The GLC Blog

Talent & technology enable sustainable economic growth. The GLC blog highlights economic development above & beyond industrial recruitment.

Learning with Middle Schoolers

posted Jul 31, 2014, 10:59 AM by Greg Laudeman   [ updated Jul 31, 2014, 11:21 AM ]

I had the privilege to learn with some of the students at the East Lake Academy for Fine Arts this week. They demonstrated how ordinary folks can generate extraordinary results when they learn together. 

It started as a discussion about using technology for project-based learning with Lakesha Carson, the East Lake Academy principal. They had purchased Chromebooks for all their sixth graders, and were planning to purchase more. But what to do with them? There had already been some discussion about creating a garden as a way to learn about health and economics as well as horticulture. Along with my colleague Dr. Valerie Radu, I suggested putting it in the broader context of the community, and using asset and capability mapping to develop ideas about how to improve prosperity and wellness for the community.

Where does the technology come in? The idea was to use Mozilla Webmaker tools to develop, document, and share their ideas.

So how did it work out? Great! The kids came up with some awesome ideas. The ideas had to be based on data, practical, and impactful. All of the ideas fit the bill: 

That's not to say we didn't have any issues! For one thing we didn't get to use Webmaker tools. The students registration verification emails got caught in the school system's spam filter. They used Prezi instead, which they already knew well. Also, the students learned a lot about socioeconomic analysis without realizing it. These are very useful skills but we didn't explicitly tell them how and why asset and capability mapping are useful until the end.

The funny thing is that I learned a lot that I already knew. There's an important difference between having information and knowing in practice:

  1. Tell them what they're going to learn and why it's useful before you start, then remind them what they learned after it's done
  2. Start with the challenge and the tools: What you want to accomplish, why it's important, and how to get it done
  3. Provide a flexibly structured process for accomplishing the challenge and exploring the tools in small chunks
  4. Make it meaningful... And, fun too!
  5. Engage community stakeholders to ask questions, discover answers, and provide feedback & guidance rather than just provide information
  6. Appreciate ordinary knowledge in order to make your expertise relevant and useful
Regular folks (middle school students, for example) have great ideas and meaningful knowledge for solving problems, which you'll discover if you're willing to learn with them. It's all about learning together.

Innovation Districts and Learning Regions

posted Jun 11, 2014, 9:18 PM by Greg Laudeman   [ updated Jul 31, 2014, 9:59 AM ]

Bruce Katz and Julie Wagner's work on innovation districts at Brookings is great stuff. It's powerful yet practical. But it's not unprecedented. Scholars have been studying innovation areas for quite some time, especially in Europe. The post is kind of long and academic, but is a good review of a lot the literatures. It's abstracted from my dissertation, so please excuse the dweebiness.

Agglomeration and propinquity reduces transaction costs, allowing firms to be smaller and more specialized. Thus, “much of the competitive advantage lies outside a given company or even outside its industry, residing instead in the location of its business units” (Porter, 2003, p. 254, emphasis in original). The rise and fall of regions may be understood by replacing the term “competitive advantage” in this quote with the word “knowledge.” The unique availability of a full range of specialized knowledge makes regions economically important.

Marshall emphasizes in particular the mutual knowledge and trust that reduces transaction costs in the local production system; the industrial atmosphere which facilitates the generation and transfer of skills and qualifications of workforce required by local industry; and the effect of both these aspects in promoting (incremental) innovations and innovation diffusion among small firms in industrial districts. (Asheim, 2003, pp. 415-416)

Many commentators maintain that improvements in communication should reduce the rationale for agglomeration (Cairncross, 2001). Others point out that this has not happened because collective assets and capabilities, transfer of tacit knowledge, and the very acts of creating knowledge and innovating require propinquity (Calhoun, 1998; Brown and Duguid, 2002; Boschma, 2005; Cooke and Leysdesdorff, 2005).

Research shows the role that the production of information and knowledge plays in our society (Machlup, 1962; Porat, 1977), and the roles of institutions and knowledge in economic theory (Williamson, 2000; Cortright, 2001). An emphasis on innovation by business thought leaders (Drucker, 1985, 2002/1985) makes agglomeration a practical matter. Scholars point to complementary public and private roles, and to balance between competition and cooperation, as important in agglomeration. In industrial agglomeration there is division of labor (specialization) among numerous small firms, broad and rapid dissemination of information, and a highly skilled workforce. Agglomerating involves increasing importance of continual, radical innovations, and collective cognizance of a globalizing economy. It requires learning, most of all (Asheim, 2003). Piore and Sabel (1984) see the integration of community life with productive activities as the means by which networks of firms maintain collective assets and continually innovate. As Asheim (2003) puts it:

