code to make the site work
8. Test the “problem” with customer data
9. Test the “solution” by building the “high-fidelity” website
10. Ask for money

(Use the Startup Tools Page as the resource for tool choices)

Step 1: Set Up Team Logistics

• Read Business Model Generation pages 1-72, and The Four Steps to the Epiphany Chapter 3
• Set up the Lean LaunchLab or a WordPress blog to document your Customer Development progress
• Use Skype or Google+ Hangouts for team conversations

Step 2. Craft Your Company Hypotheses (use the Lean LaunchLab)

• Write down your 9-business model canvas hypothesis
• List key features/Minimal Viable product plan
• Size the market opportunity. Use Google Trends, Google Insights, and Facebook ads to evaluate the market growth potential. Use Crunchbase to look at competitors.
• Calculate Total Available Market, and customer value.
• Pick market type (existing, new, resegmented)
• Prepare weekly 7-minute class progress summary: business model canvas update + weekly Customer Development summary (described after Step 10.)

• If you can’t easily explain why you exist, none of the subsequent steps matter.  A good format is “We help X do Y by doing Z”.
• Once you have a statement in that format, find a few other people (doesn’t matter if they’re your target market) and ask them if it makes sense.
• If not, give them a longer explanation and ask them to summarize that back to you.  Other people are often better than you at crafting an understandable value proposition.

Step 4: Website Logistics

• Get a domain name for your company. To find an available domain quickly, try Domize or Domainr
• 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

 For coders: set up a web host

• Use virtual private servers (VPS) like Slicehost or Linode (cheapest plans ~$20/month, and you can run multiple apps and websites)
• You can install Apache or Nginx with virtual hosting, and run several sites plus other various tools of your choice (assuming you have the technical skills of course) like a MySQL database
• If you are actually coding a real app, (rather than for class) use a “Platform As A Service” (PAAS) like Heroku, DotCloud or Amazon Web Services if your app development stack fits their offerings
• BTW: You can see the hosting choices of YCombinator startups here

Customer Discovery for the Web

Step 5: Build a Low-Fidelity Web Site

• Depending on your product, this may be as simple as a splash page with: your value proposition, benefits summary, and a call-to-action to learn more, answer a short survey, or pre-order.)
• For surveys and pre-order forms, Wufoo and Google Forms can easily be embedded within your site with minimal coding.

 For non-coders:

• Make a quick prototype in PowerPoint, or
• Use Unbounce, Google Sites, Weebly, Godaddy, WordPress or Yola
• For surveys and pre-order forms, Wufoo and Google Forms can easily be embedded within your site with minimal coding.
• Even non-coders should understand the coding buzzwords see here

For coders: build the User Interface

• Pick a website wireframe prototyping tool, (i.e. JustinMind, Balsamiq)
• 99 Designs is great to get “good enough” graphic design and web design work for very cheap using a contest format. Themeforest has great designs
• Create wireframes and simulate your “Low Fidelity” website
• Create a fake sign up/order form to test customer commitment.  Alternatively, create a “viral” landing page, with LaunchRock  or KickoffLabs
• Embed a slideshow on your site with Slideshare or embed a video/tour using Youtube or Vimeo
• Do user interface testing with Usertesting or Userfy

Step 6: Customer Engagement (drive traffic to your preliminary website)

• Start showing the site to potential customers, testing customer segment and value proposition
• Use Ads, textlinks or Google AdWords, Facebook ads and natural search to drive people to your Minimally Viable web site
• 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.
• Use Mailchimp, Postmark or Google Groups to send out emails and create groups
• Create online surveys with Wufoo or Zoomerang
• Get feedback on your Minimum Viable Product (MVP) features and User Interface

Step 7: Build a more complete solution (Connect the User Interface to code)

• Connect the UI to a web application framework (for example, Node.js, Rubyon Rails, Django, SproutCore, jQuery, Symfony, Sencha, etc.)

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.

• 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:

1. Here’s what we thought (going into the week)
2. Here’s what we found (Customer Discovery during the week)
3. Here’s what we’re going to do (for next week)
4. 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

• Go through the legal steps of setting up a company. U.S. version here.
• Search the US Patent Office (for free) for similar trademarks to yours
• When you confirmed your product and identity, and obtained a good domain name, and a trademark you think you can own, register your company on Twitter, Facebook, LinkedIn, CrunchBase, and AngelList pages
•  Incorporate the company

———

Thanks for the comments, suggestions, corrections, and additions. Updates added.

