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The Entrepreneurial Enlightenment

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.

A Deep Dive Into The Anatomy Of Premature Scaling [New Infographic]

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.  

Since February we've amassed a dataset of over 3200 high growth technology startups. Our latest research found that the primary cause of failure is premature scaling, an affliction that 70% of startups in our dataset possess.
The difference in performance between startups that scale prematurely and startups that  scale properly is pretty striking. We found that:

 - No startup that scaled prematurely passed the 100,000 user mark.
 - 93% 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.

What Is A Startup?

Definition:

Startups are temporary organizations that are designed to evolve into large companies. They move through 6 stages of development throughout their lifecycle: Discovery, Validation, Efficiency, Scale, Sustain & Conservation. Early stage startups are designed to search for product/market fit under conditions of extreme uncertainty. Late stage startups are designed to search for a repeatable and scalable business model and then scale into large companies designed to execute under conditions of high certainty. 

Every startup has an actual stage and a behavioral stage. Actual stage is measured by customer response to a product. We measure it by looking at metrics like numbers of users, user growth, activation rate, retention rate and revenue. The behavioral stage is made up 5 top level dimensions that the startup can control. The 5 dimensions are Customer, Product, Team, Financials and Business Model. Each dimension, both the actual and the 5 behavioral dimensions are always classified into one of the 6 developmental stages.

A startup is classified as inconsistent when any behavioral dimension is at a stage that is different than the actual stage. When a behavioral dimension is at a stage larger than the actual stage we call this premature scaling. Its lesser known sibling, dysfunctional scaling, occurs when the stage of a behavioral dimenion is smaller than the actual stage.

A clear example of premature scaling would be a web startup that rapidly scales up its team to 30-40 people before it has any customers. In this example, the actual stage of the startup would be in Validation (Stage 2) but the behavioral stage of the team would be in Scale (Stage 4).

Let's go through some more examples and stats for how each dimension can be scaled prematurely.

Customer:
How to scale customer dimension prematurely: Spending too much on customer acquisition before product/ market fit 
Overcompensating missing product/market fit with marketing and press
Spending money in poor performing acquisition channels.
Stats: Inconsistent startups are 2.3 times more likely to spend more than one standard deviation above the average on customer acquisition.
Examples of startups that prematurely scaled on the customer dimension: Color, Webvan, Pets.com

Product:
How to scale product dimension prematurely: Building a product without having validated problem/solution fit, Investing into scalability of the product before product/
market fit,  Adding lots of “nice to have” features
Stats: Inconsistent startups write 3.4 times more lines of code in the discovery phase and 2.25 times more code in efficiency stage. Inconsistent startup outsource 4-5 times as much of their product development than consistent startups.
In discovery phase 60% of inconsistent startups focus on validating a product and 80% of consistent startups focus on discovering a problem space. In the validation phase, where startups should be testing demand for a functional product, inconsistent startups are 2.2 times more likely to be focused on streamlining the product and making their customer acquisition process more efficient than consistent startups. It's widely believed amongst startup thought leaders, that successful startups succeed because they are good searchers and failed startups achieve failure by efficiently executing the irrelevant.
Examples of startups that prematurely scaled the product dimension: Cuil, Webvan, Joost, Google Wave, Slide, 6Apart, most startups that don't find product market fit or "build something nobody wants". 

Team: 
How to scale team dimension prematurely: Hiring too many people too early, Hiring specialists before they are critical: CFO’s, Customer Service Reps, Specialized Network/System Adminstrators or Database specialists, etc., Adopting multilevel management hierarchy, hiring managers (VPs, product managers, etc.) instead of doers, Having more than 1 level of hierarchy,
Stats: The team size of startups that scale prematurely is 3 times bigger than the consistent startups at the same stage. However startups that scale properly end up having a team size that is 38% bigger at the initial scale stage than prematurely scaled startups, and almost surely continue to grow. Startups that scale properly take 76% longer to scale to their team size than startups that scale prematurely.
Examples of startups that prematurely scaled the the fundraising dimension: Webvan, Pets.com, VOX.com. 

