Irving Wladawsky-Berger

Information, Money and Related Subjects

“Money, it is conventional to argue, is a medium of exchange, which has the advantage of eliminating inefficiencies of barter; a unit of account which facilitates valuation and calculation; and a store of value which allows economic transactions to be conducted over long periods as well as geographical distances,” writes Harvard historian Niall Ferguson in The Ascent of Money: a Financial History of the World. 

For a long time, money was embodied in precious metals like gold and silver.  The earliest known gold coins were produced in Lydia, in what is now Western Turkey about 2500 years ago.  But, with the introduction of banknotes in seventh-century China, money started to decouple from physical objects with intrinsic value.

“Today . . . we remain more or less content with paper money - not to mention coins that are literally made from junk,” writes Professor Ferguson.  “ . . . we are happy with money we cannot even see.  Today’s electronic money can be moved from our employer, to our bank account, to our favorite retail outlets without ever physically materializing.  It is this virtual money that now dominates what economists call the money supply . . .The intangible character of most money is perhaps the best evidence of its true nature.”

Given this intangible character of money, it is not surprising that major advances in information technologies have in turn led to major advances in the way we deal with money and payments.  In the 1960s, 1970s, and 1980s, mainframes, minicomputers, data networks, transaction processing and data bases enabled financial innovations like ATMs and credit cards.  Then in the 1990s, the wide adoption of the Internet and World Wide Web led not only to online banking, but paved the way for online shopping and e-commerce in general.

Smart mobile devices, broadband wireless networks, cloud-based services and big data are now ushering the next major phase in the evolution of money and payments.  Money is continuing its centuries old transformation from being embodied in objects with intrinsic value, like gold and silver, to being nothing more than information in the digital wallets of our mobile devices as well as in our digital accounts someplace out there in the cloud. 

Since just about everyone in the world, rich and poor alike, now has access to mobile devices, this major chapter in the history of money brings with it a universal inclusiveness that has been missing in the previous links between information technologies and money.  Mobile digital money is coming, - over time, - to every individual in every corner of the world.

Principles for Managing Strategy and Innovation

Through the years, I have been intrigued by the number of once powerful companies that are no longer around.  Darwinian principles seem to apply in business as much as in biology.  When technology and market environments go through major changes, as is certainly the case today, previously successful business strategies will no longer work, no matter how much you try to fix them.  Companies that are unable or unwilling to adapt to the changes in such a Darwinian climate will become marginalized or extinct.

It is not hard to understand how I come to this somewhat fatalistic view of business.  In the IT industry, I have seen many once leading companies disappear altogether or become shadows of their former selves.  IBM's near-death experience in the 1990s was very painful for me personally and for all us in the company.  Even though IBM managed to survive, as well as to regain a position of leadership in the IT industry, the experience has definitely left its imprint and colors my views of the world.

More recently, Citi, which I joined as strategic advisor in March of 2008, has gone through its own near-death experience as a result of the financial crisis of the past few years.  As we know, quite a number of once mighty financial institutions did not survive the crisis.  

Why is it that some firms are able to go through ups and downs, yet survive and thrive?  What accounts for their long term, enduring success?  Are there any principles or patterns that can help guide companies through these highly uncertain times and allow them to not only survive but emerge stronger than before?

The Legend of Apple and Xerox PARC and the Truth About Innovation

Every December for the last few years, NY Times OpEd columnist David Brooks picks the best magazine essays of the year.  He describes his choices in two of his columns, with links to the essays in their online version.  I generally really like his selections.  One of his choices this year is a New Yorker article by bestselling author Malcolm Gladwell - Creation Myth: Xerox PARC, Apple, and the truth about innovation.

Gladwell is a great storyteller.  He uses Steve Jobs’ legendary 1979 visit to Xerox PARC as the springboard for his reflections on the nature of revolutionary innovations.  While describing his version of the legend, he also gives us his version of the truth about innovation, including the evolution of an innovation concept from original idea, to lab experimentation, and on to marketplace success; the role that environment plays in the eventual fate of an innovation concept; and the messy, probabilistic, hit-and-miss nature of disruptive innovations.

Xerox founded its Palo Alto Research Center (PARC) in 1970, which brought together some of the world's best computer engineers and programmers.  In the 1970s, PARC was the mecca for innovation in computing.  In 1979, Steve Jobs asked Xerox to let him tour PARC, and in return he would allow Xerox to buy a hundred thousand shares of Apple for a million dollars.  After much discussion, Xerox agreed.

Scale and Complex Systemic Innovation

The year end issue of The Economist includes a provocative column - Big and clever: Why large firms are often more inventive than small ones.  The column addresses a fundamental question that those studying innovation have been wrestling with for years:  “Are big companies the best catalysts of innovation, or are small ones better?”

The column is based on a recent study - Scale and Innovation in Today’s Economy - by Michael Mandel, chief economic strategist of the Progressive Policy Institute. 

“Conventional wisdom these days says that small is better when it comes to innovation and putting new ideas into practice,” writes Mandel at the beginning of the report.  “Large enterprises are typically thought of as hidebound defenders of the status quo, dominating by market power and brute force rather than technological and innovative prowess. . .Yet reality is far more complicated than this simple small versus big distinction. . . After 20 years where startups have rightly dominated the innovation headlines, we will show that the pendulum may be swinging back.  As a result, there are reasons to believe that scale may be a plus for innovation in today’s economy, not a minus.”

There is little question that small, entrepreneurial start-ups are almost always the ones that bring to market highly disruptive innovations.  They excel at creative destruction, the term that economist Joseph Schumpeter  popularized almost seventy years ago to describe the process of transformation that accompanies disruptive innovation. 

Entrepreneurs have sharp incentives to break into a market with a disruptive new idea that attacks the dominance of established companies.  They are highly motivated to bring to market new products which offer significantly improved designs and/or lower costs, and thus gain competitive advantage and market share from the established leaders in their segment of the market. 

But, in what has become known as the Schumpeterian Hypothesis,  Schumpeter also believed that large companies in concentrated markets have more incentives to innovate.  By investing in new products or processes, the company can sell them to their already large customer base and reap greater rewards faster.  Moreover, in a highly competitive market, startups will have trouble holding on to the gains from their innovations because they will be quickly imitated by rivals, while large companies with greater market power will be able to better protect and hold on to the gains from their innovations.  

So, which is it?  Are large companies at a disadvantage because start-ups can move much faster in bringing new ideas to market, or is their scale an incentive for investing in innovation?  Mandel summarizes the economic research evidence in two words: It depends.

The Emergence of a Digital Money Ecosystem

At the beginning of this year I wrote that the transition to universal mobile digital money is likely to be among the most exciting, important and challenging projects the world will undertake in the coming decades.  Everything I have learned through the year indicates that, while still in the very early stages, the transition is well underway and gathering momentum. 

This transition involves a lot more than the transformation of money - cash, checks, credit and debit cards, and so on, - from physical to digital objects that we will carry in our smart mobile devices.  It encompasses the whole money ecosystem, including the global payment infrastructures, the management of personal identities and personal financial data, the global financial flows among institutions and between institutions and individuals, the government regulatory regimes, and so on.  

In other words, just about every aspect of the world’s economy is involved.  Over time, mobile devices will truly become our personal windows into an increasingly global, digital economy.  This will take decades to fully play out, - historical transitions take their time.  But, it is most definitely underway, with an increasing number of market pilots and research studies already taking place around the world.  

As part of my work with Citi, I have been spending a lot of time thinking about the implications of this historical transition to a digital money ecosystem.  The more I learn about it, the more I am convinced that this is truly a major paradigm shift that will change the very way we think about money.

Open, Collaborative Trust Frameworks

A couple of weeks ago I attended a workshop on Inventing the Future of Finance cosponsored by ID³ and the MIT Media Lab.  ID³, - the Institute for Institutional Innovation by Data Driven Design, - is a new multidisciplinary non-profit institution formed to develop architectural frameworks, open source software and educational content for the protection, sharing and monetization of sensitive data. 

