All Fired Up in Massachusetts: The State’s New Wave of Big Data Companies

Stephen O’Leary, managing director of Aeris Partners LLC

“I don’t think I’ve ever seen Kendall Square as vibrant as it is right now.”

As managing director of Aeris Partners LLC, Stephen O’Leary spends most of his time on mergers and acquisitions of tech companies: application and infrastructure software, analytical software, business information, digital media companies. Aeris is based in Kendall Square, an area of urban Cambridge, Massachusetts, that’s bursting with IT companies. (Kendall Square is also home to the Massachusetts Institute of Technology and MIT Sloan Management Review.)

O’Leary also serves as a trustee and member of the executive committee of the Massachusetts Technology Leadership Council (MassTLC), a business association focused on “fostering entrepreneurship and promoting the success of companies that develop and deploy technology across industry sectors.” O’Leary was MassTLC’s chairman in 2009 and 2010.

During his tenure as MassTLC’s chair, O’Leary ushered in the “MassTLC 2020 Challenge”: An effort to spur the state’s technology industry to create 100,000 new IT jobs and an additional 163,000 related non-IT jobs over the next 10 years.

In a conversation with David Kiron, executive editor of Innovation Hubs at MIT Sloan Management Review, O’Leary talked about why the Kendall Square region of the state is so hot, what new companies he’s paying attention to, and why he’s especially intrigued with the idea of embedding power sources right into the nation’s highways.

Let’s start with MassTLC’s call to grow employment in the information technology space in the state from 178,000 to 278,000. What metrics did you start with to come up with that 100,000 number?

We started with a study on Massachusetts employment initiated by the Massachusetts Technology Collaborative and developed by the University of Massachusetts Donahue Institute, under the leadership of Mike Goodman, an economist at UMass Dartmouth.

When MassTLC took a look at this study and started to analyze the nature of the industry in the state, it was readily apparent that we had some really good, fundamental innovation resources here.

Obviously, we’ve had a 30-plus year history in the technology space as a region. Secondly, we have the second-largest venture capital cluster on the planet. And third, we have a wealth of universities that any location would die for.

The Kauffman Foundation prepares a study, the State New Economy Index, that it publishes periodically. In this study, Kaufmann ranks each of the states by its ability and demonstrated performance in innovation. Massachusetts has come out number one in this study over the five times it’s been run, and the trendline across these studies shows a widening lead over the number two state. The 2010 report, which is the most recent, used 26 indicators to look at what’s going on in the New Economy, like knowledge jobs and technological innovation capacity. It’s a really interesting report to look at in the aggregate.

What’s so exciting about the current environment — current being since almost two years ago, when we put the MassTLC 2020 Challenge together — is that there is a remarkable movement of companies into the Kendall Square / Cambridge area and into Boston’s Seaport District. Hewlett Packard is moving Vertica into Cambridge. Staples is moving its worldwide eCommerce center here. Oracle has bought Endeca and ATG to bolster its presence in analytics and retail. Of course, we’ve got Microsoft and Google and Akamai here. It’s really been amazing. And we have startups and venture capital firms moving in. I don’t think I’ve ever seen Kendall Square as vibrant as it is right now.

So as a business association, MassTLC has tried to seize upon this energy and the growing density of our innovative companies. We look at the different clusters that are emerging.

What we see is that although Massachusetts generally missed the social media wave, there’s a whole new wave of analytics-driven companies emerging. A MassTLC study that we just completed identified some 100 companies that are either in the big data tools area or leveraging some element of big data to create industry applications. That’s a big, big base. [See MassTLC’s report “Big Data and Analytics: A Major Market Opportunity for Massachusetts” (PDF) for statistics and a listing of Massachusetts companies in the big data field.]

What are some of the big data industry clusters that you’re seeing?

Probably the most prominent are in life sciences. There seems to be a movement in life sciences away from laboratory-based discovery to data-based discovery.

The Chinese company Beijing Genomics Institute opened a U.S. subsidiary in 2010, BGI Americas Corporation, right in Kendall Square. My understanding is that it’s creating a database of large numbers of genomes or parts of genomes that will then be used as the target for data inquiries to figure out what compounds may impact these genomes favorably or unfavorably. The whole idea is to create new treatments and new approaches to agriculture, human health or animal health and environmental management,

I think data-based discovery, from a layman’s perspective, using either some kind of large-scale simulation or a more targeted analytical approach to identify opportunities represents a more economical process. When you get away from the laboratory process and have smart people run the analytics, it seems to me that there’s much more leverage in it.

I’ve seen other established and emerging life sciences companies that are using data-driven approaches. It’s interesting, because what is a DNA strand anyway but some kind of a code with four elements in it, arranged in different sequences?

So life sciences is one hot industry sector. What else?

Healthcare is another cluster. We don’t really talk about the Internet of Things here in North America, but it’s a very common topic in Europe. The European Union has published a number of articles on the Internet of Things, where the basic idea is that the physical world can be instrumented with sensors that will be cheap, pervasive and Internet-connected. That creates the potential for different ways to monitor lots of things, including people’s health.

Say you go and see a doctor once a year for a physical and he measures your cholesterol. That’s one data point that could be highly subject to what you’ve eaten in the last three days. But if there’s a way to capture a series of readings over time, that could be interesting. That’s where monitors come in.

