The LinkedIn Report on Tech Entrepreneurship

LinkedIn’s vision is to create economic opportunity for every member of the global workforce, and a key part of achieving this vision is leveraging our data assets to enable individuals to make better decisions in every aspect of their professional lives. In service of that goal, this report and the associated blog post document the demographics and relationships of more than 1200 technology entrepreneurs who raised venture capital in 2013, in hopes that it may serve as a touchstone to inform the decision making of our generation’s brightest minds.

Data

Combining LinkedIn data assets (profiles, connections, etc.) with funding data from the venture capital investing database Crunchbase, we analyze the demographics and connectivity patterns of more than twelve hundred (1,235) individuals in the senior leadership of early-stage technology startups that received a single round of venture capital funding in 2013.

Skills

Our first look at the structure of technology entrepreneurship is an analysis of the skills most common among individuals who raised a round of venture capital funding in 2013. We start with a high-level overview of focus areas and then drill down into specific technologies and platforms. The proportions below represent the number of members in the dataset associated with a given skill or skill category.

These figures reflect the rise of mobile as well as the increasing prevalence of cloud computing and software-as-a-service business models. Interestingly, while much talked about in the press, the distributed computing platform Hadoop makes a meager showing, surely owing in large measure to the reality that early stage startups rarely contend with huge volumes of data

Skill Category

• IT Infrastructure and System Management (93.8%)
• Management and Leadership (87.1%)
• Strategy (82.2%)
• Web Programming (79.9%)
• Business Development and CRM (69.1%)
• Product Development and Management (50.7%)
• Cloud and Distributed Computing (47.7%)
• Marketing - Digital and Online Marketing (46.1%)
• Consulting (43.9%)
• Marketing - Social Media Marketing (40.3%)
• Software Engineering Management and Requirements Gathering (38.8%)
• User Interface (38.2%)
• Finance - Investment Banking (36.0%)
• Statistical Analysis and Data Mining (33.3%)
• Other Software Development Skills (29.7%)
  
  

IT Infrastructure and System Management

• Mobile Devices (17.7%)
• Mobile Applications (16.4%)
• Enterprise Software (13.0%)
• Web Applications (7.5%)
• Mobile Technology (4.4%)
• Architectures (3.6%)
• Enterprise Architecture (3.5%)
• IT Strategy (3.2%)
• Wireless (2.6%)
• Information Architecture (1.9%)

Programming Languages

• Ruby / Rails (12.4%)
• JavaScript (12.2%)
• Java (9.6%)
• Python (8.7%)
• C++ (7.1%)
• PHP (6.9%)
• C (6.1%)
• Perl (3.7%)
• Objective-C (3.1%)
• Node.js (2.6%)

Data & Cloud Computing

• SaaS (15.1%)
• Cloud Computing (14.7%)
• MySQL (6.8%)
• Distributed Systems (6.3%)
• Big Data (4.2%)
• SQL (4.0%)
• Databases (3.1%)
• Amazon Web Services (AWS) (2.3%)
• Hadoop (2.3%)
• PostgreSQL (2.3%)

Education

Examining the list below we see that many of these individuals attended world-class educational institutions renowned for their business and technology curricula. For example, given that there are estimated to be more than 20 million students pursuing higher education in the United States (NSF, 2012), with a student body of just over 18,000, students from Stanford are approximately ninety times more likely than the general population of students to lead a venture-capital-backed technology company.

These statistics highlight the importance of a high quality technical education, and underscore the importance of ensuring that students from all walks of life have access to the best possible educational opportunities.

• Stanford University (5.8%)
• Massachusetts Institute of Technology (4.0%)
• Harvard Business School (3.5%)
• University of California, Berkeley (3.5%)
• The University of Texas at Austin (3.4%)
• Harvard University (2.8%)
• Carnegie Mellon University (2.6%)
• Stanford University Graduate School of Business (2.3%)
• University of Michigan (2.3%)
• University of Pennsylvania – The Wharton School (2.3%)
• University of Pennsylvania (2.2%)
• Cornell University (2.1%)
• Columbia University in the City of New York (2.0%)
• The Johns Hopkins University (1.9%)
• Boston University (1.8%)
• Yale University (1.8%)
• University of Florida (1.7%)
• University of Southern California (1.7%)
• University of Washington (1.7%)
• Northeastern University (1.6%)

Employment History

The organizations listed below utilize practices that enable them to build robust, scalable systems that power much of the world’s commerce, and individuals who successfully acquire venture capital funding are disproportionately likely to have been exposed to these technologies.

