James Surowiecki has his own take on the United States' innovative power. In his column in the New Yorker he writes about the next investment bubble and why it is good for the US. Positive externalities again (of much heralded American risk-seeking behavior). Though the losers of the dotcom bust may not quite see it that way...
In the early sixties, investors stumbled on a neat trick: if a company had “tron” or “tronics” in its name, its stock was a hit. This was the dawn of the computer age, and a host of businesses straight out of “The Jetsons”—Astron, Transitron, Videotronics—became the darlings of Wall Street. The boom ended badly, as booms so often do. In 1962, the stock market plunged, and the trons and tronics were knocked flat, most of them for good. But investors have short memories. At the end of the decade, they fell for tech stocks again (the magic word this time around was “Silicon”). Later, it was P.C.s, then biotech, and, more recently, dot-coms. Infatuation and disillusionment: it’s the American way. Now investors have found a new crush: nanotechnology.
Even if nanotech does live up to its promise, though, almost all the nanotech companies that are now so hot on Wall Street, not to mention those still dreaming of blockbuster I.P.O.s, will be gone in a decade. That’s how new industries get built in America: a horde of companies rise up, the weak or misguided fall away, and a few good ones thrive. With a general-purpose technology like nanotech or the Internet, the process is even bloodier; because you can do so many things with the technology, you pursue a lot more fruitless notions and reckless schemes before you figure out what really works.
The price of innovation is that you spend money on bad ideas as well as on good ones. Some of the money comes from venture capitalists, who factor the inevitable mistakes into their investments. And some of it comes from government (Washington is spending $3.7 billion on nanotech research over the next four years). But a good chunk comes from all those money managers and retail investors who believe that they will be getting in on the next Xerox, the next Amgen, the next Microsoft. Most of them won’t, of course; in fact, most of them will end up losing money (which is why there’s already been a great deal of finger-wagging over investor interest in nanotech). The paradox is that their losses are often society’s gain. Thanks to investors’ willingness to take a flyer on things like nanotech, companies are able to do more research and development than is economically rational; they experiment with ideas and approaches that, under leaner conditions, would never be tried. It’s a messy process, but it’s the best one we’ve found for inspiring real innovation.
That doesn’t mean that all investor manias are healthy: no one benefitted when Wall Street thought bowling was going to take over America, for instance. But when it comes to transformative technologies, overoptimistic investors are actually working for the common good—even if they don’t know it. We can be glad that investors financed the construction of thousands of miles of track in the middle of the nineteenth century, despite the fact that most of them dropped a bundle doing it. The same goes for overoptimistic investors who poured money into semiconductors thirty years ago, financed undersea fibre-optic cables in the late nineties, and now are poised to lose their shirts in the coming nanobubble. In the dreams of avarice lie the hopes of progress.
Friday
Externalities and the problem with the outsourcing debate
As Hal Varian points out in his NYT column today, the problem with the outsourcing debate is that it doesn't treat costs and benefits in the same way.
The political problem with trade is simply this: when the dollars flow offshore, it is easy to identify those who are hurt. But when the dollars flow back, it is much more difficult to discern the beneficiaries.
The debates about trade are not about whether we should accept those good deals offered to us by cheap foreign labor - of course we should. The debate is all about who will capture the benefits from those deals and who will bear the costs.
Ideally, those who benefit the most from trade would compensate those who lose. In practice, virtually everyone benefits to some degree from cheaper goods and services, so compensation for those who lose from trade should come from general revenues.
As so often in the discussion of innovation (outsourcing being one, too), problems arise in dealing with externalities. The same goes for the problem of investments by 'knowledge seekers.' If it were possible to put a price on the benefits to a region of being an R&D hub and on the risk of having other regions catch up faster, there would be no need to suddenly fear FDI. A region could make a calculated decision on how much to pay (or charge) foreign firms. Unfortunately, there are often too many uncertainties involved to arrive at hard figures - especially in R&D intensive industries. But as it is, many of these regions probably do calculate and find that the positive externalities are worth quite a lot, i.e. multi-year tax-breaks, real-estate subsidies, etc.
The political problem with trade is simply this: when the dollars flow offshore, it is easy to identify those who are hurt. But when the dollars flow back, it is much more difficult to discern the beneficiaries.
The debates about trade are not about whether we should accept those good deals offered to us by cheap foreign labor - of course we should. The debate is all about who will capture the benefits from those deals and who will bear the costs.
Ideally, those who benefit the most from trade would compensate those who lose. In practice, virtually everyone benefits to some degree from cheaper goods and services, so compensation for those who lose from trade should come from general revenues.
As so often in the discussion of innovation (outsourcing being one, too), problems arise in dealing with externalities. The same goes for the problem of investments by 'knowledge seekers.' If it were possible to put a price on the benefits to a region of being an R&D hub and on the risk of having other regions catch up faster, there would be no need to suddenly fear FDI. A region could make a calculated decision on how much to pay (or charge) foreign firms. Unfortunately, there are often too many uncertainties involved to arrive at hard figures - especially in R&D intensive industries. But as it is, many of these regions probably do calculate and find that the positive externalities are worth quite a lot, i.e. multi-year tax-breaks, real-estate subsidies, etc.
Knowledge seekers
Knowledge Seeking and Location Choice of Foreign Direct Investment in the United States, Wilbur Chung and Juan Alcacer, 2002
In the latest Knowledge@Wharton newsletter, Wilbur Chung and Juan Alcacer present the hypothesis that foreign direct investment (FDI) is not purely cost or market driven. Companies acquire firms, engage in joint-ventures and set up green fields ventures for access to unique knowledge - not just to cut cost or gain access to markets.
(The academic paper can be found here.)
While such seekers have historically been characterized as technology laggards trying to catch up with market movers, more recently scholars have embraced the idea that leaders, too, invest abroad as they seek to broaden or deepen their knowledge.
The study covers FDI in the United States (by state and by economic region).
Not surprisingly, they found that knowledge seeking is most prevalent among foreign companies in R&D-heavy industries such as pharmaceuticals, semiconductors and electronics. In fact, they found that drug makers are twice as likely to seek knowledge abroad as companies in any other industry.
Where were knowledge seekers most likely to invest? R&D-intensive areas. 'Many investments, 32% of the sample, fall into four major metropolitan areas: New York City, San Francisco, Los Angeles and Chicago,' the researchers write. In contrast, a region of the United States known mostly for agriculture - the Dakotas and Idaho - had no investments during our investigation period.'
It seems obvious that a European biotech company would conduct R&D in the US, that a knowledge seeker in pharmaceuticals would set up shop near Boston, or that a company seeking state-of-the-art IT knowledge might invest in operations in Silicon Valley. But what about the opposite direction? The column mentions GE's new research and development lab for medical systems in China. The lab focuses on product development tailored to emerging economies. Is this a unique example? (GE does seem to be a pioneer as far as spreading R&D globally goes...)
K@W concludes that leading regions in the knowledge industry should be wary about inviting foreign firms and giving them tax-breaks or other incentives.
Traditionally, investments from foreign firms have been celebrated by holding press conferences and ribbon-cutting ceremonies, as South Carolina and Alabama did when they landed BMW and Mercedes. But if Chung is right, these investments may not always be unalloyed victories. 'If many foreign firms enter seeking new knowledge, [productivity] gains may not accrue, and a nation's technological uniqueness might be more quickly replicated,' he and Alcacer point out in their paper. Of course investments from foreign firms may still bring benefits such as more jobs and spin-off economic activity as, for example, suppliers spring up near the foreign firm's new plant.
This sounds much like an absurd reversal of the current outsourcing debate - we don't want our firms to invest abroad because that means we'll lose our jobs (even though our firms will be more competitive), but we don't want foreign firms to invest here because that means we'll lose our competitive knowledge edge (even though we'll get more jobs).
Besides, the argument doesn't hold. Knowledge doesn't diminish by being shared - and if foreign firms invest in US high-tech clusters, this strengthens the competitive advantage of those clusters by increasing their innovative churn. Many of a cluster's advantages (labour pool, social networks, proximity to leading research labs/universities etc.) don't travel well.
To be fair, Chung and Alcacer acknowledge the importance of place in other parts of the discussion, and the 'threat' to American competitiveness is only vaguely alluded to in a generalized statement in their academic paper.
An objection to Chung and Alcacer's research - and to the notion of knowledge seeking via foreign expansion, in general - might be that investing abroad is a costly way to learn. After all, patents and technical manuals are widely published, and newly graduated scientists and engineers are eager for jobs.
But Chung argues that this objection misconstrues the nature of knowledge. 'Knowledge can be broken into a codifiable piece - the stuff you can write down - and a tacit piece,' he explains. ... Consider eating at a restaurant, he says. 'You don't really experience it unless you go there yourself. You can have someone tell you about it. You can order takeout from the restaurant. You can buy the cookbook. But to get the full benefit of the experience, you have to go there.'
Think about it: Which advantage is eroded more easily - an emerging economy's lower labor cost, or the United States' R&D and innovation prowess? (Doubters may want to read Thomas Friedman's recent op-ed.)
By all means, negotiate IPR protections when entering alliances and joint-ventures, but don't get paranoid about foreigners transferring their money and their researchers here.
In the latest Knowledge@Wharton newsletter, Wilbur Chung and Juan Alcacer present the hypothesis that foreign direct investment (FDI) is not purely cost or market driven. Companies acquire firms, engage in joint-ventures and set up green fields ventures for access to unique knowledge - not just to cut cost or gain access to markets.
(The academic paper can be found here.)
While such seekers have historically been characterized as technology laggards trying to catch up with market movers, more recently scholars have embraced the idea that leaders, too, invest abroad as they seek to broaden or deepen their knowledge.
The study covers FDI in the United States (by state and by economic region).
Not surprisingly, they found that knowledge seeking is most prevalent among foreign companies in R&D-heavy industries such as pharmaceuticals, semiconductors and electronics. In fact, they found that drug makers are twice as likely to seek knowledge abroad as companies in any other industry.
Where were knowledge seekers most likely to invest? R&D-intensive areas. 'Many investments, 32% of the sample, fall into four major metropolitan areas: New York City, San Francisco, Los Angeles and Chicago,' the researchers write. In contrast, a region of the United States known mostly for agriculture - the Dakotas and Idaho - had no investments during our investigation period.'
It seems obvious that a European biotech company would conduct R&D in the US, that a knowledge seeker in pharmaceuticals would set up shop near Boston, or that a company seeking state-of-the-art IT knowledge might invest in operations in Silicon Valley. But what about the opposite direction? The column mentions GE's new research and development lab for medical systems in China. The lab focuses on product development tailored to emerging economies. Is this a unique example? (GE does seem to be a pioneer as far as spreading R&D globally goes...)
K@W concludes that leading regions in the knowledge industry should be wary about inviting foreign firms and giving them tax-breaks or other incentives.
Traditionally, investments from foreign firms have been celebrated by holding press conferences and ribbon-cutting ceremonies, as South Carolina and Alabama did when they landed BMW and Mercedes. But if Chung is right, these investments may not always be unalloyed victories. 'If many foreign firms enter seeking new knowledge, [productivity] gains may not accrue, and a nation's technological uniqueness might be more quickly replicated,' he and Alcacer point out in their paper. Of course investments from foreign firms may still bring benefits such as more jobs and spin-off economic activity as, for example, suppliers spring up near the foreign firm's new plant.
This sounds much like an absurd reversal of the current outsourcing debate - we don't want our firms to invest abroad because that means we'll lose our jobs (even though our firms will be more competitive), but we don't want foreign firms to invest here because that means we'll lose our competitive knowledge edge (even though we'll get more jobs).
