Subscribe/Feeds

• Subscribe by Email
• Subscribe in a Reader
• Subscribe to Comments
• Become a Facebook Fan
• Follow on Twitter
• View Photos
• Watch Videos

Search

Wednesday, January 18th, 2012

Silicon Valley vs. Silicon Alley, Economic Security, Guadalajara

I have a few miscellaneous items for you today. First I’ll highlight this brief piece from Chicago reporter Tracy Swartz, who rode all 139 Chicago bus routes end to end.

Next, an interactive infographic on Silicon Valley (California) vs. Silicon Alley (New York). I clipped it slightly to fit my blog template, so to get a full sized version, or if it doesn’t display for you, click on over to the University of North Carolina site where it came from.

Economic Security Report Card

The Urban Institute also put out an interactive map that let’s you explore economic security in US metros. They’ve got various factors that go into this, and while you can’t add your own, you can adjust the weightings on theirs to create your own overall score. This one won’t fit on my page, so you’ll have to click on over to check it out. Here’s a static screen shot for you, however.

Via RecreActiva – Guadalajara’s Ciclovia

Streetfilms did a nice short piece on the the Ciclovia program in Guadalajara, Mexico’s second city. (If the video doesn’t display, click here).

Wednesday, December 14th, 2011

Planes, Trains, Automobiles, and Silicon Subways

Flowing Data carried a very interesting infographic showing Foursquare checkins on planes, trains, and automobiles across the United States. Check it out:

New York’s Silicon Subway

NYU’s Rudin Center also put out an interesting infographic, this one of technology startups in New York mapped along the R-train subway:

Thursday, October 20th, 2011

Announcing the Walk Indianapolis Architectural Tours

I’m pleased to be able to tell you all about another civic project I’ve been working on for some time, the Walk Indianapolis architectural tours.

These were inspired by the delightful guided tours of Chicago sights provided by the Chicago Architecture Foundation. Those are awesome, but Indianapolis doesn’t have the sheer volume of visitors or sites to make that model work locally. Instead, we decided to provide tours using a self-guided, mobile device enabled model. We recorded local architects giving overviews of significant buildings and public spaces, then made those available to be consumed on the web via audio or text, or for download to your mobile device to take with you as you walk the tour route. There’s full integration with iTunes simple downloads. (Click here to check out the downtown landmarks tour, for example).

There are two tours up presently, but hopefully more to come. I’ve already had inquiries from those looking to contribute additional content. So we’ll see what happens. You may also want to check out a similar and more extensive project out of Los Angeles called Downtown LA Walks.

This was a project I originally proposed in my Pecha Kucha presentation “15 Quick, Easy, and Cheap Ways to Make a Big Urban Design Impact in Indianapolis.” I decided to take this one on myself because I figured even if I couldn’t find anyone to help me, I could do 100% of it myself.

As it turns out, most of what I had to do involved just asking others for help. This was a joint production of many volunteers including Jeff Robinson at the Indianapolis Convention and Visitors Association (recording, web hosting, and project management), Sarah Hempstead at Schmidt Associates architects (scripts, narration), and Nathan Sinsabaugh and his team at Kristian Andersen and Associates (web design). The AIA Indiana chapter also contributed to the projects, as did Sanford Garner of A2SO4 architects (narration), Jonathan Hess of Browning Day Mullins Dierdorf architects (narration), and Megan Fernandez at Emmis Communications (editing and fact checking). Thanks to all of them for making this a reality. It turned out not to be quick – it took two years – but it was cheap (i.e., free) thanks to all of them.

I think this is but one example of the ways we can use digital media and mobile device technology to enhance our experience of public space, and to just plain make our cities more functional. When you think about the transit tracker apps, the augmented reality navigation systems, etc. that are out now, you can see we’re on the verge of something big. It’s something every city and lots of entrepreneurs ought to be looking at.

Related: Announcing the Indianapolis Neighborhood Map (another project I worked on I’d encourage you to check out)>

Sunday, October 9th, 2011

Review: The Gated City by Ryan Avent

Update: Ryan posted a reply to some of the points I raise here. It’s definitely worth reading.

The Gated City is a mini-ebook by Ryan Avent that makes the case for removing restrictions on densification in cities. In addition to being a left-leaning economist, Avent is also a journalist who is an editor at the Economist magazine and a principal contributor to its Free Exchange blog.

Avent’s journalism skills make him one of the more articulate and easy to read economists out there. This book brings Avent’s signature readability to the table and also has the virtue of being brief. This makes the book very much a recommended read. To me though that is as much for his introductory treatment of the economic value of cities as it is about the virtues of density. The primacy of urban regions in our new economic order is something that is hardly a matter of left or right. But I continue to be amazed at how few policy makers actually seem to know or care about this, particularly at the state level. Our governments continue to implement policies that are not just indifferent to the success of our cities, but in many cases outright hostile to them. More reminders of the real state of affairs are clearly needed.

Having read several other reviews of the book, I was expecting big and controversial claims to be made for density. In fact, Avent’s claims for the benefits of increased density are fairly modest. He suggests that removing artificial barriers to urban density might raise the growth rate in GDP by 25 to 50 basis points. That’s not a radical amount, though of course compounded over time adds up. He also doesn’t claim that more density is always better, that we should all live like Manhattanites, or that he professes to know what the optimum level of density is. In fact, he explicitly disavows all of those. He also says that he doesn’t care where people personally choose to live, and, while I would have preferred to see a more forthright statement on policies like urban growth boundaries and such that actively restrict suburban development, Avent does include New Urbanist critics of suburbia as among those who want to more strictly regulate land use.

In short, Avent more or less wants to reduce barriers to densification such as zoning, FAR limits, historic districts, etc. in order to allow the market to determine the optimum level of density. He hypothesizes that this would lead to an increase in density overall, and given that both the goal and practical result of much planning practice is to restrict density, I agree. (See: Planning and Free Market Density). While clearly Avent is sympathetic to urbanism and densification, in this book at least he makes a clear effort to avoid statements that might suggest he wants to force density.

On the whole, I’m personally very supportive of Avent’s goals here, though of course the best course for overcoming the huge structural biases against density is still speculative.

There are a few areas that weren’t clear and that I weren’t quite as sold on. One of them is that in some cases Avent talked about employment density and in other cases residential density. Those might be related in many cases, but I don’t think they are necessarily tightly linked. Most of the economic benefits would appear to occur from employment densification not necessarily residential. For example, until fairly recently, Chicago’s Loop business district was almost exclusively office oriented and had little residential density at all. While adjacent urbanized areas are higher density in terms of people, I don’t believe that’s the only factor supporting the Loop economy, or even the most important. (See: The Big City CBD Advantage and Employment Challenges Facing Small City Downtowns). Fully distinguishing between employment and residential density in terms of impact and policy would have been helpful.