• Microsoft (5.3%)
• Google (4.5%)
• Hewlett Packard (3.2%)
• IBM (3.0%)
• Yahoo (2.0%)
• Apple (1.8%)
• Sun Microsystems (1.8%)
• Cisco (1.6%)
• McKinsey & Company (1.6%)
• Oracle (1.6%)
• Accenture (1.5%)
• Deloitte (1.5%)
• Goldman Sachs (1.5%)
• Intel Corporation (1.5%)
• Wells Fargo (1.5%)
• Citi (1.3%)
• Motorola (1.3%)
• VMWare (1.3%)
• Dell (1.2%)
• Facebook (1.2%)

What’s more, examining past job titles of these individuals we find that more than 40% have held senior leadership positions, that is Director level or above, during the course of their career. Likewise, 20% of these individuals are serial entrepreneurs, having founded at least one company before their current venture.

Gender

The massive disparity between men and women in leading VC-funded companies is staggering.

Male (86.5%)
Female (13.5%)

How many brilliant women have been discouraged from pursuing a career in technology or entrepreneurship because of unfair challenges they face owing to their gender? Far too much opportunity is left unrealized when women are subject to societal and economic pressures that make it difficult to participate in the technology industry, and the obligation to create an open and supportive environment for individuals of all genders falls on every member of the technology workforce.

Age

Below we look at the ages of entrepreneurs who raised a round of venture capital funding in 2013. Clearly, only very infrequently are the companies of young entrepreneurs able to successfully secure venture capital funding.

Next, we examine how the size of an individual’s first round venture capital raise changes during the course of his or her life. Again we see that as the breadth and depth of a person’s experience increases, so too does the extent to which they are rewarded financially for their efforts. Unambiguously, individuals tend to command significantly more money when raising venture capital later in life.

Relationships Matter

In the network digram below we see the largest connected component of the network of LinkedIn connections among individuals who founded a venture-capital backed company in 2013. Node colors correspond to algorithmically identified communities, often relating to clusters of businesses in a particular geography. The densely connected community in the middle is dominated by members from the San Francisco Bay Area, with peripheral communities corresponding to other regions such as Boston, New York, and Austin, TX.

In this visualization we have scaled the size of each node to correspond to the size of an individuals’ first-round venture capital raise. In the next section, we explore in more detail the relationship between network structure and venture capital investment.

Predicting Venture Capital Investment

LinkedIn Engineering develops state of the art machine learning algorithms that leverage the rich structure of the Economic Graph. The scores below, labeled ‘Economic Graph Algorithm,’ are uniquely associated with each individual, and are based on a deep synthesis of an individual’s connectivity in the LinkedIn social graph in combination with self-reported profile data.

The data demonstrate that individuals who raised money in 2013 went on to develop strong professional networks in the following months. Perhaps more intriguing is the fact that when we run a similar algorithm on a snapshot of the Economic Graph as it existed in 2012 – the year before these individuals sought to raise money – we find that the results are predictive of the amount of money the individual would go on to raise in the following year (Correlation=0.38).

While this algorithm does not capture the entire story, a simple statistical model incorporating age, gender, education, employment, and features of the Economic Graph (as computed in 2014) is able to explain more than 20% of the variance associated with the amount of money a person raised in 2013. Given the capacity to quantify aspects of individuals’ ability to deliver results, it’s easy to envision how such technology could be applied to the problems of talent discovery, targeted advertising, lead generation, or even venture capital investment.

Conclusion

We live in a time when technology is reshaping the ability of each member of the global workforce to play an active role in his or her professional development. From world-class online educational resources to the network intelligence built into LinkedIn products like Connected and Job Seeker, the landscape of opportunity is changing as it becomes cheaper and easier to cultivate the experiences and relationships required to succeed in the networked economy. For the men and women interested building a business the path to success is rarely straightforward, but with any luck this analysis may illuminate a few of the stepping stones along the way.

Data-Driven Career Tips for Aspiring Entrepreneurs

• Acquire a world-class education, with a focus on management, leadership, and technology, with specific focus in the areas of mobile and cloud computing.
• Work to gain exposure to industry best practices at leading technology firms, with the goal of developing leadership experience.
• Good things come to those who wait – investing wisely in professional and educational development now will yield economic dividends as you age.
• Relationships matter -- actively develop and nurture your professional connections. Opportunities are connected to people.

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