Besides, the argument doesn't hold. Knowledge doesn't diminish by being shared - and if foreign firms invest in US high-tech clusters, this strengthens the competitive advantage of those clusters by increasing their innovative churn. Many of a cluster's advantages (labour pool, social networks, proximity to leading research labs/universities etc.) don't travel well.
To be fair, Chung and Alcacer acknowledge the importance of place in other parts of the discussion, and the 'threat' to American competitiveness is only vaguely alluded to in a generalized statement in their academic paper.
An objection to Chung and Alcacer's research - and to the notion of knowledge seeking via foreign expansion, in general - might be that investing abroad is a costly way to learn. After all, patents and technical manuals are widely published, and newly graduated scientists and engineers are eager for jobs.
But Chung argues that this objection misconstrues the nature of knowledge. 'Knowledge can be broken into a codifiable piece - the stuff you can write down - and a tacit piece,' he explains. ... Consider eating at a restaurant, he says. 'You don't really experience it unless you go there yourself. You can have someone tell you about it. You can order takeout from the restaurant. You can buy the cookbook. But to get the full benefit of the experience, you have to go there.'
Think about it: Which advantage is eroded more easily - an emerging economy's lower labor cost, or the United States' R&D and innovation prowess? (Doubters may want to read Thomas Friedman's recent op-ed.)
By all means, negotiate IPR protections when entering alliances and joint-ventures, but don't get paranoid about foreigners transferring their money and their researchers here.
Thursday
What is innovation?
What is innovation? Approaches to distinguishing new products and processes from existing products and processes, Bruce S. Tether, 2003
In this paper, Bruce Tether from CRIC discusses various definitions of innovation and some tools for identifying innovations in research.
Tether argues that innovation is sometimes defined as an achievement, sometimes as the results or consequences of that achievement, and sometimes as a business approach - and that there is considerable confusion between the three.
Innovation as achievement
It can be difficult to know how easy it will be to develop a new technology, and the extent to which people will want to use it when it is available. For economists, these represent two types of uncertainties in the development of new technologies - technological uncertainties (will it work?) and market uncertainties (will it sell, how quickly, and will competitors quickly introduce their own versions of the product if it proves successful?). The presence of these uncertainties is often an indicator of innovation and will be important in various definitions of innovation.
Innovation as achievement (in the face of risk and uncertainties) can be two-fold:
1. Achieving a significant leap forward in the technological frontier
2. Re-conceptualising existing problems and thereby restructuring technological systems
Innovation as the consequence of achievement
'Great innovations' are primarily thought great because of the consequences of technologies, and not necessarily because of the novelty of the achievement itself, which in any case has usually transformed substantially from the original achievement through the accretion of little details.
What is important here is that innovation has unintended consequences that benefit everyone. Economists call these unintended consequences spillovers or positive externalities. (There can, of course, also be negative externalities.)
Innovation as dynamic capabilities
The conceptualisation of innovation - as a process - is becoming more widespread. Here, innovation is less associated with particular acts or achievements (and their consequences), and is more associated with an attitude of mind, and a whole ensemble of behaviours and practices associated with that attitude.
A truly innovative firm is not one that introduces a new product 'once in a blue moon', but is instead one that is continuously engaged in practices intended to enhance the probability that it will 'discover' new or better products or processes of making them. ... Central to this concept of innovation is being alive to change. Being flexible - being able to adapt what is done in different circumstances, such as to particular customers needs - is usually insufficient to constitute being truly innovative.
Firms that are innovative tend to have 'dynamic capabilities'. 'A dynamic capability is a learned and stable pattern of collective activity through which the organisation systematically generates and modifies its operating routines in pursuit of improved effectiveness.' (M. Zollo and S. Winter, 2002). This requires a combination of strategic and organisational skills.
Innovation in this sense does not necessarily coincide with innovation in the form of introducing new products and services.
Product innovation
One conceptualization of product innovation (Saviotti and Metcalfe, 1984) distinguishes between technical characteristics and service characteristics of a product, and maps the two onto each other. (E.g. number of cylinders in a car's engine vs/ acceleration.) Innovation can then happen in 5 conceptually different ways. (In practice they are often interdependent.)
1. A change in the absolute values of one or more of the technical characteristics
2. A change in the mixture or balance of the technical characteristics
3. A change in the pattern of mapping between the technical characteristics an the service characteristics
4. A change in the mixture or balance of the service characteristics
5. A change in the absolute values of one or more of the service characteristics.The problem with this approach is that it is practically impossible to measure service characteristics, such as brand value objectively.
Process innovation
The pattern of innovation in processes is likely to differ from that of products, and particularly from standardised 'mass produced' products. With standardised products, a new product is typically introduced (following processes of experimentation and prototype development) after which it will remain unchanged for some time. A few minor upgrades will be introduced over time, after which a bigger, generational change will be undertaken. ... The cycle is then repeated with the third and fourth generations of the product. Over time, the scale of improvement between the generations is likely to decline. ... Innovation is fairly easily measured, at least in principle, by the scale of the jumps, or steps between the products available.
By contrast, innovation in processes - and indeed in services as well as customised products - can follow a different path. Sometimes there is rapid learning immediately after the introduction of the process - this is the learning curve, initially the process is slow and inefficient, but gradually and on a continuous basis, minor improvements are introduced. The same pattern is repeated if a substantially new process is later introduced. Alternatively, after the initial innovation, there may be a slow process of continuous improvement, but after a while the scope for improvement diminishes.
The point here is that improvements, and innovations, may be much harder to identify in processes ... than with the archetypal mass-produced standardised products because improvements are less likely to occur in definite steps. In particular, it can be difficult to distinguish between variations and innovations.
Radical innovation and the hierarchical decomposability of technologies
The literature on innovation is replete with references to radical and incremental innovations, yet there is considerable confusion about what distinguishes an incremental from a radical innovation.
3 definitions:
Freeman (1982): Radical innovations are those that transcend the technical limitations (of the existing technologies)
Saviotti, Stubs, Coombs, and Gibbons (1982): Incremental innovation can be defined as a series of quantitative changes in known parameters or in the introduction into a given product of technical characteristics already used in some similar product. A radical innovation would be, instead, the appearance of a new technical characteristic.
Tushman and Anderson (1986) focus on the impact on the industry: Competence-destroying discontinuities are so fundamentally different from previous dominant technologies that the skills and knowledge base required to operate the core technology shift. ... Competence-enhancing discontinuities are order of magnitude improvements in price/performance that build on existing know-how within a product class.
Unfortunately, each case leaves significant room for disagreement in trying to categorize specific innovations.
Constant (1987) clarifies some of the issues by conceptualising technological systems. Ontologically, systems are composed of sub-systems which are composed of an immense variety of components. ... This hierarchical decomposability suggests the absolute relativity of all change: Whether a given change is perceived as radical or incremental depends solely on the hierarchical level chosen. A new valve, a new turbine material or fabrication technique may represent a revolutionary solution to a specific sub-problem at that level; yet the same change, viewed from the level or the total aircraft system may appear only as a typical incremental innovation.
Practical approaches to identifying innovation
Tether distinguishes between 'object based' approaches (the researcher identifies innovations) and 'subject based' approaches (the researcher asks firms about their innovative behaviour).
Several approaches are presented with a special emphasis on OECD's Oslo Manual, which is considered the international standard. Although it helps in specifying innovations, in Tether's opinion it doesn't distinguish enough between adoption of innovations and innovative activity. According to the Oslo Manual, a firm is innovative if it adopts a new technology - even if this adoption occurs without any learning, adaptation or risk-taking on the part of the firm.
Recommendations
Tether recommends a 3-dimensional approach to the evaluation of innovations.
For products: Conceptual novelty, technological uncertainty, and market uncertainty.
For processes: Conceptual novelty, technological uncertainty, learning & adaptation.
Comments
This could be a useful approach in justifying my choice of industry for case studies. A problem remains, however, in that the case studies will most likely be in the service industry. How do Tether's recommendations apply to services? The analytical dimensions of product innovations work for services. However, many will develop more along the line of processes with many incremental improvements, rather than large 'jumps'.
In the end, it might be more useful to work with the concept of innovation as a process/attitude/set of practices.
A footnote: Tether emphasizes that he is talking about innovation, not invention. The difference being that an innovation has been commercialised where an invention has not.
In this paper, Bruce Tether from CRIC discusses various definitions of innovation and some tools for identifying innovations in research.
Tether argues that innovation is sometimes defined as an achievement, sometimes as the results or consequences of that achievement, and sometimes as a business approach - and that there is considerable confusion between the three.
Innovation as achievement
It can be difficult to know how easy it will be to develop a new technology, and the extent to which people will want to use it when it is available. For economists, these represent two types of uncertainties in the development of new technologies - technological uncertainties (will it work?) and market uncertainties (will it sell, how quickly, and will competitors quickly introduce their own versions of the product if it proves successful?). The presence of these uncertainties is often an indicator of innovation and will be important in various definitions of innovation.
Innovation as achievement (in the face of risk and uncertainties) can be two-fold:
1. Achieving a significant leap forward in the technological frontier
2. Re-conceptualising existing problems and thereby restructuring technological systems
Innovation as the consequence of achievement
'Great innovations' are primarily thought great because of the consequences of technologies, and not necessarily because of the novelty of the achievement itself, which in any case has usually transformed substantially from the original achievement through the accretion of little details.
What is important here is that innovation has unintended consequences that benefit everyone. Economists call these unintended consequences spillovers or positive externalities. (There can, of course, also be negative externalities.)
Innovation as dynamic capabilities
The conceptualisation of innovation - as a process - is becoming more widespread. Here, innovation is less associated with particular acts or achievements (and their consequences), and is more associated with an attitude of mind, and a whole ensemble of behaviours and practices associated with that attitude.
A truly innovative firm is not one that introduces a new product 'once in a blue moon', but is instead one that is continuously engaged in practices intended to enhance the probability that it will 'discover' new or better products or processes of making them. ... Central to this concept of innovation is being alive to change. Being flexible - being able to adapt what is done in different circumstances, such as to particular customers needs - is usually insufficient to constitute being truly innovative.
Firms that are innovative tend to have 'dynamic capabilities'. 'A dynamic capability is a learned and stable pattern of collective activity through which the organisation systematically generates and modifies its operating routines in pursuit of improved effectiveness.' (M. Zollo and S. Winter, 2002). This requires a combination of strategic and organisational skills.
Innovation in this sense does not necessarily coincide with innovation in the form of introducing new products and services.
Product innovation
One conceptualization of product innovation (Saviotti and Metcalfe, 1984) distinguishes between technical characteristics and service characteristics of a product, and maps the two onto each other. (E.g. number of cylinders in a car's engine vs/ acceleration.) Innovation can then happen in 5 conceptually different ways. (In practice they are often interdependent.)
1. A change in the absolute values of one or more of the technical characteristics
2. A change in the mixture or balance of the technical characteristics
3. A change in the pattern of mapping between the technical characteristics an the service characteristics
4. A change in the mixture or balance of the service characteristics
5. A change in the absolute values of one or more of the service characteristics.The problem with this approach is that it is practically impossible to measure service characteristics, such as brand value objectively.
Process innovation
The pattern of innovation in processes is likely to differ from that of products, and particularly from standardised 'mass produced' products. With standardised products, a new product is typically introduced (following processes of experimentation and prototype development) after which it will remain unchanged for some time. A few minor upgrades will be introduced over time, after which a bigger, generational change will be undertaken. ... The cycle is then repeated with the third and fourth generations of the product. Over time, the scale of improvement between the generations is likely to decline. ... Innovation is fairly easily measured, at least in principle, by the scale of the jumps, or steps between the products available.