Another is that the book heavily focuses on the supply side of the equation (i.e., the ability to build) as opposed to the demand side. But arguably demand had a bigger role to play in driving up housing costs in places like NYC. It came as no surprise to me that the metros Avent cities most in his dense cities list were New York and San Francisco. Those places are home to the two most successful macro-industries of the last 20 years in terms of wealth generation for their practitioners – finance and high tech. Avent notes increasing income inequality and stagnant wages for the majority. This by itself explains why the middle class is increasingly priced out of these cities. When the Fed pumps $14 trillion into propping up the financial sector in the last handful of years, it’s not unrealistic to expect that to show up in New York area housing prices. No amount of new supply would have been able to keep up with the significant deregulation of finance that occurred in the last two decades (repealing Glass-Steagall, raising the ceilings on the share of national deposits held by a single institution, etc) and Helicopter Ben’s printing presses.

Also, assume we were able to moderate the price of housing in these places somewhat. What would that do for us? Well, NYC and SF would still remain among the most expensive places in America to live. This means that they are going to continue to draw principally those who are able to tap into the particular wealth generating functions of those regions, along with those who particularly value the amenity set of those cities or who are following network path migration. However, the industry groups that are now predominant in those cities are ones that employ almost exclusively high end labor. So what this would mean in my view is that instead of say the top 1% being able to live and work in these places, we extend that down to the top 2% or 3%. That might add more new net economic growth, and even benefit the people who fall into those newly eligible brackets, but a few more near luxe jobs aren’t going to solve the fundamental problem of employing middle class Americans and restoring the engine of upward social mobility. The factories that used to be a big part of the economic life of Silicon Valley are now gone, and they aren’t coming back no matter what building restrictions we remove. Even if we could grow employment there, it would be almost certainly be more jobs for those who, as Joel Kotin put it, “already reside at the apex of society or expect to soon” thanks to their education, skills, or family connections.

With the current economic development paradigm for tier one cities emphasizing talent, higher end activities, and “global city” type affairs, I also question whether local leaders would actually want to make it easier for what are basically lower end activities to take place there. Everyone seems to want to keep climbing the value chain, not descending it. If you lower prices, you open the market to more economically marginal people and activities, and thus lower items like per capita income and GDP, unless somehow on a lifecycle basis this somehow changes the overall economic structure of a region (which would probably raise housing prices again….)

Another part of the challenge is that the business models of high tech and finance have evolved to thrive in an environment in which they a) now find themselves in a globally competitive market and b) have to pay for sky high real estate and expensive people in SF and NYC. I’m most familiar with tech. I’ve written before how the onshore tech market has reinvented its business model to focus on lean methodologies, design, being close to the customer, and rapid iterations. When you combine this with innovations in open source frameworks and cloud hosting, the average web company simply doesn’t employ that many people these days, and likely will never scale its labor force by much because the economic model of something like SaaS is almost 1:N – virtually all costs are fixed. (See: More Thoughts on the Programmer Shortage).

So to really boost employment, we’d need more than just cheaper land making labor more available at a reasonable cost. That might provide some boost. But we would also need business model innovation.

One nitpick: the choice of Phoenix as the primary example of a low density city wasn’t one that resonated with me. When I think of Phoenix I think of a retirement or leisure community, not a business center. Texas cities like Houston would have been a better choice. (Avent does mention Houston at times, however).

Avent doesn’t exactly slam sprawlvilles like Houston, but he has a clear affinity for the high end city. I can’t really begin to address this, but a few things come to my mind. Firstly, the amenity gap between cities can be seen partially in terms of life-cycle. While certain things like the collections at the Met can never be reproduced in a place like Houston, that city will only grow more sophisticated and amenity rich over time. Cities almost invariably get rich, then decide they want to use some of that money to buy class. It was true for Chicago, and it’s increasingly true now in places like Houston and Dallas, as well as emerging market cities around the world.

Second, how much of the perceived productivity of places like NYC and SF result from them having excluded all but high end activities in the first place? Houston not only has its energy cluster that has created fantastic wealth there, it has also managed to build a city where workaday businesses can do their thing. If a similar range existed in the Bay Area, it would look a lot less impressive in its stats. While it might make sense that transplanting tech works to Silicon Valley would make them more productive, it’s not clear that would be the case for workers in most other sectors. Whereas in Houston not only can the energy worker be more productive, other types of businesses and workers aren’t chased away. I’m sure he’ll correct me shortly, it strikes me that Houston could in fact be very much what Avent wants to see. It’s home to a powerful macro-industry cluster – energy – but has low enough housing costs that it doesn’t deter people who want to work in that sector from coming to Houston.

Third, Avent does believe increased density pays dividends across the board, so even places like Houston would benefit from raising their densities. And suburban type densities are very easy to raise without fundamentally changing the built form or quality of experience that people have there. So long as somehow this didn’t end up compromising Houston’s low housing costs, presumably even Houston itself would benefit from more density in Avent’s view. I mention this lest I leave the false impression that this book is all about a handful of already very dense places.

One last comment: I did not see rent control mentioned anywhere in the book. This is clearly a factor in the housing markets in both NYC and the city of San Francisco.

My main takeaway was that if we increased housing supply, we could boost the labor force in proximity to some high value economic clusters that are critical to the US economic future. Avent’s belief in the benefits of density are broader, but this is what it stressed. While I agree with the policy goals, I find it difficult to believe that what amounts to some marginal benefit is going to be sufficient to overcome the vast anti-density inertia and structural forces out there. Nor do I believe that this fundamentally solves the economic problems facing the United States, especially boosting employment over the long term, raising middle class wages, and addressing the broken engine of upward social mobility. What Avent’s prescription amounts to is tweaking the dials on the engine to squeeze out a few more horsepower. That’s a worthy goal and a potentially useful action, but only a small part of the solution to the challenges we face.

Friday, September 16th, 2011

New York Stands High

Crain’s New York Business recently released its 2011 City Facts compilation and chose to title it, “New York Stands High” as they found much to celebrate in the numbers. Among them:

• The most incredible stat to me is that NYC jobs in 2011 fell only 56K short of their all time peak in 1969. If the economy ever gets back on track, this seems likely to only go up.
• Despite its roots in a financial crisis, Crain’s labels the recent recession as “The Great Recession That Wasn’t”, describing it as “one of the mildest since WWII” in terms of NYC job losses. This will no doubt infuriate bailout skeptics.
• The number of companies operating in downtown Manhattan now surpasses its pre-9/11 total. Rents have been stagnant, however and vacancies are projected to climb.
• The tech sector finally surpassed its dotcom/Silicon Alley level peak in 2000, and NYC is on the verge of overtaking Boston as the #2 destination for tech venture capital investment.
• Though some claim many people were missed, the 2010 census showed an increase in NYC population and the city is now at an all time population high.
• The population is increasingly diverse, with, for example, Asians now accounting for over one million city residents.
• The population of downtown Manhattan grew by 150% between 2000 and 2011. Downtown apartment prices have more than doubled since 9/11.
• Between 2007 and 2011, national home prices dropped by 19.1% from peak, while Manhattan apartments actually went up 9.1% in price.

The numbers aren’t uniformly good for the city, but it has performed very well comparatively. I think this illustrates more than anything the emerging two-track economy of which we’ve read so much, which is fueling an ever widening income gap, etc. What’s good for NYC isn’t necessarily good for America, and the model of success represented by the city (as well as other outliers like Washington, DC) simply can’t be replicated elsewhere. Thus these places don’t really represent a model of success for others to emulate, and they have only a limited amount to say on what urban policy should be elsewhere. Nevertheless, in a global economy, America does need places like NYC and Silicon Valley to be as competitive and prosperous as they can be. The challenge is how to bring about a more broad based prosperity that provides jobs and upward mobility to average Americans.