It was founded by MIT Media Lab Professor Alex “Sandy” Pentland, and by John Clippinger, who is currently a Research Scientists at the Media Lab, and until recently was a Senior Fellow at Harvard’s Berkman Center for Internet and Society.  Clippinger is Executive Director and CEO of ID³, while Pentland serves as its Chief Scientist.  I just joined its Board of Directors.

One of the key missions of ID³ is the creation of trust frameworks, which it defines as:  “A combination of software mechanisms, contracts, and rules for defining, governing and enforcing the sharing and protection of information according to a common and independently verifiable standard of performance.  Whenever possible, such governance mechanisms and contracts should be self-executing and self-correcting.”

A Neural, Digital System for the Economy

Most everyone will agree that the world’s economy is undergoing historical structural changes, mostly caused by the digital technology revolution taking place all around us.  In particular, ever since the explosive growth of the Internet in the mid 1990s, we are seeing the emergence of a global, digital economy.  What does this mean?  How can we best describe the nature of this emerging digital economy?  What are some of its key implications for the overall economy?

There is clearly no simple answer to these questions.  But, I recently read one of the clearest and most elegant explanations of the changes our economy is going through in an article in McKinsey Quarterly by economist W. Brian Arthur, - The Second Economy.  Dr. Arthur is external professor at the Santa Fe Institute and visiting researcher at PARC’s Intelligent Systems Lab.

“Digitization is creating a second economy that’s vast, automatic, and invisible - thereby bringing the biggest change since the Industrial Revolution,” he writes at the very beginning of the article.  He illustrates his point with an analogy to the transformation of the US economy by the railroads in the second half of the 19th century.”

Open Services Innovation

Earlier this year, UC Berkeley professor Henry Chesbrough published a new book, Open Services Innovation: Rethinking Your Business to Grow and Compete in a New Era.  This is his third book on open innovation in the last eight years, having published Open Innovation: The New Imperative for Creating and Profiting from Technology in 2003, and Open Business Models: How to Thrive in the New Innovation Landscape in 2006.

Professor Chesbrough is in the faculty of Berkeley’s Hass Business School and executive director of the Garwood Center for Corporate Innovation and of the Program in Open Innovation.  I met him over a decade ago when I first got involved with Linux and open, collaborative innovation.  He is a top expert on the value of open innovation to business.

When I recently found out that he had published a book on services, I was eager to learn how he framed the subject.  For over ten years now, I have been thinking about the application of technology and innovation to services.  Over the years, I have given quite a few seminars on the subject, including a graduate course in MIT in the Fall of 2010.  I have also written a number of entries on services in this blog.

Jobs in the Age of Watson

On October 31, I participated in a symposium sponsored by MIT’s Center for Digital Business on The Race Against the Machine: The Future of Technology and Employment.  The symposium was associated with an event that took place later that same day on the Harvard campus, the IBM Watson Challenge.  The Watson Challenge was an exhibition Jeopardy! match between Watson, IBM’s question-answering system, three students from the Harvard Business School and three students from MIT’s Sloan School of Management.  Watson won the exhibition match, with the Harvard team finishing a close second.

At the MIT symposium, I was part of a panel on How will technology affect productivity and employment? The panel was moderated by MIT management professor Erik Brynjolfsson, who is also the director of the Center for Digital Business.  The other panel members were MIT economists David Autor and Frank Levy.  We discussed the impact of technology on jobs, in particular, the impact of advanced systems like Watson which are pushing the boundaries between human and machine capabilities

Race Against the Machine

Erik Brynjolfsson and Andrew McAfee just published an excellent short (sixty pages, less than twenty thousand words) e-book - Race Against the Machine: How The Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy.  Erik Brynjolfsson is a professor at MIT’s Sloan School of Management and director of the MIT Center for Digital Business.  Andy McAfee is Principal Research Scientist at the Center for Digital Business, as well as serving as its associate director.   

“This is a book about how information technologies are affecting jobs, skills, wages, and the economy,” they write in the opening sentence.  There are few more timely and vital subjects.  During the 2007 - 2009 Great Recession, unemployment increased by as much as 5.7%, the largest increase in the post war period. 

But, recessions are always accompanied by job losses.  A more perplexing problem is our jobless recovery since the recession was declared officially over.  The seemingly recovering economy is not putting enough people back to work.  More than two years after the recession officially ended, US unemployment is still over 9 percent.

The Emergence of Cognitive Computing

On October 21 I participate in a Colloquium on the Frontiers of IT at IBM’s Thomas J Watson Research Center.  The colloquium, - which was part of IBM’s Centennial celebration, - brought together experts across industry and academia to discuss and debate the direction of four key Grand Challenges at the very leading edge of IT:  nano systems, exascale, big data, and cognitive computing.

John Kelly, senior VP and director of IBM Research, gave an overview of these four areas.  Here is a similar version of his talk given a week earlier at the University of Melbourne.  John explained that these four areas have the potential to transform the IT industry because of their exponential growth, a result of both continual improvements and disruptive innovations.  “Exponential curves,” he said, “will either put you ahead of the competition of kill you.  It’s one of the other.”

Over the next decade, nano-devices are expected to advance by three orders of magnitude, from a billion to a trillion transistors in a chip.  We will be able to design sophisticated, powerful nano systems-on-a-chip that will be totally contained within such a trillion transistor nano device.  To do so, we will have to shift from silicon to other carbon-based materials.  This requires disruptive technologies and innovations at all levels, including new materials, fabrication processes and design tools.  The work is underway.

Unleashing the Next Age of Prosperity

A few weeks ago I met with Carlota Perez in New York.  I first met Carlota, - a friend so I will refer to her by first name, - around the time of the publication of her 2002 book: Technological Revolutions and Financial Capital:  The Dynamics of Bubbles and Golden Ages.  In her book, as well as her many articles and lectures, she frames the turbulent times we are going through into a clear, historical perspective.  Let me briefly summarize her views. 

Over the past couple of centuries, we have had a technology revolution every 40 - 60 years, starting with the Industrial Revolution in 1771, which was characterized by the emergence of machines, factories and canals.  This was followed by the age of steam and coal, iron and railways which started in 1829; steel and heavy engineering (electrical, chemical, civil and naval) starting in 1875; and the age of the automobile in 1908.  Our present information technology and telecommunications age, whose starting point Perez pegs at 1971, is the fifth such major revolution in that span.

Each such technology revolution is composed of two very different periods, each lasting 20 - 30 years.  The installation period is the time of creative destruction, when new technologies emerge from the lab into the marketplace, entrepreneurs start many businesses based on these new technologies, and venture capitalists encourage experimentation with new business models and speculation in new money-making schemes.

Services, Production and Clouds

Last week I wrote about the workshop I recently attended in IBM’s Almaden Research Lab on The Co-Evolution of Future Technologies, Skills, Jobs, and Quality-of-Life.  In particular, I discussed the talk on the IT-based transformation of services given by John Zysman, professor of political science at UC Berkeley and co-director of the Berkeley Roundtable on the International Economy.

Professor Zysman key premise is that the service transformation we are going through is truly an Algorithmic Revolution, that is, the ability to formalize and codify the activities underlying services, express them as computable algorithms and capture them in software.  Given the major advances in the power and costs of information technologies, many more such service activities are now amenable to be transformed into algorithms and embodied in software.  This is profoundly changing the nature of business and just about all other institutions in society, as  they increasingly turn to IT-based services to add value to their offerings.

Over the past several years I have given a number of seminars on technology and innovation in services.  It has been a tough subject to teach.  Services, along with their creation and consumption, have been difficult to define.  So, like many others, I have discussed services and their attributes in contrast to what they are not - physical products that are generally manufactured in factories.  But, while such a definition of services and the service sector of the economy may have worked well in the past, it does not work so well now.      

One of the major consequences of the IT-based transformation of services is the blurring of the lines between manufactured products and products delivered as services, as well as between the industrial and service sectors of the economy.  The distinction between products and services blurs, as physical products are increasingly embedded into service-based solutions, where the clients pay for the services they receive, not the products embodied in the solutions.  The traditional boundaries between the industrial and service sectors of the economy have been breaking down.