By contrast, innovation in processes - and indeed in services as well as customised products - can follow a different path. Sometimes there is rapid learning immediately after the introduction of the process - this is the learning curve, initially the process is slow and inefficient, but gradually and on a continuous basis, minor improvements are introduced. The same pattern is repeated if a substantially new process is later introduced. Alternatively, after the initial innovation, there may be a slow process of continuous improvement, but after a while the scope for improvement diminishes.
The point here is that improvements, and innovations, may be much harder to identify in processes ... than with the archetypal mass-produced standardised products because improvements are less likely to occur in definite steps. In particular, it can be difficult to distinguish between variations and innovations.
Radical innovation and the hierarchical decomposability of technologies
The literature on innovation is replete with references to radical and incremental innovations, yet there is considerable confusion about what distinguishes an incremental from a radical innovation.
3 definitions:
Freeman (1982): Radical innovations are those that transcend the technical limitations (of the existing technologies)
Saviotti, Stubs, Coombs, and Gibbons (1982): Incremental innovation can be defined as a series of quantitative changes in known parameters or in the introduction into a given product of technical characteristics already used in some similar product. A radical innovation would be, instead, the appearance of a new technical characteristic.
Tushman and Anderson (1986) focus on the impact on the industry: Competence-destroying discontinuities are so fundamentally different from previous dominant technologies that the skills and knowledge base required to operate the core technology shift. ... Competence-enhancing discontinuities are order of magnitude improvements in price/performance that build on existing know-how within a product class.
Unfortunately, each case leaves significant room for disagreement in trying to categorize specific innovations.
Constant (1987) clarifies some of the issues by conceptualising technological systems. Ontologically, systems are composed of sub-systems which are composed of an immense variety of components. ... This hierarchical decomposability suggests the absolute relativity of all change: Whether a given change is perceived as radical or incremental depends solely on the hierarchical level chosen. A new valve, a new turbine material or fabrication technique may represent a revolutionary solution to a specific sub-problem at that level; yet the same change, viewed from the level or the total aircraft system may appear only as a typical incremental innovation.
Practical approaches to identifying innovation
Tether distinguishes between 'object based' approaches (the researcher identifies innovations) and 'subject based' approaches (the researcher asks firms about their innovative behaviour).
Several approaches are presented with a special emphasis on OECD's Oslo Manual, which is considered the international standard. Although it helps in specifying innovations, in Tether's opinion it doesn't distinguish enough between adoption of innovations and innovative activity. According to the Oslo Manual, a firm is innovative if it adopts a new technology - even if this adoption occurs without any learning, adaptation or risk-taking on the part of the firm.
Recommendations
Tether recommends a 3-dimensional approach to the evaluation of innovations.
For products: Conceptual novelty, technological uncertainty, and market uncertainty.
For processes: Conceptual novelty, technological uncertainty, learning & adaptation.
Comments
This could be a useful approach in justifying my choice of industry for case studies. A problem remains, however, in that the case studies will most likely be in the service industry. How do Tether's recommendations apply to services? The analytical dimensions of product innovations work for services. However, many will develop more along the line of processes with many incremental improvements, rather than large 'jumps'.
In the end, it might be more useful to work with the concept of innovation as a process/attitude/set of practices.
A footnote: Tether emphasizes that he is talking about innovation, not invention. The difference being that an innovation has been commercialised where an invention has not.
Stroke of luck or genius?
I have often heard the saying, 'when luck knocks on the door, you have to get up and answer.' Apparently, Louis Pasteur put it far more elegantly:
'Chance favours the prepared mind.'
(discovered in 'What is innovation?')
'Chance favours the prepared mind.'
(discovered in 'What is innovation?')
Wednesday
Human interface design
The Center for Advanced Media (CAM) at Pace University researches:
* Novel and economical collaborative immersive reality systems.
* Computer-supported community building through shared virtual environments.
* Applications of artistic methods to autostereographic display.
* Digital signal processing analysis tools for financial modeling and visualization.
* Evolutionary collaborative hypermedia approaches to global database systems.
* Handwriting recognition of authorship
* VoiceXML applied to sales force automation and customer management
* Military applications of wearable computers and augmented reality
The work on immersive reality systems and databases sounds particularly relevant to long-distance collaboration and innovation...
* Novel and economical collaborative immersive reality systems.
* Computer-supported community building through shared virtual environments.
* Applications of artistic methods to autostereographic display.
* Digital signal processing analysis tools for financial modeling and visualization.
* Evolutionary collaborative hypermedia approaches to global database systems.
* Handwriting recognition of authorship
* VoiceXML applied to sales force automation and customer management
* Military applications of wearable computers and augmented reality
The work on immersive reality systems and databases sounds particularly relevant to long-distance collaboration and innovation...
ICTs versus face-to-face interaction for problem solving
Sources of ideas for innovation in engineering design, Ammon Salter, David Gann, 2003
This paper, published in Research Policy, vol. 32, no. 8, discusses where engineers find new ideas to solve design problems.
Not surprisingly, the paper suggests that personal, face-to-face interactions remain essential for designers working in project/based environments. The findings reveal that although designers are keen users of information and communication technologies (ICT), the rely heavily on close, personal interaction to solve problems, to develop ideas and to assess the quality of their work.
The authors provide an overview of generally recognized sources of ideas for innovation: primarily internal sources, but also customers, suppliers and competitors. Industrial fairs and exhibitions play an important role as well as (in some industries) professional conferences.
The engineering design process itself is principally concerned with how things ought to be. It involves thinking ahead creatively in order to make a technical object fitting the requirements of users or clients. This process of creation often involves developing new combinations of existing technologies. Hacker argues that the engineering design problem-solving process evolves through a series of iterative and overlapping phases: from problem identification, through development of different conceptual solutions, to designing a favoured solution and working out details of the physical artefact.
The role of ICT tools in this process is not clear. Some argue that new packages of ICT tools have the potential to fundamentally alter the design process (see Steinmueller, 2004). Some suggest that these new tools are leading to the codification of the knowledge-set underlying design activities (David and Foray, 1995). The new ICT tools allow for virtual exchanges across space and time between engineering design teams. New visualisation software and simulation packages can also be seen to lessen the need for face-to-face contact and tacit experience.
By contrast, Nightingale suggests that there is little or no evidence that the importance of tacit knowledge for design is declining. In fact, new ICT tools may increase the need for personal, tacit skills and face-to-face communication.
In their survey, Salter and Gann found that designers rely on close, personal relationships for developing ideas in their work. The two highest rated sources of ideas for engineering design were related to face-to-face contact (84%) and working with others on projects (81%). Previous experience was cited by over 70% of the sample.
This was supported by results from personal interviews. In interviews, designers indicated the importance of close contact with others within their team and more widely within the firm. There was considerable interchange between young inexperienced designers and more experienced staff.
Clients and end-users were considered relatively less important sources of ideas. One the one hand, they were considered too far removed from the highly technical problems that the engineers faced. On the other hand, project managers acted as gatekeeper between engineers and clients.
Despite the fact that Arup is among the highest spenders on ICT tools in the UK design engineering sector, only 25% of its designers found on-line databases and working with new equipment and software to be an important source of ideas for design. ... Our survey shows that few designers used electronic scouting or CAD programmes for solving problems. ... Interviewees suggest that these media lack the immediacy or usefulness of other forms of communication.
The survey showed that few Arup designers thought access to information was a barrier to their design activities. ... As Court et al. have suggested, few designers lack information, instead what they lack is time.
In their conclusion, the authors discuss the importance of ICT tools vs/ face-to-face communications. The research shows that although designers may be keen users of new ICT tools, they still rely on personal exchanges and visual communication for the difficult parts of their work. This finding is supported by historical and ethnographic studies of engineering design that have shown that face-to-face communication among designers is necessary when there is a high level of uncertainty in the engineering design process. ... The immediacy of sketching and face-to-face exchanges is a key part of how engineering designers solve problems. New ICT tools have not yet altered the interactive nature of the design process.
Court et al. found that even when designers work on-line, a number of face-to-face meetings are necessary to build up trust to enable successful collaboration. ... Our study confirms the Court et al. (1997) view that designers suffer from information overload. New ICT tools have tended to increase the amount of documentation in the design process. Personal contact is essential to sift through this mountain of information.
The authors find that 'mixed use' is the best way to describe the application of ICT tools in the design process.
Unfortunately, they don't analyze the difference between face-to-face interaction and personal communication using ICTs (e.g. e-mail). It would be interesting to know how much of the personal interaction needs to happen face-to-face, and how much can be mediated by ICTs.
Some comments on the authors' methodology. Many studies in this field are carried out using large scale surveys where 1 representative (often a high-level R&D manager) responds on behalf of an entire firm. Salter and Gann used a different approach to better understand nuances in engineers' approaches to innovation. Through a series of interviews, they built a cast study of the firm in question. Based on this, they then carried out a survey of the firm's design engineers. This allowed them to better understand what was happening in day-to-day work than the traditional approach would.
They offer a complementary approach to large-scale innovation surveys by focusing on a detailed study of the ideas for innovation in engineering design in a single company. ... There have been few studies of sources of ideas for innovation in engineering design. This paper attempts to fill this gap in the literature by combining interview and survey data.
This paper, published in Research Policy, vol. 32, no. 8, discusses where engineers find new ideas to solve design problems.
Not surprisingly, the paper suggests that personal, face-to-face interactions remain essential for designers working in project/based environments. The findings reveal that although designers are keen users of information and communication technologies (ICT), the rely heavily on close, personal interaction to solve problems, to develop ideas and to assess the quality of their work.
The authors provide an overview of generally recognized sources of ideas for innovation: primarily internal sources, but also customers, suppliers and competitors. Industrial fairs and exhibitions play an important role as well as (in some industries) professional conferences.
The engineering design process itself is principally concerned with how things ought to be. It involves thinking ahead creatively in order to make a technical object fitting the requirements of users or clients. This process of creation often involves developing new combinations of existing technologies. Hacker argues that the engineering design problem-solving process evolves through a series of iterative and overlapping phases: from problem identification, through development of different conceptual solutions, to designing a favoured solution and working out details of the physical artefact.
The role of ICT tools in this process is not clear. Some argue that new packages of ICT tools have the potential to fundamentally alter the design process (see Steinmueller, 2004). Some suggest that these new tools are leading to the codification of the knowledge-set underlying design activities (David and Foray, 1995). The new ICT tools allow for virtual exchanges across space and time between engineering design teams. New visualisation software and simulation packages can also be seen to lessen the need for face-to-face contact and tacit experience.
By contrast, Nightingale suggests that there is little or no evidence that the importance of tacit knowledge for design is declining. In fact, new ICT tools may increase the need for personal, tacit skills and face-to-face communication.
In their survey, Salter and Gann found that designers rely on close, personal relationships for developing ideas in their work. The two highest rated sources of ideas for engineering design were related to face-to-face contact (84%) and working with others on projects (81%). Previous experience was cited by over 70% of the sample.
This was supported by results from personal interviews. In interviews, designers indicated the importance of close contact with others within their team and more widely within the firm. There was considerable interchange between young inexperienced designers and more experienced staff.
Clients and end-users were considered relatively less important sources of ideas. One the one hand, they were considered too far removed from the highly technical problems that the engineers faced. On the other hand, project managers acted as gatekeeper between engineers and clients.
Despite the fact that Arup is among the highest spenders on ICT tools in the UK design engineering sector, only 25% of its designers found on-line databases and working with new equipment and software to be an important source of ideas for design. ... Our survey shows that few designers used electronic scouting or CAD programmes for solving problems. ... Interviewees suggest that these media lack the immediacy or usefulness of other forms of communication.
The survey showed that few Arup designers thought access to information was a barrier to their design activities. ... As Court et al. have suggested, few designers lack information, instead what they lack is time.
