Over the past two months, we have been engaged in a conversation about the future of jobs with economic development practitioners at the TEDC and IEDC conferences.

Now, we’d like to create an open forum to continue this dialogue beyond the conference setting. In the comments section of this post, you’re invited to respond to the following questions, or pose additional questions for your peers.

How will the “future of jobs” change how you approach economic development?

What mechanisms have you created to support corporations and freelance workers in your community?

Below you’ll find a video of Jon’s recent IGNITE presentation from IEDC’s Leadership Summit in San Antonio. The IGNITE structure allows speakers 5 minutes total to present in the form of 20 slides, with 15 seconds per slide. A brief overview of the presentation follows the slide show.

The Future of Jobs from GIS Planning on Vimeo.

This is a discussion about the future of jobs. The idea of what a job is has changed throughout history (and continues to change). Farmers and craftsmen have always had trades, or livelihoods. Since the industrial revolution, a fundamental shift in the nature of jobs has occurred; individuals are employed by entities (corporations) and in return for their labor (9-5), they are compensated (wages) and receive benefits (healthcare, etc.). When unemployment is high, as it has been in the aftermath of the recent recession, we must ask ourselves who should create jobs: the public sector? the private sector? Can the economy continue to grow, even if jobs are not being created? (answer: yes).

The economy grows when value is created. Corporations can create value by increasing productivity (but not necessarily increasing employment), and independent contractors can create value outside of a traditional employee-employer relationship. If we take this thought experiment to its logical extreme, could there be corporations without people on the horizon? Will trade guilds become an organizing structure for independent contractors in a variety of professions?

If jobs are no longer the most useful or accurate measure of economic development success, how can practitioners best promote economic vitality in their communities? Are there mechanisms by which cities, regions, and states can offer resources to corporations and freelancers that will support their ability to create value, regardless of hiring trends or employment status?

We invite you to participate in this conversation in the comments section below.

by Jon Roberts, TIP Strategies

No topic is of more immediate, more urgent concern than America’s job situation. The unemployment rate remains stubbornly high, the op ed pages overflow with prescriptions, warnings, and admonitions, entire communities are at financial and social risk. Among all these issues, there is a deeper discussion to be had. It goes something like this: what is a job – really – and how does it fit into the larger historical framework?

Before we tackle this question, there are a few related problems worth exploring. Whose job is it to create jobs? Well, not the public sector. At least we know that from the current giddy assault on government employment. Yes, cities, states, and federal agencies hire people but we are right to be suspicious of their contribution to the economy. They are doing work that we are paying ourselves to do. Or so the argument goes. They are like paying your own kids to mow the neighbor’s lawn. Your neighbor may like it (let’s assume he does), but your family is earning no additional income. It’s not a sustainable business model.

There’s more to be said on that topic, but let’s leave it at that. Then if not the public sector, who else? The private sector? Really? In what sense is it a reasonable expectation that the “private sector” should add employees? No private business exists in order to create jobs. It really is that simple. Businesses add employees when they have to add employees. Not before, and for no longer than they are needed. Any other attitude would result in . . . (you guessed it) an unsustainable business model.

But certainly there’s more to it than that. In a healthy economy jobs are created. It is in the interest of businesses to add employees. But this “interest” is self-interest, it is not for the good of economy as such. That can’t be a business concern. Which leads us to an interesting question: Can we have a healthy economy that isn’t producing jobs? Those who want jobs to be created, for whom it is a bit of crusade (the public sector) are powerless to do so directly. Those who could create jobs (the private sector) put themselves at substantial risk by adding workers when it compromises their competitiveness – thus making their model unsustainable. We are looking at a huge disconnect.

