The concept of transformational entrepreneurship describes one of the guiding philosophies of the Startup Genome

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The last five years the global economy has been rife with turmoil. Discussion of bankruptcy, bailouts and unemployment have dominated the headlines. On the surface many of our problems stem from giving the financial sector de facto leadership over the global economy, and enabling them to exploit the system to the brink of societal collapse. On the backs of sacrificial taxpayers the economy appears to be regaining stability, but the rumblings aren’t likely to go away for we are at the crossroads of a momentous transition into the information age. To successfully make this transition, much of the socioeconomic fabric of society needs to be reinvented. But most of the world seems lost when searching for the source of reinvention. Industrial manufacturing has long passed its golden age, armies of creative freelancers are too fleeting to create enduring structural change and returning the reins to the financial sector would again tempt economic disaster. The lack of a viable plan isn’t particularly surprising because the people, process and movement that can lead this societal transition have not yet coalesced.

There are early signs however, that the two movements of Technology Entrepreneurship and Social Entrepreneurship are beginning to converge into a promising solution. An increasing number of entrepreneurs are awakening to the possibility of combining the scalable tools and methodology of Technology Entrepreneurship with the world-centric value system of Social Entrepreneurship. Together they create a new type of entrepreneurship that could become our primary source of socioeconomic value creation. What do we call this movement? We propose we call it "Transformational Entrepreneurship."

The major socioeconomic transition we’re going through needn’t be as tumultuous as its been, but for the last few decades the financial sector has led the economy at breakneck pace into a doomed direction. Economies are based on long-term value creation, but somewhere along way short-term value extractors from the financial sector forced their way atop the economic pantheon. Its supremacy is cancerous for one simple reason: financial products cannot fundamentally create new value, they can only optimize other means of economic value creation.

Financial products are not inherently bad. Their intended purpose is to allocate capital where value can be created to maximize its potential output. But the financial sector was not satisfied in its incredibly lucrative role of financial optimizer. When the sector reached the upper limits of the growth it could create through optimization, insatiable greed propelled the sector to commit some of the most egregious feats of corruption and extortion the world has ever seen.

Exactly how the global economy collapsed is complicated, but the cause is no mystery: exploitative financial institutions on Wall Street. Enough incredibly intelligent young men and women in Generation X lived up to their idol’s famous words that “Greed is good.” Many people in the financial sector seem to behave as if they are playing a game of monopoly, where the securities they trade are not connected to the real world, and other people are merely pawns to be manipulated in pursuit of victory. This disconnect from reality via submission to the ludic fallacy not only creates erroneous models that engender massive overconfidence, it leads to a megalomaniacal worldview devoid of moral principle.

Now all around the country, citizens who are mad as hell and not going to take it any more are storming the streets and camping out in public parks, demanding justice from the economic destroyers on Wall Street and the complicit federal government. But unfortunately reining in the bad guys won’t unleash an economic revival. And pushing naive campaigns like “putting America back to work” won’t solve the crisis either. Economies don’t grow by artificially creating new jobs via governmental legislation, they grow by creating new products and services that create value. Government needs to spend less time talking about job creation and more time working to create the necessary conditions for innovation. The jobs will follow. If a worker no longer has valuable skills, then they need to retrain. Receiving a handout only makes the problem worse.

Industries that were once lucrative are drying up, and jobs that were once stable are vanishing. But growth and prosperity are not disappearing, they are just shifting to new areas of the economy. Since the industrial revolution, the agricultural sector has fed increasingly larger populations with smaller percentages of the workforce. The manufacturing sector went through a similar transition as machinery replaced most manual labor. Now the service sector is poised to do the same as software automates the repetitive intellectual tasks of accountants, clerks, stockbrokers, even doctors and lawyers. When sectors shrink because of the increased efficiency of automation, fear of economic depression is not the right response, for new frontiers of growth are often on the horizon.

Over the last few decades nearly all the economic growth and job growth in the U.S. has come from high-growth technology companies. That growth is driven by companies like Amazon, Google, Salesforce, and VMware (which didn’t even exist 15 years ago), and companies like Facebook, Twitter, Groupon and Zynga (which didn’t even exist 10 years ago). Then of course there’s Apple, which brought itself back from the grave in the beginning of this decade and is now the world's most valuable public company. Collectively these companies have created almost a trillion dollars in new wealth over the last decade and a half.

All of these companies were created by high growth technology entrepreneurs. As the world has finally started to take notice, the inner workings of entrepreneurship ecosystems like Silicon Valley have been raised to mythical proportions. Over the last 40 years Silicon Valley has evolved a complex ecosystem geared specifically toward the development of high-growth, billion-dollar technology companies. The output is awe inspiring, but the company-creation process is not magic, though neither is it well understood. More than 90% of startups fail, primarily because of self-destruction rather than competition. We at the Startup Genome Project are committed to turning the murky art of innovation into a repeatable science that can be spread to the rest of the world. To date we’ve released two critically acclaimed research reports on the factors that determine startup success and their primary cause of failure, and put our research into a software tool that is now a digital mentor for more than 13,000 startups. Human history is littered with arts that caved into science, and the startup creation process will not remain standing.

Silicon Valley now sits at the pinnacle of this socioeconomic transition, endowed with the potential to establish itself as the new center of the world economy and reignite the flame of inexorable progress. Yet in its current incarnation, it is unfit to do so. Silicon Valley has mastered the art of building high-growth technology companies but iit hasn’t yet developed the moral compass to figure out what companies are worth building. There are simply too many talented entrepreneurs today building meaningless ventures. From advertising products that get people to buy things they don’t need, to social games that are designed to addict people to wasting their time, to “mobile-local-social” products that attempt to leverage the latest technological trends without giving much thought to the importance of the problem being solved. Furthermore, the unquenchable thirst for growth that fuels much of the wealth creation must be carefully watched, for it could easily turn malignant and lead technology entrepreneurs to commit the same kind of economic atrocities as the financial sector.

Silicon Valley is like an immature superhero who has just discovered its superpowers, but are using them largely for self-interested aims. Silicon Valley needs to recognize, in the wise words of Spiderman’s Uncle Ben that “these are the years a man changes into the man he is going to become for the rest of his life” and “with great power comes great responsibility.“

The emergence of “Social Entrepreneurship” attempts to fill this moral void by refocusing energy and resources on important social problems. While Social Entrepreneurship is promising, its impact has been limited to date as its solutions are rarely devised with scalability and true economic sustainability in mind. Furthermore, while the Social Entrepreneurship community is full of bright-eyed young people intent on changing the world, many of their solutions fail to take into account the complexities of the problems they are attempting to solve, which can lead to doing more harm than good. This backfiring is far too common because the community’s propensity to descend into self-congratulation, starves the founders of the critical feedback required for them to find the holes in their vision. The standards must be set higher than good intentions.