Wednesday, August 31st, 2011

VC Investments and More Thoughts on the Programmer Shortage

The Wall Street Journal put up an interesting interactive map of the “United States of Venture Capital” that tracks VC investments in the first six months of 2011 by metro area and industry segment. Check it out. The opening screen shot is above. (h/t Richard Florida).

My previous post on the so-called “developer drought” prompted some very interesting comments you may want to read. I wanted to share a couple of follow-ups.

While I said that I thought the notion of a “drought” is overblown, it is true that there seem to be fewer developers than in the past and that we are having difficultly scaling up the developer pool in the way that we did say in the dotcom boom. I have a few thoughts on why this might be.

Firstly, there are multiple sources of demand for programmers: tech companies, consultancies, IT departments, etc. While demand seems to be robust on the tech company side and in various tech specialties, there have really been some huge changes in the consultancy and IT department markets that have depressed entry into the programming field and even prompted people to exit it.

Most notable is the rise of offshore development. As recently as 2001 or so, pretty much all development was done onshore. Then the bottom fell out of the dotcom market, the Y2K bubble came and went, and the Indian outsourcers came onto the scene with a vengeance. Today, there’s an enormous focus on the consulting and IT department sides of the house to move as much work as possible offshore, because the costs are so much lower. And having done development with teams in India, Spain, and Argentina, I can tell you the talent is solid and the motivation levels high in those places.

Along with that, we’ve seen the rise of a theory that says, as one famous article put it, “IT Doesn’t Matter.” The embedded notion is that IT is becoming more of a utility and less of a differentiator, thus the focus will switch to managing it like any other cost. That is to say, cut it as much as possible. This is certainly no universal view, but is influential in many respects.

And corporate IT hasn’t changed its fundamental paradigms as frequently in the 2000’s compared with the 1990’s, leading to the commoditization of many functions such as screwing in SAP systems.

Give America’s youth some credit for getting it on this one. They saw the long term trend here and decided to say No, Thanks to that type of career. They watched what happened to manufacturing as a 30 year squeeze that has yet to abate (and likely never will) made it a tough and increasingly poorly paid sector in which to work and in which you constantly walk around with a target on your back. Fear of that happening to them looms large. I have a friend who was on the advisory board of a Big Ten business school. That school at one point had seen enrollment in its MIS program drop from 300 to less than 30 and the school was contemplating dropping that program altogether. The days when Andersen Consulting would hire thousands of bright people off campuses, put them through boot camp to teach them the basics of coding, then send them off to move mountains are over – at least in the United States. I think we probably have seen a large drop off in the number of people entering the tech profession.

Now you might be saying to yourself, “IT? MIS majors? What the heck is that? I need real programmers.” And therein lies another trend I observed, namely the increasing estrangement between corporate IT and the tech world, and the resulting desire for not just programmers by tech companies, but a certain type of programmer.

As the IT world went one direction, the tech company world went another. Open source LAMP-stack architectures sent the cost of software to zero for a new web company. The rise of cloud computing has driven hardware and hosting costs to near zero as well. This dramatically reduced barriers to entry. Also, while corporations stayed close to home with Java and .NET, a lot of the rest of the world moved on, to architectures like Rails and platforms like iOS and Android instead of the web. This caused a reconstituting of what a startup looks like and even spawned new philosophies and methodologies of software development such as the “lean startup” and 37 Signals “Getting Real.” A lot of the success of these companies is rooted in understanding the user/customer and design (perhaps inspired by the success of Apple), as well as rapid iterations – things still done best in America.

My own Telestrian app is an example of what this new world has wrought. A decade ago, it would have taken millions of dollars to start a company. Today, I built Telestrian myself with sweat equity and a tiny amount of cash for point assistance (such as my lawyer) under a bootstrap model.

These two evolving paths have driven a wedge between the IT/consulting model and the tech model, and to some extent bifurcated the labor market and the culture to an extent far greater than in the past.

One commenter on the previous post noted: “The developers that startups want to hire are a special breed: broad and deep technical skills, very current on technology and practices, ambitious and self-directed, derives satisfaction from the startup’s vision so they will work for less $$, good communicator, proven track record of success.” This shows that tech startups are increasingly focused on a narrow model of developer to staff their teams.

I think one of the challenges facing tech hiring is that tech companies have set up artificial boundaries around their potential labor force. Back in the dotcom days, we also had to radically scale up our programming staff at the macro level. But we did it. Sure, a lot of the people went into the field who shouldn’t have and they wrote a lot of crappy code. But you absolutely had to have an e-Commerce site, the CEO wouldn’t take No for an answer, and guess what? Lots and lots of stuff of pretty good quality actually got written in a very short period of time – and even without the architectures we have that today make it so much easier to do things.

Perhaps today’s models work in a certain sense, but if there isn’t the labor force to staff them, then maybe that model needs to be rethought. Perhaps we do need to raise more capital and be open to hiring from a broader pool of people, for example.

I think the dot com era holds two important lessons. Firstly, companies hired in bright people and let them grow into the positions and figure the internet architectures out. I see no reason why we can’t do this again today. I had lunch with the VP of Applications for a .NET IT shop in Chicago today and asked him point blank if he had problems finding .NET programmers to hire or as contractors. He said No. He uses mostly contractors these days, but there isn’t a shortage on the market. Why not grab some of the .NET IT guys who’ve shown they can develop code and teach them or let them figure out what they need to do for your Rails app or whatever? Another commenter said he’s had three open programmer positions for nearly six months and hasn’t been able to fill them. In six months, even a merely competent programmer could have cross trained to a new platform and gotten productive – and would probably be fired up about getting to do so. Again, remember, we took a lot of raw material in during the dot com era and ended up a lot of good tech stuff with it. And people want a job in which they can learn something new, stretch themselves, and grow. Hire one of those water walkers of the type profiled above and they’ll get quickly bored and move on for greener pa$ture$.

Second, salaries went way up during the dot com era. I think there was a misunderstanding by some on my point around pay. Raising wages isn’t just a method of reallocating a fixed pool of talent from banking to tech or something like that. In a typical supply curve, sellers are willing to supply more product at a higher price. A higher price attracts new supply to the market. There are lots of people who left the programming field for something else. Or like me got promoted into management. Or who are in legacy technologies and haven’t skilled up on something new. Or who are in school and trying to make up their minds about what to do. Etc. These are all potential sources of new or latent talent in the marketplace. The price signal is important to bring that potential supply into the marketplace, along with potentially some business/staffing model changes to make the tech world more appealing to those people.

Of course, whether higher pay attracts them also depends on whether they believe that those salaries are permanent or part of another bubble. People got burned when the dot com bubble blew up. Even today you read about another bubble. Once bitten, twice shy, so it will take time to convince people. But while there will always been ups and downs, I believe tech is here to stay in America. We just need to find out how to attract a labor force to it and build business models that work well with the labor force they can get.