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-stage Internet 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.

Today you’re invited to benchmark your own internet startup and see how you compare to the winners.

———

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.

Happy birthday Max.

I had them leave with a pie chart.

There must be something in the air. In the last week I had four separate groups through the ranch all wanting to talk either about hiring a senior exec or a senior exec looking for a new job. Having sat through these job discussions as an entrepreneur, board member, and now an interested observer, here’s what I concluded:

1. Decide whether you’re hiring someone to help search for the business model or to help execute a business model you’ve already found (same is true is you’re looking for a job – are you going to be searching or executing?) Are you looking for a visionary or an operating executive?
2. The job spec’s for the same title differ wildly depending on whether the job requires search versus execution skills. Founders search, operating executives execute.

If you’re hiring an operating executive (CEO, VP, Executive Director, etc.)

• Don’t start with the candidate (board member x has a great VP of sales he knows, founder y wants this CEO he met at a conference, etc.)
• Don’t even start with the job spec

Since I’ve always been a visual guy, job specs with their long lists of job requirements always left me cold. My eyes would glaze over at these recruiter/board wish lists. I wished there was a way to see them at a glance. (Just to be clear this isn’t the entire hiring process, just a way to visually begin the discussion.) So here’s my suggestion: Start with a Pie Chart.

1. Draw a pie chart.
2. List all the job specs as slices
3. Adjust the width of the pie segments by importance. (Extra credit if you get the current CEO or internal candidate to help you write/draw the slices and weight their importance. Everyone involved in the hire gets to have an opinion on the slices and weights, but the person/group making the hiring decision gets to decide which ones to include.)
4. Now that you have this spec, evaluate each candidate by showing his/her competence in each slice by length
   
5. Compare candidates
   
6. Easy as pie!

Lessons Learned

• Are you hiring for search or execution skills?
• Show the job requirements visually as a pie chart
• Prioritize each requirement by the width of the pie
• Show your assessment of each candidate’s competencies by the length of the slices
• Now with the data in front of you, the conversation about hiring can start

Thanks to Denis Dovgopoliy for making the Russian version happen.

It joins the French version: Les quatre étapes vers l’épiphanie

and the Japanese version アントレプレナーの教科書 [単行本（ソフトカバー）

Now in Japanese

Pay It Forward
What’s pretty remarkable is these translations are not from a commercial publisher, but rather a labor of entrepreneurial love. All these translations have been crowd-sourced.

Entrepreneurs from Japan, France and now Russia believed they could help startups in their country if the Four Steps to the Epiphany was available in their native tongue. They translated it at their own expense. These are the first three translations and more are underway.

These individuals are “paying it forward” for their communities and country’s. Thousands of entrepreneurs are better for their efforts.

Blame it On Eric
We can blame it all on Eric Ries. When Eric was my student in one of the first Berkeley Customer Development classes, he suggested that I take my class notes, which until then had been printed at Cafepress.com, and offer it widely on Amazon. He said, “I bet there are a few people outside the class who might like to read it.” I photoshopped a cover for my notes, called it the Four Steps to the Epiphany, and bet him he was wrong.  He won the bet.

What A Long Strange Trip It’s Been
I was going to end this post here, but it’s late at night at the ranch and the coyotes are howling in the distance and somewhere closer, out in the redwoods, there’s a barn owl hooting in the trees.

Seeing this book in Russian for me is more than just another translation.

As a child, my mother fled the Soviet Union smuggled out in a hay cart in the middle of Russian Civil war. Until she died, she reminded me that on the way to Ellis Island, her first view of the United States was the Statue of Liberty in New York harbor - and she never looked back. (As kids we memorized the poem inside the statue.)

When I was growing up the odds were pretty low that the Cold War war would end with a whimper rather than a bang. Both the U.S. and the Soviet Union trained daily to kill hundreds of millions of people. Entrepreneurship was a crime in the Soviet Union. In the 1970′s the Soviet military was on the ascendency and wasn’t at all clear that the 20th century would end as the American century (or with 15,000 targeted nuclear warheads, anyones century.)

I spent my late teens here and my early 20′s here next to the sharp end of the spear, and this was no videogame. (There’s equal part irony and satisfaction that Silicon Valley and semiconductor fabs had a role in the demise of the Soviet Union.)