To successfully make the transition to the new socioeconomic era of the information age, we need to learn to focus the enormous power and efficiency of capitalism on the world’s most important problems. To do so will require figuring out how to unite the scalable tools of Technology Entrepreneurship with the moral ethos of Social Entrepreneurship. This is the essence of what we at the Startup Genome are calling Transformational Entrepreneurship.

Transformational Entrepreneurs earn their name by creating innovative solutions to the world's biggest problems that are scalable, sustainable and systematic.

A Deep Dive Into Transformational Entrepreneurship

To ground this idea, we created a matrix that positions Transformational Entrepreneurship, Technology Entrepreneurship and Social Entrepreneurship on the landscape of socioeconomic value creation.

This graph can be further divided into six categories: Exploitative Entrepreneurship, Small Business, Harmful Non Profits, Ineffective Non Profits, High Growth Entrepreneurship, Social Entrepreneurship, Transformational Non Profits and Transformational Entrepreneurship. In the following section we will discuss what factors determine where a business is placed.

The Y Axis: Economic Impact

The Y axis is relatively straightforward. We measure companies based on the economic value they create, using standard financial metrics like revenue, profit, market cap and ROI. The organizations that have the greatest impact have scalable business models that produce products and services millions of people are willing to pay for. We extend the graph in the negative direction to describe organizations that cannot sustainably support themselves like nonprofits and charities. Nonprofits that create a transformational societal impact like Wikipedia often go deeper into the negative direction of economic impact the bigger they get, because it takes more donation dollars to support their growth. There are scalable revenue generating models that some non profits can access but for the most part they have yet to be explored and developed.

The X Axis: Long Term Societal Impact

Where a business falls along the spectrum of long-term societal impact depends on what it is doing to solve one of the world's biggest problems. There is a subjective element to what one could consider a big problem, but a number of organizations, including The Copenhagen Consensus, Singularity University, The Millennium Project, The UN and The World Economic Forum have done a good job putting structure around the problem space.

The prescriptions from these organizations fall roughly into two categories. Third-world problems that consign billions to poverty and a low quality of life, and first-world problems that if solved could ignite new societal transformations and drive the continued progress of humanity. This is the sustainability / innovation dialectic and both perspectives are necessary for progress. Some people are more drawn to bringing the third world up to the prosperous living standards of the first world, establishing a healthy baseline for our emerging global village. Others want to push the edge of first-world society, extending the story of humanity farther into the realms of possibility.

The Copenhagen Consensus produced the most rigorously evaluated list of grand challenges. They began by convening many of the world's top economists who were tasked with finding the best ways of advancing global welfare in third-world countries. Their final list ranked solutions by their ability to cost effectively improve life in the developing world. It was ordered as follows:

1. Malnutrition & Hunger 2. Subsidies & Trade Barriers 3. Diseases 4. Education 5. Women Empowerment 6. Global Warming 7. Sanitation & Water 8. Conflicts & War 9. Air Pollution, and 10. Terrorism.

The frameworks for analyzing first-world problems were noticeably weaker. Perhaps this is evidence of the complacent malaise that has swept much of the first world. There seems to be a script running through the minds of many that the future has arrived. There are no major innovations on the horizon and society has reached the end of its evolution. #firstworldproblems are trivial ones like the waiter at the restaurant being too slow or being locked out of your house.  All that's left to do is to give the developing world the same quality of life as the developed world. The fact that we refer to the first world with the past tense verb "developed" is further evidence of how embedded this story of stagnation has become in our cultural consciousness.

But this story couldn't be further from the truth. We are just at the cusp of a new societal era. Humanity doesn't see new eras very often, but when they come, every aspect of society yearns for reinvention: Government, Business, Finance, Education, Health, Energy, Technology, Art and Science all need upgrading. The Industrial Revolution was the last great societal transformation, and the scientific enlightenment that ensued gave rise to modernity. With two billion broadband internet users and billions of smartphones entering circulation, the necessary tools and infrastructure are now in place for the information age to burst into full bloom, moving beyond the confines of the technology industry to reinvent all aspects of society.

Defining X Axis of Long Term Societal Impact

Establishing the X axis of long-term societal impact is our call for entrepreneurs and business leaders to turn away from incremental improvements on the status quo and focus on solving problems that will transform the world.

Here are a few guiding principles for where to place a company along the x axis of long-term societal impact and then we will provide a number of examples.

Section 1: Negative Long Term Societal Impact [-5,0]
Persuade people to buy things they don't need or that harm them long term
Exploit people
Waste people's time
Make people or the world unhealthy
Give a false sense of satisfaction or accomplishment

Many companies make a profit while making some of the world's biggest problems worse. They do this by either providing convenient painkillers that hide the problem rather than treating it, or merely shift the problem somewhere else rather than solving it. Examples include McDonalds and Zynga, discussed in more detail in the next section.

Section 2: Marginal Long Term Positive Impact [0,5]
Treat symptoms
Incrementally improve relatively efficient areas
Make people feel better about themselves
Help people make a living
Niche focus

Most businesses fall in this section.

Section 3: Transformational Societal Impact [5,10]
Approach problems systematically, treating root causes
Teach men to fish rather than giving them fish
Focus on unlocking human potential
Create more value than they capture
Seek to empower people
Improve people's relationships, their ability to create and ability to learn
They nurture ecosystems and platforms

“We don’t build services to make money; we make money to build better services” - Mark Zuckerberg in Facebook’s IPO Filing letter.

Examples: Mapping Socioeconomic Value Creation

With the basics of the framework defined, here we put it to use to classify a number of markets, product types and companies on our map of socioeconomic value creation.

An appendix which contains examples for how a number of markets and companies were mapped to this matrix of socioeconomic value creation can be found here. Where a market or company falls is not set in stone, but is in fact a very important debate. This matrix is intended to provide structure for having the conversation about the value we, as a society, are creating and what opportunities we should be directing our attention and energy towards. 