In their conclusion, the authors discuss the importance of ICT tools vs/ face-to-face communications. The research shows that although designers may be keen users of new ICT tools, they still rely on personal exchanges and visual communication for the difficult parts of their work. This finding is supported by historical and ethnographic studies of engineering design that have shown that face-to-face communication among designers is necessary when there is a high level of uncertainty in the engineering design process. ... The immediacy of sketching and face-to-face exchanges is a key part of how engineering designers solve problems. New ICT tools have not yet altered the interactive nature of the design process.
Court et al. found that even when designers work on-line, a number of face-to-face meetings are necessary to build up trust to enable successful collaboration. ... Our study confirms the Court et al. (1997) view that designers suffer from information overload. New ICT tools have tended to increase the amount of documentation in the design process. Personal contact is essential to sift through this mountain of information.
The authors find that 'mixed use' is the best way to describe the application of ICT tools in the design process.
Unfortunately, they don't analyze the difference between face-to-face interaction and personal communication using ICTs (e.g. e-mail). It would be interesting to know how much of the personal interaction needs to happen face-to-face, and how much can be mediated by ICTs.
Some comments on the authors' methodology. Many studies in this field are carried out using large scale surveys where 1 representative (often a high-level R&D manager) responds on behalf of an entire firm. Salter and Gann used a different approach to better understand nuances in engineers' approaches to innovation. Through a series of interviews, they built a cast study of the firm in question. Based on this, they then carried out a survey of the firm's design engineers. This allowed them to better understand what was happening in day-to-day work than the traditional approach would.
They offer a complementary approach to large-scale innovation surveys by focusing on a detailed study of the ideas for innovation in engineering design in a single company. ... There have been few studies of sources of ideas for innovation in engineering design. This paper attempts to fill this gap in the literature by combining interview and survey data.
Monday
Biotech/bioinformatics India overview
www.biospectrumindia.com
I just finished scanning a year's worth of BioSpectrum issues. Here's a quick overview (with a severe bias towards bioinformatics). For facts and figures, the magazine's BioData is a good resource.
India isn't among the big players yet in terms of biotech, though it does seem to be positioning itself for a leading role in bioinformatics thanks to its strong IT sector. Nevertheless, there is much excitement about biotech taking off, founded not just on euphoria, but on the availability of natural resources (diverse gene pool and ecosystems) and scientific talent, a pharma sector that is moving from manufacturing generic drugs to drug discovery and providing services (e.g. contract research), a large domestic market for bioagri and traditional medicinal knowledge that provides a unique starting point for drug discovery. Of course there is also the cost advantage of conducting biotech in India rather than the United States.
So far vaccines seems to be the single largest biotech business, including exports (mainly WHO-driven) and development of new vaccines. Bioinformatics is a small business by comparison (one tenth the revenues of vaccines in 2002/2003), but the quickest growing one. However, given that the global market is smaller to begin with and that India is entering the market with proven IT competencies, chances are good for status as a global player. Analysts expect India to capture 5% of the global market by 2005. Another sector that relies on India's established reputation as a global player for ITES (IT enabled services) is the market for contract research opportunities (CRO).
In its early stages, bioinformatics was largely a software services business based on supplying custom-made code for foreign pharma and biotech firms. Increasingly, however, Indian bioinformatics firms are launching proprietary products. A growing niche could be internet applications: 'In contrast to the accelerated growth that the internet has experienced, companies in the biotech sector have just begun to utilize the variety of internet applications available. Although maintaining a web presence and accessibility to research exists for these companies, the industry has relatively overlooked the possibilities of B2B commerce, ASP applications or the ubiquitous wireless domain,' says Aditya M Reddy, CEO of Hyderabad-based DeUS Infotech Private Ltd.
So far the main customer base (80% of data-driven drug discovery) is in the US, and to a small extent in Europe, Australia, Singapore and Japan. The domestic pharma and biotech industries are considered by many to be too young to represent a significant market yet.
Despite this, and Ernst & Young survey showed only 3 Indian cross-border alliances in biotech for 2002.
Industry insiders warn that the service business in biotech is limited and that, for India the real money is in discovering new drugs for ourselves and not in supplying information and data to foreign companies, who would then use this information to discover new molecules.
Various clusters are aggressively marketing their locations, e.g. Hyderabad (Genome Valley) and Bangalore (the biotech city).
The main bioinformatics players are Strand Genomics, CDC Linex, Bigtec, Institute of Bioinformatics, Jubilant Biosys, Ocimum Biosolutions, Mascon Life Sciences, Bilcare, Scinova, SysArris, Molecular Connections, and SERC.
The major software outsourcing companies, such as Infosys, Wipro Health Sciences (or Wipro Healthcare), TCS, Kshema Technologies, and Satyam Computer Services are also exploring opportunities. However, their strength seems to lie in providing management software for biotech and pharma companies (bio-IT), rather than specialized bioinformatics.
International players (in bioinformatics and bio-IT) are IBM/IBM India, Intel, Sun Microsystems, Oracle, and Cognizant Technologies.
I just finished scanning a year's worth of BioSpectrum issues. Here's a quick overview (with a severe bias towards bioinformatics). For facts and figures, the magazine's BioData is a good resource.
India isn't among the big players yet in terms of biotech, though it does seem to be positioning itself for a leading role in bioinformatics thanks to its strong IT sector. Nevertheless, there is much excitement about biotech taking off, founded not just on euphoria, but on the availability of natural resources (diverse gene pool and ecosystems) and scientific talent, a pharma sector that is moving from manufacturing generic drugs to drug discovery and providing services (e.g. contract research), a large domestic market for bioagri and traditional medicinal knowledge that provides a unique starting point for drug discovery. Of course there is also the cost advantage of conducting biotech in India rather than the United States.
So far vaccines seems to be the single largest biotech business, including exports (mainly WHO-driven) and development of new vaccines. Bioinformatics is a small business by comparison (one tenth the revenues of vaccines in 2002/2003), but the quickest growing one. However, given that the global market is smaller to begin with and that India is entering the market with proven IT competencies, chances are good for status as a global player. Analysts expect India to capture 5% of the global market by 2005. Another sector that relies on India's established reputation as a global player for ITES (IT enabled services) is the market for contract research opportunities (CRO).
In its early stages, bioinformatics was largely a software services business based on supplying custom-made code for foreign pharma and biotech firms. Increasingly, however, Indian bioinformatics firms are launching proprietary products. A growing niche could be internet applications: 'In contrast to the accelerated growth that the internet has experienced, companies in the biotech sector have just begun to utilize the variety of internet applications available. Although maintaining a web presence and accessibility to research exists for these companies, the industry has relatively overlooked the possibilities of B2B commerce, ASP applications or the ubiquitous wireless domain,' says Aditya M Reddy, CEO of Hyderabad-based DeUS Infotech Private Ltd.
So far the main customer base (80% of data-driven drug discovery) is in the US, and to a small extent in Europe, Australia, Singapore and Japan. The domestic pharma and biotech industries are considered by many to be too young to represent a significant market yet.
Despite this, and Ernst & Young survey showed only 3 Indian cross-border alliances in biotech for 2002.
Industry insiders warn that the service business in biotech is limited and that, for India the real money is in discovering new drugs for ourselves and not in supplying information and data to foreign companies, who would then use this information to discover new molecules.
Various clusters are aggressively marketing their locations, e.g. Hyderabad (Genome Valley) and Bangalore (the biotech city).
The main bioinformatics players are Strand Genomics, CDC Linex, Bigtec, Institute of Bioinformatics, Jubilant Biosys, Ocimum Biosolutions, Mascon Life Sciences, Bilcare, Scinova, SysArris, Molecular Connections, and SERC.
The major software outsourcing companies, such as Infosys, Wipro Health Sciences (or Wipro Healthcare), TCS, Kshema Technologies, and Satyam Computer Services are also exploring opportunities. However, their strength seems to lie in providing management software for biotech and pharma companies (bio-IT), rather than specialized bioinformatics.
International players (in bioinformatics and bio-IT) are IBM/IBM India, Intel, Sun Microsystems, Oracle, and Cognizant Technologies.
What is bioinformatics?
Workshop report: Impact of emerging technologies on the biological sciences, National Science Foundation, 1995
Essentially, bioinformatics involves the management of enormous databases of biological (especially microbiological) information. In addition, 3-D visualization is becoming increasingly important.
Narayan Kulkarni of BioSpectrum names 3 subdisciplines:
- the development of new algorithms and statistics with which to assess relationships among members of large data sets,
- the analysis and interpretation of various types of data including nucleotide and amino acid sequences, protein domains and protein structures, and
- the development and implementation of tools that enable efficient access and management of different types of information.
Recently, the field has expanded from the traditional areas of genomics (the study of total molecular sequencing of one set of all genes of an organism) and proteomics (the study of amino acid sequences and the three-dimensional structure related to the function of proteins). Newer developments are cheminformatics, glycomics (study of carbohydrates), metabolics and drug design through bioinformatics.
The NSF's 1995 report (dated, but still useful) states:
Bioinformatics is the facilitation of biological research by improving our ability to accumulate, manipulate and visualize data.
Bioinformatics involves all aspects of advanced computer science and engineering. It includes the high-speed acquisition of biological data, followed by the high throughput processing, analysis, archiving, data search and retrieval, networking, and display of complex biological data sets. This may be the single most pervasive emerging technology in terms of applications for biological research.
Large databases that can be accessed and analyzed with sophisticated tools will become central to biological research and education. The information content in the genomics of organisms, in the molecular dynamics of proteins, and in population dynamics, to name but a few areas, is enormous. Biologists are increasingly finding that the management of complex data sets is becoming a bottleneck for scientific advances. Therefore, bioinformatics will rapidly become a key technology in all fields of biology.
The present bottlenecks in bioinformatics include the education of biologists in the use of advanced computing tools, the recruitment of computer scientists into this evolving field, the limited availability of developed databases of biological information, and the need for more efficient and intelligent search engines for complex databases. Common data structures and user interfaces will be necessary to leverage investments in software development.
Aside from bioinformatics, narrowly defined, there are related fields where biology and IT meet:
- knowledge management tools and knowledge systems to aid drug discovery
- management support, e.g. software to track clinical trials or regular CRM, ERP tools for the biotech industry.
Important fields where biology and other emerging technologies meet are:
- computational biology applied to complex systems to yield progress in structural biology (e.g., molecular dynamics; chemical events in cells, tissues, organs, and organisms; and population and ecosystem dynamics);
- functional imaging tools using biosensors and biomarkers for defining the function of cells, tissues, organs, and organisms;
- transformation and transient expression technologies to allow animals, plants, and cell culture systems to be used as expression systems for production of compounds for research and commerce; and
- nanotechnologies to build small machines for microanalysis and micromanipulation.
Some of these may, of course, require IT support.
Essentially, bioinformatics involves the management of enormous databases of biological (especially microbiological) information. In addition, 3-D visualization is becoming increasingly important.
Narayan Kulkarni of BioSpectrum names 3 subdisciplines:
- the development of new algorithms and statistics with which to assess relationships among members of large data sets,
- the analysis and interpretation of various types of data including nucleotide and amino acid sequences, protein domains and protein structures, and
- the development and implementation of tools that enable efficient access and management of different types of information.
Recently, the field has expanded from the traditional areas of genomics (the study of total molecular sequencing of one set of all genes of an organism) and proteomics (the study of amino acid sequences and the three-dimensional structure related to the function of proteins). Newer developments are cheminformatics, glycomics (study of carbohydrates), metabolics and drug design through bioinformatics.
The NSF's 1995 report (dated, but still useful) states:
Bioinformatics is the facilitation of biological research by improving our ability to accumulate, manipulate and visualize data.