Of course, there are all sorts of privacy issues, and significant societal differences in countries’ willingness to adopt technologies that infringe on certain kinds of privacy. For example, in some countries, there might be a willingness to have sensors on the streets to look at all the cars because they care so much about catching terrorists. In the U.S., more people might get upset by that.

How do you think about some of the societal implications of these new innovations across countries based on cultural tendencies? This is beyond straight business talk, but there is a connection, because you can’t build a business unless people are willing to pay for it and governments are willing to let it on the market.

On the healthcare side alone, would I prefer to be more healthy than less healthy? I think I’ll take the former. And so, to me, it would be relatively straightforward to provide some data in exchange for getting better predictability. The problem with our medical system today is it’s highly reactive, not proactive about fixing things or identifying problems. I think medicine has the potential to be transformed.

Someday, probably not too far from now, we’ll have electronic medical records and large data sets of information that people can use for testing purposes and survey purposes. This seems a logical area for predictive analytics.

When I was in the Navy, we would get these very sophisticated analyses from our sonar system. I should say sophisticated for their time. The database matching was based upon trained sonarmen listening to sounds and looking at a time-series of data and saying, “Oh, this is Soviet Victor-class submarine,” or, “It’s such-and-such a ship because it’s got this such-and-such characteristics.” You needed a really smart sonarman for that. Today I’m sure it’s something a machine could do almost instantly. That kind of intelligence processing is obviously part of what this big data thing promises.

What other companies are you excited about?

There is a company called WiTricity, run by a Harvard Business School graduate named Eric Giler, based in Watertown, right next to Cambridge. To me, this is a really interesting company. Their tagline is, “wireless electricity delivered over distance.” They have a device that allows you to charge your mobile device without plugging it in or putting it on a pad. As long as it’s within physical proximity of a charging device, it will charge through a kind of induction.

Sounds crazy.

Giler has this demo that he gives when he’s talking to audiences. He puts the charger on one side of his head and then an electric-powered device on the other.

And you can see the meter go up?

Yeah, you see the induction go right through his head. He claims he’s done it enough times that if it was likely to be harmful, it would have done something to him already.

To me, a big question is, when are we going to see this embedded in highways? I asked him that a few months ago, and he said, “Funny you should mention that. I’ve been asked to go speak at a conference in Colorado about that capability.” The big idea is that we’ll have a battery in the car, and a power source embedded in the roadway.

Brilliant.

It’s really cool, but it also creates an information and big data problem, right, because you’ve got to track the consumption of this electricity. Odds are you’ve got to have something that drives the car a little bit more efficiently than a driver will, so that goes all the way to the point of cars that drive themselves, which probably will happen at some point in the future.

Google has cars like that.

Yeah, they have the self-piloting vehicles, but think about coupling that with a power source so that they can basically go as long as they want to on the highway with all the power coming from the highway.

Let me go back to what I asked you about before, which is how you see the collaboration between business and governments working. These kinds of innovations can only work if there’s a solid collaboration. Are these innovations deepening or otherwise making more enmeshed the relationships between business and government?

I guess innovation can’t help but make a tighter coupling between business and government because, of course, the biggest problem that urban areas face right now is budget constraints. Things have to be done more efficiently. Ideally, governments will serve a higher-density population because the more revenue per square meter, square mile, whatever, the better the quality of service that can be delivered.

Edward Glaeser is a Harvard professor who really knows this stuff. In his book, Triumph of the City (The Penguin Press HC, 2011), he addresses the future of cities, about ever-increasing high-rises, greater and greater density and the correlation of density with economic success. Of course, cities need to manage the density, but if there is an ability to scale and deliver services more cost-effectively, then density makes great sense.

Collaboration is an interesting thing. From my perspective as an M&A guy in the technology industry, what’s so interesting is the value-creation potential if you put certain organizations together. You start with a company that has a product that will scale very cost-effectively and serve many, many users, and you couple that with an organization that has distribution, and you get tremendous, almost instantaneous, value creation.

Analytics is giving organizations so much more power in analyzing things like those sonar images you used when you were in the Navy or when the trade-offs start to shift in density in cities.

Yeah. When you check in for an airplane, it’s rare that you interface with a desk agent now. You go to a kiosk or you print out your boarding pass on a PC or you display it on a mobile device. And there’s a ripple effect. As McKinsey notes, the act of online check-in and printing out the boarding pass triggers a process to address weight distribution in the aircraft. Whether you’re checking a bag or not addresses the luggage-carrying capacity. It addresses your frequent flyer status and calculates how much you’ve flown.

You see analytics in the evolving science of retail store site selection. It’s not a coincidence that you have AT&T and Verizon and Sprint and T-Mobile all on the same street corners almost everywhere you look. That’s often done with spatial analytics. Home Depot locates every one of its stores using spatial analytics.

You don’t get clusters of cell phone retail stores just because their competitors are there in the same space?

No, no. It has to do with local attributes of the demographic groups, the drive-time distance or commute distance to that store, the traffic density. All these different dimensions draw insight from data. And data are exploding. The collection and the retention of data today are at an unheard of scale.

The new Internet protocol, the IPv6, has the potential for so much more connectivity. We did a quick analysis that we didn’t include in our big data study, but the number of potential Internet addresses supported by IPv6 is within a factor of a trillion of the estimated number of atoms on earth.

That’s some data point.

Yeah. There are an estimated 10⁵⁰ atoms, and there are approximately 10³⁸ unique IP addresses.