The IT-based Transformation of Services

On September 27 I participated in a workshop at IBM’s Almaden Research Lab on The Co-Evolution of Future Technologies, Skills, Jobs, and Quality-of-Life.  The key objective of the workshop was to explore how new technologies are changing the economics of work activities, and to understand the frameworks, theories and models that might help us better deal with these economics changes.

In a series of talks and panel discussions, the workshop first reviewed the historical patterns of technology innovations and economic cycles, and then looked at the future of work economics in three key areas: technologies and societal infrastructure; skills and jobs; and careers and quality-of-life measures.  I gave a presentation on Job Creation, Education and Entrepreneurship in the Emerging Knowledge Economy.

John Zysman, professor of political science at UC Berkeley and co-director of the Berkeley Roundtable on the International Economy, gave an excellent talk on Production, Clouds, and the Transformation of the Global Economy.  He presented a particularly interesting point of view on the ongoing IT-based transformation of services, which he calls an algorithmic revolution.  His discussion of services is largely based on his 2006 paper, The 4th Service Transformation: The Algorithmic Revolution, which was later followed by a more comprehensive 2010 paper, Services with Everything: The ICT-Enabled Digital Transformation of Services co-written with Stuart Feldman, Jonathan Murray, Niels Christian Nielsen and Kenji E. Kushida.

Leadership and Rational Thinking

As part of its Centennial celebrations, IBM held a conference in New York in September - THINK: A Forum on the Future of Leadership.  The two day THINK Forum brought together leaders from government, business and academia  to discuss the future of leadership from a number of angles, including the changing nature of the corporation, the importance of systems thinking, leading in times of deep structural changes and bringing science to leadership.

After the Forum, I spent some time reflecting on what I had heard in the various talks and panels.  Lots of different opinions and points of views were expressed.  But, I believe that an overriding message kept coming through loud and clear: to make progress in addressing the very complex problems that we all face, we must leverage the power of rational thinking.

Several speakers pointed out that the world is no longer just connected via the Internet, as we have been saying for the past fifteen years.  It is now becoming hyperconnected, given the proliferation of smart mobile devices and sensors all around us.  In such a hyperconnected world, changes now propagate and build on each other faster than ever, rendering just about all private and public institutions increasingly unpredictable and harder to manage.

But, a number of speakers also pointed out that our ability to understand the world around us is directly related to the tools at our disposal.  And, we now have an array of highly sophisticated tools that, when properly used, can help us make sense of all that complexity.  In particular, just like centuries ago telescopes enabled us to peer into the sky and better understand the universe and our role in it, information has now become a similar such tool, enabling us to now peer into our highly complex world and help us understand what is going on.

Innovation in Higher Education

A glance at the latest US employment figures from the Bureau of Labor Statistics reveals sharp differences in unemployment rates by educational attainment: college degree or higher: 4.3%; associate degree or some college: 8.2%; high school graduates, no college: 9.6%; and no high school diploma: 14.3%.  Moreover, while the overall unemployment rate remains over 9 percent, a recent McKinsey report found that employers are having trouble filling specific positions because they could not find applicants with the right skills.  The report projects that if economic conditions improve, there will be a shortage of 1.5 million workers with college degrees by 2020, but a surplus of almost 6 million of workers with no high school degree.  It also projects a continuing shortage of workers with technical and health care skills not necessarily requiring a college degree.

Just about every such study points to a similar trend: for the foreseeable future, the US economy will need better educated workers with specific skill requirements.  Workers without a post-secondary education face a contracting set of job opportunities.  Those with higher educational attainments will be in the best position to obtain good jobs with good pay. 

Thus, we need to significantly increase the number of students receiving post-secondary education.  However, our colleges and universities, the very institutions to which the country should turn to help us address these increased educational demands, are facing problems of their own. Tuition costs have risen much faster than the rate of inflation and keep going up, thus making it harder for them to serve the students most in need of their services.  Many educational institutions are facing financial difficulties.  The financial crisis has been aggravating the situation, at both public and private institutions.  Government education budgets are under huge pressure at all levels, - local, state and national.

Incremental steps will not make much of a dent on the problem. We need to look at higher education through the lens of disruptive innovation, argues a report published last February, - Disrupting College: How Disruptive Innovation Can Deliver Quality and Affordability to Postsecondary Education.  The report is written by Clayton Christensen, Michael Horn, Louis Caldera and Louis Soares.

Social Business: e-business 2.0 . . . and Beyond

IBM executive Sandy Carter has just published a new book - Get Bold: Using Social Media to Create a New Type of Social Business.  I know Sandy well, having worked with her at IBM for over a decade in various initiatives.  She is now Vice President of Sales for Social Business and Collaboration Solutions, as well as one of IBM's key Social Business evangelists and strategists.

IBM announced its Social Business initiative in the Fall of 2010.  Its basic definition is simple and practical: A Social Business embraces networks of people to create business value.  When I first learned about Social Business, I thought of it as the natural evolution of IBM’s Internet and e-business strategies.  Let me explain. 

When first announced in 1997, the basic definition of e-business was equally succinct: Leverage the Internet for Business Value.  So, as Web 2.0 technologies and Social Media applications emerged several years later, it is natural that e-business would have now evolved into something like e-business 2.0, continuing to leverage (the more recent advances of) the Internet for business value.  But, as Sandy observes in Get Bold, Social Business goes way beyond its Web 2.0 implications.

The Limits of Meritocracy

In March of 2010, The Atlantic published an excellent article by Don Peck which painfully described the dire consequences of a long period of high unemployment on US society -  How a New Jobless Era will Transform America.  According to Peck, the consequences of prolonged unemployment are not only bleak but truly systemic in nature -  “a slow-motion social catastrophe.”  Joblessness is more devastating to families and communities than poverty, he wrote:

“The Great Recession may be over, but this era of high joblessness is probably just beginning.  Before it ends, it will likely change the life course and character of a generation of young adults.  It will leave an indelible imprint on many blue-collar men.  It could cripple marriage as an institution in many communities.  It may already be plunging many inner cities into a despair not seen for decades.  Ultimately, it is likely to warp our politics, our culture, and the character of our society for years to come.”

Peck just published another very good article in the September 2011 issue of The Atlantic - Can the Middle Class be Saved?  In this article, his focus is on what he refers to as The Culling of the Middle Class:

“Arguably, the most important economic trend in the United States over the past couple of generations has been the ever more distinct sorting of Americans into winners and losers, and the slow hollowing-out of the middle class.  Median incomes declined outright from 1999 to 2009.  For most of the aughts, that trend was masked by the housing bubble, which allowed working-class and middle-class families to raise their standard of living despite income stagnation or downward job mobility.  But that fig leaf has since blown away.  And the recession has pressed hard on the broad center of American society.”

The Passing of an Era

The IBM Personal Computer was announced on August 12, 1981.  Having sold its PC business to Lenovo in 2005, IBM itself did not mark the occasion, and as far as I know, neither did Lenovo or the other companies still selling IBM PC’s.  But, the 30th anniversary of this important event in the history of computing was duly noted by IBM Fellow Mark Dean, - a member of the small team that designed the original machine, - in a nostalgic and thoughtful blog.  At the beginning, Mark writes:       

 “It’s amazing to me to think that August 12 marks the 30th anniversary of the IBM Personal Computer.  The announcement helped launch a phenomenon that changed the way we work, play and communicate.  Little did we expect to create an industry that ultimately peaked at more than 300 million unit sales per year.  I’m proud that I was one of a dozen IBM engineers who designed the first machine and was fortunate to have led subsequent IBM PC designs through the 1980s.  It may be odd for me to say this, but I’m also proud IBM decided to leave the personal computer business in 2005, selling our PC division to Lenovo.  While many in the tech industry questioned IBM’s decision to exit the business at the time, it’s now clear that our company was in the vanguard of the post-PC era.”

“I, personally, have moved beyond the PC as well.  My primary computer now is a tablet.  When I helped design the PC, I didn’t think I’d live long enough to witness its decline.  But, while PCs will continue to be much-used devices, they’re no longer at the leading edge of computing.  They’re going the way of the vacuum tube, typewriter, vinyl records, CRT and incandescent light bulbs.”