Bioinformatics involves all aspects of advanced computer science and engineering. It includes the high-speed acquisition of biological data, followed by the high throughput processing, analysis, archiving, data search and retrieval, networking, and display of complex biological data sets. This may be the single most pervasive emerging technology in terms of applications for biological research.
Large databases that can be accessed and analyzed with sophisticated tools will become central to biological research and education. The information content in the genomics of organisms, in the molecular dynamics of proteins, and in population dynamics, to name but a few areas, is enormous. Biologists are increasingly finding that the management of complex data sets is becoming a bottleneck for scientific advances. Therefore, bioinformatics will rapidly become a key technology in all fields of biology.
The present bottlenecks in bioinformatics include the education of biologists in the use of advanced computing tools, the recruitment of computer scientists into this evolving field, the limited availability of developed databases of biological information, and the need for more efficient and intelligent search engines for complex databases. Common data structures and user interfaces will be necessary to leverage investments in software development.
Aside from bioinformatics, narrowly defined, there are related fields where biology and IT meet:
- knowledge management tools and knowledge systems to aid drug discovery
- management support, e.g. software to track clinical trials or regular CRM, ERP tools for the biotech industry.
Important fields where biology and other emerging technologies meet are:
- computational biology applied to complex systems to yield progress in structural biology (e.g., molecular dynamics; chemical events in cells, tissues, organs, and organisms; and population and ecosystem dynamics);
- functional imaging tools using biosensors and biomarkers for defining the function of cells, tissues, organs, and organisms;
- transformation and transient expression technologies to allow animals, plants, and cell culture systems to be used as expression systems for production of compounds for research and commerce; and
- nanotechnologies to build small machines for microanalysis and micromanipulation.
Some of these may, of course, require IT support.
Sunday
Business ecosystems - perfect metaphor for the biotech industry
Strategy as Ecology, Marco Iansiti and Roy Levien, 2004
Another article from the March edition of HBR. Iansiti and Levien compare networks of suppliers, distributors, outsourcing firms, makers of related products or services, technology providers, etc. to ecosystems in nature. Certainly not a new concept for anyone who has read up on networks recently, but they carry the analogy further to derive business strategies and insights. An interesting read.
Like an individual species in a biological ecosystem, each member of a business ecosystem ultimately shares the fate of the network as a whole, regardless of that member’s apparent strength. From their earliest days, Wal-Mart and Microsoft—unlike companies that focus primarily on their internal capabilities—have realized this and pursued strategies that not only aggressively further their own interests but also promote their ecosystems’ overall health.
They have done this by creating “platforms”—services, tools, or technologies—that other members of the ecosystem can use to enhance their own performance. Wal-Mart’s procurement system offers its suppliers invaluable real-time information on customer demand and preferences, while providing the retailer with a significant cost advantage over its competitors. (For a breakdown of how Wal-Mart’s network strategy contributes to this advantage, see the exhibit “The Ecosystem Edge.”) Microsoft’s tools and technologies allow software companies to easily create programs for the widespread Windows operating system—programs that, in turn, provide Microsoft with a steady stream of new Windows applications. In both cases, these symbiotic relationships ultimately have benefited consumers—Wal-Mart’s got quality goods at lower prices, and Microsoft’s got a wide array of new computing features—and gave the firms’ ecosystems a collective advantage over competing networks.
Assessing Your Ecosystem’s Health
So what is a healthy business ecosystem? What are the indications that it will continue to create opportunities for each of its domains and for those who depend on it? There are three critical measures of health—for business as well as biological ecosystems.
Productivity. The most important measure of a biological ecosystem’s health is its ability to effectively convert nonbiological inputs, such as sunlight and mineral nutrients, into living outputs—populations of organisms, or biomass. The business equivalent is a network’s ability to consistently transform technology and other raw materials of innovation into lower costs and new products. There are a number of ways to measure this. A relatively simple one is return on invested capital.
Robustness. To provide durable benefits to the species that depend on it, a biological ecosystem must persist in the face of environmental changes. Similarly, a business ecosystem should be capable of surviving disruptions such as unforeseen technological change. The benefits are obvious: A company that is part of a robust ecosystem enjoys relative predictability, and the relationships among members of the ecosystem are buffered against external shocks. Perhaps the simplest, if crude, measure of robustness is the survival rates of ecosystem members, either over time or relative to comparable ecosystems.
Niche Creation. Robustness and productivity do not completely capture the character of a healthy biological ecosystem. The ecological literature indicates that it is also important these systems exhibit variety, the ability to support a diversity of species. There is something about the idea of diversity, in business as well as in biology, that suggests an ability to absorb external shocks and the potential for productive innovation. The best measure of this in a business context is the ecosystem’s capacity to increase meaningful diversity through the creation of valuable new functions, or niches. One way to assess niche creation is to look at the extent to which emerging technologies are actually being applied in the form of a variety of new businesses and products.
Considering the proposition that the biotech industry has entered a phase characterized by many small forms forming alliances/networks with each other, research institutes and pharma multinationals, the analogy seems particularly relevant.
Another article from the March edition of HBR. Iansiti and Levien compare networks of suppliers, distributors, outsourcing firms, makers of related products or services, technology providers, etc. to ecosystems in nature. Certainly not a new concept for anyone who has read up on networks recently, but they carry the analogy further to derive business strategies and insights. An interesting read.
Like an individual species in a biological ecosystem, each member of a business ecosystem ultimately shares the fate of the network as a whole, regardless of that member’s apparent strength. From their earliest days, Wal-Mart and Microsoft—unlike companies that focus primarily on their internal capabilities—have realized this and pursued strategies that not only aggressively further their own interests but also promote their ecosystems’ overall health.
They have done this by creating “platforms”—services, tools, or technologies—that other members of the ecosystem can use to enhance their own performance. Wal-Mart’s procurement system offers its suppliers invaluable real-time information on customer demand and preferences, while providing the retailer with a significant cost advantage over its competitors. (For a breakdown of how Wal-Mart’s network strategy contributes to this advantage, see the exhibit “The Ecosystem Edge.”) Microsoft’s tools and technologies allow software companies to easily create programs for the widespread Windows operating system—programs that, in turn, provide Microsoft with a steady stream of new Windows applications. In both cases, these symbiotic relationships ultimately have benefited consumers—Wal-Mart’s got quality goods at lower prices, and Microsoft’s got a wide array of new computing features—and gave the firms’ ecosystems a collective advantage over competing networks.
Assessing Your Ecosystem’s Health
So what is a healthy business ecosystem? What are the indications that it will continue to create opportunities for each of its domains and for those who depend on it? There are three critical measures of health—for business as well as biological ecosystems.
Productivity. The most important measure of a biological ecosystem’s health is its ability to effectively convert nonbiological inputs, such as sunlight and mineral nutrients, into living outputs—populations of organisms, or biomass. The business equivalent is a network’s ability to consistently transform technology and other raw materials of innovation into lower costs and new products. There are a number of ways to measure this. A relatively simple one is return on invested capital.
Robustness. To provide durable benefits to the species that depend on it, a biological ecosystem must persist in the face of environmental changes. Similarly, a business ecosystem should be capable of surviving disruptions such as unforeseen technological change. The benefits are obvious: A company that is part of a robust ecosystem enjoys relative predictability, and the relationships among members of the ecosystem are buffered against external shocks. Perhaps the simplest, if crude, measure of robustness is the survival rates of ecosystem members, either over time or relative to comparable ecosystems.
Niche Creation. Robustness and productivity do not completely capture the character of a healthy biological ecosystem. The ecological literature indicates that it is also important these systems exhibit variety, the ability to support a diversity of species. There is something about the idea of diversity, in business as well as in biology, that suggests an ability to absorb external shocks and the potential for productive innovation. The best measure of this in a business context is the ecosystem’s capacity to increase meaningful diversity through the creation of valuable new functions, or niches. One way to assess niche creation is to look at the extent to which emerging technologies are actually being applied in the form of a variety of new businesses and products.
Considering the proposition that the biotech industry has entered a phase characterized by many small forms forming alliances/networks with each other, research institutes and pharma multinationals, the analogy seems particularly relevant.
Search
Courtesy of Micah Alpern, I now have a search engine on the blog! Unfortunately, I think it only links to the blog homepage, although the link to Google's cached snapshot should be a bit more useful. Also, it only works if Google has actually crawled the link in question. Since those occasions are few and far between, I'm not sure how useful it will turn out to be... Cool, nevertheless.
Saturday
When at first offshoring doesn't succeed
Tough Shift - Lesson in India: not every job translates overseas, Scott Thurm, 2004
In Wednesday's Wall Street Journal, writes about one ValiCert's travails as it tried to offshore programming work, first by hiring Infosys and later by opening its own subsidiary in Bangalore.
In a nutshell, offshoring didn't work because
- ValiCert kept changing the definition or goals of offshored projects. Many projects were cancelled or delayed after months of work. This led to a) Infosys changing team members designated to ValiCert or b) software engineers at ValiCert's subsidiary becoming utterly frustrated
- Offshored projects were usually small parts of larger efforts and required intensive coordination. This approach failed because of difficulties in managing teams spread across 14 time zones, and because a lot of information that was considered intuitive or taken for granted in Silicon Valley was not available in Bangalore.
- Coordination and communication problems led to severe delays, inefficiencies and a breakdown of trust between the Indian and US teams.
Eventually, ValiCert learned how to make profitable use of offshoring and now believes that the company would not have survived without it. If at first ValiCert believed that colleagues would swap work across the globe every 12 hours, helping ValiCert 'put more people on it and get it done sooner,' now it offshores entire projects, such as adapting an entire program to a different operating system. It has also improved its communications flows between operations in India and the US to ease or at least spread fairly the burden of communicating across time zones.
Nevertheless, Brent Haines, in charge of coordinating the US and Indian teams commented that such collaboration requires extensive planning, ... 'something very unnatural to people in software.'
ValiCert merged with Tumbleweed in Feb 2002. The combined Redwood City, Calif., company's 150 engineers today are almost evenly divided among California, the Tumbleweed operation in Bulgaria, and the India office started by ValiCert. In Bulgaria, engineers write and test software, and scan millions of e-mails daily for traces of spam. In India, engineers test software, fix bugs and create new versions of one product. Last September, Tumbleweed released its first product developed entirely in India, a program that lets two computers communicate automatically and securely. Mr. Marur's team had worked on it for over for 18 months. Core development for new products remains in California, where engineers are closer to marketing teams and Tumbleweed's customers.
In Wednesday's Wall Street Journal, writes about one ValiCert's travails as it tried to offshore programming work, first by hiring Infosys and later by opening its own subsidiary in Bangalore.
In a nutshell, offshoring didn't work because
- ValiCert kept changing the definition or goals of offshored projects. Many projects were cancelled or delayed after months of work. This led to a) Infosys changing team members designated to ValiCert or b) software engineers at ValiCert's subsidiary becoming utterly frustrated
- Offshored projects were usually small parts of larger efforts and required intensive coordination. This approach failed because of difficulties in managing teams spread across 14 time zones, and because a lot of information that was considered intuitive or taken for granted in Silicon Valley was not available in Bangalore.
- Coordination and communication problems led to severe delays, inefficiencies and a breakdown of trust between the Indian and US teams.
Eventually, ValiCert learned how to make profitable use of offshoring and now believes that the company would not have survived without it. If at first ValiCert believed that colleagues would swap work across the globe every 12 hours, helping ValiCert 'put more people on it and get it done sooner,' now it offshores entire projects, such as adapting an entire program to a different operating system. It has also improved its communications flows between operations in India and the US to ease or at least spread fairly the burden of communicating across time zones.
Nevertheless, Brent Haines, in charge of coordinating the US and Indian teams commented that such collaboration requires extensive planning, ... 'something very unnatural to people in software.'