All these thorny questions and we haven’t even come to the really difficult one yet (what, after all, is a job?). Suffice it to say that if we ask whose job it is to create jobs, there is no easy answer – or perhaps no answer at all. We need to be asking a different question. Something like this: what are the conditions under which jobs will be created (by the private sector, of course). Are the answers easier to come by? Let’s try. Jobs get created when two things happen: there is a steady demand for product and services, and new workers are required to fulfill that demand. So what are the conditions under which this occurs? Consumers are confident and have the income (or credit) to act on their desires. And workers are able to increase the productivity of the company. Not just one of these things needs to happen. Both do. If I can increase my productivity (i.e., satisfy the demand for goods efficiently) without adding workers, I have no economic motivation to do so.

Before we leave this topic, we need to see the paradox this represents. If the only way I can sell my goods and services is to have customers able to do so, but the only way I can stay competitive is to reduce my labor costs, then who will there be to buy what I have to sell? As paradoxes go, this one is a doozy. Against this background we’re ready to ask our question:
What is a job?

Some historical context is relevant here. The concept of a job is not something we should take for granted. By that I mean people working directly for a company (an employer) who provides wages for specific activities. In fact, it’s a relatively recent development. Industry as we know it – and the structures that support industry – are a recent historical phenomenon. Prior to the 17th century, a merchant class was something of a novelty. There were farmers, to be sure, and craftsmen. Farmers typically worked for themselves, or they were indentured, but no one gave them a paycheck. Craftsmen did not go to a job in a factory and punch a clock. People did jobs, but they didn’t have a job. Even the rise of the merchant class did not immediately usher in an employer-employee structure, at least not in the corporate sense.
So you know what comes next (what always comes next in economic history). You guessed it. The Industrial Age. The 19th century changed everything. The idea of a workforce preceded the idea of a job. To put this somewhat differently, we were creating an economy that required specialized skills. Highly specialized skills – the ability to do one thing very, very well. This economy resulted in corporations, something that also had never existed before. The idea of a workforce had an almost transformative effect. If you weren’t “working for” a company, you weren’t working at all. Freelancers, housewives, apprentices – these all existed largely outside of the idea of the workforce.

Now all this is grossly over-simplified, but not entirely without basis, and certainly not without a point.
The point is that the notion of a job is not a fixed idea. It can change, it has changed, and it will (we think) change again. To explore this idea is to engage in a thought experiment. It is to imagine a growing cadre of highly talented individuals who fit their skills to the specific needs of corporations. They see that corporations have less and less need for things that machines can do. To put this more provocatively, the industrial age is over, and the machines have won (“I, for one, welcome our robot overlords,” to paraphrase from the Simpsons.). An economic model that seeks to create jobs by ignoring this reality is a failed model.

If we begin from that premise, entirely different models open up to the imagination. A flexible talent pool that moves to solve problems. A new cooperative corporate model in which consumers are themselves marketers, testers, and shareholders. Social innovators who build networks of services and products that operate first in a closed, then an open system. – Can we imagine any of this? Yes, because it is already happening. Social networking is redefining traditional sales models. “Professional services” are reconsidering where their value lies as search functions redefine legal analysis and insurance claims.

Simply put, there is no sector of the U.S. economy that is not fundamentally altering its business models. In this series of radical changes, why would we expect to solve the jobs question (i.e., to reduce unemployment) by expecting companies to hire people into permanent full-time jobs? This conception of “jobs” fits a model that simply doesn’t conform to business realities. And, for that matter, it doesn’t conform to the needs of the would-be worker.

None of this is simple. None of this will happen in a predictable way. None of this will be painless. But the changes have already begun. It works as a thought experiment not only because we can imagine it, but because we sense its inevitability.

The future of jobs is that they have no future. Passive job seekers desperately hoping to find job postings that fit their skills is the sad and painful dead end of an economic system that has run its course.

To say that the transition will be hard is more than an understatement. In fact, it will be as wrenching as the shift away from an agrarian economy was. Entire industries will cease to exist, communities will be in turmoil, families will suffer terrible indignities.

We could, perhaps, have eased the blow of this transition, but that opportunity has passed (if it ever was an option). Just as in the private sector, more efficient government is more efficient because it can do more with less. And in these times, that means fewer people. And fewer people employed (regardless of which sector) means higher unemployment.

