MIT's Innovation Secrets

The fact that MIT innovation, entrepreneurship, and industry collaboration have significantly impacted the world’s innovation economies is well known. The Boston Globe's list of the top 50 of MIT’s ideas, inventions and innovators that helped shape our world include the disposable razor, radar detection, the spreadsheet, email, the transistor radio, and the world wide web. There have been 87 MIT-connected winners of the Nobel Prize, the last was the economics prize awarded in 2017. Several entrepreneurs are likely future candidates, notably Professor Bob Langer (chemistry) and Professor Andrew Lo (finance). MIT’s global impact is indisputable, but has been slightly stealthy as compared to other schools.

MIT’s technological breakthroughs, and some of its faculty are well known, for instance public intellectual, Noam Chomsky, or Leader of the Human Genome Project, Eric Lander. However, the most visible impact of MIT today is perhaps not the research on campus, but the impact felt through its innovation focused industry partnerships, alumni and spinout companies.

According to the MIT Entrepreneurial Impact Report (2011), MIT alumni have founded 33,000+ companies, those companies represent some 3.3 million jobs and they make up a combined $2 trillion in annual world sales (equivalent to the 11th largest economy in the world).[1] Now, that report used some very creative extrapolation, but it remains plausible to say that MIT is connected to thousands of startup companies. I have personally worked with around 1500 of them. These startups have many paths, starting with having licensed technologies from MIT’s 150+ Departments, Labs, and Centers, through having a MIT faculty, non-degree MIT connections such as postdocs or postdoc alums, Visiting Scholar/Research Affiliates, executive education or professional education course certificate holders or startups where MIT Faculty or Staff is on the Board of Directors. The sheer magnitude, by any measure, is breathtaking.

Bloomberg innovation index ranks MA the most innovative state in the US. In 2016, Philips moved its research hub to Cambridge. In 2017, GE moved its headquarters to Boston. Many others moved or are moving significant R&D activity to the area (Amazon, Google, Pfizer, Novartis, etc.). These efforts help leverage booming innovation activity in the Cambridge/Boston area.

The notion that MIT has an almost unparalleled innovation ecosystem is something everybody “knows”, at least in Boston. Even mighty Harvard is playing catchup; Harvard’s Innovation Lab (iLab) was founded in 2011. The Harvard Paulson School of Engineering and Applied Sciences will expand into a purpose-built facility in Allston as late as 2020. Despite some early wins, their response to innovation is still in the making.

In Silicon Valley, of course, it is different. I once approached the event staff of a Silicon Valley innovation network event and she asked me where I was from. MIT, I said “Is that a college in California?”, she proceeded. I did not dignify that observation with an answer. I just looked straight ahead, dumbfounded. Silicon Valley is different. It is its own epicenter. Stanford is the only school. Palo Alto the only true epicenter, although small, on the inside of it all, and San Francisco the only acceptable city to be the container where all the innovation is poured through and presented for a larger audience.

What that experience taught me was not to drink the Kool-Aid. At that point, I had worked at MIT for at least three years. I had started to internalize the aura of MIT. No more. However, my slight challenge, was that selling that Kool-Aid was an instrumental part of my job. I was representing MIT’s Corporate Relations Office in their important efforts to convince corporations worldwide about the value of partnering with the world’s top technological institute. My colleagues and I would say things like “it is difficult if not impossible, coming from the outside, to keep pace with the rapidly changing research landscape at MIT”. We would imply that keeping pace was indispensable for any corporation, otherwise, they would be outpaced by technology, or worse, by their competition.

My job was to build out a new program, the MIT Startup Exchange. Working in close partnership with the 75-year old MIT Industrial Liaison Program (ILP), we provided targeted and facilitated access for our members to more than 1500 MIT-connected startups. I had built the program from an Excel sheet of startup URLs to a community with trusted connections to startup founders and a set of services. The preceding year, over 600 meetings were arranged and several partnerships were announced between ILP member companies and MIT-connected startups.

What is the secret of MIT’s innovation ecosystem? In a word: overlap. Spades of it. Because it is decentralized, because everyone wants to just do their own thing, there is little coordination.

Coordination is generally bad for innovation.