In a learning economy, the competitive advantage of firms and regions is based on innovation, interactive learning processes. … [O]ne problematic aspect of the learning economy has been its focus on ‘catching up’ learning based on incremental innovations, and not radical innovations requiring the creation of new knowledge. (pp. 426-427)

The concept of “learning regions” was proposed to explain how agglomeration fosters continual and radical innovations, and to illuminate modern issues related to globalization, knowledge-intensive enterprises, and technological change (Florida, 1995). Amin (2008) and other scholars (Tolliday & Zeitlin, 1992; Burrows, Gilbert & Pollert, 1992) contrast these socioeconomic phenomena with large-scale, standardized production that they refer to as Fordism, in reference to industrial approaches popularized by automotive magnate Henry Ford. In a global, post-Fordist, innovation-oriented economy, regions matter more than ever because “regions themselves are becoming focal points of knowledge-creation and learning … [that] function as collectors and repositories of knowledge and ideas, providing an underlying environment or infrastructure that facilitates the flow of knowledge, ideas, and learning” (Florida, 1995, p. 528). Florida goes on to say:

Learning regions provide the crucial inputs for knowledge-intensive economic organization to flourish: a manufacturing infrastructure of interconnected vendors and suppliers; a human infrastructure that can produce knowledge workers, facilitates the development of a team orientation, and which is organized around life-long learning; a physical and communication infrastructure which facilitates and supports constant sharing of information, electronic exchange of data and information, just-in-time delivery of goods and services, and integration into the global economy; and capital allocation and industrial governance systems attend to the needs of knowledge-intensive organizations. (p. 534)

The challenges for firms, Florida (1995) maintains, are to “adopt new organizational and management systems that harness knowledge and intelligence,” to maintain “a balance between cutting edge innovation and high-quality and efficient production,” “to spur individual genius and creativity … and the collective mobilization of knowledge,” and “to build integrated and dense global webs of innovation and production” (p. 534). All of which implies a shift away from “the increasingly dysfunctional Fordist model” to sustainable advantage based on “continuous improvement of technology, continuous development of human resources, the use of clean production technology, elimination of waste, and a commitment to continuous environmental improvement” (p. 535). The implication is that firms cannot do these things on their own but require an intellectual, physical, and social environment that enables them to do them collectively: a learning region.

The learning-region paradigm emphasizes the networks or associational characteristics of a region in which firms are embedded, subsuming individual entrepreneurs and workers to consider how they function together rather than operate independently (Granovetter, 1985; Saxenian, 1994; Morgan, 1997). Various forms of proximity—cognitive, organizational, social, institutional, and geographical—provide stability and enable interactive learning (Boschma, 2005), but excessive stability and static interactions resulting from “institutional thickness” can impede innovation (Amin and Thrift, 1995; Hauser, Tappeiner & Walde, 2007). Dynamic social networks with abundant weak ties within regions allow for knowledge spillovers and new opportunities for interactive learning. Broader extra-local networks bring new capabilities, ideas, and technologies into regions (MacKinnon, Cumbers, and Chapman, 2002). Both types of ties reduce transaction costs for knowledge as well as other resources, contributing to innovation by making it easy to connect disparate chunks of information into usable and useful knowledge.

Embeddedness must be balanced by autonomy. If it is not, regions can get locked into a particular technology, following it from boom to bust. “It is the type of network relationships between organizations (firms, institutions) rather than their spatial clustering alone that determines the ability of regions to adapt” (Boschma and Lambooy, 1999, p. 393). Dynamism in social networks—lots of weak ties and shifting relationships—allows clusters (or the communities or regions in which they operate) to diversify, reinvent and revitalize themselves, and avoid technologically-determined path-dependency. Stronger, more stable ties provide governance, particularly to and through institutions, and reduce uncertainty, making it more practical for actors to take risks (Morgan, 1997).

Some regional-learning literature, particularly prior to Florida’s explication of the concept, extends resource-based theories of organizations to explain why firms cluster together by industry (see, for example, Porter, 1990). Breznitz and Taylor (2010) contrast such factor-oriented theoretical perspectives with others that focus on social structure of regions, such as the dynamics of the “triple helix” of academia, government, and industry (Etzkotwitz and Leydesdorff, 1997; Etzkowitz, 2008) and an interactive model of innovation (Morgan, 1997). Cooke (2002) suggests that regional learning is essentially collaborative economic action by a localized socioeconomic system in response to natural socioeconomic disequilibrium. This requires social connections that are dynamic yet resilient: “knowledge is in the network,” Cooke (2002) maintains, “because each move in the interactive innovation process requires learning from other than those involved in the preceding move” (pp. 2 – 3, emphasis in the original). Breznitz and Taylor (2010) conclude that social structure is as important for innovation as economic factors, and more important to growing and retaining producers of technological innovations.