The Startup Genome As A Transformational Company
I would be remiss not to include a personal story describing the transformational philosophy guiding the direction of the Startup Genome, the company I founded last year with Bjoern Herrmann and Ertan Dogrultan. A few years ago when I was immersed in the futurist community, I learned about Moore's Law and the more expansive accelerating pace of technological change. The implications for the future of society were immense and I was struck with an impulse to find a way to contribute to the revolution on the horizon. My search process led me to conclude that one of the biggest leverage points for socioeconomic evolution would be to find a way to increase the success rate of startups. Startups are the primary carrier and distributor of technological innovation but 90% of them are failing, mostly due to self-destruction rather than competition. We set out to find a scalable solution to this problem and arrived at the Startup Genome. We conducted research with leading thinkers in the field on the primary causes of startup failure and released our findings to the world. This research formed the basis for intelligent technology tools that will enable businesses small and large to be more innovative and scale faster to success. We believe this can accelerate the pace of innovation all around the world, and together with a new generation of transformational entrepreneurs, unleash a socioeconomic revolution.

Conclusion

The opportunity to reinvent society is within our power, but the future doesn't invent itself. We must create a culture that encourages and empowers transformational entrepreneurs and celebrates little else. Anything less is selling short ourselves, our ancestors, and the future of the human race. That may feel like hyperbole, but the latent socioeconomic revolution that now lurches beneath the surface has only arisen four other times in human history. Revolutions are dangerous transition periods that can cause a societal slide into turmoil just as easily as a rise into transformation. It's up to transformational entrepreneurs to rise to the occasion of the present moment.

We encourage everyone to look within themselves and around their environment and seek out opportunities for transformational change. Ask the entrepreneurs you know how the company they are starting is transformational. Ask students and job seekers what transformational problem they want to solve. Ask everyone else what transformational ideas, projects and companies they are excited about. Get people talking, reading, writing, researching and creating in the spirit of transformation -- because it is our best hope for reviving socioeconomic progress.

Further Exploration: Transformational Thinkers And Entrepreneurs

The Founders Fund Manifesto
Long Shots, Vinod Khosla
Why Software is Eating the World, Marc Andressen
Innovation: Crucial to Our Future, Judy Estrin
What's Better: Saving the World or Building Another Facebook App?, Vivek Whadwa
Do Great Things, Justin Rosenstein
The End of the Future, Peter Thiel
The Failed Promise of Innovation in the U.S, Michael Mandel

A special hat tip to Tyler Emerson for compiling this list and many great discussions over the last year on this subject. Tyler is the founder of Belong, an upcoming initiative that aims to facilitate, inform and honor the people investing in the long-term potential of humanity.

 

Last week we put out a mini report on Startup Ecosystems, where our main focus was on the comparison of Silicon Valley, New York City and London. Along with this mini report we also put out a ranked list of startup ecosystems, but we noticed that many people interpreted this ranking to be based on much more than it was, so we want to clarify what it was based on.

The list we put on the top 25 startup ecosystems was simply ranked based on the “average throughput” or the total activity in the Startup Genome dataset. Given the Startup Genome has one of the largest datasets on entrepreneurial activity worldwide, with over 16,500 startups in total, we thought analyzing the data by location could create more transparency for the many entrepreneurial ecosystems emerging worldwide.

However to be clear, this list should not, and wasn’t intended to be used to determine which ecosystem is best. Activity is simply one factor to determine the quality of an ecosystem. Additionally, although our dataset is large, it is not completely random, as there is some selection bias based on language, where we received the most press, and our focus on Internet startups.
Some have also noted, the places where our dataset doesn’t correlate with datasets that measure the size and quantity of VC deals in various geographic regions. It seems a large part of this discrepancy comes from the fact that although we have thousands of companies that have raised funding, many startups don’t. This early stage focus slants our perspective in a direction there’s been little insight into, as there is little public data about this cohort of pre-VC companies.

But what we can see is that there is a clear demand for a more detailed ecosystem ranking.
In the coming months we plan on creating a robust ranking system based on a diversity of performance indices, supplemented with additional data sets, to better capture the strengths and weaknesses of different startup ecosystems. Currently, we only have a large enough sample to do a detailed performance analysis on a small set of the top 25 ecosystems. This is why we haven’t put out this kind of ranking system yet. But since the release of the report last week we’ve had dozens of people and organizations from ecosystems around the world offering their help and support to help us cross that threshold.

For the last 50 years the technology startup scene was dominated by Silicon Valley and a handful of smaller ecosystems. Only in the past few years have new startup ecosystems started to spring up all over the world. We’re excited to be a part of helping these startup ecosystems figure out what they need to do to flourish.

Let us know in the comments or over email at feedback@startupcompass.co what factors you think are an important measure of ecosystem health.

And here’s an interview Bjoern did with Silicon Allee on a similar topic.

(The original post can be found here on Techcrunch)

Falling startup costs have caused an explosion in the number of software companies being started. As a result, new startup ecosystems are springing up all over the world to support the success of these companies and jumpstart regional economic growth. Since startups are one of the biggest drivers of job growth and economic growth, this is a big democratizing force. Previously, most startups were located near Venture Capitalists in Silicon Valley, Boston and New York City, because as Paul Graham noted “when starting a startup was expensive, you had to get the permission of investors to do it.” Now companies are being started everywhere. 

Entrepreneur magazine claimed “the overarching theme of SXSW this year was that you don’t need to be in Silicon Valley to do a startup.” With so many options, how do entrepreneurs decide where to start their company? What are the advantages and disadvantages of different ecosystems? And what are the characteristics that differentiate entrepreneurs across ecosystems?

There has been plenty of qualitative reporting about benefits of different startup ecosystems, but to date there’s been very little data to support these intuitions.

One year ago, we started the Startup Genome Project to crack the innovation code and increase the success rate of startups. In September, we launched the Startup Compass, and have had more than 13,000 companies use this simple benchmarking tool to evaluate their performance, align their team and better allocate their product development and customer acquisition resources. As a result, we have now crossed the threshold of critical mass of data in the world’s top startup ecosystems to begin comparing them to each other. For the first time we now have the opportunity to create a Startup Ecosystem Index with a live pulse on how the world’s startup ecosystems are evolving. 