The 20th Anniversary of Linux

In mid-August I traveled to Vancouver to attend LinuxCon, the industry’s premier Linux conference.  The conference is organized by the Linux Foundation, which is the nonprofit consortium dedicated to fostering the growth of Linux.

This year marks the 20th anniversary of Linux, which made the conference particularly special.  Most of the keynotes reflected on the impact of Linux on the computer industry and on society in general.  A number of additional activities were also planned to celebrate this important milestone.

The history of Linux was summarized in this charming three and a half minute video:
 
“ . . . It was August of 1991, and a 20 year old computer science student named Linus Torvald sat down at his computer in Helsinki to post what is now one of the most famous entries in computer history: ‘Hello everybody out there, I am doing a free operating system, just a hobby, won’t be anything big and professional like gnu, it probably will never support anything other than AT-hard disks, as that is all I have’ . . . word of the Linux open source project quickly spread around the globe . . . Linus named his OS kernel Linux, and chose a penguin as a mascot after a little incident at the zoo.” 

“He soon made a very important decision that would shape Linux’s future just as much as the technology.  He chose the GPL license created by a visionary named Richard Stallman.  The Linux kernel, along with the GPL license and other GNU components revolutionized the computer industry with a few very simple, yet very important freedoms:  the freedom to use the software for any purpose; the freedom to change the software to suit your needs; the freedom to share the software with your friends and neighbors; and the freedom to change the changes you make. . .”

 . . . and the rest is history.

Job Creation and America's Future

This past June, the McKinsey Global Institute published one of the most comprehensive reports I have seen on the high unemployment and jobless recovery the US has been going through for the past few years - An Economy that Works: Job Creation and America’s Future.  The report is based on a McKinsey research study that surveyed 2,000 business leaders, conducted detail interviews with a number of human resource executives, examined in depth those sectors of the economy with the highest potential for growth, developed a number of detail scenarios for how the US employment picture might evolve into the future, and made several concrete recommendations on what the country should do to address our very serious unemployment issues.

Right at the beginning the report hits us in the face with a few statistics highlighted in big text that succinctly capture the job picture in 2011: US jobs have declined by 7 million since December 2007; 20% of men are not working today, up from 7% in 1970; there has been a 23% drop in new business creation since 2007; the jobless recovery is projected to last 60 months; 10% of Americans move annually, down from 20% in 1985.

The very next page uses the same big text format to summarize the very tough challenges the country faces: we need 21 million jobs by 2020 to return to full employment, - that is, to return to the 5% pre-recession unemployment level instead of the current level of over 9%; the job-growth scenarios modeled by McKinsey ranged from 9.3 to 22.5 million, so only their most optimistic high growth scenario gets us back to full employment; in 2020, there will likely be a 1.5 million shortage of college graduates in the workforce; even today, 40% of companies have had job openings for six months that they have not been able to fill due to lack of the proper skills; and 58% of employers said that they will hire more temporary and part-time workers.

“The United States faces an immediate challenge:,” the executive summary starts out saying, “finding employment for 7 million people still out of work from the 2008–09 recession and reviving robust job creation in the decade to come.  But simply employing a nation’s people is not enough. In a globalized, information-age economy, there is no more important economic priority than building a strong workforce.”

Innovation and Entrepreneurship in Large Metropolitan Areas

For several years now I have been thinking about the differences between various models of innovation and entrepreneurship.  In particular, I have been trying to understand the key differences between the innovation and entrepreneurship models that have worked so well in Silicon Valley, the Boston-Cambridge area and similar high-tech, VC-based regions, and the models that might be more applicable to large metropolitan areas like New York and London.

The Silicon Valley model has become the most prominent example of what it means to be a successful innovation hub.   Over the last few decades, it has been the leading region in the creation of new high-tech products and companies based on advanced digital technologies.  A number of regions around the world have tried to become the next Silicon Valley, hoping to develop the right ecosystem mixture, - including technologists, entrepreneurs, venture capitalists, - that will establish their region as a world class center of innovation.  Most such efforts have fallen short of their goals, - a number ending in outright failure. 

Why is that?  To begin with, most successful high-tech innovation hubs have been built around the great engineering universities in their midst - Stanford and UC Berkeley for Silicon Valley, and MIT for the Boston area.  Over the years, these regions have brought together and carefully nurtured a large and fluid community of technologists and, entrepreneurs who share ideas as they move from company to company - as founders, employees, managers, board members or investors.  They have achieved a remarkable network effect particularly suitable for high-tech innovation that give them an advantage in scale that is almost impossible to replicate.

Their university-based, high tech innovation model is particularly oriented toward finding The Next Big Thing, - that is, the next big technology, product or service that will take world markets by storm, transform whole industries, and in the process, create considerable wealth for their creators and investors.  They have been at the center of several waves of disruptive innovations and creative destruction over the past few decades, and will continue to do so into the future.

But, beyond a few niche areas, this is not a model of innovation and entrepreneurship generally suitable for a large metropolitan region like New York.  A model that would work for New York has to leverage the key strengths of the region.  Let me briefly discuss three such New York strengths in particular.

A New Style of Work

About a year ago I wrote a blog on the post retirement phase of my life.  Tom Foremski, a journalist blogger and friend who reports on the business and culture of innovation in Silicon Valley Watcher, wrote an interesting comment in my blog:

“In some ways, I see your post-retirement life as being somewhat futuristic, in that it will be the way many people will be working in the future.  It's what I call an "atomic" model - collaborating with others on specific tasks/projects and then dissolving those collaborations as you work with others on different projects. In some ways, this is the way Hollywood has been working for decades.  And it's also one that I increasingly see in Silicon Valley.”

“It's a model that increases individual productivity and also organizational productivity because you bring in consultants/experts for specific tasks.  Why have them sitting around on salaries in-between projects?”

“You've retired from the old style of working and you are now pioneering the new style of working :)”

Tom himself made such a transition when in 2004 he left his position as the Silicon Valley reporter for the Financial Times to found Silicon Valley Watcher, one of the first journalists to leave a position with a major newspapers to make a living as a journalist blogger.

I have been very intrigued with this new distributed work phase of my career, where I am associated with several institutions instead of one primary one, as was the case when I worked full time at IBM until I retired in May of 2007 after 37 years with the company.  In particular, I have thought a lot about the role of the Web and related technologies as key enablers of such a distributed style of work.  

The Science of Complex Systems

When I look back over my long, relatively eclectic career, complex systems have been a common theme in all the activities I’ve been involved in.  It started in the 1960s, when I was an undergraduate and graduate student at the University of Chicago majoring in physics, - the study of complex natural systems.  The research for my thesis was focused on the highly complex world of atoms and molecules.  

After finishing my studies, I joined IBM Research in 1970 and switched to computer sciences.  My main research interests were centered on large computer systems, including mainframes, supercomputers and distributed systems.  In the 1990s, my work was focused on the kinds of complex systems and applications made possible by the advent of the Internet, World Wide Web and e-business. 

Then, around ten years ago, I became very interested in the applications of technology to market-facing, people oriented complex systems, especially systems involving services.  Over the past few years, I have also become increasingly interested in economic systems. 

In addition, I started to notice that a number of the concepts and principles I learned many years ago as a physics student seem to apply to these new kind of complex organizational systems I was now interested in.  Let me explain.

Fixing the US Jobs Problem

Last week, I wrote about the recent work of Michael Spence, professor of economics at NYU’s Stern School of Business, professor and dean emeritus at the Stanford Graduate School of Business, and the recipient of the 2001 Nobel Prize in economics. 

In The Evolving Structure of the American Economy and the Employment Challenge, which was published in March of this year by the Council on Foreign Relations, Professor Spence and co-author Sandile Hlatshwayo, examined the impact of globalization over the last twenty years.  They divided the economy into two segments: tradable and nontradable.  They then looked at the trends in each segment by analyzing data from 1990 to 2008 from the US Bureau of Labor Statistics and the Bureau of Economic Analysis.  Their analysis uncovered a tale of two very different economies. 