The triple-helix theory (Etzkowitz & Leydesdorff, 1997; Etzkotwitz, 2008) posits that a general type of social-network structure must exist for regional learning, and evolves in a particular way to sustain innovation. Generally, Etzkotwitz (2008) maintains, triple-helix regional learning emerges as the distinction between business and science is blurred, and as government facilitates this blurring with resources and regulatory relief. Civil society and voluntary associations provide the space for the helices to connect and overlap. “A triple helix regime typically begins as university, industry, and government enter into a reciprocal relationship with each other in which each attempts to enhance the performance of the other” (Etzkotwitz, 2008, p. 8). As industries become more knowledge-intensive, government and university play more important roles as enablers.  The triple helix evolves as each strand—academia, government, or industry—takes on new roles similar to the roles of the others in support of the others’ core competencies, as each strives to make the others successful. Performance of each helix improves as individuals and information circulate through it, and individuals and information circulating between the helices fuels innovation.

Innovation is an interactive learning process, says Morgan (1997), with powerful feedback loops incorporating common and tacit knowledge, “that is shaped by a variety of institutional routines and social conventions” (Morgan, 1997, p. 493). Agglomeration, or clusters of complementary specialized entities in proximity and cooperating with each other, is a hallmark of learning regions. But the clusters are byproducts of the innovation process, of social propagation of knowledge from individuals to community, and of mobility within the region between firms (Cooke, 2002). These are made possible in turn by norms of reciprocity and trust—social capital—that facilitate network development, support interactive learning and innovation, and thereby provide competitive advantage. Cook maintains that “[C]lustering [exists] for learning, knowledge transfer, collaboration, and the exploitation of spillovers” (p. 3). The “innovation as interactive learning” theory further explicates and supports the “evolving triple helix as source of sustained radical innovation” theory: The triple helix provides the institutional infrastructure for interactive learning, and interactive learning provides the means by which the triple helix evolves.

Brown and Duguid (2002) maintain that the only means of constructing regional advantage is to capitalize on local knowledge that is simultaneously “leaky” and “sticky.” Such knowledge inevitably leaks out of particular organizations but sticks in a particular region because it inheres to an embedded boundary, spanning local social networks.  Also consider what may be called “optimal proximity,” presented by Boschma (2005): a loosely coupled system, balancing local “buzz” with extra-local linkages, combining community and market relations, and providing institutional checks and balances, to create a common knowledge base with diverse but complementary capabilities. This involves cognitive, organizational, social, and institutional capabilities across and within geographical limits. Brown and Duguid (2002) and Boschma (2005) make essentially the same point: Sustained innovation capacity comes from leveraging unique local human assets for acquiring relevant global human assets and constantly recombining them. These perspectives are essentially elaborations on Marshall (Asheim, 2003), Piore and Sabel (1984), and others.

In the same ways that interactive learning enables firms to generate marketable innovations, case studies have shown that interactive learning by policy makers (Hassink, 2005) and boundary spanning by civic organizations (Safford, 2009) can be important for regions to recover from path dependency and revitalize. Cooke and Leysdesdorff (2005) maintain that regions provide “constructed advantage”—as opposed to comparative and competitive advantages—by intentionally aligning and integrating the regional economy, governance, knowledge infrastructure, and community and culture. Constructed advantage involves combining symbolic/creative, synthetic/technical, and analytic/scientific forms, linking the subsystems for knowledge creation, exploration, and exploitation, enabled by the triple helix. Gertler and Wolfe (2004) look at regional foresight exercises as interactive learning by individuals, organizations, and regions that allow them to adapt and innovate. Such broad-based collective learning can overcome the barriers to learning intrinsic to capitalism. Cross-sector interactive learning allows for the creation of the entirely new organizations necessary for the creative forgetting and unlearning by organizations and social systems. It leads to deep regional economic restructuring (Johnson, 1992; Hudson, 1999; Boschma and Lambooy, 1999).