ValiCert merged with Tumbleweed in Feb 2002. The combined Redwood City, Calif., company's 150 engineers today are almost evenly divided among California, the Tumbleweed operation in Bulgaria, and the India office started by ValiCert. In Bulgaria, engineers write and test software, and scan millions of e-mails daily for traces of spam. In India, engineers test software, fix bugs and create new versions of one product. Last September, Tumbleweed released its first product developed entirely in India, a program that lets two computers communicate automatically and securely. Mr. Marur's team had worked on it for over for 18 months. Core development for new products remains in California, where engineers are closer to marketing teams and Tumbleweed's customers.
On the European biotech sector
Why does the European biotech sector underperform? Mark Greener, 2004
In its December / January 2004 issue, Eurobusiness (now discontinued) carried a story on the worries of the European biotech sector.
While biotech in Europe shows impressive growth and success, it is definitely underperforming compared to the US industry. The main reason for this, according to Greener is a lack of venture capital.
The European biotech sector is younger and less mature than in the US. Companies are smaller - with market capitalizations that often fall short of investment funds' thresholds; their products are less developed and require more patience from investors; and there are few high-profile success stories yet to encourage vc's.
These drawbacks are exacerbated by risk-averse investors (much funding of European biotech ventures actually comes from US, not European, sources) and a lack of successful, co-ordinated stock exchanges. Most financing comes from partnerships with or acquisitions by large pharma firms.
Also, an aversion to GM food, a difficult regulatory environment, and a lower rate of entrepreneurship don't help.
The problem is, of course, that a lack of funds and success stories can stifle growth and reduce spending on new R&D, thereby endangering the future of the entire biotech - and by extension also pharma - industry.
An aside: There is a vc fund that has adapted it's venturing model to the European market. Instead of investing in 10 firms, hoping that one will be an overwhelming success, it's revenue model is based on, say, 5 out of those 10 companies delivering reasonably solid returns. Now if only I could remember the name of the vc fund and where I read about it...
In its December / January 2004 issue, Eurobusiness (now discontinued) carried a story on the worries of the European biotech sector.
While biotech in Europe shows impressive growth and success, it is definitely underperforming compared to the US industry. The main reason for this, according to Greener is a lack of venture capital.
The European biotech sector is younger and less mature than in the US. Companies are smaller - with market capitalizations that often fall short of investment funds' thresholds; their products are less developed and require more patience from investors; and there are few high-profile success stories yet to encourage vc's.
These drawbacks are exacerbated by risk-averse investors (much funding of European biotech ventures actually comes from US, not European, sources) and a lack of successful, co-ordinated stock exchanges. Most financing comes from partnerships with or acquisitions by large pharma firms.
Also, an aversion to GM food, a difficult regulatory environment, and a lower rate of entrepreneurship don't help.
The problem is, of course, that a lack of funds and success stories can stifle growth and reduce spending on new R&D, thereby endangering the future of the entire biotech - and by extension also pharma - industry.
An aside: There is a vc fund that has adapted it's venturing model to the European market. Instead of investing in 10 firms, hoping that one will be an overwhelming success, it's revenue model is based on, say, 5 out of those 10 companies delivering reasonably solid returns. Now if only I could remember the name of the vc fund and where I read about it...
Bringing innovations to market in networked industries
The New Rules for Bringing Innovations to Market, Bhaskar Chakravorti, 2004
Bhaskar Chakravorti, author of 'The Slow Pace of Fast Change,' discusses the pitfalls of innovation in networked industries in this HBR article. (See also this earlier post.)
Chakravorti bases his argument on game theory and network economics.
When a market is in equilibrium (i.e. Nash equilibrium) every player in a market believes that he or she is making the best possible choices and that every other player is doing the same. Equilibrium in a market lends stability to the players' expectations, validates their choices, and reinforces their behaviors. When an innovation enters the market, it upsets the players' expectations and choices and introduces uncertainty in decision making.
So, once a market reaches equilibrium, it resists new ideas and new products and significantly favors incumbents who maintain the status quo.
A market's hostility to innovations becomes stronger when plazers are interconnected. In a networked market, each participant will switch to a new product only when it believes others will do so, too. ... When America's first transcontinental railroads were built in the 1860's, for example, factories and businesses that were close to waterways did not immediately relocate near railways. They did so only when they felt their customers and suppliers were making the switch, too.
Communications technology provides virtual connections between market participants and can affect adoption of new products. Using these technologies, market participants sent signals about their behavior and allow others to form expectations.
For instance, E. Remington and Sons introduced the first typewriter in 1874, a time when penmanship was still a highly respected skill. Most writers (with the exception of Mark Twain) initially shunned the typewriter. The growth of railroads, telephones, and telegraph lines led to the dispersal of companies and the depersonalization of communications. the typewritten document became the standard for written communications in business. Use of the typewriter spread. Thus, the railroads, the telephone, and the telegraph implicitly increased the speed with which consumers accepted the typewriter.
That influence is a two-edged sword.
Networked markets allow for the rapid diffusion of news, ideas, and, in theory, innovations. But they also erect formidable barriers to the adoption of innovations - primarily because of the interdependencies between players.
This reminds me of Barabasi's work on power laws in networks.
Once enough plazers in a networked market decide to switch to a new product, other players' motivation to do so becomes stronger. Beyond that threshold, the network becomes innovation's ally rather than its foe.
This sounds much like a game theoretical explanation of Shumpeter's 'creative destruction.'
Chakravorti also emphasizes the importance of hubs for innovators. Aligning interests with the most connected industry players gives an innovator access to a large network with very little effort.
While he goes on to recommend a strategy for innovators who are trying to move from one equilibrium to another in order to promote their new products, there is little mention of markets that are not yet in equilibrium. I could imagine that the bioinformatics industry is still too young to have reached a Nash equilibrium and that network ties are not yet stable enough to deter innovation. Or, to put it another way, the biomedical industry experienced two 'waves:' Has the industry reached equilibrium in the second wave yet?
And what will happen to an industry so dependent on, even defined by, innovation once it does reach equilibrium?
Bhaskar Chakravorti, author of 'The Slow Pace of Fast Change,' discusses the pitfalls of innovation in networked industries in this HBR article. (See also this earlier post.)
Chakravorti bases his argument on game theory and network economics.
When a market is in equilibrium (i.e. Nash equilibrium) every player in a market believes that he or she is making the best possible choices and that every other player is doing the same. Equilibrium in a market lends stability to the players' expectations, validates their choices, and reinforces their behaviors. When an innovation enters the market, it upsets the players' expectations and choices and introduces uncertainty in decision making.
So, once a market reaches equilibrium, it resists new ideas and new products and significantly favors incumbents who maintain the status quo.
A market's hostility to innovations becomes stronger when plazers are interconnected. In a networked market, each participant will switch to a new product only when it believes others will do so, too. ... When America's first transcontinental railroads were built in the 1860's, for example, factories and businesses that were close to waterways did not immediately relocate near railways. They did so only when they felt their customers and suppliers were making the switch, too.
Communications technology provides virtual connections between market participants and can affect adoption of new products. Using these technologies, market participants sent signals about their behavior and allow others to form expectations.
For instance, E. Remington and Sons introduced the first typewriter in 1874, a time when penmanship was still a highly respected skill. Most writers (with the exception of Mark Twain) initially shunned the typewriter. The growth of railroads, telephones, and telegraph lines led to the dispersal of companies and the depersonalization of communications. the typewritten document became the standard for written communications in business. Use of the typewriter spread. Thus, the railroads, the telephone, and the telegraph implicitly increased the speed with which consumers accepted the typewriter.
That influence is a two-edged sword.
Networked markets allow for the rapid diffusion of news, ideas, and, in theory, innovations. But they also erect formidable barriers to the adoption of innovations - primarily because of the interdependencies between players.
This reminds me of Barabasi's work on power laws in networks.
Once enough plazers in a networked market decide to switch to a new product, other players' motivation to do so becomes stronger. Beyond that threshold, the network becomes innovation's ally rather than its foe.
This sounds much like a game theoretical explanation of Shumpeter's 'creative destruction.'
Chakravorti also emphasizes the importance of hubs for innovators. Aligning interests with the most connected industry players gives an innovator access to a large network with very little effort.
While he goes on to recommend a strategy for innovators who are trying to move from one equilibrium to another in order to promote their new products, there is little mention of markets that are not yet in equilibrium. I could imagine that the bioinformatics industry is still too young to have reached a Nash equilibrium and that network ties are not yet stable enough to deter innovation. Or, to put it another way, the biomedical industry experienced two 'waves:' Has the industry reached equilibrium in the second wave yet?
And what will happen to an industry so dependent on, even defined by, innovation once it does reach equilibrium?
Thursday
The Bioeconomy and what it means for regional economies
Prospects for a Bioeconomy: The Biomedical Industry and Economic Development, Cinda Herndon-King and Richard S. Seline, 2000
Without many too many facts to fall back on, I have proposed that hi-tech industry industries are moving away from a pure cluster model towards a 'network of competing and cooperating clusters.' This report backs me up as far as the biomedical industry is concerned. There's more on networks of innovation and regions collaborating to compete at the website of New Economy Strategies.
Cinda Herndon-King and Richard Seline analyzed 28 regions in the United States, with a special emphasis on the 4 most important clusters: Boston, San Diego, the Bay Area and Seattle. At the time the report was written, biotech was poised to pick up investments and momentum from the slacking internet bubble economy.
Herndon-King and Seline provide a comprehensive overview of the biomedical industry. They point out the enormous market potential of the health care industry in the U.S., mainly due to a population with a higher life expectancy that is aging overall. However, much of the potential also arises from the fact that genomic pharmaceuticals allow much more personalized healthcare and a much vaster scope of treatments - beginning with highly targeted preventive care.
They cite Mark Dibner and list 7 factors which distinguish the biomedical industry from other high tech sectors:
1. Financing: The start-up costs of business are high, and generally not financed by the entrepreneur
2. Reliance on research base: Most (55%) of biotechnology companies engage in activities which are in the research and development phase only.
3. Time to market: Typically, between five to twelve years is required. Return on investment for early investors is not based on product sales but from increasing valuation of the company, realized upon exit.
4. Regulatory environment: The cost of the the drug development and approval process is estimated at an average of $300 to $500 million per drug. The time required for approvals can be highly variable, and can often depend on factors outside the control of the submitting company.
5. Dependence on patent issues: Attracting investment requires a strong global intellectual property position.
6. Alliances and outsourcing: Due to the high costs of doing business, biotechnology firms extensively leverage outside skills, technology and capital through alliances. Reliance on academic innovation has emerged as the primary factor affecting biotechnology industry cluster devlopment.
7. Influence of public perception and environment.
Two major trends that form a recurring theme throughout the report are:
1. the interrelationship of tools and enabling technology with basic scientific discovery. The distinction between providing equipment or software and conducting basic research is blurred since so much discovery depends on the development of specialized or custom-made new tools.
2. the requirement for interdisciplinary approaches to biomedical research, bioinformatics being a case in point for both trends.
The authors go on to describe 2 phases of the industry:
The first wave business model centered on the 'full integrated pharmaceutical company' that licensed, financed, managed, and fought the federal regulatory labyrinth around (typically) a university patent or paper. This fully-integrated model housed the research, the testing, the manufaturing, and the distribution and sales for all aspects of bringing a drug or product to the market.
The second wave of the biotech industry is best defined by the reliance upon outsourcing and business networks rather than the integration model. Simply, the biotech and life science industry has found alliances, networks among researchers-vendors-suppliers, and a more concentrated and accelerated focus of both the science and the economics to be not just valuable but competitive propositions.