When the Cold War ended I waited for the victory parade down Main Street.

We never did have a parade, but as a consolation prize there’s now a McDonalds in Red Square, entrepreneurship is trying to blossom in a place that had 60 U.S. nuclear weapons aimed at it, my book (a revolutionary manual for capitalism,) is in Russian, and I’ve been asked to give my Secret History of Silicon Valley talk when I visit Moscow for the first time in September.

Good enough.

One of the key distinctions between an entrepreneur and an operating executive is an entrepreneur’s almost seamless agility in the face of changing circumstances versus an operating executive’s intense execution focus on a plan. World-class entrepreneurs learn how to combine both.

WTF?
Driving home over the mountains from a Coastal Commission hearing, I had time to ponder an email I received from a city official as the road wound through the Redwood trees. The Coastal Commission had found that a zoning change his city requested didn’t conform to the Coastal Act, and we denied it. I felt sorry for him because he had put together a project that depended upon the property owner, developer, unions, hotel operator, local neighbors, city council, weather, wind speed, phase of the moon and astrological sign all aligning just to get the project in front of us. It was like herding cats and pushing water uphill. Reading his email I was sympathetic realizing that if you substituted customers, channel, product development, hiring, board of directors, and fund raising, he was describing a typical day at a startup. I felt real kinship until I got to his last sentence:

“Now we’re screwed because we had no Plan B.”

Say what?

I had to read his email a few times to let this sink in. I kept thinking, “What do you mean there’s no plan B?” When I shared it with the other commissioners who were public officials, all of them could see that there could have been tons of alternate plans to get a project approved, and there were still several options going forward.  But the mayor just had been so intently focussed on executing a complex Plan A he never considered that he might need a Plan B.

By the time the mountain road unwound into rolling pastures and then flattened into the farmland just south of Silicon Valley, I realized that this was a real-world example of the difference between an entrepreneur and an operating executive.

There’s Always a Plan B
My formal definition of a startup is a temporary organization in search of a scalable and repeatable business model. Yet if you’ve founded a company you know that regardless of any formal definition, startups are inherently pure chaos. As a founder, keeping your company alive requires you to think creatively and independently because more often than not, conditions on the ground will change so rapidly that any original well-thought-out plan quickly becomes irrelevant. (It’s equally true for startups, war, love and life.)

The reality is that to survive requires a mindset which can quickly separate the crucial from the irrelevant, synthesize the output, and use this intelligence to create islands of order in the all-out chaos of a startup.  

To do this you are instinctually creating and testing multiple hypotheses which are creating an infinite number of possible future plans. And when the inevitable happens and some or all your assumptions were wrong, you pivot your model into the next plan and continue forward.  You do this until you find a scalable and repeatable business model or you die by running out of money.

Great entrepreneurs don’t just have a Plan B, they have Plans B through ∞

Lessons Learned

• A startup is initially about the search for a repeatable and scalable business model
• Most of the time your hypotheses about Plan A, B and C are wrong
• Searching requires agility, tenacity, resilience, curiosity, opportunism and pattern recognition
• Execution requires a different set of skills. At times it means bringing an operating executive
• Operating executives excel at focussed execution
• World-class technology CEO’s learned how to combine Searching and Execution (Gates, Jobs, Ellison, Bezos, Page, et al)

Ok, I get a lot of these. Is this some grad student or post doc who wanted to do some independent study?

The email continued,  ”The problem I’m working on is that many founders are either making uninformed decisions or inefficiently learning the new skills they need. The solution I’m exploring is a just in time learning methodology that accelerates founders’ learning curve by aggregating relevant content, peers and mentors.”

Hmm, now I’m getting intrigued. This sounded like one heck of an interesting guy and it’s a subject I care about. I wondered where he got his MBA from?

The email closed by saying, “The project is a hybrid between academic and entrepreneurial circles and I’d really love to begin a dialogue with people in the academic world also interested in solving this problem. Your name has come up a lot in that regard. Let me know if this interests you and if you have any time to speak.”

It was signed Max Marmer.

I set up a meeting and at Cafe Borrone some kid who looked 18-years old came up to me and introduced himself as Max. “How old are you? I asked. “18,” he replied.

Holy sx!t.