This is not an economic forecast. Employment in the traditional sense will continue to go up and down. But the pattern, the move away from a 20th century employment model, is inevitable. Anything else is… unsustainable.



Jon will be presenting on this theme as an IGNITE presentation at IEDC’s 2012 Leadership Summit, January 29-31 in San Antonio, TX.

via Harvard Business Review

by Thomas Duesterberg

In what now seems a distant past, company research facilities like Xerox PARC and Bell Labs fueled innovation and growth for dominant American manufacturing firms. As the pace of technological change has quickened and the costs of R&D have grown, that model has ceased to work. Meanwhile, global competition has intensified the imperative to innovate; even long-standing manufacturing companies, such as Parker Hannifin, Timken, Kennametal, and United Technologies, strive to have 20% or more of their products be new or substantially revamped each year. Although many companies still maintain proprietary research operations (Google X lab, for example), they’re increasingly turning outward and depending on distributed or open research, in which firms or clusters of firms tap into larger networks of academic and applied work to drive new product and process development.

Of course, no single model of distributed R&D works for all companies. Large firms like Proctor & Gamble can push R&D and product innovation out through their supplier networks. P&G maintains a goal of 50% of its total innovation from outside the company, and half of that from outside suppliers. As Henry Chesbrough has argued, such a model requires rethinking internal organization as well as effectively working with the broader research community. Japanese automakers have long relied on their suppliers as innovation partners. U.S. automakers too have pushed product and process improvement out through their supply chain via the relentless drive to achieve 3% cost reduction year after year and still build competitive new models. Large firms can also buy smaller ones to acquire new technology.

Smaller companies in the manufacturing sector, competing in a global environment for increasingly sophisticated products, often don’t possess the financial strength or the in-house technical expertise to take advantage of the available science and engineering resources that can help them innovate and grow. New types of local and regional consortia or clusters are popping up in response to this problem, sometimes facilitated by public-private partnerships. An interesting example, just getting under way, is the Midwest Project for SME-OEM Use of Modeling and Simulation–a consortium of large OEMs like General Electric, Proctor & Gamble, and Deere; the State of Ohio; and several projects funded by the National Science Foundation (NSF), including the Center for Manufacturing Services, the Ohio Super-Computer Center, and the Network for Computational Nanotechnology (NCN). NCN serves as a virtual laboratory through online simulation and education. It develops models and simulation tools to predict behavior at the device, circuit and system levels for nanoelectronics, nanomechanics, and nanobio systems. It serves over 180,000 users and mounts over 10,000 simulations a year, and also provides access to supercomputers to its users as needed.

The idea behind the Manufacturing HUB, a NSF-funded initiative at Purdue and a key part of the Midwest Project, is similar to the NCN but more explicitly designed to aid small and medium manufacturers (SMEs) in getting access to models, computing power, and technical expertise to aid their product and process innovation. The models and computational resources will give SMEs access to the resources needed to solve advanced problems in areas like fluid flow, structural behavior, and material strength which are crucial to building advanced products and processes.

The common thread of these developments is building and accessing larger networks — beyond the single firm or even clusters of small firms — to create the new products and processes needed to compete in a global manufacturing market. Many questions about these models remain to be solved with actual experience — systems integration, disconnect between R&D and production, intellectual property rights issues, tragedy of the commons, leaking competitive advantage — but the trends are well embedded at this point.

What are you seeing in your business or research that can point to the strengths and weaknesses of these models?

THOMAS DUESTERBERG

Thomas Duesterberg is the executive director of the Program on Manufacturing and Society in the 21st Century at The Aspen Institute.

via Harvard Business Review

by Chandrakant Patel

I joined Memorex Corporation in the early 1980s as a mechanical design engineer. You may recall the commercial “Is it live, or is it Memorex?” featuring Ella Fitzgerald. Ella sings live, and the frequency of her delivery makes a wine glass shatter. The same delivery, recorded and played back on a Memorex audio tape, makes a structurally similar wine glass shatter, proving the high quality of reproduction of Memorex’s tape. The commercial was clever, and viewers understood it. In an era of physical innovation, people understood instinctively how things worked, even if they weren’t familiar with the underlying theories of physics. That understanding of why certain things happen in a given system, under given conditions, is equally necessary today, but over the last three decades, we have abstracted it away.