As we’ve started to dig into the data we have begun to uncover valuable insights into the strengths and weaknesses of different startup ecosystems. As this study study progresses we hope it will yield insights for entrepreneurs deciding where to start their company, investors deciding where to allocate their capital, large companies looking for acquisition targets and policy makers who want to make their startup ecosystems flourish. The world is in need of economic revival and unleashing a Entrepreneurial Renaissance is our best hope. 

Currently, the three most popular ecosystems worldwide are Silicon Valley, New York City and London. And today, we are releasing 22 insights on how they compare.

Defining Characteristics of Each Ecosystem:

Silicon Valley: Biggest throughput. Strong early stage funding ecosystem. More mentors. Most Ambitious. High Risk. 

New York City: Diverse. Niche Focus. Marketplace and Social Network focus. High risk.

London: Well educated. Bet big on perceived proven winners. Project Management / E-Commerce Focus. Low Risk.

1. Startup Throughput: The Silicon Valley startup ecosystem is 3x bigger than New York City, 4.5x bigger than London, 12.5x bigger than Berlin, and 38x bigger than Boulder.
2. Startup Success Rate: The Silicon Valley ecosystem has proportionally 22% more companies that make it to the scale stage than in NYC and 54% more than in London.
3. Availability of Capital: On average Silicon Valley startups raise 2-3x more money in the first 3 stages of development: Discovery, Validation, and Efficiency. But in the scale stage, compared to Silicon Valley, New York City startups raise 27% more money and London startups raise 30% more money.
4. Job Creation: In the Efficiency and Scale stages, Silicon Valley startups create 11% more jobs than NYC startups and 38% more jobs than London startups.
5. Risk Profile: The number of high risk companies decreases steadily through the startup lifecycle, except in New York City where the number of high risk companies spikes from 45% to 67%, and has 4x more high risk companies in the scale stage than Silicon Valley.
6. Product Types: Compared to New York entrepreneurs Silicon Valley entrepreneurs are 2x more likely to build games, 50% less likely to build marketplaces, 23% more likely to build social networks, 3.5x more likely to build infrastructure and 2.5x less likely to build financial tools. Compared to entrepreneurs in Silicon Valley, London entrepreneurs are 50% more likely to build e-commerce products, 35% less likely to build social products, 3.5x less likely to build products based on user-generated content and 2x more likely to build project management software.
7. Market Type: Silicon Valley entrepreneurs are 13% more likely to tackle new markets than London entrepreneurs whereas London entrepreneurs are 21% more likely than entrepreneurs in Silicon Valley to tackle existing markets with better products. New York entrepreneurs have the highest proportion of companies trying to resegment existing markets with niche products. They are 30% more likely to build something niche than entrepreneurs in London.
8. Market Size: Entrepreneurs in Silicon Valley are much more “ambitious” than entrepreneurs in New York City and London. Silicon Valley entrepreneurs are 22% more likely to estimate their market size as greater than 10 billion compared to New York City entrepreneurs and 120% more likely than entrepreneurs in London. They are also almost 2x less likely to estimate their market size to be less than 100 million.
9. Revenue Streams: Subscription is the most popular revenue stream everywhere. Compared to London, Silicon Valley entrepreneurs are 4.4x more likely for their primary revenue stream to be Lead Generation, 3.6x more likely for it to be virtual goods and 2.6x less likely for it to be the rapidly fading model of license fees.
10. Perceived Competitive Advantage: Compared to Silicon Valley Entrepreneurs, New York City entrepreneurs are 4.3x more likely to consider content their primary competitive advantage, 40% more likely for it to be niche focus, and 90% less likely for it to be team. Compared to Silicon Valley entrepreneurs London entrepreneurs are 58% more likely to consider technology their primary competitive advantage and 5.3 less likely to consider user experience to be.
11. Product Development: London and NYC companies outsource 34% more of their product development than Silicon Valley companies.
12. Adaptability: Pivoting happens much more frequently in Silicon Valley. Pivots happen 45% more on average in Silicon Valley than New York City and 33% more than London.
13. Mentorship: The Silicon Valley and New York City ecosystems have more helpful mentors than the London ecosystem. Silicon Valley companies have 46% more helpful mentors than companies in London.
14. Thought Leaders: In Silicon Valley, Steve Blank and Paul Graham are the most popular startup experts. In London, Paul Graham is by far the most popular expert and NYC shows their local pride, voting Fred Wilson as their favorite startup expert.
15. Work Ethic: Companies in Silicon Valley work 35% more than companies in New York City. In Silicon Valley teams work 9.5 hours a day on average vs. 8 hours in London and 7 in New York City.
16. Founding Team Composition: Silicon Valley founding teams are 34% more likely to be technical heavy than founding teams from NYC. Whereas NYC founding teams are almost 2x as likely to be business heavy than Silicon Valley founding teams.
17. Founder Education Background: In London most founders have a masters degree, whereas in Silicon Valley and NYC most founders have just an undergraduate degree. But NYC has 2.2x more founders with PhDs than Silicon Valley.
18. Founder Gender: New York City has almost double the female founders of Silicon Valley and London (80-20 vs 90/10 ratios, respectively).
19. Founder Age: The average age of founders in all three ecosystems is about the same, with an aggregate average of 33.5.  
20. Founder Experience: Silicon Valley founders have on average started almost twice as many startups as founders from NYC and London.
21. Founder Motivation: Silicon Valley has 30% more founders that want to change the world than London or New York. New York has 50% more founders that want to make a good living than Silicon Valley or London. London has 2x more founders that want to make a quick flip than Silicon Valley or New York.
22. Founder Challenges: New York City startups are 3.7x less likely for team building to be their biggest challenge, at the same time they are almost 2x as likely to consider “having too much do and being over capacity” their biggest challenge.

These insights are part of a new Startup Genome research initiative on Startup Ecosystems, in which we will be releasing regular mini reports on new startup ecosystems as we receive a critical mass of data. We've brought on two brilliant researchers to work on this project: Danny Holtschke from Maastricht University and Jessica Richman from Oxford University.  

Here is a list, in ranked order by average throughput, of what we’ve found to be the 25 most active startup ecosystems around the world.

1. Silicon Valley (San Francisco, Palo Alto, San Jose, Oakland)
2. New York City
3. London
4. Toronto
5. Tel Aviv
6. Los Angeles
7. Singapore
8. Sao Paulo
9. Bangalore
10. Moscow
11. Paris
12. Santiago
13. Seattle
14. Madrid
15. Chicago
16. Vancouver
17. Berlin
18. Boston
19. Austin
20. Mumbai
21. Sydney
22. Melbourne
23. Warsaw
24. Washington D.C.
25. Montreal

To reach the critical mass needed to analyze these burgeoning ecosystems, we are partnering with local media outlets who can help us get enough entrepreneurs in their area to sign up for the Startup Compass and contribute to the Startup Genome. In exchange we are offering them exclusive early access to data they can share with their ecosystem. 