A new kind of organisation is spearheading the phenomenon: knowledge-based communities, i.e. networks of individuals striving, first and foremost, to produce and circulate new knowledge and working for different, even rival, organisations. One sign that a knowledge-based economy is developing can be seen when such individuals penetrate conventional organisations to which their continuing attachment to an “external” knowledge-based community represents a valuable asset. As these communities develop their activities, they become agents of change for the economy as a whole. (David & Foray, 2002, p. 9)

A knowledge-intensive community is a community where a large proportion of members is involved in the production and reproduction of knowledge and, hence, the creation of a public (or semi-public) space where knowledge is circulated and where codification and dissemination costs have been radically reduced through the use of new information and communication technologies. (David & Foray, 2002, p. 14)

References: https://sites.google.com/a/laudeman.com/portfolio/other-content

An Innovative Approach to Workforce Development

posted May 9, 2014, 8:54 AM by Greg Laudeman

Here is an innovative way to re-engage the long-term unemployed in stable, well paying jobs. It builds on practices and tools that technologists have developed in the last few decades. These practices and tools have proven very effective for “geeks”—e.g., highly skilled technologists—but have yet to make it into the mainstream of workforce development. This is because they are so different from current workforce development practices and tools.

The primary difference between the new approach and the current approach is that the work is distributed: This model does not depend on centralized authorities or knowledge resources. Instead, online social media and informal problem-based events are used to connect experts with novices, and those in between, and improve everyone’s skills. The media and events often involve a friendly combination of competition and collaboration to effectively engages and motivates persons with diverse background and capabilities. The new model builds on technology practices and tools to create supportive interpersonal connections and provide experiential learning:

1.     Provide online social network system that is focus on developing valuable skills by:

a.     Building supportive interpersonal connections to individuals currently working in targeted occupations

b.     Coordinating, organizing, and scheduling experiential learning activities

c.      Put individuals on career pathways that capitalize on their experience and knowledge, educational resources in their community, and the specific needs of local employers

2.     Conduct problem-based experiential learning activities and events that address issues and needs of specific employers and the general community:

a.     Build supportive interpersonal connections to individuals currently working in targeted occupations

b.     Demonstrate and develop soft skill as well as technical skills and overcome biases against long-term unemployed

c.      Move individuals among career pathways that capitalize on their experience and knowledge, educational resources in their community, and the specific needs of local employers

This approach does not replace traditional education, training, and workforce development. Instead it complements and supports traditional approaches, increasing their efficacy.

Why is this innovative model needed?

Basically, an innovative approach to workforce development is needed because the old methods just don’t work. There are many good jobs going unfilled while there are many folks who have effectively dropped out of the labor pool. The economy has fundamentally changed it recent decades, yet workforce development is done in much the same way as it was done in the early 20th century. We need a new approach that not only accommodates but actually capitalizes on today’s economic realities.

A recent article in the Washington Post [1] examined the plight of the long-term unemployed. It noted that, “long-term unemployment has become a trap that is difficult to escape” and “could become a permanent underclass, left behind by the nation’s broader economic recovery.” Skills deteriorate during unemployment. The long-term unemployed tend to take jobs that are less stable and steady, don’t fit their abilities, and pay less than their previous jobs. To make matters worse, employers often place a stigma on the long-term unemployed and won’t even consider their applications.

What’s to be done? Well, it is commonly understood that who you know is as important as what you know. For the long-term unemployed this means rebuilding social connections as well as redeveloping relevant skills. One commentator maintains that, “Employees stopped learning how to go out and find success for themselves” [2]. But the fact is that finding success is not and has never been an individual endeavor. Even the ability to get into, let alone make it through, a training or educational program depends a great deal on how much social support one has. Recent research [3] shows that the most successful college graduates are those who develop supportive interpersonal relationships with professors and get involved in experiential learning.

Today’s technology world provides innovative practices and tools to solve this problem. Social media and networking software provide means for individuals to connect with others around common interests. This technology greatly reduces transaction costs: the difficulty of finding, making arrangements with, and coordinating with others. Software developers are especially good at using special purpose social networks like Github (https://github.com/) and Stackoverflow (http://stackoverflow.com/) for developing skills and sharing techniques. This is the way technology experts stay up-to-date.

Another way that computer programmers and similar technologists learn new skills is via face-to-face events such as hackathons and unconferences. For technologists a hack is an elegant solution to an interesting problem, and hackers are—in contrast to the term’s negative connotations—skilled problem-solvers. A hackathon is a problem-focused meeting during which participants self-organize (there no or minimal agenda) to develop solutions. Hackathons are friendly competitions in which teams form around competing solutions. At the end, the teams demo their solutions and everyone votes on which is best. Unconferences are similar, but are organized, so to speak, around a general topic. Again, there is no agenda. Participants create the agenda as part of the event, and self-organize around sub-topics, sharing information via informal discussion or collaboration. It’s almost like taking away the formal panels and presentations of a regular conference, and concentrating on the discussions that happen in the foyers, hallways, and lobbies. The difference is that during unconferences technologies such as wikis are used to capture and share content created by participants.