As advances in technology have allowed us to work in more virtual ways, we have literally and figuratively lost touch with the products we’re building. The result is that now have a crucial gap in our systems, because we no longer fully understand how each component of the system works. Not understanding the physical complexity of a given infrastructure may result in grave consequences for the IT industry. For example, if engineers don’t possess the know-how needed to limit the material and energy cost of setting up and operating cloud services, IT can’t scale as it needs to.

We’ve lost the capability of understanding such physical complexities for three reasons:

1. The rise of software. Layers of software distance consumers, designers, and engineers from the underlying physical infrastructure.

2. The trend toward off-site data storage. In the 1980s, I designed large hard drives the size of washing machines that stored about 1000 MB of data on 14-inch disks. Data storage was very tangible. Today, consumers and enterprises store their data in the more intangible “cloud.”

3. Offshoring manufacturing and design. In the early 1980s, those hard drives I worked on were manufactured right next door to our R&D facility. With their read-write heads rotating microns above the disk, their large mass, and their numerous components, they were highly susceptible to external shock and vibration. That meant applying meticulous analysis and experimentation associated with the dynamics of structures. Because the engineers who had designed the drives were right next to the factory, they understood how their designs fared in manufacturing. Since they knew the customer environment in which the hard drives operated, they were better equipped to understand system-level consequences. In the late 80s, manufacturing left the U.S. to lower-cost geographies, but the design work continued in the U.S. As hard drives became smaller and improved technology reduced the number of components, design and value-added engineering also left the U.S. At the same time, companies in the U.S. also realized that there was an opportunity in making large scale data storage systems consisting of hundreds of small hard drives. They achieved differentiation by adding software layers for management and application development, rather than by designing better hardware. The result is that today, most consumers and software designers don’t think about the thousands of physical rotating disks on which their software and storage needs depend. But the systemic challenges associated with physical design have not gone away.

In our “software and sheet metal” age, the knowledge of hardware design and operation must now exist at a system level. For example, the high heat density of racks that house multiple drives and computer systems necessitate high-speed fans for cooling. These cooling fans, rotating at high speeds, cause vibrations that may align in frequency with one of the read/write arm frequencies in the hard drives. As in the Memorex commercial of yesteryear, that stimulus causes read/write failures and reduction in data throughput. The vibration problem that we wrote off in the age of standalone drives has manifested itself in new large-scale systems installed in data centers.

Problems like this are becoming more and more difficult for today’s engineers to solve, because you can’t fix problems in a system without understanding its components. With design and manufacturing of components gone, the “out of sight, out of mind” scenario has resulted in a loss of engineering knowhow to get to the root cause. Therefore, when it comes to complex hardware, instead of taking a systemic perspective steeped in fundamentals to address the root cause, we make up for the hardware failures by adding redundancies. In the case of hard disk drives, the mantra is “drives are cheap,” so we over-provision with redundant drives and data replication. Indeed, our data is replicated in many drives in a given location to account for drive failures, and geographically dispersed to avoid regional catastrophes like a natural disaster. Such over-provisioning adds to the cost of service and, in a resource-constrained world, is not sustainable. While we have provided IT access to about 20% of the world, we will not be able to increase that scale — akin to Moore’s law of scaling in semiconductors — unless we reduce our total cost of ownership by at least 20%. Traditional scaling of IT to the masses is going to hit a wall.

Furthermore, in the future, we will need to build software-based applications to enable the efficient and reliable operation of physical systems such as pumps, motors, waste water systems, water distribution systems, and the power grid. In this expanded role for IT, how can we manage such physical systems without knowing how to design and manufacture them? While it is not practical to turn on a dime with respect to returning manufacturing and design to the U.S., we must take action now by building a cadre of people with “hands-on” knowledge garnered in high schools, vocational schools and universities. In addition, to facilitate IT-based management of physical systems, we will need to be analyzing data streams from power components, pumps, compressors, etc. The analyses of these data streams will require interdisciplinary scholarship in computer science and mechanical engineering.