We have a number of great supporters already including Endeavor, Mamstartup in Warsaw,Startupi in Sao Paulo, SGentrepreneurs in Singapore, and Startup America & Microsoft BizSpark in other cities around the world.

We'd love to find local support for each of these ecosystems. If you are interested or have any suggestions please contact us at contact@startupcompass.co

There is so much more we'd like to do with this project but we are a start-up ourselves and our resources are limited, so we are also opening up the opportunity for a few sponsors to underwrite some of research and development costs of the Startup Ecosystem Index in exchange for appearing on the reports. To date our research reports have been downloaded more than 25,000 times and have been covered in over 100+ blogs and publications in more than 15 languages. We'd love to have a vision aligned company help us create even more impact. If you are interested or have any suggestions please send us an email at contact@startupcompass.co

We hope you are as excited as we are about the potential of this project to further democratize entrepreneurship around the world. And if you run a software company, do check out the Startup Compass. In addition to helping you make better decisions, you will be contributing to generating insights that can allow startup ecosystems everywhere to flourish.

If you would like receive the full Startup Genome Ecosystem report once it’s released you can sign up here.

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Finally, we'd like to share what a few friends in Silicon Valley, New York City and London had to say about their startup ecosystem: 

"People in Silicon Valley really believe in "pay it forward". It's not all transactional and tit-for-tat. Folks help each other and those not as far along as them. It's also very accepting of failure; if you have some real catastrophes on your resume, that's considered a badge of honor - there are not a lot of places on the planet that's true. It's also the easiest place in the world to start a company. Everyone is here to help you kick ass. :) "

- David Weekly, Founder of PBworks

I moved my first company, Tickle.com, from Boston to San Francisco in 2000.  As a Boston-area native, I feel like most people from back east are highly protective of their ideas. I was amazed to find people in Silicon Valley to be openly sharing ideas, even if another entrepreneur may steal it. It took me several years to really get it.  Silicon Valley is full of great ideas, but ideas are cheap... and execution is the hard part. If you think you have a great unique idea, I'd bet 5 other people in Silicon Valley already thought of it.  It's because we share ideas, we riff off each other and sometime great companies are born.  But the key to taking a new born idea to an IPO is the ability to execute. Silicon Valley has the best combination of factors to provide for that success including the highest concentration of VC's, highest density of tech entrepreneurs and engineers, great schools pumping out more smart grads every year, countless hugely successful VC-backed world-changing companies, pride in a merit-based system that rewards intelligence and hard work and above all... an attitude that supports collaboration to build incredible things.  It's extremely hard to replicate all of that in another location, especially the belief that we, in Silicon Valley, can change the world through innovation.

- Rick Marini, Founder of Branchout

The diversity and multicultural nature of the London startup ecosystem both in terms of startup founders and those working in startups makes London a vibrant and exciting place to be. My own startup Enternships.com is comprised of people of various nationalities including American, Iraniana, Romanian, Indian, Chinese as well as British, which enables us to share insights from different parts of the world whilst working towards a common vision.

London also provides a great base to access global markets - with Europe on your doorstep and strong global communications links and a relatively smaller pool of people (compared to Silicon Valley) working on similar issues you have a better chance of standing out, being recognised and ability to access emerging economies. 

- Rajeeb Dey, Founder of Enternships

The beauty of the London startup ecosystem is that all parts of the startup value chain are worldclass: Universities and research institutions as an innovation engine, successful entrepreneurs and angel investors act as mentors, a financing ecosystem that ranges from early to late stage, creative input and thinking from all of the arts, tech companies and large industry, and finally some of the world’s leading media companies. There are few places in the world that can claim this combination of assets to be natural, and while there are still lots to work on, the breadth of startups in London is a testament to these origins. 

- Philipp Moehring, Associate at Seedcamp

BraveNewTalent currently has it's HQ in London but also has an office in Silicon Valley and Bangalore. There is a cluster of tech talent in all three locations. We chose to locate our development team in London so we could compete better for the 50X engineers than we could in the Valley. 

In London there is a fantastic network of peers among the other tech Founders. I find the community hugely helpful. 

- Lucian Tarnowski, Founder of Brave New Talent

People always speak about Europeans being less risk friendly due to cultural reasons. I believe this is too superficial. Entrepreneurs are less risk friendly because the market favors this behaviour. In Europe you have the same downside as a startup in the US but in case things go right you will face a slower and thus smaller upside than you do in the US. Europe is fragmented into countries with their own markets, cultural behaviours, media and language. This slows things down to the extent that startups have to treat countries with populations of only 8 million with their own market entry strategies. This fundamental difference in the system creates market dynamics that favor behaviour that seeks to limit downsides (e.g. skipping product/market search aka cloning).

The only way out of this is to think global and act global from day one. In Europe, London may be the only place that provides that kind of international uplink . But London is more than that. London's strength is that it is more than "just" a web-tech startup hub. It is one of the most important cities in dozens of industries: finance, media, advertising and fashion to name a few. This creates an environment that's very special and unique in London. 

- Andreas Klinger, Founder of Lookk

I believe NYC is the most diverse ecosystem of all these three cities. It has a quickly growing startup community, the access to capital and the talent pool, but at the same time it is also the home of big media, of style, of finance. Above all, NYC is very supportive of entrepreneurial initiatives and ideas.  

It wasn't a strategic decision, but all three co-founders ended up in NYC. We have been considering to move the company to SFO, but believe that because our company is at the intersection of sustainability, e-commerce and design, it makes more sense to be in NYC. Plus, we just love it here ;-)

- Fabian Pfortmueller, Founder of Holstee

NYC has key assets for the founder with vision beyond the start-up realm to leverage:

- culture (arts & multi-cultural population)

- commerce (multiple global industries) 

- connectivity (midway west coast, europe/middle east/africa, midway from Boston to DC, schools & government)

It may have been the case thus far that entrepreneurs have been overshadowed by Wall Street, but as the Mayor has indicated, Silicon Alley is strategically & geographically well positioned for more startup capital & resources.