When I asked Max why he was interested in solving entrepreneurial education problems he replied, “I was always interested in big picture trends for where the world is headed. I spent time with organizations like the Institute for the Future and Singularity University. My conjecture became that the world’s biggest problem isn’t poverty or disease or any oft-stated major problem, but that we don’t have enough people engaged in trying to solve these problems. A big piece of the solution lies in the scalable impact of entrepreneurship and an increase of successful entrepreneurs. But potential impact consistently fails to be realized because of self-destruction.”

I don’t think I touched my sandwich. I tried to remember what I was doing at 18 and whatever it was I wasn’t this. Max continued, “That’s why I’m really interested in ways of optimizing the entrepreneurship ecosystem to allow more entrepreneurs to go from idea to reality. To do this requires: a methodology, tools and systematically reducing friction.”

Tune In, Turn On, Drop Out
Max entered Stanford in the fall of 2010 as a freshman, took as many of the engineering entrepreneurship classes as he could and independent study with me. (He was part of the Sandbox network - a group of incredibly smart under 30 year olds.)

Max dropped out of Stanford after his first quarter.

But he left to work on what he told me he came to do - crack the innovation code of Silicon Valley and share it with the rest of the world. He set up Blackbox.vc, a seed accelerator for technology startups (and one of the tour stops for entrepreneurs from around the world.) They went to work gathering deep knowledege of what makes successful Internet startups.

Max and his partners interviewed and analyzed over 650 early-stage Internet startups. Today they released the first Startup Genome Report— a 67 page in-depth analysis on what makes early-stage Internet startups successful.

Startup Genome Report
Some of their key findings:

1. Founders that learn are more successful: Startups that have helpful mentors, track metrics effectively, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth.

2. Startups that pivot once or twice times raise 2.5x more money, have 3.6x better user growth, and are 52% less likely to scale prematurely than startups that pivot more than 2 times or not at all.

3. Many investors invest 2-3x more capital than necessary in startups that haven’t reached problem solution fit yet. They also over-invest in solo founders and founding teams without technical cofounders despite indicators that show that these teams have a much lower probability of success.

4. Investors who provide hands-on help have little or no effect on the company’s operational performance. But the right mentors significantly influence a company’s performance and ability to raise money. (However, this does not mean that investors don’t have a significant effect on valuations and M&A)

5. Solo founders take 3.6x longer to reach scale stage compared to a founding team of 2 and they are 2.3x less likely to pivot.

6. Business-heavy founding teams are 6.2x more likely to successfully scale with sales driven startups than with product centric startups.

7. Technical-heavy founding teams are 3.3x more likely to successfully scale with product-centric startups with no network effects than with product-centric startups that have network effects.

8. Balanced teams with one technical founder and one business founder raise 30% more money, have 2.9x more user growth and are 19% less likely to scale prematurely than technical or business-heavy founding teams.

9. Most successful founders are driven by impact rather than experience or money.

10. Founders overestimate the value of IP before product market fit by 255%. 

11. Startups need 2-3 times longer to validate their market than most founders expect. This underestimation creates the pressure to scale prematurely.

12. Startups that haven’t raised money over-estimate their market size by 100x and often misinterpret their market as new.

13. Premature scaling is the most common reason for startups to perform worse. They tend to lose the battle early on by getting ahead of themselves.

14. B2C vs. B2B is not a meaningful segmentation of Internet startups anymore because the Internet has changed the rules of business. We found 4 different major groups of startups that all have very different behavior regarding customer acquisition, time, product, market and team.

———

I’m not sure I believe every one of the report conclusions – it just covers very early stage web startups, and the methodology is still shaky – but this is a landmark study. I think these guys have gone a long way to turn hypotheses about early-stage Internet startups into facts. And they’re just getting started.

Congratulations.  A+

Download the full Startup Genome report here.

——-

I can’t wait to see what Max does by the time he’s 21.

He had me in for an interview. We covered a wide range of topics.

0:22 – the Entrepreneurial explosion
1:45 – Are we in a Bubble?
3:20  - The Last Bubble
6:30 – Rules for the New Bubble
8:05 – Metrics for Success
10:10 – Total Available Market in the Billions
11:45 – Is this a Really a Bubble – the greater fool theory
13:00 – VC’s – The Pact With the Devil
14:10 – What to Use VC’s $’s for?
15:36 – How to Get Customer Centric – an unnatural act
17:00 – The Secrets to Social Networks – Bowling Alone
17:45 – Who Are the Best Entrepreneurs?
18:45 – Entrepreneurs are Artists
21:39 – What Makes Silicon Valley Special?
22:50 – Risk and Culture in Silicon Valley

The FounderLy team interviewed me and got me to give a better explanation of what I was trying to say in this 2 minute video clip.

