Silvija Seres: The Epic Startup Gender Gap
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This document discusses women in technology and entrepreneurship. It notes that women founders receive less than 3% of venture capital and face barriers from being older or non-male. Myths are dispelled, including that women don't do tech or focus on "pink" problems. The history of women in tech is reviewed. Advice is provided for female entrepreneurs, investors, and regulators to increase diversity. Barriers like unconscious bias and lack of role models are addressed.
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Silvija Seres: The Epic Startup Gender Gap
- 1. Women, tech and entrepreneurship Silvija Seres OBR StartupDay Oslo, 12 Sept 2016
- 3. Women and investment Women founder CEOs get less than 3% of Venture Capital. Startupbootcamp.org, March 2016 What women face is that it is difficult to get past the average VC who is male, white and under 35. Many women entrepreneurs are in their 40s and 50s so face an additional age barrier. FORBES, March 2016 #3
- 4. A few personal anecdotes I laughed at #4 Ah, so you’re the required pair of breasts? “ Sorry, we just really wanted to golf.“This may be a bit technical for you.“ I guess you’ll want to go back to the hotel now. “ Can you tell me what she can do?“
- 5. And one that fires me up #5 They still don’t take us seriously, two young women trying to do tech. “
- 6. Myth 1: Women don’t do tech A recent Modis survey of U.S. adults who work in the tech industry found that 55% think the biggest challenge to diversity in tech is age. This is followed by gender (21%), ethnicity (18%), and religion (6%). #6 Yet, when you look at the history og IT and computing, when you look at shipping in Norway, when you look at entrepreneurship in developing world, and engineering in Eastern Europe… FORBES, March 2016There are preconceived notions that women and “older people”, i.e. 50+, don’t know much about tech. FORBES, March 2016
- 7. Here are a few girls that did IT #7 Ada Lovelace, the first programmer Race Hopper, inventor of the first compiler Radia Perlman, spanning-tree protocol Hady Lamarr, spread spectrum technology Programming was a pink-collar profession for about the first decade. There were some men, but it was actually hugely women.
- 8. And a few more… #8 Shafi Goldwasser, 2012, complexity theory and cryptography Fran Allen,2006, optimizing compilers Barbara Liskov, 2008, distributed computing ACM Turing Awards
- 9. Myth 2: Women focus on pink problems In most countries women are the traditional entrepreneurs. #9
- 10. Myth 3: Female uassuming humility #10 It’s not really about asking for the raise, but knowing and having faith that the system will actually give you the right raises as you go along. That might be one of the initial ‘super powers,’ which quite frankly, women who don’t ask for a raise have. Because that’s good karma. It’ll come back because somebody’s going to know that’s the kind of person that I want to trust. Microsoft CEO, Satya Nadella, at the Grace Hopper Celebration of Women In Computing Sheryl Sandberg, COO of Facebook: “We need to start giving women the credit they deserve. One way of changing this, is documenting the role women played in the dawn of technology.” So: Keep calm and code on? ?WTF
- 11. ITs diversity problem Boy’s toys narrative: By the 1980s, computer programming seemed to be an exciting job opportunity for women. It had surpassed both law and physical sciences as women’s choice for studies. At its 1984 peak, 37% of computer programmers were women. By 2011, it was only 12%. #11 When women stopped coding
- 12. Silicon Valley’s diversity advantage #12 1. Sergey Brin, Russia, $31 billion 2. George Soros, Hungary, $24 billion 3. Len Blavatnik, Ukraine, $21.5 billion 4. Rupert Murdoch, Australia, $14.2 billion 5. Patrick Soon-Shiong, South Africa, $12 billion 6. Elon Musk, South Africa, $10.3 billion 7. Thomas Peterffy, Hungary, $9.1 billion 8. Pierre Omidyar, France, $8.2 billion 9. Jan Koum, Ukraine, $7.6 billion 10. Do Won and Jin Sook Chang, Korea, $5.2 billion Where Silicon Valley gets its brains from: 10% of Forbes 400 Over 50 percent of tech startups in Silicon Valley are founded by immigrants.
- 13. Silicon Valley’s diversity problem #13 Silicon Valleys other diveristy problem: 71 percent are men, 60 percent identify as white, 23 percent Asian, 8 percent Latino, and 7 percent black.