Update: Check out this new piece over at New Geography: “Supply of Tech Workers Greater Than Estimated Demand”

Tuesday, August 30th, 2011

Is There Really a Developer Drought?

One of the most common memes I come across in the tech world is that there is a huge shortage of quality software developers out there. No matter the market – Silicon Valley, Chicago, New York – you’ll soon enough hear about the talent shortage.

For example, someone recently told me that if I wanted to work as a developer in New York, “I’d have a job by noon.” A couple of recent articles in Chicago highlight supposed challenges there. Technori notes that “the #1 question we get every day is ‘How do I find a good developer in Chicago?’” and they recently put a lengthy primer on how to find one. And Alex Wilhelm recently chimed in with a piece on “Chicago’s Great Web Developer Drought.”

But is the developer shortage really as bad as it is portrayed? I’m skeptical.

First, when someone says there’s a shortage of talent and that they can’t find a good programmer, what that shows me is that the market is actually sending a very clear and important signal: your salaries are too low. In New York, I hear that the banks have sucked up all the good coders. Well how did that happen? Maybe they offered a market price. What this tells me is that there isn’t a shortage of developers, just a shortage of developers willing to work for ramen noodle money in a very expensive city.

Not once in its lengthy advice piece on hiring programmers in Chicago did Technori suggest paying a generous salary. But maybe that ought to be the first thing you try. Wilhelm notes that Groupon has sucked up a huge amount of Ruby on Rails talent. But that’s not just because of the options. Groupon also pays its developers very well. Unsurprisingly, it’s fairly easy for them to recruit.

I think what’s happened in a lot of places is that in trying to build the next great tech hub, they’ve basically tried to copy the entire business model of Silicon Valley. But perhaps other places ought to rethink that. Maybe in Chicago people aren’t willing to work 24×7, sleep on a sofa, and make peanuts in order to have a shot at a big exit one day, someday, maybe. Perhaps in these markets the compensation focus should be heavier on cash money, at least for funded startups. You build that into your business plan and raise capital appropriately.

Realistically, if there are more would-be buyers than sellers, then the market price has to go up to bring balance. It’s that simple. I don’t think startups need to put a deal on the table that’s based solely on the headline salary. Startups are generally great places to work, let you do really cool and interesting stuff, and do offer upside potential. But the cash side of the equation can’t be ignored either. Because while one business model after another has been upended and destroyed by the globalized, networked age, there’s one thing that’s remained as steady as the Rock of Gibraltar: Want to secure someone’s services? Open your checkbook.

Second, my own personal experience makes me wonder how big this so-called “drought” could be, at least in Chicago. I personally coded an entire Ruby on Rails SaaS application (www.telestrian.com), wrote the only program ever I’m aware of to recover data from corrupted gzip files, co-founded and was a principal author of an open source, clean room implementation of the Java standard class library prior to Sun open sourcing Java, etc. Yet no one has ever even so much as inquired about hiring me as a developer. Granted, I’m not really looking to work as a pure coder. But if you are really as desperate to find a developer as you say you are, wouldn’t you be turning over rocks to find one?

Lastly, most development problems aren’t rocket science. Even if it’s hard to find Rails hackers, there are tons of solid, competent Java and .NET developers all over our major cities, even in corporate IT shops. Why not hire one of them and let them skill up on Rails? That’s basically what I did with myself. When I wrote Telestrian, I wanted to learn Rails too, so I solved both problems at once by buying a Ruby book, buying a Rails book, and starting to write code. (Incidentally, IMO Ruby is the best language I’ve ever used, at least from a programmer perspective). I think you could probably get a competent web developer on one platform doing useful work on a different one inside of a month.

Now we all know that a great developer is 10-100x as productive as an average one, etc, etc. But do most straightforward development problems require a truly elite programmer? I would suggest that most web site development in cities like Chicago or New York is not what Mark Suster has called “a San Jose problem” – that is, a problem that requires deep, arcane technical skills best brought to bear by a Stanford CS Ph.D. And for those, maybe you’d be better off going to Silicon Valley anyway. (Given the rarity of niche skills in some of these areas, I really can believe SV companies have some recruitment issues). For most problems, maybe there’s an answer closer to home. Because a good coder in one platform is likely to be a good coder in another after picking it up.

Obviously the better the programmer you can get the better. And I’d never suggest hiring someone that can’t cut it. But I think the talent pool is probably a lot deeper than we suspect.

Now I’ll be the first to admit I haven’t personally tried to hire any programmers lately, so I’m willing to be convinced that I’m wrong. And I’m not going to say there isn’t something of a tight market out there. But it strikes me that there can’t be the absolute shortage of talent that I keep hearing about. More likely, the aspiring tech communities in these cities simply need to bring their compensation in line with marketplace reality in order to attract that talent that already there out of the banks and other shops and into the tech industry. Please feel free to share your opinion in the comments.

Sunday, June 19th, 2011

Replay: Resolving the Paradox of Success

In a previous posting on innovation, I talked about how coming up with innovative new ideas is surprisingly easy. It is actually trying to do them that is hard. I pointed out many of the structural barriers to this, most of which lie in the realm of organizational dynamics.

One of the problems is what I call the “paradox of success”. That is, it is harder for someone, be it an individual or company, to do something new and different to the extent that what they are currently doing is already successful. This actually seems, like the Prisoner’s Dilemma, prima facie rational. The investment and level of risk one takes on by giving up something that is already working is much higher than giving up on something that’s failing. The probability weighted R might be the same, but the I is much different between those situations in an ROI calculation.

It comes as no surprise to me to hear entrepreneurs talk about starting a business after losing a job or going bankrupt. That lowers the risk threshold to the new dramatically. If you have to quit a six figure job to launch an uncertain new business, that’s a much more high stakes move. Similarly, I’m not surprised to hear people who found religion to say that they turned to Jesus after they “hit rock bottom”.

However, there is an underlying assumption about this analysis, namely that the future will more or less resemble the present and past. If that assumption is wrong, then the whole thing can break down. The subprime mortgage business seemed like a good one until it hit a wall. If you were in the vulnerable sub-sector of the housing industry, it might have made more sense to actually get out early and establish yourself in something new before you and everyone found yourself on the street. But I see little evidence much of this happened, whether that be in traders or real estate agents.

This assumption that the future resembles the past or that we can extrapolate trends seems to be buried deep in the human psyche. I noted before how this was one of the classic errors Dietrich Dörner identified in how people fail at complex problems. It’s always dicey to talk evolution. You can always gin up a plausible sounding evolutionary rationale for a behavior. But it does strike me that biologically there might in fact be good reason to favor having this assumption genetically embedded. The primitive world was in fact a fairly static, slowly changing system. Which animals are dangerous or not, what foods are safe or poisonous, the danger of fire and ice, etc. – all of these things it is good to learn fast and learn once. We heated our house with a wood stove growing up. One time as I kid a touched it burned my hand good. After that, I was much more careful around it. Why would I assume that somehow a hot stove wouldn’t burn me next time? Indeed, behaviors like this seem to get so ingrained in us that even when they stop giving us the results we want, we keep on trying them anyway.