If you can’t see the video click here.

Week 4 of the class.
Last week the teams were testing their hypotheses about their Value Proposition (their company’s product or service.) This week they were testing who the customer, user, payer for the product will be (and discovering if they have a multi-sided business model, one with both buyers and sellers.) Many of them had heard the phrase “product/market fit” before, but now they were living it. And for some of the teams the halcyon days of “we’re taking this class so we can just build our great product and get credit for it” had come to a screeching halt. The news from customers was not good.

Let the real learning begin.

The Nine Teams Present
This week, our first team up was PersonalLibraries (the team that had software to help researchers manage, share and reference the thousands of papers in their personal libraries.) Going into the first four weeks their business model hypotheses looked like this:Last week we told them team: 1) see if the market size was really large enough to support a business, and 2) to find that out they were going to have to 
talk to more customers
 outside of Stanford. So during the past week, the team got feedback from >60 researchers from 
cold calls, in-person interviews, and a web survey.  (We were impressed when we found that they did the in-person interviews by hiring usertesting.com for $39 to set up test scenarios, gave the users specific tasks to accomplish with their minimum viable product, videotaped the customer interactions and summarized customer likes and dislikes.) The good news was that customers said that their minimum viable product (easily organizing research papers) was correct. The bad news was that users would play with their product on-line for a while and leave and never return.  Politely it was described as “poor customer retention” but in reality it was because the product was really hard to use.

But it was their market size survey that had the team (and us) even more concerned; last weeks “hot” market of biomed researchers looked like it was only $30m market, and the total available reference manager market was another $80M.The question was, even if they got the product right, were there enough customers to make it a business?

If you can’t see the slides above, click here.

For next week, they decided to improve the product by adding more tutorials, do a 2^nd Customer Survey and begin to create demand for their product with AdWords Value Prop Testing and Landing Page A/B Testing.

The feedback from the teaching team was that customer feedback seems to be saying that this product is a “nice to have” versus “got to have.” Is the lack of excitement the MVP? Users?  Is this a hobby or a business?

Agora Cloud Services
The Agora team started the 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.

They began with a set of questions:

• What are our new hypothesized value propositions?
• Which segments have we identified and which do we want to narrow in on?
• Which value added services do public clouds want to attract customers for?
• Is there a certain segment of buyers that continually makes purchasing decisions (as opposed to only once at the very beginning of a company).
• How can we attract buyers to our channel before they make purchasing decisions?
• Longer-term work/planning: what other experiments should we be constructing
• Sales process: buyer/ user/ influencer etc.?  Demand generation?

The Agora team decided to formalize the customer discovery process by coming up with a set of Customer Discovery principles and questions that were as good as any I’ve seen.

They had 16 interviews with target customers (Zynga, Yahoo, VMware, Walmart,  Zeconder, etc.) as well as channel partners and cloud industry technology consultants.

Agora was in a classic two-sided market (having both buyers and sellers. The Business Model Canvas is a great way to diagram it out. Each side of a market has it’s own Value Proposition, Customer Segment and Revenue Model.) They learned that one their core customer hypothesis about their buyers, “startups would want to buy computing capacity on a “spot market” was wrong. Startups were actually happy with Amazon Web Services. The Agora team was beginning to believe that perhaps their ideal buyers are the companies that have to handle variable and unpredictable workloads.

If you can’t see the slides above, click here.

The Agora team left the week thinking that it was time for a Pivot: find cloud buyers and sellers who need to better predict demand.  Perhaps in market segment: medium-large companies that do 3D modeling and life sciences simulations

The feedback from the teaching team “great Pivot” and very clear Lessons Learned presentation. Keep at it.

(For the teaching team one of the most important ways to track the teams progress was through the weekly blogs we made each team keep. This of this as their on-line diary. They hated doing it, but for us it added a window into their thinking process, allowed us to monitor how much work they were doing, and more importantly let us course correct when needed.

BTW, If I was on the board of a startup with a first time CEO I might even consider asking for this in the first year as they went through Customer Discovery. Yes it takes time, but I bet it’s less than time than you would spend having coffee with an advisor each week.)