- 14. Leadership’s diveristy problem #14 “Lean in” is not good gender equality, and not an attractive option for a generation that views life as a whole package, not a race. We need fewer impossible superwomen, and more plain smart women who want both a life and to get something big done.
- 15. We need less of this #15 Closed circles Non-transparent skills Silent money Predictably traditional investments
- 16. And more of this #16 I haven’t done this before, so I am sure I’ll be very good at it.
- 17. The 4. industrial revolution This time is different: Exponential, polar and combinatorial. Societies will change – fast! We need all the talent and all the money in the right places. #17
- 18. XO and women #18 Good news: • Critical skills for the 21st century favor women • Hot sectors attract women (edtech, medtech, biotech, 3D, VR, AI) • The new labor-market works for the flexible and the fast
- 19. Women and sectors Women are most commonly in B2C sectors such as E- Commerce, Fashion, Media (large female consumership). Women are also increasingly well represented in sectors such as Healthcare, Wearables, Education, Biotech. Digital Health, IoT, AI, VR and Foodtech are hot sectors. Social Entrepreneurship is in. #19
- 20. General advice #20 MORE VISIBILITY! SHARPER PROFILES! BOTH VISION AND DELIVERY! BETTER FRIENDS!
- 21. Norway’s global FEI position From the GEDI 2015: identifying and analyzing the conditions that foster high potential female entrepreneurship development #21 Female Entrepreneurship Index (FEI) 2015
- 22. Practical advice for female entrepreneurs Make a kick-ass product or service Build a loyal superstar team Think bigger than big Sell, sell, sell and sell some more Create visibility (get on the dance floor) Weave own network (professional & personal affinity) Cherish mentors Find investor affinity with your sector/space Consider online funding and crowdfunding Just ignore the ones who don’t believe women can do it. #22
- 23. Practical advice for lady-investors Risk-alleviating incentives such as kapitalfunn, they make active investment more attractive than passive ownership. Investor education, informal networks, advisory activities for incubators. #23 You can’t be what you don’t see. “Some women take themselves out,” Sandell replied, pointing to two women who were just shy of the general partner investing level who left the firm for personal reasons. Sandell said that the majority of the general partners at the firm are promoted from within and rise from the ranks of an associate to the general partner. To get on or stay on in a VC team: beat the unconscious bias Scott Sandell, managing partner and head of technology at New Enterprise Associates (NEA) Including more women in VC: Including more women in angel activities:
- 24. Practical advice for all investors Look for high-potential female entrepreneurs, you may find amazing talent and market opportunity for a fraction of the price. #24
- 25. Practical advice for regulators Environmental factors og greatest consequence: • equal legal rights, access to education, networks, technology, capital, social norms, values, and expectations • ALTERNATIVE RISK and a variety og attractive investment and entrepreneurial paths • family-related institutions such as greater provision of childcare services and family leave #25 Women tend to start ventures at a later age (ages 35- 40) than men, and must manage work-family conflicts
- 26. Thank you! Questions? silvijaseres.com and silvija.seres@technorocks.com @silvijaseres #26
Notas del editor
- My shuriken…
- You have the opportunity to make a difference. There is more to engineering than maths. You will have lots of attention. Letters will be addressed to Mr. People will worry about your safety.
- First decade: 350m to 2bn inyternet, 750m to 5bn mobile.
- Facebook and Twitter’s average revenue per user and monthly active users are both seeing stagnant year-over-year growth rates. Continuing barriers to accelerating growth include things like phases in adoption cycles and dependence on developing markets with low spending power and infrastructure, Meeker said.
- Ada: translated an articla about Babbages Universal Machine and added comments about computing Berboulli Numbers. http://www.dailydot.com/via/women-who-changed-tech-industry-forever/
- amturing.acm.org
- The first billion.
- Facebook and Twitter’s average revenue per user and monthly active users are both seeing stagnant year-over-year growth rates. Continuing barriers to accelerating growth include things like phases in adoption cycles and dependence on developing markets with low spending power and infrastructure, Meeker said.