David Hume famously refuted the idea that there is any logic at all in the concept of the future resembling the past. We believe it reflexively, but there is actually no logical reason to even believe the laws of nature are constant. But this appears to be unquestioned. This general notion is programmed into us a priori. I believe it is literally bred into the species.

The problem is that the modern economy is not a stable, slow changing system and it is becoming increasingly less so with time. It is a different class of phenomena than those with which the human species evolved. In this environment, the logic of risk is different. In a rapidly changing environment, the safe course can actually be the more dangerous one. A company that is too laser focused on its market could miss a fundamental shift that leaves it high and dry. The skills that command a premium today might be obsolete tomorrow, or suddenly tradeable in the global market leaving you competing for a job with someone in India making a fraction of the onshore wage.

We’ve seen many business models begin to falter. Industries as diverse as newspapers, land line telephones, and IT services have been radically upended in just the last few years. Creative destruction is operating at a speed heretofore unknown. In this environment it is most likely a matter of when, not if, the way things you are doing them today will be not just not as successful as they used to be, but completely unsuccessful. If you aren’t prepared, this could be catastrophic.

That’s why innovation and change aren’t just empty buzzwords. They are an imperative. We have to use our brains and intellectually realize that the safe course isn’t as safe as it might appear, overcome our inborn predisposition to assume a static world, and look at the risk situation rationally. We have to overcome our instincts.

Frankly, this world isn’t going to be pleasant for most of us, myself included. I don’t like uncertainty about the future any more than the next person. But that is the world that we are going to be in. The one thing we can be certain of is that things are very likely to change significantly in the future. We don’t now how much, when, or to what, but we have to be ready for it.

I think this means a few things. One, overly focused solutions, while en vogue in some B-school theory, is heavily vulnerable to niche exhaustion. Overspecialization leads to death. So unless your plan is to get in and get out, it’s risky. You at least need to be constantly examining when the likely end date is. Two, that means to increase your chances of having long term staying power, you should be placing some bets on the new, and probably some diverse bets, spreading some money around the table instead of piling on the chips on Red 14. I have a friend who owns a software company. The keep building small software as a service applications and seeing whether they get take-up. They idea is to try a lot of different things and see which one hits rather than putting too much investment in one big thing. Given the low cost of entry for web applications today, this is a smart move. And three, from and individual perspective, we should be wary of overspecializing even if that is what the market demands. At least to some extent, we should remain broad as well as deep. This is the famous “T shaped” person model. Someone with deep expertise today, but a base in many things. Today’s hot skill isn’t going to stay that way forever.

What does this mean for cities? Firstly, cities themselves have to eat the dog food. You can’t target being an innovation hub for business if your civic strategy is the status quo or rooted in totally traditional thinking. Cities too need to be spreading some bets around the table, trying new things, etc. This is extremely difficult to do in a political environment, which is why good leadership in a community is so important. You need leaders to make the case for change. By the way, this applies as much to cities that are succeeding today as it does to those who are struggling. Even more so perhaps, since struggling cities probably at some level know they need to try something different while successful cities can delude themselves that they have it all figured out. Secondly, cities need to look at how they can create a culture of innovation that permeates the people and businesses that locate there. Rather than targeting a few sectors that appear to be hot for innovation, the real answer is how to infuse innovation and a forward thinking view into everything we do.

By the way, this does not mean pitching what we do today away wholesale. But it does mean a willingness to try new things, and a willingness to see some of them fail, which is inevitable. That’s a tall order. But if you can get there, I’m convinced it will pay big rewards down the road.

This post originally ran on April 30, 2009.

Sunday, February 27th, 2011

A Better Way to Find, Look At, Analyze and Display Civic Data

You all know that I love doing data driven posts. But I found myself frustrated that it would make me literally hours to create even simple blog posts doing what I figured was very basic analysis like putting up something about what happened in the latest Census estimates release. There was just tons of tedious work involved.

It can be surprisingly difficult to answer seemingly basic questions about cities, like:

• Which large metro areas grew their GDP the most in the last year?
• How does Chicago benchmark against New York on job creation?
• What counties in Indiana increased their Hispanic population share in the last decade by the most?
• How did the population growth rate in the city of Chicago compare to Cook County, the metro area, state, and nation last year?
• Where do the people who move to Indianapolis come from?

Answering these questions can involve lots of drudge work to download raw data, manipulate it in Excel to find what you want, then to type it into an HTML table or put it into a chart you can use in a post, presentation, or document. It take literally take hours, sometimes days.

There are tons of free tools that let you access data, but every one I’ve seen is almost useless for real data analysis. They more or less only let you look up facts – like the population of Chicago – or display grids of numbers. It’s telling that the Census Bureau’s tool is actually called “Fact Finder.” If they create graphs, it’s mostly what they want to show, not what you to, and almost invariably only in Flash, so that you can’t take it out of their system without doing a screen shot.

Conversely, there are tons of pro tools that do fantastic stuff, programs like SAS, ArcGIS, or Moody’s Economy.com. The problem is that these cost huge amounts of money, are aimed at high end power users doing hard core statistical analysis and the like, or both; and are often hard to use as a result. There’s a reason that there’s an entire job category out there called “GIS Analyst”.

So I gave up in my search to find something that met my needs, and instead decided to build my own private database and query tools. Then I discovered that’s what half the world is doing, which seems like a waste. So I figured if this is so valuable to me, which it is, maybe it’s valuable to others and they might use it too.

And so my latest venture, the Telestrian data terminal was born. (See www.telestrian.com). For people who work with data about cities, counties, regions, and states, Telestrian is all about providing three bigtime benefits:

• Huge time and money savings. I can honestly say that having Telestrian for my own use during development has reduced the amount of time I spend on many data analysis tasks by over 95%. I’m serious. Stuff that would have taken me hours or been nearly impossible before I can now do in a few seconds. And as we all know, time is money.
• New capabilities. Notice that I’ve been posting more maps lately? That’s because I can actually make them now. And with Telestrian, so can you – and a lot more.
• New revenue opportunities. If you are a consultant, I’ll show you how Telestrian can power new types of engagements you can sell. In fact, I originally thought it would make a nice proprietary tool for my own consulting business.

And if you’re wondering whether this is the system with the IRS migration data, the answer is Yes! so read on.

You can read more about the benefits and walk through a few examples in my white paper, A Better Way to Find, Look At, Analyze, and Display Civic Data. I’ll highlight a few examples of the benefits in action.

Massive Time Savings

You’ve seen lots of studies that rate metro areas on college degree attainment, like Brookings’ wonderful State of Metropolitan America. Let’s say we’re doing an update to that study for them, and want to look specifically at growth in the share of people who have professional or graduate degrees. Which of the top 100 metros areas had the greatest change in their percentage of population with graduate or professional degrees?

With the Telestrian system, you can answer that question in about 30 seconds. We just go do that data element and do it. Telestrian gives you a common toolset on every data element. The Query tab is what most people gravitate to, since it is what lets you look up data by geography and date like other sites do. But that’s arguably the least powerful thing in the system. If you go to Analyze, you can run powerful parameterized queries that let you mine the data in a snap. Here’s the query you want. You can click to enlarge this screen shot:

Note that we set a threshold to only look at places greater than 510,000 people in population. This gives us the top 100, which is what Brookings looks at.