Financials:
How to scale fundraising dimension prematurely: Raising too much money, thereby making the startup undisciplined, giving lots of breathing room for other dimensions to scale prematurely, and eliminating exit optionality.
Stats: Before scaling, funded inconsistent startups are on average valued twice as much as consistent startup and raise about three times as much money.
Examples of startups that prematurely scaled the the fundraising dimension: Cuil, Webvan, Color.

Business Model:
How to scale business model prematurely: Focusing too much on profit maximization too early, Over-planning, executing without a 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.
Stats: Inconsistent startups monetize 0.5 to 3 times as many of their customers early on.
Examples of startups that prematurely scaled the business model dimension: Myspace,  Groupon (time shall tell), 6Apart, Lala. 

The focus of this post is on premature scaling, but for context, here are a few example of dysfunctional scaling: Tokbox, Friendster, Orkut, Wesabe, Digg, SixApart, Myspace (on product), and ChatRoulette.

In our research we also found that the following attributes have no influence on whether a company is more likely to scale prematurely: market size, product release cycles, education levels, gender, time that cofounders knew each other, entrepreneurial experience, age, number of products, type of tools to track metrics and location.

Now to further illustrate how we describe startups let's look at an example mapped onto the Startup Lifecycle Canvas.

Below we have an infographic where we plot Color, today's most talked about inconsistent startup, against Rally, a startup we worked closely with while building out the model, that was consistently in the Efficiency stage 2 months ago when they made this announcement. Although now I'm happy to say they're starting to scale. 

To view the infographic in full, scroll to the bottom of the image and select "download full size". If you're having trouble reading the infographic you can download it here.

You can read more about premature scaling in our full report here. And you can also assess your own startup for premature scaling with our tool the Startup Genome Compass, which we released on Monday.

This post doesn't discuss how different types of startups vary thru the developmental stages. That's for another time.

Navigate Your Startup To Success With The Startup Genome Compass

Today we are releasing the first benchmarking application for startups based on the Startup Genome framework. Founders can now assess their type and stage, diagnose themselves for premature scaling and compare themselves to other startups across more than 25 key performance indicators. Try it here.

Entrepreneurs are the consummate explorers of our generation. Every inch of land has been claimed by one of the world's 204 countries but the world of ideas is expanding ever rapidly into the realm of the unknown. The future of the world was forever altered when Christopher Columbus and the Western World discovered The Americas. Today, societal transformations are triggered by the commercialization of new technology. The world of technology startups is our era's Great Frontier. Search Engines, Social Networks and Microblogs were delivered to the massed because brave entrepreneurs ventured into the unknown. But as we've written before, despite the enormous societal and economic importance of startups the failure rate is still at more than 90% primarily because of self-destruction rather than competition.
The reason the self-destruction rate is so high is fairly simple; the tools and knowledge of entrepreneurship are still very primitive.

Three months ago the Startup Genome team released a groundbreaking research report that spread like wildfire through the startup ecosystem, far surpassing our expectations. To date we've had more than 15k downloads, 100k unique visitors, 100+ publications, and entrepreneurs and VC's all over considering it a must read. Honestly, we didn't think content would have such an impact on a startup community that is so characterized by its preference for experiential learning over theory. But it turned out entrepreneurs were hungry for a map to make sense of the territory they'd been exploring. The Startup Genome Report was one of the first detailed maps of the entrepreneurial journey, describing the different types of startups and the stages startups move through as they grow from an idea into a large company generating big profits. Little pieces of the map had been floating around Silicon Valley in the form of war stories from serial entrepreneurs and grizzled investors. But the stories illustrated lessons that lacked a structure to unite them and put them in proper context. The first Startup Genome Report was a big first step towards creating a coherent picture of the territory startups explore.

But in order for entrepreneurs to improve their odds of success they are going to need to change their behavior. While maps are an excellent tool to develop a general intuition of a space, it is difficult to change behavior if you can't orient yourself on the map and receive regular feedback on your movement.


The Startup Genome Compass

Which is why today we are releasing the Startup Genome Compass.

Many startups have trouble figuring out the right priorities to set and measuring their effectiveness once they do, almost always landing in the proverbial grey zone. "Is a 5% increase in retention good? Do I have enough users to declare product/market fit? Is now the right time to step on the gas pedal and scale?" We attempt to help entrepreneurs answer these questions by putting their metrics into the right context.