- Neil Anderson, Partner at Hubitat

 

The Startup Genome was born last February and today at the anniversary mark we’d like to take the time recognize its growth and accomplishments in its first year of existence.

Over the last few years technology entrepreneurship has exploded around the globe and has come to be recognized as the primary engine of new job creation and a leading driver for economic growth. At the same time, more than 90% of startups fail, primarily due to self-destruction rather than competition. This struck us as an enormous lost opportunity for personal and societal value creation, so we initiated the Startup Genome Project to crack the code of innovation and enable businesses all over the world to be more successful. In February 2011, we announced the Startup Genome Project and shared our first call to action: contribute data to the Startup Genome Project and help us bring the magic of Silicon Valley to the rest of the world.

Several months earlier Max was doing independent research at Stanford with adjunct professor and retired serial entrepreneur Steve Blank. Under his guidance he designed a lifecycle model that synthesized Steve’s insights with other entrepreneurship thought leaders that included Alex Osterwalder, Janice Fraser, Eric Ries, Sean Ellis, Dave Mcclure and Geoffrey Moore.
After Bjoern and I tested the model hands on with 50 startups, we built a survey and asked the greater startup community to contribute data to the project so we could take the Startup Genome to the next level. To our excitement more than 650 startups participated.

Three months later, at the end of May, we released the findings from research in the first Startup Genome Report: a new framework for understanding the success and failure of startups. The response was overwhelming: 50,000 unique visitors, 100+ publications in more than 15 languages, including Huffington Post, CNet, GigaOm CNN Money, more than 10,000 downloads of the report, 3,200 new survey responses and hundreds of emails from entrepreneurs all around the world thanking for us our work. Central to our success was the addition of Ron Berman to the Startup Genome team, a 3rd year PhD at UC Berkeley doing quantitative marketing research.

In the summer we were ready to take the Startup Genome to the next level. The Startup Genome Report generated a lot of attention and acclaim, and got us a lot more data, but we needed to take the big step of building our first software product. The only challenge was we still hadn’t found someone who could lead the Artificial Intelligence part of the product we envisioned. We met with a few dozen potential candidates, many of whom were our friends, but circumstances or interest level never aligned. In the midst of the search, Bjoern and I continued to make progress. I continued to refine the Startup Genome as a predictive model, Bjoern worked on the design and front end for the application and we both did a lot of customer development.

Then we caught two amazing breaks. Radu Spineanu, a serial entrepreneur, amazing engineer and friend of Bjoern’s from Romania came to stay at our startup house, Blackbox Mansion and in his spare time helped us build the architecture for our prototype. The other big break started to unfold a week before Radu arrived. Ertan Dogrultan, who recently dropped out of his Machine Learning PHD from UCLA to move out to the Bay Area and pursue building a startup in the datamining space. Before he graduated he had done a data mining project that used Crunchbase data to try to predict startup success. His professor saw the Startup Genome Report when we launched it in May and he encouraged Ertan to reach out to us. The three of us met, liked each other right away, and Ertan started working with us part time during the summer, helping us to translate the whole Startup Genome data model from linear formulas to much more robust bayesian classifiers.

We launched the Startup Genome Compass in combination with a new report on Premature Scaling on August 29th and it was another homerun. We received coverage all across the web including TechCrunch, Forbes, and PBS, reached more than 25,000 downloads of our reports, the research was recognized by various top Universities & found its way into the curriculum of 50+ Universities and had 13,000 companies use the product over the next few months. Shortly after, Ertan joined full time and the founding team solidified the dream combination of bottom up data mining (Ertan), top down conceptual modeling (Max) and product vision (Bjoern). 

In the last few months we have turned our attention to the future. While our communication with you all has primarily been as a research endeavor, it has been our intention all along to build a software company. Harnessing the massive leverage of information technology for societal impact is a core tenet the Startup Genome Project and we would be short sided not to utilize that leverage ourselves.

The research conducted so far was merely the necessary foundational work to build the increasingly intelligent business software tools of the future. In recent years, large companies like Google, Amazon and Zynga have leveraged predictive analytics technology to run circles around their competitors. Predictive Analytics haven’t been accessible to small companies because they require large datasets, expensive data warehouses and custom models built by specialists. We are looking to change that by building the next layer of the software as a service stack, what our friend Evangelous Simoudis at Trident Capital calls Insight as a Service. We will share more details as the vision becomes reality. Meanwhile we will have new writing, research and tools coming out next month in March. Stay tuned. We look forward to continuing to share this journey with you of empowering business all over the world.

Guest post by Pemo Theodore, EZebis

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A great many small businesses are run by women, about 50% in the US. So why are there less technology startups led by women? It could be that women have to make adjustments to adapt to the greater demands of the lifestyle of a high growth technology entrepreneur. Women have been proven to be good credit risks and are a major force now in in the upper management in the Fortune 500, so perhaps tech entrepreneurship is just one more area where women will soon prove their equal competency to men. There could be a new focus on the strengths of women in business to counteract old erroneous images in the culture and to encourage more women to become high growth technology entrepreneurs. In the startup world there is a certain stereotype of the type of founder that investors love to fund: young, white, male and geeky. Female entrepreneurs need to challenge this stereotype by showing that they possess alternative approaches to solving problems that can make for great startups and disrupt industries in new ways.

A lot of feminine strengths may not match up to historical and portraits of successful entrepreneurs.  This could mean that some women may need to learn skills and shore up certain qualities to be a good fit.  Many spoke about the need for great female entrepreneurial role models and mentoring of women both by men and women, which includes peer mentoring as well.  Women entrepreneurs may also need to learn about the venture and angel industry and to identify the best investors to whom they should pitch their startup.  There are now many women friendly investors, many of whom I interviewed.  It is helpful for women entrepreneurs to grow their networks and to get to know investors before stepping up to the plate to raise investment capital.  This can help a female entrepreneur’s general confidence and help her identify the best avenues for her to target.  Here are some interesting stats on women who raise venture from a 2007 survey by British Researcher Library House:

Female Venture Capitalists 

Consumer internet already has a number of successful women and this may be an area that women feel comfortable leveraging their strengths to create successful startups.  If women can learn to better leverage their strengths: networking, forming fabulous teams and advisory boards, and managing their businesses with resourcefulness and creativity, they could become very proficient at playing the startup game. 

In February, 2011, we started a very ambitious project to crack the innovation code of Silicon Valley and increase the success rate of startups all over the world.