This has implications for regional economies that focus on biotech/biomed:
The Second Wave therefore is permeating regional strategies: proximity is no longer a value proposition in all elements of the lifecycle. Proximity to new ideas, to faculty, to research facilities promises greater innovation (defined as a social process among inputs of the science and outputs of entrepreneurial formation), but as firms mature the proximity demand within a region is challenged. Seattle for instance found in the late 1980s that no strategic marketing firms existed in their region and thus turned to Los Angeles and New York for assistance. Over a three year period, enough demand was created in Seattle that approximately 30 firms were established to serve the growing strategic marketing and sales requirements – many were outpost from Los Angeles and New York, others were home-grown. Currently San Diego has exceeded its manufacturing capacity – land is in short supply and costly; an initiative is underway to partner with border cities in Mexico and communities outside of California for non-essential manufacturing services.
There is a shift from self-contained regional clusters to specialized networked regions (see graph on page 44 of the report).
This is a reflection of changes in the industry itself as it moved from full vertical integration within one firm to a greater reliance on networks and alliances.
Proximity matters but not as it once did - like a fully-integrated company, regions believed that they must manage or control all aspects of the product cycle. With the determination that not every region has all the critical ingredients, more and more expectations arise for networking with other institutions, knowledge, talent and entrepreneurs beyond the local community. Proximity matters because innovation is a social process but not all aspects of the product testing and development must rely on the capacity to 'rub shoulders' with the testing, trials, and manufacturing aspects of the industry.
But the question remains: Which aspects require shoulder rubbing, and which don't?
Without many too many facts to fall back on, I have proposed that hi-tech industry industries are moving away from a pure cluster model towards a 'network of competing and cooperating clusters.' This report backs me up as far as the biomedical industry is concerned. There's more on networks of innovation and regions collaborating to compete at the website of New Economy Strategies.
Cinda Herndon-King and Richard Seline analyzed 28 regions in the United States, with a special emphasis on the 4 most important clusters: Boston, San Diego, the Bay Area and Seattle. At the time the report was written, biotech was poised to pick up investments and momentum from the slacking internet bubble economy.
Herndon-King and Seline provide a comprehensive overview of the biomedical industry. They point out the enormous market potential of the health care industry in the U.S., mainly due to a population with a higher life expectancy that is aging overall. However, much of the potential also arises from the fact that genomic pharmaceuticals allow much more personalized healthcare and a much vaster scope of treatments - beginning with highly targeted preventive care.
They cite Mark Dibner and list 7 factors which distinguish the biomedical industry from other high tech sectors:
1. Financing: The start-up costs of business are high, and generally not financed by the entrepreneur
2. Reliance on research base: Most (55%) of biotechnology companies engage in activities which are in the research and development phase only.
3. Time to market: Typically, between five to twelve years is required. Return on investment for early investors is not based on product sales but from increasing valuation of the company, realized upon exit.
4. Regulatory environment: The cost of the the drug development and approval process is estimated at an average of $300 to $500 million per drug. The time required for approvals can be highly variable, and can often depend on factors outside the control of the submitting company.
5. Dependence on patent issues: Attracting investment requires a strong global intellectual property position.
6. Alliances and outsourcing: Due to the high costs of doing business, biotechnology firms extensively leverage outside skills, technology and capital through alliances. Reliance on academic innovation has emerged as the primary factor affecting biotechnology industry cluster devlopment.
7. Influence of public perception and environment.
Two major trends that form a recurring theme throughout the report are:
1. the interrelationship of tools and enabling technology with basic scientific discovery. The distinction between providing equipment or software and conducting basic research is blurred since so much discovery depends on the development of specialized or custom-made new tools.
2. the requirement for interdisciplinary approaches to biomedical research, bioinformatics being a case in point for both trends.
The authors go on to describe 2 phases of the industry:
The first wave business model centered on the 'full integrated pharmaceutical company' that licensed, financed, managed, and fought the federal regulatory labyrinth around (typically) a university patent or paper. This fully-integrated model housed the research, the testing, the manufaturing, and the distribution and sales for all aspects of bringing a drug or product to the market.
The second wave of the biotech industry is best defined by the reliance upon outsourcing and business networks rather than the integration model. Simply, the biotech and life science industry has found alliances, networks among researchers-vendors-suppliers, and a more concentrated and accelerated focus of both the science and the economics to be not just valuable but competitive propositions.
This has implications for regional economies that focus on biotech/biomed:
The Second Wave therefore is permeating regional strategies: proximity is no longer a value proposition in all elements of the lifecycle. Proximity to new ideas, to faculty, to research facilities promises greater innovation (defined as a social process among inputs of the science and outputs of entrepreneurial formation), but as firms mature the proximity demand within a region is challenged. Seattle for instance found in the late 1980s that no strategic marketing firms existed in their region and thus turned to Los Angeles and New York for assistance. Over a three year period, enough demand was created in Seattle that approximately 30 firms were established to serve the growing strategic marketing and sales requirements – many were outpost from Los Angeles and New York, others were home-grown. Currently San Diego has exceeded its manufacturing capacity – land is in short supply and costly; an initiative is underway to partner with border cities in Mexico and communities outside of California for non-essential manufacturing services.
There is a shift from self-contained regional clusters to specialized networked regions (see graph on page 44 of the report).
This is a reflection of changes in the industry itself as it moved from full vertical integration within one firm to a greater reliance on networks and alliances.
Proximity matters but not as it once did - like a fully-integrated company, regions believed that they must manage or control all aspects of the product cycle. With the determination that not every region has all the critical ingredients, more and more expectations arise for networking with other institutions, knowledge, talent and entrepreneurs beyond the local community. Proximity matters because innovation is a social process but not all aspects of the product testing and development must rely on the capacity to 'rub shoulders' with the testing, trials, and manufacturing aspects of the industry.
But the question remains: Which aspects require shoulder rubbing, and which don't?
Wednesday
Biotech resource
I found a newish industry magazine that covers biotech in India: Biospectrum. They provide a great industry overview, lots of stats and profiles - and best of all, all their back issues are online.
Thanks Reuben, for linking to my blog and motivating me to start posting again!
Thanks Reuben, for linking to my blog and motivating me to start posting again!
Saturday
Cities as drivers of innovation and economic growth
The economy of cities, Jane Jacobs, 1969
Jane Jacobs sees cities as fundamentally different from other economic regions - not as larger and more complicated villages. In her book, she describes an anthropological view of the earliest cities as centers of trade between non-agricultural tribes that develop sophisticated agricultural techniques as they grow. This conflicts with the view traditionally held at the time that hunter/gatherer villages developed agriculture and subsequently grew to become cities.
Jacobs perspective allows a new analysis of cities and their interactions with the rural areas around them. Since she focuses on cities' imports and exports, her's could be seen as simply an input-output model that treats the city (ie. agglomeration economy) as black box. However, the anthropological background she provides and her analysis of divisions of labor within the city go a long way towards opening the black box and understanding it. Her description of entrepreneurship and incremental innovation makes intuitive sense: People doing their job, naturally find ways to improve on certain aspects - mainly through trial and error. If they get positive feedback, they may shift their focus from the original work to elaborating the improvements. One of Jacobs' examples is Mrs. Rosenthal, a New York seamstress. Mrs. Rosenthal was unhappy with the way her dresses fit her customers, so she used her sewing and fitting skills to create bras. She was so successful with this improvement that she went on to give up on sewing dresses and founded Maidenform instead. One of the most important factors in this example is that Mrs. Rosenthal was originally engaged in local work, which she adapted. Maidenform, by contrast became an export business (ie., exporting out of the city of New York). Once the new line of business was firmly established, factories could be set up in rural areas to save costs and improve efficiency. This example is representative of Jacobs's description of the city as a self-reciprocating, open system.
Jacobs emphasizes that this kind of innovation can only happen in cities where there is a high density of people and jobs as well and if a high degree of specialization can be supported by the economy. Since established businesses are constantly being moved to rural areas, the city must create new sources of income, ie. new exports. To achieve this, a vibrant local economy is necessary to serve as the basis for innovation. The inefficiency of cities is an advantage for the trial and error process of incremental innovation: a large variety of different kinds of work is happening in one place, which encourages new combinations; the sustainability of high degrees of specialization lets innovations succeed before they are fully developed, and replication of work means that many instances of trial and error can occur in tandem.
While individual specialization is important, according to Jacobs, cities should not specialize. They need to maintain many different avenues of innovation/trial and error because only a fraction will succeed. Efficiency works against innovation in this case. Some of the most important specializations/innovations that cities provide have been the generic ones that allow new businesses of all kinds to form: venture capitalists, lawyers, printers, leasing of factory equipment, agencies to provide temporary workers, etc.
Even though Jacobs doesn't touch on radical high-tech innovations or consumer-driven innovation (cf. von Hippel's work), she provides a very tangible, practical account of how agglomeration economies work. Her model gives many insights into what it takes to create an agglomeration economy or to revive a stagnating city.
An interview with Jane Jacobs.
Jane Jacobs sees cities as fundamentally different from other economic regions - not as larger and more complicated villages. In her book, she describes an anthropological view of the earliest cities as centers of trade between non-agricultural tribes that develop sophisticated agricultural techniques as they grow. This conflicts with the view traditionally held at the time that hunter/gatherer villages developed agriculture and subsequently grew to become cities.
Jacobs perspective allows a new analysis of cities and their interactions with the rural areas around them. Since she focuses on cities' imports and exports, her's could be seen as simply an input-output model that treats the city (ie. agglomeration economy) as black box. However, the anthropological background she provides and her analysis of divisions of labor within the city go a long way towards opening the black box and understanding it. Her description of entrepreneurship and incremental innovation makes intuitive sense: People doing their job, naturally find ways to improve on certain aspects - mainly through trial and error. If they get positive feedback, they may shift their focus from the original work to elaborating the improvements. One of Jacobs' examples is Mrs. Rosenthal, a New York seamstress. Mrs. Rosenthal was unhappy with the way her dresses fit her customers, so she used her sewing and fitting skills to create bras. She was so successful with this improvement that she went on to give up on sewing dresses and founded Maidenform instead. One of the most important factors in this example is that Mrs. Rosenthal was originally engaged in local work, which she adapted. Maidenform, by contrast became an export business (ie., exporting out of the city of New York). Once the new line of business was firmly established, factories could be set up in rural areas to save costs and improve efficiency. This example is representative of Jacobs's description of the city as a self-reciprocating, open system.
Jacobs emphasizes that this kind of innovation can only happen in cities where there is a high density of people and jobs as well and if a high degree of specialization can be supported by the economy. Since established businesses are constantly being moved to rural areas, the city must create new sources of income, ie. new exports. To achieve this, a vibrant local economy is necessary to serve as the basis for innovation. The inefficiency of cities is an advantage for the trial and error process of incremental innovation: a large variety of different kinds of work is happening in one place, which encourages new combinations; the sustainability of high degrees of specialization lets innovations succeed before they are fully developed, and replication of work means that many instances of trial and error can occur in tandem.
While individual specialization is important, according to Jacobs, cities should not specialize. They need to maintain many different avenues of innovation/trial and error because only a fraction will succeed. Efficiency works against innovation in this case. Some of the most important specializations/innovations that cities provide have been the generic ones that allow new businesses of all kinds to form: venture capitalists, lawyers, printers, leasing of factory equipment, agencies to provide temporary workers, etc.
Even though Jacobs doesn't touch on radical high-tech innovations or consumer-driven innovation (cf. von Hippel's work), she provides a very tangible, practical account of how agglomeration economies work. Her model gives many insights into what it takes to create an agglomeration economy or to revive a stagnating city.
An interview with Jane Jacobs.