The tradable sector includes those parts of the economy most subject to global competition from foreign companies and suppliers, - e.g., manufacturing, energy, back-office services.  It significantly improved its value added per job or productivity, but had negligible incremental employment, primarily because a growing number of jobs have been moving offshore.  The nontradable sector, which includes those parts of the economy which must be produced and consumed locally, - e.g., government, health care, construction, - had virtually all the job growth during this period but significantly lower value-added.

As they wrote in the Executive Summary, the employment picture does not look good over the next several years, perhaps longer:

“Given the prospect of slowing employment growth in nontradables and rising competitive pressure on tradables, major employment problems in the near future are a certainty.  Even if the nontradable sector is able to continue to absorb the growth in the labor force, pressure on wages and salaries will be downward, and consequences for income distribution unavoidable.”

“To create jobs, contain inequality, and reduce the U.S. current-account deficit, the scope of the export sector will need to expand.  That will mean restoring and creating U.S. competitiveness in an expanded set of activities via heightened investment in human capital, technology, and hard and soft infrastructure. The challenge is how to do it most effectively.”

The Employment Challenge in the US Economy

A couple of years ago, McKinsey, the global management consulting firm, launched a new website called What Matters.  It asks a big question and invites a wide array of people to write essays giving their points of view on the topic.  In 2009, for example, What Matters addressed Innovation, and asked, Where will the world’s primary centers of innovation be?  I was invited to participate and contributed an essay, “What’s Next in the Knowledge Economy?”

Earlier this year I was once more invited to contribute an essay on the topic of Growth and Productivity, focused on the question: Has the US passed peak productivity growth?  I wrote “The next golden age of innovation”, which was posted last month.

A number of eminent economists also contributed essays on Growth and Productivity.  I was truly humbled to have my essay posted alongside theirs.

Two of the essays in the section revolve around recent work by Michael Spence to try to understand the reasons for the current jobless recovery in the US economy, a fairly unique situation where business conditions have significantly improved while unemployment remains high.  Professor Spence is the recipient of the 2001 Nobel Prize in economics.  He is currently in the faculty at  NYU’s Stern School of Business, as well as professor and dean emeritus of the Stanford Graduate School of Business.

IBM's Centennial

IBM is turning 100 years old on June 16.  The company is commemorating its 100th anniversary with a year-long set of activities around the world.  It is using the opportunity to reach out to many of its constituents in business, government and academia and engage with them in a variety of celebratory events, such as seminars and conferences.  In addition, IBM Chairman Sam Palmisano is inviting all members of its extended family - employees, partners, retirees, families and friends - to pledge at least eight hours of community service during 2011.

If you look at the fast changing IT industry, it is hard enough to find companies that have survived thirty years, let alone one hundred.  It is even harder to find a company that has survived this long, is in great competitive shape and continues to be among the leaders in its industry.  So, as The Economist observed in 1100100 [100 in binary] and Counting in its June 9, 2011 issue:      

“The firm’s centenary is an occasion to reflect on many things digital, but one question stands out: why is IBM still alive and thriving after so long, in an industry characterised perhaps more than any other by innovation and change?  This is not just of interest to business historians.  As IBM enters its second century in good health, far younger IT giants, such as Cisco Systems, Intel, Microsoft and Nokia, are grappling with market shifts that threaten to make them much less relevant.”

The Evolution of My Complex Relationship with Blogging

From time to time, I like to reflect on my feelings about blogging, and then write about them in an entry in my blog.  I have not done so in a while, and it has now been just about six years since I started this blog, so I thought that it would be a good time to return to the subject.

I started blogging at the urging of colleagues at IBM.  In the Spring of 2005 the company was getting ready to launch a major blogging initiative to encourage its employees to participate in the rapidly growing blogosphere.  My colleagues felt that as someone closely associated with IBM’s Internet strategy, it was important that I personally become an active blogger.
 
For several years my friend and colleague John Patrick had been urging me to start a blog.  John has always been a pioneer in embracing new technologies.  He was one of the first people I knew who had a blog, - which is still going strong after all these years.  I resisted John’s exhortations, partly due to the commitment of time and energy it entailed, and partly due to fears that I would not have enough interesting things to write about every week.  But, the excitement building up in IBM around the new blogging initiative finally pushed me over the edge.  I posted my first blog on May 16, 2005.

Money Doesn't Necessarily Buy Competitive Advantage

Just about every company will tell you that innovation is one of its highest priorities.  How can you tell if the company truly means it, or if it's mostly wishful thinking or marketing hype?  We can see if the company is putting its money where its mouth is by measuring how much it spends on innovation relative to other companies in its industry.  But, this is much easier said than done.  There is no consensus as to which budget line items to include in measuring innovation spending.  So, as often happens, people will try to use a well defined, concrete line item as a proxy for estimating the measurement they are really after.

Research and development is often used as such a proxy for innovation.  Many assume that since both R&D and innovation are supposed to translate into competitive advantage, looking at how much companies spend on R&D equates to how serious they are about innovation.  But, as Michael Schrage, a Research Fellow in MIT’s Center for Digital Business wrote in an FT article in November of 2005:

“Any policymaker, chief executive or innovation champion who relies on R&D intensity and R&D budgets as a meaningful or usable metric to assess global competitiveness virtually guarantees shoddy analysis and distorted decisions.  Few things reveal less about a company's ability to innovate cost-effectively than its R&D budget.  Just ask General Motors.  No company in the world has spent more on R&D over the past 25 years.  Yet, somehow, GM's market share has declined.”

“The simple fact,” he later added, “is that R&D spending - whether in euros, dollars or as a percentage of sales - is an input, not a measure of efficiency, effectiveness or productivity.  Ingenuity, invention and innovation are rarely functions of budgetary investment.”

Reflections of the Evolution of Capitalism

The Cold War was an era of military, political and economic conflicts between the communist world led by the Soviet Union, and the Western world, led by the US.  The two sides were also engaged in fierce debates about the merits of their key political and economic philosophies:  the communism and one-party states of the countries in the Soviet camp, versus the democracies, capitalism and market economies of the West.  These debates were settled by 1991 with the collapse and dissolution of the Soviet Union.

China, Vietnam and other countries have one-party political systems ruled by their communist parties, but in the last couple of decades they have also embraced market economies.  Their economic systems look more like a kind of state capitalism, with the government behaving like one giant corporation, than anything resembling Soviet style communism.  For all practical purposes, only Cuba and North Korea have remained faithful to the highly centralized style of communism once practiced in the Soviet Union.  The sorry state of their economies speaks for itself.

Given that most countries around the world now have economies based on some form or another of capitalism and open markets, you would expect that the passionate ideological debates of the past are over.  Not so.  The economic debates in the US and many other countries are actually fiercer than ever, but they are taking place within the broad framework of capitalism.  Capitalism continues to evolve, and different people have their own ideas about how that should happen. 

There are many lenses through which to view the evolution of capitalism.  Let me offer my reflections on the topic through a few such lenses.

The Management of Disruptive Innovations

The management of disruptive innovations is very different when looking at relatively simple or self-contained technologies, products or services versus highly complex platforms and infrastructures.  A lot of the hype you often hear when new innovations come about is the result of people not properly understanding the different dynamics that apply to simple versus highly complex innovations.  Unrealistic predictions are then made about the near term impact and rate of adoption of the new innovation, because the innovation in question is quite complex in nature, but the predictions assumes that it is on the simpler end of the spectrum. 

Let me illustrate what I mean by giving a few examples of different kinds of disruptive innovation across the spectrum from relatively simple to highly complex.

Reflections on the Transition to an Information Society

In the 1920s, Russian economist Nikolai Kondratiev observed that capitalist economies go through long term cycles of booms and depressions every 50 years or so.  These economic cycles became known as Kondratiev Waves.  More recently, Carlota Perez expanded on Kondratiev’s work, describing the central role of technological revolutions, disruptive innovations, and financial and production capital in these economic cycles.

Perez identified five such technology-based revolutions and economic cycles since the onset of the Industrial Revolution in 1771, the first one being the age of machines, factories and canals.  This was followed by the age of steam and coal, iron and railways starting in 1829; steel, electricity and heavy engineering in 1875; the age of oil, the automobile, and mass production in 1908; and our present age of digital technologies, information and telecommunications which Perez pegs as starting in 1971.