- https://www.google.no/search?q=boy%E2%80%99s+toys%E2%80%9D+narrative&ie=utf-8&oe=utf-8&client=firefox-b&gfe_rd=cr&ei=9_3UV7XcNOvk8AeK9KXACw#q=woman%20computer%20science In 1967, Cosmopolitan Magazine ran an article called The Computer Girls, which proclaimed: “Now have come the big, dazzling computers – and a whole new kind of work for women: programming.”By the 1980s, computer programming seemed to be an exciting job opportunity for women. It had surpassed both law and physical sciences as women’s choice for studies. Then, in 1984, it all came to an abrupt end. Patricia Ordóñez, assistant professor of computer science at the University of Puerto Rico, was a student at Johns Hopkins University at the time. In an interview with NPR, she explained: “I remember this one time I asked a question and the professor stopped and looked at me and said: You should know that by now. And I thought: I am never going to excel.” By the 1980s, computer programming seemed to be an exciting job opportunity for women. It had surpassed both law and physical sciences as women’s choice for studies. Then, in 1984, it all came to an abrupt end. Patricia Ordóñez, assistant professor of computer science at the University of Puerto Rico, was a student at Johns Hopkins University at the time. In an interview with NPR, she explained: “I remember this one time I asked a question and the professor stopped and looked at me and said: You should know that by now. And I thought: I am never going to excel.” Around the same time, movies like Tron (1982), War Games (1983) and Weird Science (1985), featuring male computer hacker heroes, almost certainly contributed to this “boy’s toys” narrative. The result was that by the time young men arrived at university, they had already been exposed to computers and computer programming, while women were often starting from scratch. The uneven playing field left many women discouraged. Female enrollment rates in computer science programmes plummeted. At its 1984 peak, 37% of computer programmers were women. By 2011, it was only 12%.
- They came from 23 countries on every continent except Antarctica. Four emigrated from India, and three each from China, Hungary, Israel, Russia and Taiwan. They made their money in everything from tech to investing to real estate. Quite a few, like Koum, came with little to nothing. Igor Olenicoff and his family arrived with $800 and four suitcases, only to be robbed. Born in Pakistan, Shahid Khan came to the U.S. at 16 and realized in his first days that even as a dishwasher he could earn more than most people in his home country. Silicon Valley talent comes from all over the world. Approximately 30 percent of software, semiconductor and computing companies in the US are founded by foreigners, and over 50 percent of tech startups in Silicon Valley are founded by immigrants. .
- managing unconscious bias https://www.theguardian.com/technology/2016/feb/04/slack-diversity-report-silicon-valley http://www.pbs.org/newshour/bb/how-silicon-valley-is-trying-to-fix-its-diversity-problem/ https://medium.com/tech-diversity-files
- managing unconscious bias https://www.theguardian.com/technology/2016/feb/04/slack-diversity-report-silicon-valley http://www.pbs.org/newshour/bb/how-silicon-valley-is-trying-to-fix-its-diversity-problem/ https://medium.com/tech-diversity-files
- managing unconscious bias https://www.theguardian.com/technology/2016/feb/04/slack-diversity-report-silicon-valley http://www.pbs.org/newshour/bb/how-silicon-valley-is-trying-to-fix-its-diversity-problem/ https://medium.com/tech-diversity-files
- managing unconscious bias https://www.theguardian.com/technology/2016/feb/04/slack-diversity-report-silicon-valley http://www.pbs.org/newshour/bb/how-silicon-valley-is-trying-to-fix-its-diversity-problem/ https://medium.com/tech-diversity-files
- t’s only 2016, but the real world is quickly moving into the realm of science fiction. Drones, driverless cars and not-really-hoverboards are (or soon will be) commonplace. We’ve also seen technology change industries not normally associated with the term “cutting edge” — Uber has all but replaced taxis for many people, and Airbnb made finding lodging as easy as opening an app. But with these new toys and technologies come questions. Whether it’s about which regulations apply to disruptive players, what new tech means for existing jobs or why hoverboards keep exploding, there’s a learning curve with integrating new technology into our lives. Here’s the one question everyone should be asking: What does this mean for my insurance? There’s a reason so many people think insurance — what it covers, how it’s sold and more — needs an overhaul. The industry is slow to react, and when finances, security and safety are on the line, you don’t want to be playing catch-up. Do I need insurance for my drone? What does a driverless car mean for auto liability? When the lines of coverage are blurred, it leaves a grey area of confusion at best and a complete gap in protection at worst. The good news is that change is coming (and in some cases is already here). And the opportunity is too big to be ignored for long. Beginning in 2016, we’ll start seeing established companies and newcomers alike move to fill insurance coverage gaps being created by new technology and industries. Current evolution We’ve already seen changes come, slowly, to the sharing economy — the phrase for the industry that allows everyday folks to use what they already own (like their cars or homes) to provide goods and services to other people. Take Airbnb, for instance. Many people don’t have liability coverage through their homeowner’s or renter’s insurance. If your insurer found out you were using your house as a makeshift bed and breakfast, your policy was likely to be canceled. Now, though, there are more options for protection. Umbrella policies help cover a wider