The Startup Genome Compass is a benchmarking tool for entrepreneurs to reduce this grey zone and make better product and business decisions by automatically classifying them by type and stage and comparing them against startups in the same type and stage across more than 25 key performance indicators

Possible Use Cases of the Startup Genome Compass

1. Measure progress by seeing your key performance indicators in comparison to startups that are similar to you.

2. Avoid premature scaling by identifying whether the 5 dimensions of your startup are aligned within and with each other. The 5 dimensions are customer, product, team, business model, financials and market.

3. Set the right priorities and align your team based on the benchmark your type and stage.

4. Find your weaknesses.  See if your user growth or conversion funnels are good enough to move to the next stage.

5. Explore resources and tips that are relevant for your type and stage

6. Share your report with Mentors and Investors so they can support you better

7. Use the benchmark as a supplement for your monthly board meeting.

Tell us how you end up using the Startup Genome Compass, how you it was helpful for you and where you'd like to see us take the product in the future. feedback@startupcompass.co.


Premature Scaling

In addition to the benchmark, the Startup Genome Compass also diagnoses startups for what our research team has found is the dominant cause of failure: premature scaling.

We have found that startups progress along 5 core interdependent dimensions: Customers, Product, Team, Business Model and Financials. In a startup many of these dimensions are highly uncertain, in many cases, all of them. The art of high growth entrepreneurship is to master the chaos of getting each of these 5 dimensions to move in time and concert with one another. Most startup failures can be explained by one or more of these dimensions falling out of tune with the others. If a startup shows signs of premature scaling on any of the five dimensions we refer to it as inconsistent.

In our current dataset we have detected inconsistency - indicators of premature scaling - in 70% of startups. The difference in performance numbers are pretty astonishing.

1. No startup that scaled prematurely passed the 100,000 user mark.

2. Startups that scale properly grow about 20 times faster than startups that scale prematurely.

3. 93% of startups that scale prematurely never break the $100k revenue per month threshold.

If you want to learn more about Premature Scaling and how it manifests you download our new mini report Startup Genome Report Extra: Premature Scaling. It contains 25 graphs and contributions from Brad Feld, Fred Destin, Michael Jackson, Bill Liao, Saad Khan and many more.

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.

 

Sign up for the Startup Genome Compass

If you a part of an Internet startup you can sign up for the Startup Genome Compass here. Every startup helps us get closer to cracking the code of innovation and spreading the magic of Silicon Valley with the rest of the world. All your data is anonymized, treated absolutely confidential and will not be shared.

Finally, we'd like to share a little bit of our roadmap with you. We'd love to get your feedback on where you think we should take the product and what we can do to help you be more successful in making your world-changing ideas come to life.

Our Roadmap for the Product

1. We will give you more relevant content based on an extended typology and substages we have identified, but haven’t implemented yet.

2. We will add tools for more areas of your startup: founder & employee salaries, founder personality types, team composition & culture, how much money to raise and when, estimated valuations for your startup and cloud forensics.

3. We will automate the data collection to make your life easier.

4. We will make it easier to make decisions for you by visualizing and augmenting the data more effectively.

5. We will be able to detect progress over bi-weekly and weekly intervals to give a shorter feedback loop.

6. We will integrate your data with other applications such as fundraising tools, and dealflow management solutions.


- Our Methodology


Further reading:

Discover The Patterns Of Successful Internet Startups In The Startup Genome Report

Today we are releasing the first Startup Genome Report with in-depth analysis on what makes internet startups successful based on data from over 650 startups. Here is a small window into the report with 14 indicators of success.

There are tens of thousands of potential young Steve Jobs, Bill Gates, and Mark Zuckerbergs all over the world, sitting in their dorm rooms and little apartments dreaming up the next global phenomenon. Unfortunately the entrepreneurs they look up to are perceived as almost mystical figures that are impossible to emulate. The first challenge these young entrepreneurs have is to demystify their heroes and learn how they became successful. If they have enough strength to get their company off the ground they will experience an amazing roller coaster ride.