Bam, here’s the answer:

You’ll note that on the left there are a ton of options for working with the results. Maybe we want to dump that into a blog post like this one in a form you can actually read, for example. In just a couple clicks we can export an HTML table that we can paste right here:

Or maybe put these into a bar chart. Voilà!

Yes, Telestrian system even truncates those overly long metro area names if you want it to. At this point we’ve spent about one total minute in the system.

If you’ve worked with this data at all, you’ll know that it comes from two completely different data sets. The 2000 data comes from Census 2000 and the 2009 data comes from the American Community Survey. So you’d have to manually extract both, merge them, merge in the population data somehow, trim it down to the top 100 metros, calculate the percentage attainment, calculate the percentage point change, sort on that, then hand create the tables or charts. But what’s worse, you may remember that the Census 2000 data is distributed in that old 1990’s era CMSA/PMSA stuff that isn’t comparable with today’s metro area definitions. So you have to download the county data and manually re-aggregate all the 2000 data to current metros yourself, unless you find a source that did it for you already.

Or you can just spend about a minute in the Telestrian tool.

Beyond change in the percentage of a parent data value, there are several other functions you can use in your search too, such as total raw value, total change, percent change, density, and location quotient. The Telestrian data terminal can almost turn you into a one man Brookings Institution.

New Capabilities

Calculating data like the above is tedious, but conceivably doable. But there are some things that are almost impossible to do yourself without the right tools. One of them is to create thematic maps of your results, like those red-blue election maps. Most people create those with ArcGIS, but if you don’t have or can’t use it, or don’t have a graphic designer on call, making one can be almost impossible. I sure didn’t know how to make them.

Using ArcGIS to make a simple thematic map is like using a tactical nuclear weapon to get rid of the spider in your bath tub. That’s why I built it right into the system, letting you render almost any of those Analyze queries directly to a thematic map. We do that in the app on the Map tab, which is similar to analyze but gives you some other options. Let’s just map our same query for all US metros:

In blues, we see places where the percentage of people with graduate degrees increased, in reds those where it actually decreased. I could have picked my own thresholds for coloring, but decided to go with one of the built in algorithms, in this case a 5 bucket sort. This took about 30 seconds total to create by the way, so don’t think that just because I filed this under “new capability” it doesn’t mean it wouldn’t save you lots of time too even if you already have and can use ArcGIS.

By the way, these maps are images files (PNG), not Flash, so you can actually right click and save them to use them as you see fit. And you can make them pretty much as big or small as you want with no resolution loss or distortion. To see an example of what I mean by that, just click here.

Make More Money

This one also saves time and gives you new capabilities, but additionally it enables consultants to make more money too. Cities and states spend hundreds of millions of dollars on human capital and “brain drain” initiatives. But frankly very few places have much of a clue about their human capital networks. Where do people who move in come from? Where do people to leave go? How much money and how big of families are they taking or leaving?

A big problem is the data. The Census Bureau only publishes net migration, but doesn’t talk about where people come from or go to. The IRS publishes that in its migration data, but it is super painful to use. For one thing, other than the last handful of years, the data only comes in the form of over 3,500 Excel spreadsheets. (They will mail those to you on a CD for $500). And the data only tracks state-state and county-to-county when often what we really care about is metro-metro or metro-state. Unless you have and can use (sparse matrix, anyone?) a tool like SAS (which is thousands of dollars a year and doesn’t come with any data) and crack the code on data import, it’s virtually hopeless.

But with Telestrian, all that data has been processed for you, and presented not just at the county-county and state-state level, but also at the metro-metro, and metro-state level. And there are tons of summary metrics taken from the IRS files, as well as other bespoke calculations of things like migration rates and intra-metro migration (e.g., core to suburb moves). Over 100 items in all.

Want to know where the money is going when it leaves Atlanta and how much of it ends up there? Here you go, looking at 2000-2008:

Of course this data is available in raw form, exportable to Excel if you want it. Again, it’s about 30 seconds or so to make this.

This only scratches the surface of what you can do with migration. I hope it is easy to see that there are huge market opportunities for consultants to use this to start helping cities and states map out their human capital networks and find ways to take advantage of them. Much more on this later.

So What Is Telestrian?

So what does Telestrian actually do? A full feature summary is available for your perusal, but in brief, Telestrian provides the following.

• Data Repository. It contains an aggregated data repository of over 600 data elements, including core data such as population, sex, age, race, migration, education, immigration, commuting, highway congestion, health data, labor force and unemployment, jobs and wages, GDP, personal and household income, poverty, and more. I consider this a “starter set” and there’s virtually unlimited room to expand, which I have big ambitions to do.
• Common Analysis Toolset. Run parameterized queries to mine the data and analyze results sets. Includes things like filtering by state or population; applying functions like percent change, total change, or location quotient; and calculating CAGR, index values, percentage of parent, and much more.
• Task Automation. In addition to automatically applying functions like the above, Telestrian also automatically applies rollups of regions, allows saving of commonly used geography lists so you don’t have to recreate them over and over, defining custom regions, etc. The various components of the system are also integrated to enable rapid end to end processing.




• Visualization. Render results to bar, column, area, line, and pie charts (Flash or image), or export to Excel/CSV or HTML tables. Thematic maps can be made at the national level for states, counties or metros, or at the state level for counties.

The focus of the system is data about cities, counties, regions (MSA, CSA, EA, etc), and states, though national level data is also available.

Pricing is currently on an annual basis at only $495/year (a bit over than $40 a month). But for a limited time to my loyal readers who work for organizations who might be able to use this, I am offering it at $395/year (less than $35/month). If you use it for one project like that grad degree one, it already paid for itself. I might offer a monthly plan in the future, but it will be at a price premium to the annual, and not include access to IRS data. A free trial is available with no credit card required and no obligation so you can try it for yourself without risk. IRS data is not included in the trial.

Consider that just to have the IRS send you their raw data on a CD – in the form of over 3,500 spreadsheets – is $500 by itself. You’d pay well over $300/year just for GIS free mapping with something like Indiemapper. To say nothing of the untold thousands you could spend on high end products.

For those of you who work as consultants, planners, journalists, analysts, economic developers, agency staffers, etc. who work with this data and need to do more than just look up simple facts, I’d ask you to take a look, and if you see the value – which I’m confident you will – please buy.

Since this is the official launch day, I’d ask that you please be gentle if we run into performance or other type issues right here at the start. I will increase site capacity as fast as I can if need be, and of course candid feedback is always welcome. Again, the link is www.telestrian.com.

I’ll wrap up with a couple more fun examples, but before I do I want to tell you a few problems Telestrian is NOT designed to solve:

• If you need statistical analysis like multi-variate regressions, you need SAS or SPSS or something.
• If you need data at the zip code, Census tract, or other level below city or county, you need tools from ESRI or one of the many specialist providers who will help you decide where to locate your store or whatever else you need.
• If you need to look at detailed breakdows like jobs at the 4-digit NAICS code or black-female-and-hispanic, look for something like Moody’s Economy.com
• If you need to know the unemployment rate the minute it hits the wire, get a Bloomberg terminal.
• If you need non-US data, again go get Moody’s Economy.com

If you have problems like these that involve very detailed, complex, or time sensitive considerations, I’m sorry. You probably do need to spend a lot of money and hire some specialists.