In each of these cycles, unrealistic expectations in the new disruptive technologies led to over-investments in new companies.  This eventually turned into unsustainable speculation, causing a financial bubble, which eventually crashed and resulted in a period of economic stagnation. 

In the past four cycles, once the impact of the financial bubble and economic stagnation worked themselves out, a golden age of innovation and production followed, where new paradigms based on the new technologies significantly transformed the economy and just about every single industry, as well as re-shaping the institutions of society, and the nature of work, government and even people’s personal lives.

But now,  given our jobless recovery and continuing slow growing economy in the US, we are pondering whether we are once more at the onset of a new golden age of innovation, or at the beginning of something different which will become known as The Great Stagnation.  While I am hopeful that technology, innovation and globalization will eventually lead to all kinds of new jobs, a much improved economy and a higher standard of living, none of us really knows which of these two scenarios will prevail in the future.

The Community Library in Our Emerging Knowledge Economy

In early March, I participated in a presentation and discussion on The Community Library in the 21st Century along with Maxine Bleiweis, the director of the Westport Public Library. 

Libraries have been an integral part of civilization from our earliest history, including ancient Mesopotamia, Egypt, Greece and Rome.  Greek and Roman scholars came to their libraries to discuss issues and learn from each other.

Free, open public libraries were first established in communities across the UK and the US in the second half of the 19th century.  Along with the rise of public schools during the same period, they were an important part of the transition from the agricultural to the emerging industrial economy which required a more literate, better educated work force.  

From the 1880s through the 1920s, almost 1700 public libraries were built in the US, through the philanthropic efforts of industrialist Andrew Carnegie.  His Carnegie Library Grants promoted community libraries for self-education, which was particularly important during a time when the US was absorbing large numbers of immigrants from around the world.

Complexity and Design in Warfare

On March 11 I participated in a workshop in Washington, - Design Unbound, - organized by The Highlands Forum.  The workshop explored how design-oriented approaches can help us better understand and deal with the very complex problems we are increasingly encountering in all aspects of business, economies, government, public policy, military operations and society in general.

The Highlands Forum is an informal, cross-disciplinary group sponsored by the Office of the US Secretary of Defense.  Its mission is to explore new ideas and emerging trends that will help support high-level Department of Defense (DoD) policy and strategy.  It was organized in 1994 by retired US Navy captain Richard O’Neill, who continues to serve as its leader. 

The Forum holds several meetings a year, each centered on a specific topic, mostly related to information technologies and their impact on society.  Experts from government, industry, academia, and a variety of professions are invited to discuss their ideas on the subject - to be part of a kind of strategic conversation.  Some of the areas explored by the Forum are emerging technologies, organizational development, economic competition, and the changing concept of security. 

Over the past few meetings the Forum has focused on various topics related to complex systems, - how to best understand and manage them in the present, as well as predict and shape their future directions.  In this recent meeting we discussed how to apply the concept of design to address such complex systems and problems.

A Time of Institutional Recomposition

There is little question that our economy, our society and just about all our institutions are going through major structural changes mostly caused by the digital technology revolution that has been all around us for the past several decades.  Such technology-based structural changes are not new.  In her 2002 book Technological Revolutions and Financial Capital:  The Dynamics of Bubbles and Golden Ages, scholar and writer Carlota Perez puts our own turbulent times into a clear, historical perspective.

According to Perez, over the past couple of centuries, we have had a technology revolution every 40 - 60 years, starting with the Industrial Revolution in 1771, which was characterized by the emergence of machines, factories and canals.  This was followed by the age of steam and coal, iron and railways which started in 1829; steel and heavy engineering (electrical, chemical, civil and naval) starting in 1875; and the age of the automobile in 1908.  Our present information technology and telecommunications age, whose starting point Perez pegs at 1971, is the fifth such major revolution in that span.

To better understand the dynamics of a technology revolution, we should split it into two different periods, each lasting 20 - 30 years.  The installation period is the time of creative destruction, when new technologies emerge from the lab into the marketplace, entrepreneurs start many new businesses based on these new technologies, and venture capitalists encourage experimentation with new business models and speculation in new money-making schemes.  Inevitably, this all leads to the kind of financial bubble and crash we are all quite familiar with from our recent experiences.

After the crash, comes the deployment period, the time of institutional recomposition.  The now well accepted technologies become the norm.  New paradigms emerge for guiding innovation and for determining winners and losers in the marketplace.  Over time, these new paradigms significantly transform the economy and everything around it, as well as re-shaping social behavior and the institutions of society.

The Co-Evolution of Humans and our Tools

Tools have played a critical role in human evolution for a very, very long time.  As the Tools entry in Wikipedia observes: 

“Tools are the most important items that the ancient humans used to climb to the top of the food chain; by inventing tools, they were able to accomplish tasks that human bodies could not, such as using a spear or bow and arrow to kill prey, since their teeth were not sharp enough to pierce many animals' skins . . . The transition from stone to metal tools roughly coincided with the development of agriculture around the 4th millennium BC.  Mechanical devices experienced a major expansion in their use in the Middle Ages with the systematic employment of new energy sources: water (waterwheels) and wind (windmills). . . Machine tools occasioned a surge in producing new tools in the industrial revolution.  Advocates of nanotechnology expect a similar surge as tools become microscopic in size.”

Beyond extending our physical capabilities, tools have played a major role in the evolution of our brain and mental powers:  “Using tools has been interpreted as a sign of intelligence, and it has been theorized that tool use may have stimulated certain aspects of human evolution - most notably the continued expansion of the human brain.”

Business Winners: Combining Scale with Agility

A few weeks ago I posted an entry inspired by an excellent article in The World in 2011, The Economist’s annual issue offering predictions for the following year and beyond.  Another article in the same issue caught my attention, Multinationimbles, by Matthew Bishop, who is the US Business editor of The Economist.

The article is built around a somewhat provocative premise: “The business winners will be those that combine scale with agility.”  It is provocative because people generally associate agility with entrepreneurial startups, and scale with more mature, established companies, although a few relatively young companies like Amazon, Google and Facebook have already achieved scale to complement their entrepreneurial agility. 

But the potential oxymoron in the article’s premise is the notion that a large mature company can achieve this combination of scale and agility.  Doesn’t this violate Schumpeter’s 70-year-old theory of creative destruction?  Once large and successful, aren’t companies that once revolutionized their industries supposed to be too slow and locked into the sources of their past success to respond to the new waves of entrepreneurs now attacking them with innovative products and services? 

Bishop’s article focuses primarily on the few mature companies that have achieved this important scale-agility combination: GE, Procter & Gamble, Wal-Mart, and especially IBM. 

“In June 2011, with much fanfare, IBM will celebrate its 100th birthday.  Big Blue is a rare example of corporate survival: few companies last that long, and at times it didn’t look as if IBM would either.  Its secret is not resilience alone, but an ability to reinvent itself.  As Lou Gerstner recounted in his bestseller, “Who Says Elephants Can’t Dance?”, he brought the firm back from the brink after he became its chief executive in 1993 by shifting its focus from selling hardware to selling services.  Since Mr Gerstner left, IBM has reinvented itself again - this time in how it is run as much as in what it sells - with the result that it will mark its centenary as a role model for what a company needs to be to prosper in the second decade of the 21st century.”

Bishop predicts that in 2011, “the biggest winners will be companies that can combine the advantages of scale with the agility to respond to fast-changing market conditions.”

Design Takes Over: Making Beauty Out of Necessity

Toward the end of 2010, The Economist published The World in 2011, its annual issue with predictions for the following year on the variety of topics it normally covers.  As summarized in the introductory article From the Editor, the 2011 predictions presented a balanced view of the next year, articulating both the magnitude of the challenges we face as well as the major opportunities for progress:

“It will be a tale of two economies: a rich world struggling with a weak and jobless recovery, and an emerging world growing four times as fast.  Europe will be divided between a solid centre of its euro zone and a wobbly periphery.  . . Look at politics, and you will often see two clashing forces, too . . .  America faces gridlock between the White House and Congress . . . A sense of division, and frustration, will also prevail in international affairs. . . For all the talk of co-operation on global issues  . . .  it will often seem like a zero-sum world. . . But the gloom will be overdone.  The year ahead will produce striking examples of the power of technology and imagination to address fundamental problems of the age. . .”