One would think after so many successes and failures of technology startups in the last 50 years that there would be clearer patterns aspiring entrepreneurs could study to mitigate the amplitude of the extreme highs and lows that characterize the entrepreneurial journey. But unfortunately that's not the case… yet.

As a result too many entrepreneurs idolize Steve Jobs as a one of a kind genius, with superpowers mere mortal entrepreneurs just don’t have access to. People overlook that Steve Jobs isn’t doing anything radically different than other entrepreneurs. He just knows the rules of the game and plays it extremely well. What separates the top performers in any field, be it entrepreneurship, basketball or music is not a magic formula they possess secret knowledge of, but rather their ability to intensely focus on what matters most and their complete dedication to improving their craft.

Hundreds of people built social networks before Mark Zuckerberg came along. But Facebook emerged as the winner, and it now has the potential to grow into the most important company of this era. Zuckerberg wasn’t more intelligent, more ambitious, better educated or wealthier than other entrepreneurs who built social networks, he just played the game better. If there was one factor where Zuckerbeg truly differentiated himself from other entrepreneurs it was probably his ability to learn and adapt.
This trait seems to be emerging as the defining factor of successful entrepreneurs. Paul Graham calls this flexibility. Steve Blank describes entrepreneurship as a search process for a repeatable and scalable business model with the primary driver of success being learning from customers. Eric Ries describes the engine of startups as a 3 part loop, Build-Measure-Learn designed to radically reduce waste by increasing the speed of learning.

We just completed an in-depth analysis with data from more than 650 startups and one of the clearest results we found was that 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. 
Once we started analysing the data it was staggering to see how clearly were able to find the patterns that described why Internet startups succeed and fail. We were able to break down the lifecycle of a startup into 6 discrete stages and identified 4 very different types of startups. Companies that didn't move through the stages we defined were significantly less successful. The assessment was purely based on milestones related to the interaction between their product and the market.  And the assessment did not include any traditional indicators of success such as funding, user growth, time or the background of the founders.
Many entrepreneurs that we have talked with during our research, especially younger ones, considered describing the repeating patterns of startups an impossible task or even a disgraceful reduction of the artistry of entrepreneurship to numbers and graphs. With this report we do not mean to imply that there is no art to entrepreneurship but rather that entrepreneurship is strongest at the intersection of science and art. By gaining a deeper understanding of the repeating patterns underlying success and failure
entrepreneurs can dramatically increase their ability to innovate.
 


Based on the first Startup Genome report we are releasing a new survey for entrepreneurs to assess their startup. Entrepreneurs that fill out the test will be given their startup personality type, with personalized advice for what to focus on based on aggregate data from the startup genome project. The data we collect with this survey will allow us to give entrepreneurs even more granular feedback.
In the 20th century large companies became dramatically more efficient as a result of scientific management. This was arguably one of the biggest causes for the explosion of wealth the world saw in the last century. The Startup Genome Report is a major step towards triggering the same transformation for entrepreneurship and innovation. In a time where progress seems to be slowing down, this could unlock another century of transformative growth and prosperity.
Following are 14 more of our key findings. If you would like to read the full report, you can download it here.

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.
Check out the full report for more details.

If you have any questions about our methodology you can read this blogpost by Ron Berman: http://www.systemmalfunction.com/2011/05/deciphering-genome-of-startups.html or send us an email at feedback@startupcompass.co
Following is a little infographic by kissmetrics giving a sneak peak on the Startup Genome Report.

Help The Startup Genome Project Bring Silicon Valley To The Rest Of The World

All of us have been struck by the amazing learning experience being in Silicon Valley. The ecosystem that has evolved here is so advanced and unique that over the last 30 years it has been the single most influential driver of innovation globally. It is fair to say that the Valley is the "holy land" of technology entrepreneurship. 

It is our belief that entrepreneurs are the world's most influential force for positive change. A recent Kauffman Foundation study showed that nearly 100% of US job growth comes from highly scalable startups. At the same time more than 90% of all startups fail. Imagine for a moment if we could make the multi trillion dollar market of new venture creation a few percent more effective by improving the overall success rate of startups. These few percent cumulated over time could be what allows the world to reach escape velocity from the problems of our era (clean water, renewable energy, poverty, disease, aging, climate change and education).