D.C. Veritas, was the team building a low cost, residential wind turbine that average homeowners could afford. From a slow start of customer interaction they made major progress in getting out for the building. This week they refined their target market by building a map of potential customers in the U.S. by modeling wind speed, energy costs, homeownership density and green energy incentives. The result was a density map of target customers. They then did face-to-face interviews with 20 customers and got data from 36 more who fit their archetype.  They also interviewed two companies – Solar City and Awea in the adjacent market (residential photovoltaic’s.)

If you can’t see the slide presentation above, click here.

The teaching team offered that unlike solar panels which work anywhere, they’ve narrowed down the geographic areas where their wind turbine was economical. We observed that their total available market was getting smaller daily. After the next week figuring out demand creation costs, they ought to see if the homeowners were still a viable target market for residential wind turbines.

Autonomow, the robot lawn mower, came in with a major Pivot. Instead of a robotic lawn mower, they were now going to focus on robotic weeding and drop mowing as a customer segment. (Once you use the Business Model Canvas to keep score of Customer Discovery a Pivot is easy to define. A Pivot is when you substantively change one or more of the Business Model Canvas boxes.)

Talking to customers convinced the team that the need for robotic weeding was high, there was a larger potential market (organic crop production is doubling every 4 years and accelerating,) and they could make organic produce more affordable (labor cost reduction of 100 to 1) – and could possibly change the organic farming industry!  And as engineers they believed weed versus crop recognition, while hard, was doable.

During the week the team drove the 160 miles round-trip to the Salinas Valley and had on-site interviews with two organic farms. They walked the fields with the farmers, hand-picked weeds with the laborers and got down into the details of the costs of brining in an organic crop.

They also talked by phone to organic farmers in Nebraska and the Santa Cruz mountains.

They acquired quantitative data by going through the 2008 Agricultural Census. Most importantly their model of the customer began to evolve.

If you can’t see the slide above, click here.

Our feedback: could they really build a robot to recognize and weeds and if so how will they kill the weeds without killing the crops?  And are farmers willing to take a risk on untested and radical ideas like robots replacing hand weeding?

The Week 4 Lecture: Customer Relationships
Our lecture this week covered Customer Relationships (a fancy phrase for how will your company create end user demand by getting, keeping and growing customers.) We pointed out that get, keep and grow customers are different for physical versus virtual channels. Then different again for direct and indirect channels. We offered some examples of what a sales funnel looked like. And we described the difference between creating demand for products that solve a problem versus those that fulfill a need.

If you can’t see the slide above, click here.

———

The biggest lesson for the students this week was the entire reason for the class – no business plan survives first contact with customers – as customers don’t behave as per theory. As smart as you are, there’s no way to predict that from inside your classroom, dorm room or cubicle. Some of the teams were coming to grips with it. Others would find reality crashing down harder a bit later.

Next week, each team tests its demand creation hypotheses. The web-based teams needed to have their site up and running and be driving demand to the site with real Search Engine Optimization and Marketing tests.

Over the last decade we assumed that once we found repeatable methodologies (Agile and Customer Development, Business Model Design) to build early stage ventures, entrepreneurship would become a “science,” and anyone could do it.

I’m beginning to suspect this assumption may be wrong.

Where Did We Go Wrong?
It’s not that the tools are wrong, I think the entrepreneurship management stack is correct and has made a major contribution to reducing startup failures. Where I think we have gone wrong is the belief that anyone can use these tools equally well.

Entrepreneurship is an Art not a Job
For the sake of this analogy, think of two types of artists: composers and performers (think music composer versus members of the orchestra, playwright versus actor etc.)

Founders fit the definition of a composer: they see something no one else does. And to help them create it from nothing, they surround themselves with world-class performers. This concept of creating something that few others see – and the reality distortion field necessary to recruit the team to build it – is at the heart of what startup founders do. It is a very different skill than science, engineering, or management.

Entrepreneurial employees are the talented performers who hear the siren song of a founder’s vision. Joining a startup while it is still searching for a business model, they too see the promise of what can be and join the founder to bring the vision to life.

Founders then put in play every skill which makes them unique – tenacity, passion, agility, rapid pivots, curiosity, learning and discovery, improvisation, ability to bring order out of chaos, resilience, leadership, a reality distortion field, and a relentless focus on execution – to lead the relentless process of refining their vision and making it a reality.