This was the 25th edition of “The World in . . . .”  To mark the occasion,  The Economist also included a section on The World in 2036, peering 25 years ahead on a variety of topics, including the economy, technology, religion and collaboration.

I particularly enjoyed reading Design Takes Over, the 2036 prediction by Paola Antonelli, senior curator for architecture and design at New York’s Museum of Modern Art.  She starts her short and elegant article, by first explaining the importance of design in our increasingly fast changing and complex world:

Why Do Firms Exist?

Ronald Coase, the eminent British economist and University of Chicago professor emeritus, turned 100 on December 29.  In 1937, Professor Coase published a seminal paper: The Nature of the Firm, which along with many other achievements earned him the 1991 Nobel Prize in economics.

The Economist marked Professor Coase’s 100th birthday with an article, Why Do Firms Exist?,  that reviews his major accomplishments.  I like its edgy first paragraph:

“For philosophers the great existential question is: ‘Why is there something rather than nothing?’  For management theorists the more mundane equivalent is:  ‘Why do firms exist?  Why isn’t everything done by the market?’”

Professor Coase’s work provides simple answers to to these questions.  He explained that, in principle, a firm should be able to find the cheapest, most productive goods and services by contracting them out in an efficient, open marketplace.  However, markets are not perfectly fluid.  Transaction costs are incurred in obtaining goods and services outside the firm, such as searching for the right people, negotiating a contract, coordinating the work, managing intellectual property and so on.  Thus, firms came into being to make it easier and less costly to get work done.

The Evolution of the World's Digital Payments Infrastructure I

The huge success of the Internet and World Wide Web was made possible by the continuous advances in digital technologies over the past few decades.  The technology advances were absolutely necessary, - but not sufficient.  The underlying IT architecture supporting the new Web-based applications had to radically evolve as well in order to take advantage of the advances in technology.  And the organizational architecture of the private and public sector institutions that were embracing these new Web-based applications had to similarly change, in order to translate these technology advances into productivity and quality improvements.

Web applications typically run on a three tier IT architecture.  In tier one, users link to the Internet with their PCs, smartphones and other devices, and access the Web with their browsers and related software.  These tier one clients connect to the tier two http-based web servers, which process the browser requests, access tier three back-end systems as required, collect all the needed information and send it back to the clients.  Tier three comprises the different applications and information in back end systems, including mission critical transaction processing and data bases.

This three tier architecture has contributed greatly to the success of e-business solutions, by making it possible to quickly combine the standards, universal reach and connectivity of the Web-based systems in tiers one and two, with legacy and new applications, data bases and other back end resources in tier three.

As we now contemplate the evolution toward universal mobile digital money and smart digital wallets, I believe that we are facing major changes not unlike those that accompanied the advent of the Web and e-business, which will require similar technology, architecture and organizational innovations.  The need for privacy and security concerning money, credit cards and personal IDs requires a highly sophisticated IT infrastructure to support this transition.  Today’s payment systems and the organizations that operate them will need to significantly evolve in order to handle the combination of huge transactional volumes, very low costs and high degree of security, as well as compliance with the variety of financial regulations in countries around the world.

The Evolution of Money

In 2010, the BBC and the British Museum collaborated in a project called A History of the World.  The heart of the project was a BBC Radio program which focused on one hundred objects from the collection of the British Museum, around which you can tell the history of humanity over the past two million years.  That history is presented in a series of fifteen minute podcast about each of the objects, written and narrated by British Museum Director Neil MacGregor and broadcast over the BBC throughout the year.

The objects and podcasts are organized into a number of themes.  Money is one of the themes.  It is represented by four objects:

• one of the world’s first gold coins produced over 2500 years ago in Lydia, western Turkey, whose last king was Croesus, of rich as Croesus fame;
• a 1375 banknote from the Ming Dynasty, one of the world’s first paper banknotes;
• a silver coin minted in Bolivia in the late 16th Century; these were known as pieces of eight and used as the world's first global currency throughout the Spanish Empire;
• and a plastic credit card exemplifying the changing role of money in the modern world.

Money, as one of the podcasts observes, has been one of the great constants in human affairs, right up there with sex and war.  Money was not necessary when people lived in small communities where they knew and trusted their neighbors and could therefore exchange labor, food or goods in kind.  But the need for inventing money arose once civilization started to expand and people were dealing with strangers they may never see again and could not trust, as was the case in Lydia and neighboring communities a few thousand years ago.  Money has played a major role in the world ever since, giving rise to commerce and economies, enabling the organization of companies and public institutions, and helping communities become more productive and raise their standard of living.

The MIT Systems Thinking Conference

I recently participated in MIT’s 2010 Systems Thinking Conference for Contemporary Challenges.  This annual conference is sponsored by Systems Design and Management (SDM) - an interdisciplinary program between MIT’s School of Engineering and Sloan School of Management.  The SDM program aims to provide mid-career professionals with a systems perspective that will help them address and solve large-scale, global, complex challenges.  Most of the students in the classes I have taught at MIT are enrolled in SDM.

The Systems Thinking Conference is intended to showcase innovative ways of addressing complex challenges, in particular, how to integrate technology, management and social sciences to successfully solve very tough problems.  The agenda included sessions on sustainability and urban systems, health care and services.  The talks covered a wide range of subjects, from the global development of Boeing’s 787 to the home of the future.  I was co-organizer of the session on service systems, gave a talk on Technology and Innovation in the Service Economy and moderated a panel with the other speakers in the session.

John Sterman - professor in MIT’s Sloan School of Management and director of the Systems Dynamics Group - gave a very interesting talk: A Banquet of Consequences: Systems Thinking and Modeling for Climate Policy.  The title of his talk is based on a quote by Scottish writer Robert Louis Stevenson: Everybody, soon or late, sits down to a banquet of consequences.

Lessons from the Rescue of the Chilean Miners

I first visited Chile about 25 years ago, and have continued to do so from time to time, most recently in September of 2009 when I went to Santiago to join in the celebration of the 80th anniversary of IBM Chile.  I will return in a few weeks to participate in the Smarter Cities meeting that IBM is holding in Santiago on November 23.  Over the years, I have met, worked closely with, and established personal connections with a fair number of people in the country.

This personal connection added an extra dimension to my interest in the rescue of the 33 Chilean miners, although the rescue story has been so compelling that I am not sure anything extra was needed to capture my attention.  Along with a large portion of the world, I was transfixed by the rescue of the miners. Would everything work as planned?  What if something went horribly wrong as we were all watching on live television?  Disaster movies have taught us that just as you become confident and relaxed, things start going haywire.  Would that happen here?

Thankfully, everything went smoothly.  There was indeed a lot of drama, but it was all provided by the emotional reunion of the miners with their families as each reached the surface, as well as by the warm welcome they each received from everyone present, including Chilean president Sebastian Piñera and mining minister Laurence Golborne.  We held our breaths from the time the first miner, Florencio Ávalos started his ascent right before midnight (Chile time) on October 12, to the time the last one reached the surface less that 24 hours later, Luis Alberto Urzúa, their shift supervisor and overall leader.

A lot of the attention is now likely to focus on how the miners and their families deal with their new celebrity status and potential financial rewards.  Everyone agrees that while their fame may be lucrative, it will also be stressful.  There will be lots of opportunities for public appearances, press and TV interviews, and possible book and film deals.  Some will undoubtedly find their new fame too stressful and will yearn for their simpler lives as miners.

Leveraging Commercial Best Practices to Maximize Government Productivity

On October 6, the Technology CEO Council released its report One Trillion Reasons: How Commercial Best Practices to Maximize Productivity Can Save Taxpayer Money and Enhance Government Services.  The report identifes a set of recommendations aimed at reducing US government spending by one trillion dollars over the next decade.  The Council believes that their recommendations are actionable, proven ways of reducing the deficit, which are based on real-world expertise, information technologies and organizational practices that are already being successfully applied in the private sector.