Two weeks ago we launched the Startup Genome Compass, a benchmarking tool for startups and our new research on the primary cause of failure for startups. The response was overwhelming. More than 8,500 high-tech startups started using the application and our research reports have been downloaded more than 25,000 times. Now it can be found all over the Web in blog posts, infographics, and in over 15 languages. It has been extremely humbling for us to be able to touch the lives of thousands of entrepreneurs living around the globe. 

In the last six months the Startup Genome Project has collected a tremendous amount of data on startups, built a theoretical model based on synthesizing ideas from entrepreneurship's eminent thought leaders and taken big strides towards demystifying the process of entrepreneurship and innovation. 

The basis of our theoretical model is looking at a startup as a product centric organism that interacts with its environment, the market. The core dimensions that define this organism are customer, product, team, business model and financials. The key challenge for a startup is to keep those five dimensions in sync with the actual customer response. An example for getting out of sync would be moving too quickly on the product dimension. The result would be an over-engineered product that is less likely to be adopted. 

In order to group and benchmark startups, we segment them by type and stage. Different types of startups are differentiated by the complexity of their customer interaction and customer acquisition. Stages are described by the life cycle through which a startup evolves on its path to becoming a large company. Each stage has a different set of goals and key activities. For example, in the first stage, Discovery, the startup performs a mostly qualitative search process, where the exit criteria are problem/solution fit. In the next stage, Validation, the startup performs more quantitative testing with a working software prototype. (More details about our methodology can be found here.)

Since we've been working on the Startup Genome Project, numerous Fortune 100 executives have reached out to us, wondering if our tools and research could also be applicable for their work. While our original focus was on startups, we've discovered that our methodology extends beyond just measuring the progress of startups to being able to measure the progress of a diverse array of innovation projects. Much of the theoretical groundwork for this leap of insight was laid by Clayton Christenson and Steve Blank.

Clayton Christenson made the important distinction that disruptive innovation was fundamentally a different activity from sustaining innovation, requiring different rules, different managerial tactics, and different types of people. Steve Blank then connected the emerging science of entrepreneurship to the disruptive innovation occurring in large companies by noticing that the ideal organizational structure for disruptive innovation was a startup. The problem is despite the emerging science of entrepreneurship, innovation is still perceived as somewhat of a dark art. Bill Gates, Steve Jobs and Marc Benioff appear to have performed innovative feats capable only by the super-human, because it's very difficult to describe how they were able to disrupt enormous markets with seemingly unbeatable foes.

But now the Startup Genome can begin to uncover what makes these innovation projects succeed or fail and can offer a new paradigm for the management and accounting of innovation.

Here are a few relevant findings from our research, and three use cases where our tools and research can help.

Selected Research findings

1. Most successful startups pivot at least once. Startups that pivot once or twice raise 2.5x more money, have 3.6x better user growth, and are 52 percent less likely to scale prematurely than startups that pivot more than two times or not at all. A pivot is when a startup decides to change a major part of its business.

   Large companies tend to inhibit pivoting for their "internal startups."

2. Different type of markets and products require different type of founders and resources. B2C vs. B2B is not a meaningful segmentation anymore because the Internet has changed the dynamics of customer interaction. We found four different major groups of startups that all have very different behavior regarding customer acquisition, time requirements, market risk and team composition.

   Large companies tend to project learnings from their main business on their innovation initiatives, which leads to mistakes.

3. The major reason for failure of startups is premature scaling. About 70 percent of our dataset showed up as premature scaling or inconsistency. One driving factor for inconsistency is too much capital, teams that are too large, bad team compositions, too little testing, etc. - pretty much everything a large company does, anticipating high certainty in their planning. 

   The results:
   

   • No startup that scaled prematurely passed the 100,000 user mark.
   • 93 percent of startups that scale prematurely never break the $100k revenue per month threshold.
   • Startups that scale properly grow about 20 times faster than startups that scale prematurely.
   
   Large companies tend to pressure their "internal startups" to scale prematurely. 

4. Early-stage startups spend most of their time discovering. Consistent startups spend two to four times as much time discovering who their customers are, whereas inconsistent startups are focused on validating that customers want their product. Consistent startups are searching. Inconsistent startups are executing. 

   It's widely believed among startup thought leaders that successful startups succeed because they are good searchers and failed startups achieve failure by efficiently executing the irrelevant. 

   Large companies tend to jump to execution after their initial market research and miss out on two import stages: Discovery and Validation.

5. Startups that monetize too early are more likely to fail. Trying too hard to monetize leads to inconsistency. Ninety-three percent of inconsistent startups make less than 100k a month when scaling the business. While money can be an important validation indicator, stressing it too heavily will lead startups to ignore opportunities and drift towards non-scalable opportunities that are likely to turn into small business or custom consultant shops.

   Large companies tend to focus on revenue instead of the key value proposition they want to provide with a new product or service. The result is typically mediocre value propositions.

 

Use cases 

• We can help large companies assess startups and make decisions on when the right time is to invest.
• We can help large companies assess internal startups in order to make more effective buy or build decisions.
• We can facilitate the integration process after an acquisition by using our framework as an alternative measure of progress and control system.

It is estimated that 70-95 percent of acquisitions fail. A significant percentage is due to the friction that is created by trying to integrate the startup with the large company's financials, HR department, product, market and business model. Most startups when they are acquired are uncertain on many of these dimensions, and forcing them to conform on any one of these dimensions to the large company can stunt their growth and often kill them. 

For example, a parent company may want to use a startup for lead generation that has a lot of users but no business model. As a result, the startup's product deviates from the original value proposition, and this can cause the user base to erode and cause significant vision conflict within the team. 

Our framework can solve some of these ailments by enabling the parent company to measure the stage of the development of the startup and only begin integrating the startup once they've reached a requisite level of maturity and stability.

As competitive pressures continue to increase, innovation will increasingly become the lifeblood of every large company. When innovation stops, a company's days become numbered. The Startup Genome does not provide a serum for infinite living, but we're working on building the tools and infrastructure for healthier living.

(this was also posted on Sandhill.com)

What makes startups succeed or fail? This is a question we are intent on answering. We believe increasing the success rate of startups has the potential to dramatically increase economic growth all around the world. On May 28th, we released our first report at blog.startupcompass.co. On August 29th we released our first benchmark application, the Startup Genome Compass to help startups reduce premature scaling. 