Both founders and entrepreneurial employees prefer to build something from the ground up rather than join an existing company. Like jazz musicians or improv actors, they prefer to operate in a chaotic environment with multiple unknowns. They sense the general direction they’re headed in, OK with uncertainty and surprises, using the tools at hand, along with their instinct to achieve their vision. These types of people are rare, unique and crazy. They’re artists.

Tools Do Not Make The Artist
When page-layout programs came out with the Macintosh in 1984, everyone thought it was going to be the end of graphic artists and designers. “Now everyone can do design,” was the mantra. Users quickly learned how hard it was do design well (yes. it is an art) and again hired professionals. The same thing happened with the first bit-mapped word processors. We didn’t get more or better authors. Instead we ended up with poorly written documents that looked like ransom notes. Today’s equivalent is Apple’s “Garageband”. Not everyone who uses composition tools can actually write music that anyone wants to listen to.

“Well If it’s Not the Tools Then it Must Be…”
The argument goes, “Well if it’s not tools then it must be…” But examples from teaching other creative arts are not promising. Music composition has been around since the dawn of civilization yet even today the argument of what “makes” a great composer is still unsettled. Is it the process (the compositional strategies used in the compositional process?) Is it the person (achievement, musical aptitude, informal musical experiences, formal musical experiences, music self-esteem, academic grades, IQ, and gender?)  Is it the environment (parents, teachers, friends, siblings, school, society, or cultural values?) Or is it constant practice (apprenticeship, 10,000 hours of practice?)

It may be we can increase the number of founders and entrepreneurial employees, with better tools, more money, and greater education. But it’s more likely that until we truly understand how to teach creativity, their numbers are limited.

Lessons Learned

• Founders fit the definition of an artist: they see – and create– something that no one else does
• To help them move their vision to reality, they surround themselves with world-class performers
• Founders and entrepreneurial employees prefer operating in a chaotic environment with multiple unknowns
• These type of people are rare, unique and crazy
• Not everyone is an artist

The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. This post is part three. Part one is here, two is here. Syllabus is here.

The Nine Teams Present
This week, our first team up was PersonalLibraries (the team that made software to help researchers manage, share and reference the thousands of papers in their personal libraries.) To test its Value Proposition, the team had face-to-face interviews with 10 current users and non-users from biomedical, neuroscience, psychology and legal fields.

What was cool was they recorded their interviews and posted them as YouTube videos. They did an online survey of 200 existing users (~5% response rate). In addition, they demoed to the paper management research group at the Stanford Intellectual Property Exchange project (a joint project between the Stanford Law School and Computer Science department to help computers understand copyright and create a marketplace for content). They met with their mentors, and refined their messaging pitch by attending a media training workshop one of our mentors held.

If you can’t see the slides above, click here.

In interviewing biomed researchers, they found one unmet need: the ability to cite materials used in experiments. This is necessary so experiments can be accurately reproduced. This was such a pain point, one scientist left a lecture he was attending to find the team and hand them an example of what the citations looked like.

The team left the week excited and wondering – is there an opportunity here to create new value in a citation tool? What if we could help scientists also bulk order supplies for experiments? Could we help manufacturers, as well, to better predict demand for their products, or perhaps to more effectively connect with purchasers?

The feedback from the teaching team was a reminder to see if the users they were talking to constitute a large enough market and had budgets to pay for the software.

Agora Cloud Services
The Agora team (offering a cloud computing “unit” that Agora will buy from multiple cloud vendors and create a marketplace for trading) had 7 face-to-face interviews with target customers, and spoke to a potential channel partner as well as two cloud industry technology consultants.

They learned that their hypothesis that large companies would want to lower IT costs by selling their excess computing capacity on a “spot market” didn’t work in the financial services market because of security concerns.  However sellers in the Telecom industries were interested if there was some type of revenue split from selling their own excess capacity.

On the buyers’ side, their hypothesis that there were buyers who were interested in reduced cloud compute infrastructure cost turned out not to be a high priority for most companies. Finally, their assumption that increased procurement flexibility for buying cloud compute cycles would be important turned out to be just a “nice to have,” not a real pain. Most companies were buying Amazon Web Services and were looking for value-added services that simplified their cloud activities.

If you can’t see the slides above, click here.