Fun With Data

Here are a couple more fun pieces of data analysis.

First, a comparison of job growth in New York vs. Chicago vs. the US. I actually go through how to do this example in the Telestrian User’s Guide (yes, the system actually has documentation).

This is a great example of how you can query data at any geography level simultaneous if the data supports it, and the use of indexes for comparison of regions with very different sizes. If you’re familiar with the Current Employment Statistics, you’ll also know that the US data and Metro data come from two separate data sets, but I allow you to query them together.

By the way, I created every single chart in my Chicago vs. New York blog post from last fall combined in about five minutes using a development version of the system. If you at all benchmark or compare cities, I think you’re in the sweet spot of the product. That’s doubly true if you compare places at different geographic levels (such as metro vs. nation or county vs. state, etc) since Telestrian puts no arbitrary restrictions on what geographies you can query together.

One more. Here’s a national county map of unemployment rates for October 2010 (not seasonally adjusted):

It’s a cool graphic, but I especially posted it because data visualization guru Nathan Yau wrote a long blog post at his widely read blog Flowing Data that explained how to a create a map almost like this in 14 easy steps – easy if you know how to program in Python that is. As he put it, “There are about a million ways to make a choropleth map. You know, the maps that color regions by some metric. The problem is that a lot of solutions require expensive software or have a high learning curve…or both.” Yau’s solution requires you know to know how to write computer software. Telestrian is almost de minimis in cost to any real organization and only requires you to know how to surf the net. With that, about 30 seconds later you can have your map.

You can also check out my recent metro GDP post, or my Chicago Census post, which used this system to power the data analysis.

Thanks so much for reading and I hope you’ll check it out and decide to buy – remember, it’s www.telestrian.com. It’s a great way to support the work I do – but much more importantly I’m confident the business value is very real and significant because I’m enjoying it every day myself.

Friday, January 28th, 2011

Replay: The Importance of Social Structures to Urban Success

[ As a follow-up to my Cost of Clout piece I am re-running this 2008 post demonstrating the important of social structures and culture to urban success. ]

There seems to be a popular belief that what it takes to create an industry cluster in bioscience or whatever is to pair research with commerce. That is, to find an academic institution doing cutting edge research, and connect it with venture capital and entrepreneurs to start companies to commercialize it. Soon enough, you have a “cluster” of businesses that takes off like a rocket. This is the perceived Silicon Valley model, and no company epitomizes it more than Google, which was started by two Stanford students to commercialize their graduate research.

But is this true? There are many top flight research universities in this country, but few major startup clusters. When major research institutions fail to generate commercial spinoffs, this is often blamed on a lack of venture capital. But is that really the case, or is something else at work?

Anyone interested in this matter simply must read AnnaLee Saxenian’s seminal book, “Regional Advantage: Culture and Competition in Silicon Valley and Route 128“. A social scientist at UC Berkeley, Saxenian lived and worked in both Silicon Valley and Boston’s Route 128 technology corridor. She wondered why Route 128, which started out with far more of a technology business and economic base than Silicon Valley, eventually lost ground to become a clear number two. She sees this resulting from the different social structures that exist in the various areas.

According to Saxenian, Route 128 suffered from a culture that was oriented towards a traditional maturing industry, not a rapidly changing one like technology. This included more deliberative decision making; vertical integration and self-sufficiency; hierarchical, centralized command structures; focus on economies of scale; a high friction job market; geographically dispersed locations; and low levels of cooperation and sparse networks between firms in the region. In other words, all the standard traits of a typical large corporation. While she doesn’t dwell on this point, it also comes across that Boston, probably due to its New England locale with all the history there, was a much more closed society. The social network and hierarchy was more fixed (the phrase never appeared in the book, but I couldn’t help but think Boston Brahmin) and the process of establishing trust and credibility much slower than California. While famous as one of the bluest states, Massachusetts is socially conservative in many ways, and highly risk averse. This is the land of the suit and tie, and the difference between that environment and California casual was more than just a surface thing.

Silicon Valley, of course, was just the opposite. It adopted social structures that were very focused around innovation and time to market. It was open, with rapid, decentralized decision making. Firms quickly specialized, focusing on their core competency, and established close links with suppliers to fill in the rest of the value chain. These links were often such that it was not clear where one company ended and the other began. The clearly functioned on high degrees of trust. Even direct competitors often talk to exchange ideas and help each other solve problems. Here’s a quote:

Competitors consulted one another with a frequency unheard of in other areas of the country. According to one executive: ‘I have people call me quite frequently and say, “Hey, have you ever run into this one?” and you say “Yeah, about seven or eight years ago. Why don’t you try this, that or the other thing.” We all get calls like that.’ (33)

Clearly this is quite unique. I’m not even sure if it’s all legal, but hey, it works for them.

The job market in Silicon Valley is extremely fluid, with people constantly changing jobs, starting companies, etc. It is expected that you won’t stay that long with any given employer. Route 128 operated on the “company man” model and to leave was to show disloyalty, often resulting in ostracism. Since Silicon Valley was a new country with almost all immigrants of one type or another, family history and credentials meant little. What mattered was whether you could perform.

Now of course it was almost entirely men, originally white men, who set this up. The tech industry is famous for being one of the most gender imbalanced. What I found particularly interesting was that many of the founders had Midwestern roots. Again quoting:

This collective identity was strengthened by the homogeneity of Silicon Valley’s founders. Virtually all were white men; most were in their early 20’s. Many had studied engineering at Stanford or MIT, and most had no industrial experience. None had roots in the region; a surprising number of the community’s major figures had grown up in small towns in the Midwest and shared a distrust for established East Coast institutions and attitudes. They repeatedly expressed their opposition to ‘established’ or ‘old-line’ industry, and the ‘Eastern establishment.’ (30, emphasis added)
….
The many examples of engineers with humble origins who became millionaires by starting successful companies had no parallel in the more stable social structures of the East. Jerry Sanders, founder of Advanced Micros Devices … grew up in south Chicago, the son of a traffic light repairman. (38, emphasis added)

To digress for a moment, remember how I said the contrarian, ornery Hoosier/Midwestern attitude is, in the right context, a huge strength, not a weakness. This shows that in action. These guys didn’t toe the conventional wisdom line. Instead they created a whole new business model. I’ve got to believe the Midwest mindset played a huge role in making this possible. The unfortunate thing is that they had to leave the Midwest to do it. Imagine if they’d stayed home and made it happen around one of the great engineering schools there? Alas, to this day Midwesterners often have to leave to turn things into reality. Famously, Marc Andreessen had to leave Illinois to start Netscape, and in fact had U of I actively hampering him all the way. If the Midwest cracks the code on this piece alone, it would be a huge step in the right direction.

(By the way, for a wonderful look at how these Midwesterners invented Silicon Valley and the “elder days” of semiconductor business, see Tom Wolfe’s 1983 Esquire essay, “The Tinkerings of Robert Noyce“.)