range of issues. Smaller insurers such as Peers are providing adequate insurance coverage. And even if Airbnb’s Host Protection Coverage and Host Guarantee only provide secondary coverage and don’t completely fill the gap in protection, they show that these companies recognize the need for such products. Leaving your customers out to dry isn’t the best way to build a business. Technology isn’t slowing down and waiting for insurance to catch up. Or look at Uber. There used to be a gap in insurance coverage where an Uber driver would be covered by their own auto insurance when they were off the clock, covered by Uber’s insurance when driving a passenger but covered by neither when they were looking for a customer. Just like with Airbnb, Uber drivers could get their coverage canceled if they tried to file a claim when they were using their car for commercial purposes. Your best solution was hoping you picked up a whole lot of passengers to cover the cost. But in the last few months, we’ve seen rideshare coverage expanding. First it was small companies like Metromile, but major insurers like USAA, GEICO, Farmers and MetLife are all stepping up to provide some form of rideshare insurance. Room for growth The sharing economy has begun to evolve, but there are new professional sectors around the corner that soon will go through the same growing pains. Drones are going to take off in 2016. Even if we don’t get the long-hypothesized utopian drone delivery services we’ve been promised, they’re already in use in some industries; insurance companies, for example, are using them to survey damaged properties. Some specialized companies provide commercial drone insurance, and earlier this year AIG was the first major player to offer their own insurance. But personal drone use is still underinsured, even with the FAA predicting one million drones sold during the 2015 holiday season. As with ridesharing, there are use cases for which insurers simply aren’t offering coverage. Does your homeowner insurance cover drones? The answer is a case-by-case “it depends,” which is hardly helpful. The companies that provide comprehensive coverage for all facets of drone ownership, ranging from personal injury liability to hull and body protection, will find a lot of paying customers. Rethinking auto Even a sector that has a long history — auto insurance — could be due for a shake-up. Self-driving cars are taking a huge part of the insurance equation out of play by removing drivers, and a whole host of questions pops up with that: Who’s liable for damages? What will an auto insurance policy actually cover? Some analysts think that car insurance premiums could drop as much as 60 percent in the next 15 years as computerized drivers take over and the number of accidents plummet (and we’re shown just how bad at driving we’ve been this whole time). And that’s only for personal use. What about the additional insurance needs for, say, driverless delivery startups? Or the even more complicated scenario of two new industries merging as ridesharing companies come equipped with a driverless fleet? We’ll fundamentally be changing the way we interact with cars, and insurance will have to change along with it. Will driverless cars hit the road en masse in 2016? Probably not. Ford is predicting 2020 at the earliest. But we’re already seeing the beginnings, and insurers should begin looking into their options now or they’ll find themselves on the outside looking in — again. The Insurance of Things A seemingly persistent problem for people across the globe are data breaches that put our sensitive personal data into the wrong hands. Corporations use data breach insurance to protect themselves from the costs associated with breaches, but it’s time for data breach insurance to spread to the masses. As more and more devices connect online, the so-called Internet of Things, we find ourselves giving to cloud platforms more and more private data ripe for the taking. That’s why data breach insurance will be crucial for both manufacturers and consumers. As we’ve seen with, for example, the Target data breach, it can be costly for the companies who have been hacked to make corrections and satisfy customers’ need for restitution. Data breach insurance will (and does) protect companies from liability costs, but only an estimated one in three companies has data breach insurance. That number is going to have to grow as the number of online devices do, or companies are going to find themselves in for a rude awakening in the form of lawsuits, fines and bad publicity. And it’ll be just as important for consumer-facing insurance to come into play if and when personal or financial information is stolen and used against customers. With more and more points of failure introduced, from devices to kids’ toys to appliances and more, it will be important for this protection when the inevitable data breaches do occur. Related Articles Microinsurance Is The Answer To The Insurance Industry Insurance Is The Next Frontier For Fintech Sequoia Invests $13 Million In A Seed Round For Lemonade, Which Is Looking To Transform Insurance But this additional insurance cost could be offset by the lowering of other insurances. With devices constantly online and talking, sending status reports to different parties, the risk of fire, flood, burglary and more are reduced. Car insurance prices will drop as vehicles become safer, and home protection costs will go down, too, as houses become somewhat unsettlingly self-sufficient. So where do we go from here? Technology isn’t slowing down and waiting for insurance to catch up. But that just means there will already be markets ready to buy protection once insurers join the game. And if they don’t? Well, there will always be newcomers who see a great opportunity. And that’s more dangerous to existing insurers than any exploding hoverboard.