The goal of the Startup Genome project is to crack the innovation code that has made Silicon Valley the global center of innovation. Solving this puzzle not only has the potential to raise the output of Silicon Valley to heights never seen before, but would allow the magic of Silicon Valley to be shared with the rest of the world. We believe the success of the Startup Genome project could mark the beginning of a new era, an era we are calling the Entrepreneurial Enlightenment.

Benchmark your Startup and Contribute to the Startup Genome Project by filling out this survey

Help us realize this vision

We have laid the foundation for the Startup Genome Project by creating a system that allows us to the synthesize best practices for creating successful startups. We've combined insights from many thought leaders including Steve Blank, Alex Osterwalder, Janice Fraser, Eric Ries, Sean Ellis, Dave Mcclure and Geoffrey Moore; with Steve, Alex and Janice directly supporting the project.

We've established our methodology by engaging with 50+ technology startups in Silicon Valley. Our early prototypes suggest significant improvements in focus, iteration speed, time to pivot and effective outreach to mentors & service providers. But in order to take the Startup Genome Project to the next level we need a much larger dataset to validate the work that has been done so far. You can contribute by filling out the survey. It requires about 5 minutes.

Once you fill out the survey, we will send you a comparative analysis within 2-3 weeks that shows you other startups that are similar to you and gives strategic recommendations on topics such as what metrics to track. As we recieve more data we will be able to make more targeted recommendations and predictions in areas such as business models, relevant content for what you're currently executing and much more.

In the next few months we will release the results of our research and sometime soon after that a first version of a software product leveraging the Startup Genome. 

If you would like to learn more about the formation of this project see our post: Introducing the Startup Genome

Introducing the Startup Genome Project

The Economic Significance of the Startup Genome
The role of technology entrepreneurship in our global economy has never been more important. The service and industrial sectors have dominated the global economy for hundreds of years but soon their sun will set. Information technology has been accumulating momentum expoentially for the last few decades, and now the infrastructure is in place for the global economy to be completely reorganized in information technology's image. Every job where a human performs some repeatable process will be put into software. While as many as 50% of today's jobs may become irrelevant, a greater number of new jobs will be created during this transformational period. The Kauffman Foundation found that scalable startups are the engines the drive nearly all economic growth and job creation. 

The increasing economic importance of startups represents a tremendous opportunity. Startups in Silicon Valley have created millions of jobs and trillions of dollars of wealth over the last 3 decades and yet the market potential of technology startups is only in the beginning of its unfolding. The international community has taken notice and new startup ecosystems are being built up all over the world with the hopes of replicating what Silicon Valley has created. Spearheading this movement are organizations like Sandbox, Seedcamp, Techstars, OpinnoFounders Institute500 Startups and Singularity University. And on an individual level, the brightest people all around the world, are increasingly seeing entrepreneurship as the career path of choice. Starting a company is sexier than a becoming a suit on Wallstreet.

The Mystery of Success 
But despite the supreme economic importance of scalable startups, we still don't understand the patterns of successful creation. More than 90% of startups fail, due predominantly to self-destruction rather than competition. For the less than 10% of startups that do succeed, most encounter a handful of near death experiences along the way. 
There seems to be somewhat of a contradiction. If the way we create startups today doesn't work very well, how do so many startups go on to create millions if not billions of dollars of wealth?  One explanation is that the threshold for success is not that high. In today's economic climate it is possible to succeed by just getting a few important things right, even if you get everything else wrong. But with the complexity of today's modern world why is the bar for success not higher? One reason is the insatiable market demand for the delivery of even incremental increases in value.  Another reason is the inability of large companies to react quickly to changing consumer demand. While large companies became extremely efficient executers at the turn of the 20th century with the advent of Taylorism, they haven't learned to adapt quickly, which is a death knell with today's pace of change as fast as it is. So startups can be immensely successful just by getting a few things right, the bar is no higher. But if success requires only getting a few things right, why haven't we gotten much better at more consistently creating successful startups?