To be able to build these applications, and run IT cost-effectively, the high-tech industry needs engineers with equal facility in computer science and mechanical engineering — people who thoroughly understand the physical complexity and limitations of these systems and who can use that knowledge to build smarter, more well-integrated software. Very few people have those skills today, so we must train them. As salaries begin to level off globally, this will allow a return of manufacturing and component design to the U.S.

CHANDRAKANT PATEL

Chandrakant D. Patel is an HP Senior Fellow and Director of the Sustainable Ecosystems Research Group at Hewlett Packard Laboratories. Chandrakant has been a pioneer in microprocessor and system thermo-mechanical architectures, management of available energy as a key resource in “smart” data centers, and most recently, application of the IT ecosystem to enable a net positive impact on the environment. He teaches at Chabot College, U.C. Berkeley Extension, Santa Clara University, and San Jose State University.

via The Official Google Blog

The website Google for Veterans and Families brings together Google products and platforms for servicemembers and their families. We believe it will be useful to all veterans, whether still in the service, transitioning out, or on a new path in their civilian lives. Here are some examples of what you’ll find on the site:

VetConnect – This tool helps servicemembers connect, communicate and share their experiences with others who have served using the Google+ platform.

Google Veterans Channel – A YouTube channel for discussion about military service for veterans, their families and the public. Veterans can share their experiences with each other as well as with civilians to help shed light on the importance and complexity of service. If you have not served, this is a great place to offer your thanks by uploading a tribute video.

Resume Builder powered by Google Docs – We found that Docs can be a particularly helpful tool to transitioning servicemembers seeking employment. Resume Builder generates an auto-formatted resume that can be easily edited, saved and downloaded to share with potential employers.

Tour Builder powered by Google Earth (coming soon). A new way to tell your military story. Today, you can view some sample “tours”— 3D maps of veterans’ service histories, complete with photos and videos. Stay tuned for more details and updates on the Google Lat Long Blog.

This week, we introduced the Veterans Job Bank in partnership with the Department of Veterans Affairs. The Veterans Job Bank is a customized job search engine in the National Resource Directory (NRD), which is powered by Google Custom Search technology and crawls the web for JobPosting markup from Schema.org to identify veteran-committed job openings.

via American Human Development Project


Click here to explore a set of interactive maps with data from 2008-2011. In the map above, I selected “High School Freshmen not Graduating after 4 Years” from the “dashboard of risks” menu, for all states, all ethnic groups, and the most recent data set. You can also view data by top 10 metropolitan areas, congressional districts, and so on.

Whites in Washington, DC, live, on average, twelve years longer than African Americans in the same city.

In the 2007–9 Great Recession, college graduates faced an un- and underemployment rate of 1 in 10; the rate for high school dropouts was greater than 1 in 3.

In no U.S. states do African Americans, Latinos, or Native Americans earn more than Asian Americans or whites.

These startling facts are just some of the issues covered in The Measure of America 2010-2011. With a foreword by Jeffrey D. Sachs, the second volume in The Measure of America series is an easy-to-understand guide to where different groups stand today, and why. The book contains American Human Development Index ranking for all 50 states, 435 congressional districts, major metropolitan areas, racial and ethnic groups, as well as men and women. It concludes with a set of recommendations for priority actions required to improve scores on the Index across the board and to close the stark gaps that separate groups.

The Measure of America 2010-2011 also shines a spotlight on risks to progress and opportunity, and identifies tested approaches to fostering resilience among different groups: Who is most at risk for obesity? How can workers secure better footholds in the job market? How important is early childhood education? This report provides the tools necessary to build upon past policy successes, protect the progress made over the last half century from emerging risks, and develop an infrastructure of opportunity that can serve a new generation of Americans.