References:

1.     “Long-term unemployed struggle to find — and keep — jobs,” Ylan Q. Mui, The Washington Post, April 18, 2014, http://www.washingtonpost.com/business/economy/long-term-unemployed-struggle-to-find--and-keep--jobs/2014/04/18/134c48f6-c4ad-11e3-bcec-b71ee10e9bc3_print.html

2.     “Why Many Unemployed Workers Will Never Get Jobs,” Ira Wolfe, Huffington Post, Business Blog, May 7, 2014, http://www.huffingtonpost.com/ira-wolfe/why-many-unemployment_b_5273611.html

3.     “Gallup: College Type Has Little to Do With Success,” Allie Bidwell, U.S. News and World Report, May 6, 2014, http://www.usnews.com/news/articles/2014/05/06/gallup-purdue-index-measures-the-magic-equation-to-student-success

"The Customer-activated Enterprise"

posted Oct 17, 2013, 3:28 PM by Greg Laudeman   [ updated Oct 17, 2013, 3:29 PM ]

IBM has just released a fascinating study about technology strategy, based on interviews with over 4,000 executives. Karstin Bodell did a wonderful presentation for the Chattanooga Technology Council on the study. The big take-away: "the most successful organizations actively encourage customers and citizens to influence the decisions [the organizations] make." What does being "customer-activated" have to do with technology? Everything.

IBM says three themes will determine an organization will succeed, or not. The first is openness to customer influence. The executives IBM interviewed, particularly those from high performing organizations, saw sharing control with customers as a competitive imperative. They are expanding their partnerships and empowering employees to increase collaboration with customers. And, they are using digital technology as the means for customer engagement.

A related theme is that high performing organization create  engaging customer experiences; for customers as individuals rather than targeted market segments. Executives in high-performing organizations are increasingly personally focused on customer experiences tailored to individual interests and needs. How can an enterprise with thousands or millions of customers hope to do this? Digital technology.

Actually, it's more than that; high-performing organizations are developing integrated digital-physical strategies. "Say what?!? What the heck does that mean?," you may ask. IBM says, "the very distinction between the virtual and material is evaporating." It means that physical products have computers built into them, and software products are built into places and things. Phones with GPS are the tip of this iceberg. Organizations that figure out how to integrate the digital and physical will be the winners. More practically, if your IT strategy is separate from your overall business strategy, you are at a disadvantage.

The really fascinating conclusion IBM's study is that "The most flourishing enterprises are typically those that liaise with closely with the customers, partners and suppliers, and actively promote the development of employee networks." Or, in regular language, if you want to be successful you have to work really well with folks inside and outside your organization, and you have to make technology a big part of this, without making it all about technology. Its just a means to an end. The goal is to have customers, employees, and suppliers guide your organization to success.

You can find "The Customer-activated Enterprise: Insights from the Global C-suite Study" online at http://www-935.ibm.com/services/us/en/c-suite/csuitestudy2013/.

"Ahead of the Curve"

posted Oct 14, 2013, 5:09 PM by Greg Laudeman   [ updated Oct 17, 2013, 6:11 AM ]

The Boston Consulting Group (BCG), with support from Microsoft, provides an insightful report on how small & medium enterprises (SMEs) make use of information technology. The central issue here is how—and whether—IT actually makes SMEs and other organizations more competitive, productive, profitable, etc. This is far from a non-issue. IT investment rarely has clear or certain return. Costs can multiply and benefits can be elusive. You can find BCG's report here.

BCG looked at SMEs in five countries. They found that SMEs:
  • SMEs operate more efficiently via technology, which means more working capital and higher profit margins.
  • Technology-enabled collaboration with customers and employees is critical to being competitive. Technology leaders among SMEs have a broader and more engaged customer base.
  • The cloud (internet-based, distributed computing) allows leading SMEs to be work more flexibly and to scale farther & faster than they could otherwise. It also makes their systems more reliable.
  • Experimentation with business models, to tune the current approach or try something totally new, is much easier with cloud-based systems. 
  • Leading SMEs invest in technology smarter. They invest in a disciplined, focused manner, often by tapping local partners and global experts.
The policy conclusions are reasonably simple, in concept. Be sure SMEs have technology infrastructure and networks services readily available to them. Address concerns about data security and privacy. Nurture local IT ecosystems. Broaden and strengthen the technology skills base. Support interoperability and open standards as means to foster innovation. Reduce government-induced costs related to IT.

These are powerful insights that apply on local and regional, as well as national levels. Indeed, these ideas add up to an effective and relatively low-cost strategy to grow local economies.

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