These extremely fluid job markets, open social institutions, high trust customer and supplier interactions, and competitor information exchange create an environment of so-called “dense networks”. In a period of rapid change and innovation, these networks, by efficiently distributing information and dispersing risk, create an environment with very rapid speed to market and high levels of adaptability. A traditional Route 128 do it all yourself model simply can’t keep up with the power of this vast network.

It was this network, more than anything, that created the Silicon Valley we know today. The “cluster” we see in Silicon Valley is not an artifact of spatial co-location. It comes from the network. According to Saxenian:

Spatial clustering alone does not create mutually beneficial interdependencies. An industrial system many be geographically agglomerated and yet have limited capacity for adaptation. This is overwhelmingly a function of organizational structure, not of technology or firm size … The current difficulties of Route 128 are to a great extent a product of its history. The region’s technology firms inherited a business model and social and institutional setting from an earlier industrial area. (161-162).

Sound familiar? It describes the Midwest perfectly. What I find interesting is how Saxenian illustrates her thesis not using a struggling Midwestern burg as a case study, but rather Boston’s Route 128, the second largest technology hub in America, home to possibly the greatest collection of universities in the country, with massive access to capital, etc. If this town had its problems, how much more so places without those advantages? It certainly shows the scale of the challenge in building industry clusters.

Obviously, changing the social structure, culture, and institutions of a region is difficult to do. Even positive articles highlight the scale of the challenge. I’ll refer a recent article on Milwaukee startups that I linked that quotes a local businessman saying, with some pride I gather, “Milwaukee is a one-strike-you’re-out town.” That’s not a good thing. Silicon Valley shows that failure and risk taking are good. The way to innovate is to figure out how to try lots of things and to fail quickly and cheaply. If you are overly concerned that you’ll be permanently ruined if your business goes bankrupt, you’re not that likely to take a chance.

It reminds me of a discussion I once had with a friend from Germany. He told me, “We’re the children of the people who stayed” and bemoaned the highly conservative outlook of his countrymen. He noted the extreme reluctance to take risks because in Germany, if you go bankrupt, you’re stigmatized for life. Obvious some of that carried over to heavily German Milwaukee.

I should note that one should not over-internalize Saxenian’s case studies into some sort of cookbook solution. Every city and region needs to find its own unique path to success based on its own culture, institutions, history, etc.

I would be remiss I did not point out a few areas where I was skeptical of the Silicon Valley model. One intriguing factoid from the book was that in 1962 federal government purchases, principally defense related, accounted for over half of Route 128’s sales. Indeed, the area got its start in technology through defense related research during World War II. Could it be that dependency on government contracts is really what caused the dysfunctional culture there? Government largesse encourages rent seeking behavior at the expense of building a competitive business.

Also, Saxenian highlights how the non-business social networks in Boston substitute for the type of technology networks in Silicon Valley. But is this a bad thing? The books paints a portrait of Silicon Valley as a bunch of geeky guys who toil away long hours on tech projects and even talk about technology at the bar when they do go out. It’s like a community of idiot savants. Some might say “get a life!”

What’s more, there is some research that suggests dense networks themselves aren’t a recipe for success. In an thought provoking paper called “Why the Garden Club Couldn’t Save Youngstown” Sean Safford contrasts the experiences of Youngstown and Allentown, both small steelmaking cities. Despite similar dense networks, Youngstown failed while Allentown fared much better. His conclusion that was the dense networks in Youngstown only reinforced an already closed leadership circle who were economically aligned, while Allentown’s served to bridge otherwise non-overlapping groups.

Perhaps to a great extent, the key attribute is less the networks themselves, than the ability of outsiders and new thinking to penetrate them. Silicon Valley’s social structure was open, Route 128’s wasn’t exactly closed, but there were barriers to entry. In a globalized world of ever faster change, the ability to respond and adapt, to process new ideas and react to rapidly shifting global forces, is critical. This puts a bit premium on dense social networks that are also open and flexible.

This is somewhat the thesis also of Richard Florida. He has a somewhat different spin, saying that the economy is now powered by the creative class, and they want to live in places that are open, tolerant, etc. This is his “three T’s” model: talent, technology, and tolerance. The last appears not to be so much valuable in its own right, but for what it says about the openness of social networks. Thus a large number of gays in a community isn’t what drives economic growth per se. Rather, a thriving gay community is a signaling mechanism that lets people know that diverse ideas and people are welcome.

I think we all know places where the social network is impenetrable. This isn’t necessarily a function of size, prosperity level, etc. I mentioned the Boston old money, social register concept. In any number of southern cities, who your daddy is, or what sorority you went to in college is a huge determinant of your place in a social hierarchy. If you don’t come from the right family, the right schools, etc., you can forget it.

Perhaps this explains my Cincinnati conundrum. Here’s a city with better assets than almost any in America, but it is one of the all time relative decline stories in US history and to this day is on a moderately stagnant, slow growth path. Why is that? There was an intriguing study I saw recently called Who Rules Cincinnati? [dead link] This is by an independent researcher named Dan La Botz, who I get the impression is some sort of hard core left activist, so keep that in mind. Nevertheless, he uses a similar approach to the Garden Club study to track social networks in the city, coming to the conclusion that officers of seven major corporations basically run Cincinnati, mostly to that city’s detriment. Another person I know offered the interesting insight that when he meets someone in a bar in Cincinnati, the first question they ask him is where he went to high school. This both indicates a highly inbred culture as evidenced by the assumption one must have gone to high school in Cincinnati, and shows that the school you attended is an important social marker. (It perhaps also shows a lack of regard for higher education).

It could be that the Midwestern cities that have the best potential for future growth are those with the most open social networks, as well as exhibiting other of the characteristics Saxenian cites. I think this would be fertile ground for social science research. It also makes me wonder if perhaps that goes part of the way to explaining the relative success of the Midwest’s larger state capitals. State capitals constantly have people traveling and doing business there from all corners of the state. This flow in and out might potentially prevent a social structure from completely congealing into a small, impenetrable elite. I sense another potential dissertation topic here.

The key takeaway is not to focus on purely the institutional infrastructure (universities, venture capital funds, labor force, etc.) when trying to set out an economic strategy. The local culture, norms, and social practices, and in particular the density and openness of the social networks is critical. Clearly, as anyone who has found themselves mired in a corporate or governmental bureaucratic organization, changing a culture is an extremely difficult thing to do. But it is something that clearly warrants an examination.

This post originally ran on July 13, 2008.

Older Posts »

Telestrian Data Terminal

A production of the Urbanophile, Telestrian is the fastest, easiest, and best way to access public data about cities and regions, with totally unique features like the ability to create thematic maps with no technical knowledge and easy to use place to place migration data. It's a great way to support the Urbanophile, but more importantly it can save you tons of time and deliver huge value and capabilities to you and your organization.

Try It For 30 Days Free!

About the Urbanophile

Aaron M. Renn is an opinion-leading urban analyst, consultant, speaker, and writer on a mission to help America’s cities thrive and find sustainable success in the 21st century.

Full Bio

Contact

• arenn@urbanophile.com
• twitter.com/urbanophile
• linkedin.com/in/aaronmrenn

Please email before connecting with me on LinkedIn if we don't already know each other.