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 [转帖] 创业公司基因组报告 |
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tutu
[博客]
[个人文集]
头衔: 海归准将
声望: 专家
性别: 
加入时间: 2004/02/21
文章: 4238
来自: 广州：gz_venture_club AT yahoo DOT com
海归分: 180035
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作者：tutu 在 海归商务 发贴, 来自【海归网】 http://www.haiguinet.com
创业的朋友们有没有想过是否会有一个创业公司成功的公式？现在就有4位创业者联合发布了这样一份创业公司基因组的报告——到底是什么使得硅谷的创业公司会成功，什么又会降低其成功的概率呢？
4位创业者（Bjoern Herrmann，Max Marmer，Fadi Bishara和Aleksandra Markova）总共收集了超过650家的互联网创业公司的数据才得出这样一份基因组报告。
此外，他们的这个项目还得到了加州大学伯克利分校和斯坦福大学著名教授的支持，希望能够创建一套新的更好的理论通过考察互联网创业公司的一般门槛和发展进程来更加有效的评估这些创业公司。
以下为该基因组报告中列出的14个创业公司最有趣的趋势，有许多还会令你大吃一惊：
1.善于学习的创始人更能成功：那些拥有良好的导师，有效的数据监测体系和善于学习的创始人的创业公司所能拿到的投资是一般公司的7倍，其用户增长率也会快3.5倍。
2.那些pivot（变革方向）过一到两次的创业公司能拿到的投资是从未Pivot过或者Pivot超过两次的创业公司的2.5倍，并且用户增长率也会快3.6倍，而且其在冒然拓展方面的 概率也会小52%。
3.许多投资者投给那些还未到达problem solution fit阶段（具体指找到问题，提出解决方案的阶段）的创业公司的资金一般是其真正需要的2到3倍。另外，尽管有指标显示单个创始人团队和那些没有技术性共同创始人的团队的成功可能性更低，有许多投资者也会对他们进行过度投资。
4.投资者手把手的对创业者进行帮助几乎对创业公司的运营 情况没什么影响或者影响不大。不过合适的导师能够大大的影响一个公司的融资能力。（不过这并不等于说投资者对公司的估值和收购没有重大影响）
5.和有2个创始人的创业团队相比，单个创始人的团队通常要花3.6倍更多的时间将公司带到快速发展阶段，另外他们Pivot的可能性也要比双创始人团队小2.3倍。
6. 业务型创业团队在发展销售型创业公司的成功可能性上要比发展产品型创业公司的成功可能性高6.2倍。
7.技术型创业团队在发展没有网络影响的产品创业公司的成功概率上要比发展有网络影响的创业公司的成功概率高3.3倍。
8.一个既拥有技术创始人又拥有业务创始人的创业团队融到的资金一般会比起纯技术团队或者纯业务团队高30%，用户增长率也会快2.9倍，并且冒然拓展的可能性也会低19%。
9.大部分的成功创业者更多的是靠影响驱动，而非人们通常所说的经验和资金。
10.在Product Market fit阶段（具体指的就是你生产多少产品，消费者就买多少产品，你增加多少服务器，用户就会增加多少的这样一个阶段）到来之前，创始人通常会高估IP的价值超过255%。
11.创业公司证明产品的市场的实际时间通常是创始人起先预计的2到3倍，另外这种创业前对市场开拓所需时间的低估也正是后来创业者冒然拓展的一个重要原因之一。
12.还没有融到资金的创业公司通常会高估其市场价值超过100倍。
13.冒然拓展是创业公司失败的一个最为普遍的原因之一，由于快速拓展的时机并不成熟使得他们失败。
14.由于互联网的发展改变了生意规则，用B2C还是B2B给互联网创业企业分类已经失去了意义。另外我们还发现了4种主要不同类型的创业公司，它们在顾客获取，时间，产品和市场，团队等方面都有不同的行为。
希望以上这份创业公司基因组报告的精华部分能够帮到创业的朋友们，增加创业成功的概率。
--------------------------转载自三十六kr-------------------------------------
这里有完整版的报告。
https://startupgenome.cc/
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: https://www.systemmalfunction.com/2011/05/deciphering-genome-of-startups.html or send us an email at [email protected]
Following is a little infographic by kissmetrics giving a sneak peak on the Startup Genome Report.
February 8, 2011 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
February 4, 2011 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, Opinno, Founders Institute, 500 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!
Startup Genome Prototype: The Pivot on Prezi
If you like the visual appeal of the Prezi we've also built a prototype of Four Steps to the Epiphany, translating the entire book into this visual format which you can see here. This Prezi is about twice the size of the pivot so you'll need to give it about 2 minutes to load.
We'll keep you updated on our progress.
-Max Marmer
P.s. Benchmark your Startup and Contribute to the Startup Genome Project by filling out this survey.
作者：tutu 在 海归商务 发贴, 来自【海归网】 http://www.haiguinet.com
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 [转帖] 创业公司基因组报告 -- tutu - (22733 Byte) 2011-5-30 周一, 18:31 (2862 reads)
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