A number of the CEOs involved in this study also met with senior White House and Federal Reserve economic officials to discuss their recommendations, which emphasize both the need to reduce the nation’s growing  deficit as well as laying a foundation for future innovation and growth. 

To quote from the report: “Our government has an opportunity to dramatically reduce spending and cut the deficit, while also improving its level of service to citizens.  By harnessing major technological shifts and adopting best business practices, we can not only make our government far more productive, but also foster greater innovation in areas ranging from healthcare to education and energy – innovation that will generate economic growth and job creation.

“We have seen this repeatedly over the past several decades in our own industry, and in the impact of new technology models across our economy and society.  Again and again, new capabilities have simultaneously reduced costs and sparked innovation.”

Entrepreneurship and Innovation in Large Companies

In March of 2009, The Economist published a special report on entrepreneurship.  Its lead article said: “For most people the term “entrepreneur” simply means anybody who starts a business, be it a corner shop or a high-tech start up . . .  A disproportionate number of entrepreneurial companies are, indeed, small start-ups.  The best way to break into a business is to offer new products or processes.”

But the article then went on to define entrepreneurship as something that applies not only to new or small companies.  It defined the term as: “somebody who offers an innovative solution to a (frequently unrecognised) problem.  The defining characteristic of entrepreneurship, then, is not the size of the company but the act of innovation.”

Given my forty year association with IBM, as well as my more recent involvement with Citigroup, it is not surprising that I am particularly interested in entrepreneurship and innovation in large companies.  I have little experience with startup companies, but I have lots of experience with large, global companies, not just IBM and Citigroup, but many others I interacted with as part of my work, or that I closely followed because they were competitors.

Organizational Innovation

Almost seventy years ago, Austrian economist Joseph Schumpeter popularized the term creative destruction to describe the process of transformation that accompanies disruptive innovation.  The Wikipedia creative destruction article further observes: 

“In Schumpeter's vision of capitalism, innovative entry by entrepreneurs was the force that sustained long-term economic growth, even as it destroyed the value of established companies that enjoyed some degree of monopoly power . . . Companies that once revolutionized and dominated new industries . . . have seen their profits fall and their dominance vanish as rivals launched improved designs or cut manufacturing costs.” 

While entrepreneurship does not preclude leveraging innovative ideas and new market opportunities to revitalize a large, mature organization, the concept is generally associated with startup companies.  The entrepreneur identifies a market opportunity based on an innovative new idea, starts a company in order to bring the new innovation to market, and over time, gains competitive advantage and market share from the established leaders in that segment of the market.

The rivalry between startups and established companies was particularly pronounced during the dot-com bubble of the late 1990s.  There was a buzz in the air that in the Internet-based new economy, born-on-the-Web startups had an inherent advantage over existing, brick-and-mortar businesses.  Because of their grounding in the physical world, it was claimed that established companies could not possibly compete in this fast-moving digital space and were therefore headed for extinction.

The startup-versus-mature hype was taken to silly extremes during the dot-com bubble.  But, there is little doubt that the nature of innovation is quite different in each kind of company.  Startups are looking to leverage innovation to get a foot-hold in the marketplace, whereas more mature companies are looking to leverage innovation to reinvent themselves and remain leaders in their industry.

Can New York Remain the World's Media Capital?

Over the past two years, SUNY’s Levin Institute hosted a series of panel discussions to explore the state of innovation in New York City.  Innovate New York - Envisioning an Inventive City was jointly sponsored by the Levin Institute, the New York Academy of Sciences and the Sloan Foundation.  Its basic premise was:

“New York is a global city, a diverse blend of culture, vitality, and extraordinary talent.  But the wealth of science and technology talent and innovation is less apparent, at least in the form of a thriving technology economy.”  The Innovate New York series aimed to discuss “where New York stands relative to its competitors, and to identify approaches that could capitalize on New York's strengths, shore up its weaknesses, and plant it firmly on the map as a capital of innovation.”  Panel discussions were held in a variety of areas, including finance, media, services, life sciences, arts, and culture.

I personally participated in a couple of the panel discussions, and in my role as Senior Fellow at the Levin Institute, was involved in helping to organize the series. 

The Sloan Foundation has agreed to renew its sponsorship of Innovate New York, this time focused on one industry, - media and communications, - which will enable us to explore the topic in considerable more depth.

The Limits of Strategy

When I look back upon my long career, one of the major factors shaping my views of business, strategy and innovation is the creative destruction that I saw buffeting the IT industry over most of that time.  In particular, having lived through IBM’s own near-death experience, respect - if not fear - for the hurricane-power forces of disruptive change is edged deep down in my psyche.

Why were so many companies in the IT industry done in by such disruptive technology and market changes?  Is it that in spite of all their efforts in strategy formulation, their management was unable to anticipate them and were caught by surprise?  Or it is that, as if actors in a kind of Greek tragedy, they see the changes coming and understand what needs to be done, but are somehow unable to make the needed strategy and cultural transformations?

Nobody has captured the drama that so many IT companies and their leaders went through from 1975 to 2000 like Ernest von Simson in his recently published book The Limits of Strategy: Lessons in Leadership from the Computer Industry.   

With his partner and wife, Naomi Seligman, Ernie founded The Research Board (RB) in the mid 1970s, an IT strategy think tank whose invitation-only membership was limited to the top chief information officers of the largest companies around the world.  Members voted on the top topics they were interested in, and the RB then conducted their research, interviewed top IT company executives as well as other experts, invited them to address their meetings, and then produced a private report available only to their members.

Reinventing Relationships

On September 16, I will join the IBM Lotus team in an event in New York City - Reinventing Relationships.  The event will explore how the Web, collaboration and social software "will transform - actually reinvent - how organizations relate to their customers, partners, employees and citizens through more compelling experiences.”

Once upon a time, new technologies were first deployed in large institutions - enterprises, universities and research labs, the military and civilian government agencies, - from which they eventually trickled down to the rest of the economy as their prices and complexity dropped.  Forty years ago, for example, the computer industry consisted primarily of expensive mainframes and supercomputers that only larger institutions could afford to buy and operate.

But, this trickle-down approach to technology diffusion dramatically reversed itself with the advent of inexpensive technologies, especially digital technologies.  As a result of the incredible advances in digital components and personal computing over the past thirty years, many new innovations are first emerging in consumer markets and among communities of experimental users, from which they eventually trickle-up into the worlds of business and government applications.  Besides personal computing, we have seen such consumer and user-driven innovations in cellular and smartphones, game players, Linux, and perhaps most prominently, with all kinds of innovations around the Internet and World Wide Web.

Machine and Human Intelligence

A recent OpEd in the New York Times caught my attention - The First Church of Robotics by Jaron Lanier, a self-described “computer scientist, composer, visual artist, and author,” who did pioneering research in Virtual Reality in the 1980s.  I have met Lanier, and a few years ago participated in a panel on Virtual Worlds which he moderated.  In his excellent OpEd, he writes:

“The news of the day often includes an item about some development in artificial intelligence: a machine that smiles, a program that can predict human tastes in mates or music, a robot that teaches foreign languages to children.  This constant stream of stories suggests that machines are becoming smart and autonomous, a new form of life, and that we should think of them as fellow creatures instead of as tools.”

“. . . What bothers me most about this trend, however, is that by allowing artificial intelligence to reshape our concept of personhood, we are leaving ourselves open to the flipside: we think of people more and more as computers, just as we think of computers as people. . . When we think of computers as inert, passive tools instead of people, we are rewarded with a clearer, less ideological view of what is going on - with the machines and with ourselves.”

Jason Lanier’s OpEd inspired me to reflect on the successes and failures of artificial intelligence (AI) over the past several decades, as well as on some of the essential differences between machine and human intelligence.

The term artificial intelligence is often used in quite different ways.  At one end, is the more applied kind of AI, which is essentially the application of advanced engineering to machines and systems in particularly clever ways that are inspired by and remind us of human intelligence.  At the other end is what is sometimes called strong AI, which aims to develop machines that match or exceed human intelligence and cognitive abilities like reasoning, planning, learning, vision and natural language understanding.