From the tens of thousands of startups created in Silicon Valley and the hundreds that have bloomed into billion dollar companies a lot of experience of both success and failure has been accumulated. Through this the startup community has learned a lot about what works and what doesn't. But the way we pass down this hard earned wisdom in the form of advice is severely flawed. While the war stories of success and faillure are often inspirational, entrepreneurs have trouble undersanding cause from correleation, skill from luck and the factors that make advice relevant or not. Our insights are like the puzzle pieces of a massive jigsaw puzzle, scattered across thousands of minds throughout The Valley. Since very little of the puzzle pieces have been matched together, every startup, with the benefit of a few trusted advisors, needs to beat a new path towards success.

Signs of Awakening
Until very recently the startup community has been ineffective at stiching any of its learnings together into repeatable processes and fundamental principles. The seminal work in the space was Steve Blank's book The Four Steps to the Epiphany. Steve was able to synthesize decades of startup experience into a model that described the key differences between success and failure. One of his biggest insights was that most startups fail because they can't find customers not because their technology doesn't work. The solution to this problem was a methodology Steve called Customer Development. Customer Development recognized that most of a startups beliefs on day one were simply hypotheses, and outlined a rigorous way to test these hypotheses, effectively applying the scientific method to business. Eric Ries collaborated closely with Steve Blank and took Customer Development to the next level by combining it with Agile Development and Lean Manufacturing Principles. Eric called this the Lean Startup and its message has spread like wildfire around the world becoming a movement of sorts. Meanwhile, others have independently made important contributions in narrower domains such as Alex Osterwalder in Businesss Models, Sean Ellis in Marketing, and Dave Mcclure in Metrics
The Lean Startup and its compliments have done a tremendous job raising awareness that there is a better way to run startups, and many entrepreneurs have begun incorporating these principles and tactics into their workflow, but it's all really just the tip of the iceberg of what's possible. 


Inside Look Into The Startup Genome
To take the next step we've been working on laying the groundwork for the Startup Genome Project.
We want to do for startups what Pandora did for music in order to understand how innovation happens at a fundamental level and the spread the knowledge of these principles worldwide.

We believe an interdsciplinary approach is possible, where insights from a diverse set of fields and perspectives can be integrated into a personalized solution stack, that entrepreneurs can use on a daily basis to figure out what their goals should be, and recieve recommendations for resources they need to take the next step.
I believe we now have the foundations for this project to expand very rapidly. Similar to how Pandora broke music down into a few hundred attributes, we’ve created a taxonomy for startups, which allows us to classify them into different types. This approach helps us organize principles, tactics, and methodologies in relation to specific factors. When we define the factors these things depend on we can begin creating a system to manage the chaos and complexity of organizing the information about what makes startups successful. While the common wisdom seems to be that the number of factors is infinite or indefinable, our initial set of variables has brought a lot of clarity. 

The second foundational component of the Startup Genome was our realization that we could treat the startup as an organism and take many cues from the field of evo-devo biology. This approach allowed us to create developmental models of startups, where we can define the gating factors a startup needs to pass through in order to evolve. The developmental approach enables us to synthesize the models of many entrepreneurial thought leaders, such as Steve Blank, Eric Ries, Sean Ellis and Geoffrey Moore by making it possible to express at exactly what stage in the life cycle each method is relevant and how they relate to each other. 
Lastly, when we combine the classification system with the developmental approach we can create unique developmental models for every type of startup. This allows us to recommend the information, methodologies and contacts that are exactly relevant for what a startup is currently working on.

We've laid out an ambitious roadmap to bring together specialists from a diverse set of fields to develop methodologies, models and knowledge entpreneuers can use to make their startups more successful. Currently the areas we are working on are:

- Business models
- Product Design
- Agile Development
- Sales
- Measurement
- Customer Development
- Market type
- Finance
- Teams 
- Personality and Psychology
- Technology and Market Trends
- Systems Theory & Complex Adaptive Systems
- Classification, Taxonomy & Typing
- Developmental Progression

Finally, if you're more of a visual person, here is a model I made a few months ago in Prezi that shows a proof of concept of the developmental approach and shows how Customer Development and the Business Model Canvas interact to describe the process of the pivot. This model was based on a weekend of work with Steve Blank and Alex Osterwalder, which Steve describes in more detail here.

Please give the Prezi about 60 seconds to load, it is a big puppy. Enjoy!