The Agora team left the week thinking that the questions going forward were:

• žHow do we get past Amazon as the default cloud computing service provider?
• How viable is the telecom market as a potential seller of computing cycles?
• We need to further validate buyer & seller value propositions
• How do we access the buyers and sellers? What sort of sales structure and salesforce does it require?
• Who is the main buyer(s) and what are their motivations?
• Is a buying guide/matching service a superior value proposition to marketplace?

The feedback from the teaching team was a reminder that at times you may have a product in search of a solution.

D.C. VeritasD.C. Veritas, the team that was going to build a low cost, residential wind turbine that average homeowners could afford, wanted to provide a renewable source of energy at affordable price.  They started to work out what features a minimum viable product their value proposition would have and began to cost out the first version. The Wind Turbine Minimum Viable Product would have a: Functioning turbine, Internet feedback system, energy monitoring system and have easy customer installation.

The initial Bill of Material (BOM) of the Wind Turbine Hardware Costs looked like: Inverter (1000W): $500 (plug and play), Generator (1000W): $50-100, Turbine: ~$200, Output Measurement: ~$25, Wiring: $20 = Total Material Cost: ~$800-$850

The team also went to the whiteboard and attempted a first pass at who the archetypical customer(s) might be.

To get customer feedback the team posted its first energy survey here and received 27 responses. In their first attempt at face-to-face customer interviews to test their value proposition and problem hypothesis (would people be interested in a residential wind turbine), they interviewed 13 people at the local Farmer’s Market.

If you can’t see the slide presentation above, click here.

The teaching team offered that out of 13 people they interviewed only 3 were potential customers. Therefore the amount of hard customer data they had collected was quite low and they were making decisions on a very sparse data set. We suggested (with a (2×4) that were really going to have to step up the customer interactions with a greater sense of urgency.The teaching team offered that out of 13 people they interviewed only 3 were potential customers. Therefore the amount of hard customer data they had collected was quite low and they were making decisions on a very sparse data set. We suggested (with a 2×4) that were really going to have to step up the customer interactions with a greater sense of urgency.

Autonomow
The last team up was Autonomow, the robot lawn mower. They were in the middle of trying to answer the question of  “what problem are they solving?” They were no longer sure whether they were an autonomous mowing company or an agricultural weeding company.

They spoke to 6 people with large mowing needs (golf course, Stanford grounds keeper, etc.) They traveled to the Salinas Valley and Bakersfield and interviewed 6 farmers about weeding crops. What they found is that weeding is a huge problem in organic farming. It was incredibly labor intensive and some fields had to be hand-weeded multiple times per year.

They left the week realizing they had a decision to make – were they a  “Mowing or Weeding” company?

If you can’t see the slide above, click here.

Our feedback: could they really build a robot to recognize and kill weeds in the field?

The Week 3 Lecture: Customers
Our lecture this week covered Customers – what/who are they?  We pointed out the difference between a user, influencer, recommender, decision maker, economic buyer and saboteur. We also described the differences between customers in Business-to-business sales versus business-to-consumer sales.  We talked about multi-sided markets and offered that not only are there multiple customers, but each customer segment has their own value proposition and revenue model.

If you can’t see the slide above, click here.

Getting Out of the Building
Five other teams presented after these four. All of them had figured out the game was outside the building, with some were coming up to speed faster than others. A few of the teams ideas still looked pretty shaky as businesses. But the teaching team held our opinions to ourselves, as we’ve learned that you can’t write off any idea too early. Usually the interesting Pivots happens later. The finish line was a ways off. Time would tell where they would all end up.

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Next week each team test their Customer Segment hypotheses (who are their customers/users/decision makers, etc.) and report the results of face-to-face customer discovery. That will be really interesting.

In it I observed that the barriers to entrepreneurship are not just being removed. In each case they’re being replaced by innovations that are speeding up each step, some by a factor of ten.

My hypotheses is that we’ll look back to this decade as the beginning of our own revolution. We may remember this as the time when scientific discoveries and technological breakthroughs were integrated into the fabric of society faster than they had ever been before. When the speed of how businesses operated changed forever. As the time when we reinvented the American economy and our Gross Domestic Product began to take off and the U.S. and the world reached a level of wealth never seen before.  It may be the dawn of a new era for a new American economy built on entrepreneurship and innovation.

If you can’t see the video above, click here.)

If you’ve seen my other talks, after the first 11 minutes you can skip to ~1:04 with the Sloan versus Durant story and some interesting student Q&A. You can follow the talk along with the slides I used, below.

(If you can’t see the slide presentation above, click here.)