When there is no coordination, interesting things start to happen. Spill-over effects. Coincidences. Competition. If you can choose between five breakfast meetings or fifteen lunch meetings, all offering free food, which one will you go to? Clearly the one that has the best combo of food, networking, and proximity—and feel good factor. These decisions mean that the best events draw the best audiences, obviously, and you get the audience you deserve. It’s like any market. However, in order to have such market dynamics occur, you need scale and proximity. Research out of MIT Sloan has documented that just being in the Kendall Square zip code significantly improves a startup’s success rate, speed to funding and exit.[2] Why is that? The appeal of Kendall Square as it has evolved over the last decade from an industrial wasteland, is the sheer availability of resources, the talent, the social scene, and the choices. It is a technology hotbed and a commercial real estate paradise.

Here we are, in the middle of the second internet revolution, pondering the industrial internet of things, connecting devices, cars, infrastructure, even borders, to the web, and more importantly allowing more autonomy to people, teams, and organizations than ever before. People here are starting to feel that we are in a historic moment where it all ‘comes together’ around us, in terms of technology and entrepreneurship.

I literally mean the very surroundings of MIT’s campus; Kendall square is booming. One MIT startup, the fabulous quant hedge fund Domeyard LP run by Christina Qi, told me choosing an office in a downtown skyscraper instead, came at a 30 percent discount to a Kendall square address. The downtown location does not stop Domeyard from pioneering high frequency trading using advanced big data techniques inaccessible to mainstream fund managers.

Boston/Cambridge may not have a Silicon Valley but it does have a Kendall Square with an unmatched proximity factor not requiring a minute spent in traffic—a community of offices, labs, residential towers, restaurants, and retail shopping, and open space for espresso, networking lunches, concerts, a farmer's market, a canoe/kayak rental, a river walkway being renovated and more. What’s not to like. This is innovation on steroids. Corporations are flocking to the area, hoping to get inspired, or even connected, to this vibe, which is considerably more difficult.

In Annalee Saxenian’s classic study Regional Advantage (1994), she concludes that Silicon Valley is superior to Boston 128 as an innovation ecosystem because of its informal relationships, proximity between firms, competitors and capital, as well as risk appetite having to do with the outsider status of upwardly mobile Californians as compared to the “established” elites on the US East Coast.

Arguably, this is Boston’s decade to prove all of this wrong, or at least to indicate that the region has evolved. The very same proximity logic Saxenian described is playing itself out in Boston, starting in Kendall Square around MIT, and stretching into downtown and into the city’s Seaport District which then Boston Mayor Thomas M. Menino declared his in his 2010 vision to redevelop into a new “Innovation District.” This vision has largely come true. Boston’s Innovation District has brought more than 5,000 new jobs to the area since 2010.

If there is a secret behind MIT’s innovation ecosystem, it is the unplanned redundancy.

Planned redundancy is futile. You cannot plan innovation that way or indeed at all. Innovation happens despite planning, but when multiple sets of actors and resources somehow play together (and occasionally against each other) in order to create a dynamism of competitive collaboration. Innovation can indeed only be observed by its aftermath and in retrospect.

Attempting to copy other regional ecosystems, notably Silicon Valley, nearly always fails.

These efforts invariably target the wrong thing; copying behavior or trying to recreate institutions that only arose because of a local unmet need or from a dedicated group with a grievance. Taking inspiration from other places is not wrong. The copycat mentality is often wrongheaded. Copycat behavior is much more rewarding when it comes to relatively simple things like producing products cheaper or taking a working product to another geography. It fails miserably when human dynamics are an integral part of the local practice.

The next wave of tech innovation is already causing disruption. Digital machines foster autonomy, artificial intelligence, and people analytics. Material machines change the fundamental characteristics of fabrics and fibers. Hybrid machines combine hardware, software, and sensors to create powerful mini factories. MIT right now has critical mass of each as they are starting to work together. But even if that secret's out, copying it would take decades of hard work and serendipity.

[1] Roberts & Eesley (2011), Entrepreneurial Impact: The role of MIT – an updated report, https://ilp.mit.edu/media/webpublications/pub/literature/Entrepreneurial-Impact-2011.pdf

[2] Fehder (2016), “Evaluating Entrepreneurship Programs: Theory and Evidence” by Daniel Fehder (2016), MIT PhD Thesis file:///C:/Users/Yegii_H1/Downloads/960802466-MIT.pdf