- Pipe vs platform Networked organisation https://medium.com/@EskoKilpi/work-as-interaction-bfecdd8ea1a1#.2zpozui7d In an economy, people essentially produce goods and services for people. Companies are theoretically intermediary organizational forms that arrange the development, production and delivery processes. The digital world we live in today allows us to imagine and experiment with totally new value creation architectures. The concepts that govern our thinking and language in relation to work are not just semantic entities, but influence what we perceive and what we think is possible or not possible. Usually we are not aware of how these concepts prime our thinking. We simply think and act along certain lines. A seminal concept related to how we perceive work is the division of labor, the notion of work as activities separated from other activities, as jobs. The industrial management paradigm is based on the presupposition that activities are the independent governing factors of creating value. The organizational structure of (independent) jobs comes first. Then an appropriate system of coordination and communication is put into effect. The scheme of interaction conforms to the planned division of labor as a secondary feature. What if the Internet, network sciences and the huge advances in social technologies made it possible, or even necessary, to think differently? What if networks and interaction should be seen as the governing factors? As jobs and communication are mutually dependent, it means that if there are changes in interaction, so the activities will change. The smartphone has now become information technology’s key product. Surely, then, it has an impact on the way we work.
- Eastern European nations like the Czech Republic, Poland, Hungary, Slovakia, and Slovenia all have better Female Entrepreneurship Index (FEI) ranks than GEI ranks, indicating that they are particularly strong performers when it 12 2015 FEI rank comes to fostering female entrepreneurship. A different pattern emerges among the East Asian nations of Japan, Korea, Taiwan, and Singapore which all have better GEI ranks than FEI ranks, indicating that these nations do better at encouraging entrepreneurship in general than they do at creating the right conditions for entrepreneurship among women.
- Research female-savvy investors (female angels, partners at VC firms) and funds focused on women entrepreneurs: Golden Seeds, Astia, The Rising Tide, 500 Startups’ 500Women Fund, Broadway Angels & others : Kickstarter, Indiegogo, Portfolia
- Research female-savvy investors (female angels, partners at VC firms) and funds focused on women entrepreneurs: Golden Seeds, Astia, The Rising Tide, 500 Startups’ 500Women Fund, Broadway Angels & others : Kickstarter, Indiegogo, Portfolia
- Research female-savvy investors (female angels, partners at VC firms) and funds focused on women entrepreneurs: Golden Seeds, Astia, The Rising Tide, 500 Startups’ 500Women Fund, Broadway Angels & others : Kickstarter, Indiegogo, Portfolia
- It is not easy to determine which entrepreneurs will successfully grow their businesses exponentially (Acs and Mueller, 2008). Rather than focusing on ‘gazelle’ firms that have increased their revenues 20% annually for at least four years, starting from a base of US$1 million, it may be a more productive strategy to promote a healthy entrepreneurial eco-system that supports a diverse array of ‘high potential’ female-owned firms from which gazelles can grow. We define ‘high potential’ female entrepreneurs as those who exhibit characteristics associated with high growth outcomes but which may currently be an aspiration rather than an achievement. Thus, high potential female entrepreneurs are ‘market expanding, export oriented, innovative’ entrepreneurs (Acs, Szerb, and Autio, 2014).