Tuesday
Business process outsourcing moves up the value-chain
Special Section: BPO, a global market for services, Knowledge at Wharton, 25 September 2003
Knowledge at Wharton has a special section on business process outsourcing. One of the most interesting articles in the section is about BPO moving up the value-chain.
Cutting costs is not the only reason why outsourcing such tasks makes sense for its clients; it’s also about higher quality of work, says Aggarwal. “Among the more unusual emerging developments is that business process offshoring is not merely a way to reduce cost by migrating core functions,” adds Spohr of A.T. Kearney. “It is also a strategic initiative to take advantage of technological advances and the human capital available offshore to fundamentally restructure an organization’s operating model.”
These new business models are necessary for the efficiency gains from new communications technologies to finally kick in.
An example of a BPO firm that has moved beyond call-centers and crunching code is Evalueserve with headquarters in Bermuda, a subsidiary in New Jersey and its main operating plant just outside of New Delhi.
Evalueserve provides services like patent writing, evaluation and assessment of their commercialization potential for law firms and entrepreneurs. Its market research services are aimed at top-rung financial services firms, to which it provides analysis of investment opportunities and business plans. Another major offering is multilingual services -- Evalueserve trains and qualifies employees to communicate in Chinese, Spanish, German, Japanese and Italian, among other languages. That skill set has opened market opportunities in Europe and elsewhere, especially with global corporations.
Dieter Ernst's work focuses on how outsourcing manufacturing influences the spread of knowledge around the world. Outsourcing services should have an even more dramatic effect, since transportation is even easier and cheaper. Also, outsourcing manufacturing seems to be mainly cost-driven, with companies in developed countries outsourcing to the developed and developing world. BPO - or service outsourcing more generally - can go in any direction. Globally competitive companies in Taiwan, India and Israel can get R&D from subsidiaries/joint-ventures/partners in Silicon Valley. The ultimate R&D outsourcing example is InnoCentive. High-end professional medical and legal services are already being outsourced by U.S. firms and governments.
So far, India is in the best position to take advantage of the BPO trend - and seems likely to keep it for some time.
The expansion of the labor force by more than 2 million new English-speaking college graduates each year will provide plenty of room for growth. Also, the labor arbitrage between India and the U.S. is so significant that it will take a long time for it to catch up. What’s more, any rise in wage costs is getting offset by declining telecommunication rates (some 30% over the last couple of years), thanks to improvements in infrastructure and technology.
Of course, others are competing to get into the business as well. China is one contender, although some say that a) it can't overcome the language barrier and b) the domestic market's service requirements will use up all the available talent. Mauritius wants to capitalize on its linguistic advantages and is getting help from India to catch up. A solid telecoms infrastructure, tax incentives, and compromises on visas and advance work permits should help. New Yorkers' parking tickets are processed in Ghana. VietnaPhilippineslipines, central European countries and many others are competing for part of the cross-border business that is expected to grow to $178.5 billion by 2005. Indian BPO companies themselves have started outsourcing as costs rise in their own country.
Knowledge at Wharton has a special section on business process outsourcing. One of the most interesting articles in the section is about BPO moving up the value-chain.
Cutting costs is not the only reason why outsourcing such tasks makes sense for its clients; it’s also about higher quality of work, says Aggarwal. “Among the more unusual emerging developments is that business process offshoring is not merely a way to reduce cost by migrating core functions,” adds Spohr of A.T. Kearney. “It is also a strategic initiative to take advantage of technological advances and the human capital available offshore to fundamentally restructure an organization’s operating model.”
These new business models are necessary for the efficiency gains from new communications technologies to finally kick in.
An example of a BPO firm that has moved beyond call-centers and crunching code is Evalueserve with headquarters in Bermuda, a subsidiary in New Jersey and its main operating plant just outside of New Delhi.
Evalueserve provides services like patent writing, evaluation and assessment of their commercialization potential for law firms and entrepreneurs. Its market research services are aimed at top-rung financial services firms, to which it provides analysis of investment opportunities and business plans. Another major offering is multilingual services -- Evalueserve trains and qualifies employees to communicate in Chinese, Spanish, German, Japanese and Italian, among other languages. That skill set has opened market opportunities in Europe and elsewhere, especially with global corporations.
Dieter Ernst's work focuses on how outsourcing manufacturing influences the spread of knowledge around the world. Outsourcing services should have an even more dramatic effect, since transportation is even easier and cheaper. Also, outsourcing manufacturing seems to be mainly cost-driven, with companies in developed countries outsourcing to the developed and developing world. BPO - or service outsourcing more generally - can go in any direction. Globally competitive companies in Taiwan, India and Israel can get R&D from subsidiaries/joint-ventures/partners in Silicon Valley. The ultimate R&D outsourcing example is InnoCentive. High-end professional medical and legal services are already being outsourced by U.S. firms and governments.
So far, India is in the best position to take advantage of the BPO trend - and seems likely to keep it for some time.
The expansion of the labor force by more than 2 million new English-speaking college graduates each year will provide plenty of room for growth. Also, the labor arbitrage between India and the U.S. is so significant that it will take a long time for it to catch up. What’s more, any rise in wage costs is getting offset by declining telecommunication rates (some 30% over the last couple of years), thanks to improvements in infrastructure and technology.
Of course, others are competing to get into the business as well. China is one contender, although some say that a) it can't overcome the language barrier and b) the domestic market's service requirements will use up all the available talent. Mauritius wants to capitalize on its linguistic advantages and is getting help from India to catch up. A solid telecoms infrastructure, tax incentives, and compromises on visas and advance work permits should help. New Yorkers' parking tickets are processed in Ghana. VietnaPhilippineslipines, central European countries and many others are competing for part of the cross-border business that is expected to grow to $178.5 billion by 2005. Indian BPO companies themselves have started outsourcing as costs rise in their own country.
R&D in Brazil
This week, the Knowledge Economy team of the Development Gateway is focusing on Brazil as a potential tech and innovation powerhouse.
Brazil has over the past years been receiving increasing public and private investments aimed at boosting and expanding innovative activities in the country.
Brazil is the largest recipient of foreign direct investment (FDI) in Latin America, and Brazilian entrepreneurs point to FDI as a major source of new technology transfer and to the licensing of foreign technology as a major form of acquiring new technology.
When it comes to the internal capacity to absorb and create new technologies, -while Brazil has been broadening access to education at all levels-, the Brazil Competitiveness meeting hosted by the World Economic Forum in June this year pointed out that only a relatively small number of high-tech professionals are graduating. The Forum recommended that Brazil increase the number of graduating professionals and improve education, primarily by increasing specialization in fields related to the more competitive industries of the country. The Forum also pointed out other weaknesses of Brazil's innovation system, among them insufficient linkages between universities and other actors.
This again points to the importance of building local absorptive capacity rather than relying too heavily on foreign direct investment. (See also a Foreign Policy article, which Reuben pointed out.)
I recently read an article describing the Xylella fastidiosa Genome Project. The Brazilian scientists in the project made use of Europe's distributed team organization for sequencing the genome and adapted it to their own conditions - thereby greatly improving on the European model in the author's opinion. Spreading the research across numerous labs (34 sequencing labs, 1 bioinformatics lab and collaboration with 2 European labs) also helped to train more scientist in biotechnology, and to create a better base/more absorptive capacity for future research projects and the biotech industry. The choice of the organism to sequence was also significant - a citrus pathogen, which is of great interest to academics and agribusiness.
At the time, the project created quite a stir: Brazil was the first developing country to join genome sequencing as a serious player; theirs was the first plant genome to be sequenced. From EMBnet news (April 2000):
In two years, Brazil (or at least São Paulo state) has gone from essentially nothing to being one of the larger producers of sequence data in the world. It has done so not by investing massively in a large sequencing facility, but by bringing together a large number of individual labs, many of which are already using these new data and know-how in their own research. In this way, the genome projects have already had a major impact on Brazilian science.
The world has not really taken notice yet, but I would bet that within another year or two ONSA and the HCGP will have achieved the same recognition as TIGR and CGAP. Bioinformaticians and genome scientists take note!
Brazil has over the past years been receiving increasing public and private investments aimed at boosting and expanding innovative activities in the country.
Brazil is the largest recipient of foreign direct investment (FDI) in Latin America, and Brazilian entrepreneurs point to FDI as a major source of new technology transfer and to the licensing of foreign technology as a major form of acquiring new technology.
When it comes to the internal capacity to absorb and create new technologies, -while Brazil has been broadening access to education at all levels-, the Brazil Competitiveness meeting hosted by the World Economic Forum in June this year pointed out that only a relatively small number of high-tech professionals are graduating. The Forum recommended that Brazil increase the number of graduating professionals and improve education, primarily by increasing specialization in fields related to the more competitive industries of the country. The Forum also pointed out other weaknesses of Brazil's innovation system, among them insufficient linkages between universities and other actors.
This again points to the importance of building local absorptive capacity rather than relying too heavily on foreign direct investment. (See also a Foreign Policy article, which Reuben pointed out.)
I recently read an article describing the Xylella fastidiosa Genome Project. The Brazilian scientists in the project made use of Europe's distributed team organization for sequencing the genome and adapted it to their own conditions - thereby greatly improving on the European model in the author's opinion. Spreading the research across numerous labs (34 sequencing labs, 1 bioinformatics lab and collaboration with 2 European labs) also helped to train more scientist in biotechnology, and to create a better base/more absorptive capacity for future research projects and the biotech industry. The choice of the organism to sequence was also significant - a citrus pathogen, which is of great interest to academics and agribusiness.
At the time, the project created quite a stir: Brazil was the first developing country to join genome sequencing as a serious player; theirs was the first plant genome to be sequenced. From EMBnet news (April 2000):
In two years, Brazil (or at least São Paulo state) has gone from essentially nothing to being one of the larger producers of sequence data in the world. It has done so not by investing massively in a large sequencing facility, but by bringing together a large number of individual labs, many of which are already using these new data and know-how in their own research. In this way, the genome projects have already had a major impact on Brazilian science.
The world has not really taken notice yet, but I would bet that within another year or two ONSA and the HCGP will have achieved the same recognition as TIGR and CGAP. Bioinformaticians and genome scientists take note!
Saturday
Biz-history lesson
The Company: A Short History of a Revolutionary Idea, John Micklethwait, Adrian Wooldridge, 2003
HBS Working Knowledge just alerted me to this new book by 2 Economist editors.
“The most important organization in the world is the company: the basis of the prosperity of the West and the best hope for the future of the rest of the world.” And so John Micklethwait and Adrian Wooldridge, editors at the Economist, begin their account of the rise of this most “remarkable institution.” Reporting on over 5,000 years’ worth of company history, from the Sumerian families who traded along the Euphrates and Tigris rivers in Mesopotamia in 3000 BC to today’s multinational corporations, the authors provide an absorbing, but surprisingly concise, narrative of the influences of the company in shaping our world. Filled with fascinating literary and cultural references, the reader is guided on a journey that includes the medieval guilds of northern Europe, the British and Dutch chartered and joint-stock companies, and nineteenth century American railroad companies.
HBS Working Knowledge just alerted me to this new book by 2 Economist editors.
“The most important organization in the world is the company: the basis of the prosperity of the West and the best hope for the future of the rest of the world.” And so John Micklethwait and Adrian Wooldridge, editors at the Economist, begin their account of the rise of this most “remarkable institution.” Reporting on over 5,000 years’ worth of company history, from the Sumerian families who traded along the Euphrates and Tigris rivers in Mesopotamia in 3000 BC to today’s multinational corporations, the authors provide an absorbing, but surprisingly concise, narrative of the influences of the company in shaping our world. Filled with fascinating literary and cultural references, the reader is guided on a journey that includes the medieval guilds of northern Europe, the British and Dutch chartered and joint-stock companies, and nineteenth century American railroad companies.
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