The role of technology startups in our global economy has never been more important. Startups may seem insignificant compared to large multinational companies that have trillions of dollars of wealth sloshing around in public markets, but a recent Kauffman Foundation study found that the majority of job growth in the United States is driven by technology startups.

The power of information technology has been steadily increasing for the last three decades and has recently reached a level of maturity that has started to trigger a reorganization of the global economy. It has never been easier or cheaper to create a startup thanks to infrastructure like open source software, software as a service, cloud hosting, globally ubiquitous payment processing, viral distribution channels, real-time collaboration, on demand logistic services and hyper-targeted advertising.

As a result, the pace of change is speeding up and the implications of this are immense. Billion dollar startups are emerging faster and faster. The quick ascent of startups like Google, LinkedIn, Facebook, Twitter, Zynga and Groupon are harbingers of a major structural economic change on the horizon. The service sector has dominated the global economy for the last few decades but its sun will set. Just as machinery replaced most manual labor, software will replace repetitive intellectual tasks. Turbo Tax eliminated many accountants, Amazon eliminated many retail jobs and E-Trade eliminated the majority of stockbrokers. In the near future jobs that are more complex yet still methodical will also be replaced by software. Creative Commons is reducing the need for lawyers, Khan Academy shows how one good teacher can replace many bad teachers and the profession of doctors will be disrupted by startups like Halcyon Molecular that turn healthcare from emergency care into a preventative self-care. Balancing out that massive decrease in jobs will be what Richard Florida calls the rise of the creative class.

As the waves of disruption come ever faster, the only way for a company to be competitive will be to behave like a startup. In the landmark book the Innovator’s Dilemma, Clayton Christensen found large companies are excellent at sustaining innovation but by and large fail at disruptive innovation. Startups thrive on creating disruptive innovations. Recently, thought leaders in entrepreneurship have come to the conclusion that in order for large companies to be effective at disruptive innovation they need to make structural changes that make them behave nearly identically to startups. 

The increasing economic importance of startups, along with decreased barriers to entry has caused interest in entrepreneurship to explode around the globe. New startup ecosystems are being built up all over the world with the hopes of replicating the success of Silicon Valley. Spearheading this movement are startup accelerators like Seedcamp, Techstars, Opinno, Founders Institute, 500 Startups, and Sandbox, but they are accompanied by hundreds of others. On an individual level, the brightest people worldwide, are increasingly seeing entrepreneurship as the career path of choice. The release of The Social Network has captured the imagination of today’s young people, and catapulted Mark Zuckerberg to the same status as Gordon Gekko in Wall Street almost 25 years ago.

But despite the increasing economic importance of scalable startups, we still don't understand the patterns of successful creation. 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, we just are not very good at creating startups yet.

Eight months ago we launched the Startup Genome Project, with the goal of increasing the success rate of startups and accelerating the pace of innovation around the world by turning entrepreneurship into a science. If successful, it's hard to imagine the type of impact this could have.

Some of the world's biggest transformations occurred when arts were turned into sciences. The scientific revolution in the 16th century triggered the age of enlightenment. The development of scientific management, which peaked in the early 1910’s, made large companies dramatically more efficient and arguably was one of the biggest causes of the explosion of wealth the world saw in the last century.

We believe the effects of cracking the code of innovation by turning entrepreneurship into a science will trigger a new era, that we are calling the Entrepreneurial Enlightenment. In the midst of the largest global depression in almost a century, a revolution in entrepreneurship could propel the world to a level of wealth never seen before by enabling scientific discoveries and technological breakthroughs to be integrated into the fabric of society faster than ever before. Offering hope that we may finally be able to master some of the most pressing challenges, including water, energy, food, health, security, poverty and education.

No revolution is triggered alone. In the quest to make entrepreneurship a science, we are standing on the shoulders of giants. In just the last 2-3 years the number of people extracting and codifying the informal learning of entrepreneurs has hit a point of critical mass. Steve Blank kicked off the move towards a science of entrepreneurship with his seminal book The Four Steps to the Epiphany. In the book, he introduced the concept of Customer Development. A few years later Eric Ries combined Customer Development with Agile Development and Lean Manufacturing principles to create the Lean Startup methodology. Interest in the Lean Startup has morphed into a global movement. Other major contributors to the science of entrepreneurship include Dave Mcclure on Metrics, Sean Ellis on Marketing, Alex Osterwalder on Business Models and Paul Graham with his essays.

Yet despite this huge knowledge base emerging about how startups work, startups have been able to absorb little more than the basic patterns of how to build a startup. Most founders don't know what they should be focusing on and consequently dilute their focus or run in the wrong direction. They are regularly bombarded with advice that seems contradictory, which is often paralyzing. And while startups are now gathering way more qualitative and quantitative feedback than they were just a few years ago, their ability to interpret this data and use it to make better product and business decisions is sorely lacking. The primary cause of these problems is that we lack the necessary structure to synthesize our accumulated knowledge on the nature of startups. We are missing a common language and framework to describe and measure entrepreneurship and innovation.

Three days ago we launched the Startup Genome Compass, a benchmarking tool for startups and our new research on the primary cause of failure for startups: premature scaling.

There's been some confusion about exactly what we mean by premature scaling and we wanted to respond to the feedback we've received and elaborate on the findings from our research. To make it clearer, we need to go a little bit deeper into the theory and methodology.  

Dimension	Examples for inconsistency (= indicators of premature scaling)
Customer	Spending too much on customer acquisition before product/market fit and a repeatable scalable business model Overcompensating missing product/market fit with marketing and press
Product	Building a product without problem/solution fit Investing into scalability of the product before product/market fit Adding “nice to have” features
Team	Hiring too many people too early Hiring specialists before they are critical: CFO’s, Customer Service Reps, Database specialists, etc. Hiring managers (VPs, product managers, etc.) instead of doers Having more than 1 level of hierarchy
Financials	Raising too little money to get thru the valley of death Raising too much money. It isn’t necessarily bad, but usually makes entrepreneurs undisciplined and gives them the freedom to prematurely scale other dimensions. I.e. over-hiring and over-building. Raising too much is also more risky for investors than if they give startups how much they actually needed and waited to see how they progressed.
Business Model	Focusing too much on profit maximization too early Over-planning, executing without regular feedback loop Not adapting business model to a changing market Failing to focus on the business model and finding out that you can’t get costs lower than revenue at scale.