Redesigning Knowledge Work

"A worsening shortage of high-skill knowledge workers is one of the biggest challenges facing organizations. These talented and highly paid experts—doctors, lawyers, engineers,salespeople, scientists, and other professionals—are companies’ most valuable assets.

In response, some firms are redefining the jobs of their experts, transferring some of their tasks to lower-skill people inside or outside their organizations, and outsourcing work that requires scarce skills but is not strategically important.

Redesigning jobs in this fashion involves several basic steps: identifying the gaps between the talent your firm has and what it will need; creating narrower, more-focused job descriptions in areas where talent is scarce; choosing from various options for filling the skills gap; and revamping talent- and knowledge-management processes to accommodate the new way of working."
Martin Dewhurst, Bryan Hancock, and Diana Ellsworth, Harvard Business Review, Jan-Feb 2013

In my opinion, this is a dangerous extension of the industrial model. And, it is just the opposite of what should be happening (trans-disciplinary skills) to solve today's wicked problems. In addition it adds additional layers of communications - boundaries that lead to errors and oversights.

The Information: A History, a Theory, a Flood

Freeman Dyson writes an interesting and provocative review of the new book by Gleick in the New York Review of Books, 3/10/11.

Gleick begins his book with a chapter titled "Drums That Talk". Dyson reviews this chapter and concludes:

"The story of the drum language illustrates the central dogma of information theory. The central dogma says, “Meaning is irrelevant.” Information is independent of the meaning that it expresses, and of the language used to express it. Information is an abstract concept, which can be embodied equally well in human speech or in writing or in drumbeats. All that is needed to transfer information from one language to another is a coding system. A coding system may be simple or complicated. If the code is simple, as it is for the drum language with its two tones, a given amount of information requires a longer message. If the code is complicated, as it is for spoken language, the same amount of information can be conveyed in a shorter message."

After two historical examples of rapid communication in Africa and France, "the rest of Gleick’s book is about the modern development of information technology. The modern history is dominated by two Americans, Samuel Morse and Claude Shannon. Samuel Morse was the inventor of Morse Code. He was also one of the pioneers who built a telegraph system using electricity conducted through wires instead of optical pointers deployed on towers. Morse launched his electric telegraph in 1838 and perfected the code in 1844. His code used short and long pulses of electric current to represent letters of the alphabet."

"Claude Shannon was the founding father of information theory. For a hundred years after the electric telegraph, other communication systems such as the telephone, radio, and television were invented and developed by engineers without any need for higher mathematics. Then Shannon supplied the theory to understand all of these systems together, defining information as an abstract quantity inherent in a telephone message or a television picture. Shannon brought higher mathematics into the game."

Dyson writes, "According to Gleick, the impact of information on human affairs came in three installments: first the history, the thousands of years during which people created and exchanged information without the concept of measuring it; second the theory, first formulated by Shannon; third the flood, in which we now live."

The reviewer writes a wonderful description of science:

"The information flood has also brought enormous benefits to science. The public has a distorted view of science, because children are taught in school that science is a collection of firmly established truths. In fact, science is not a collection of truths. It is a continuing exploration of mysteries. Wherever we go exploring in the world around us, we find mysteries. Our planet is covered by continents and oceans whose origin we cannot explain. Our atmosphere is constantly stirred by poorly understood disturbances that we call weather and climate. The visible matter in the universe is outweighed by a much larger quantity of dark invisible matter that we do not understand at all. The origin of life is a total mystery, and so is the existence of human consciousness. We have no clear idea how the electrical discharges occurring in nerve cells in our brains are connected with our feelings and desires and actions.

Even physics, the most exact and most firmly established branch of science, is still full of mysteries. We do not know how much of Shannon’s theory of information will remain valid when quantum devices replace classical electric circuits as the carriers of information. Quantum devices may be made of single atoms or microscopic magnetic circuits. All that we know for sure is that they can theoretically do certain jobs that are beyond the reach of classical devices. Quantum computing is still an unexplored mystery on the frontier of information theory. Science is the sum total of a great multitude of mysteries. It is an unending argument between a great multitude of voices. It resembles Wikipedia much more than it resembles the Encyclopaedia Britannica."

Dyson describes this flood of information in the context of evolution:

"The explosive growth of information in our human society is a part of the slower growth of ordered structures in the evolution of life as a whole. Life has for billions of years been evolving with organisms and ecosystems embodying increasing amounts of information. The evolution of life is a part of the evolution of the universe, which also evolves with increasing amounts of information embodied in ordered structures, galaxies and stars and planetary systems. In the living and in the nonliving world, we see a growth of order, starting from the featureless and uniform gas of the early universe and producing the magnificent diversity of weird objects that we see in the sky and in the rain forest. Everywhere around us, wherever we look, we see evidence of increasing order and increasing information. The technology arising from Shannon’s discoveries is only a local acceleration of the natural growth of information."

Dyson closes his review with some thoughts about the future:

"The vision of the future as an infinite playground, with an unending sequence of mysteries to be understood by an unending sequence of players exploring an unending supply of information, is a glorious vision for scientists. Scientists find the vision attractive, since it gives them a purpose for their existence and an unending supply of jobs. The vision is less attractive to artists and writers and ordinary people. Ordinary people are more interested in friends and family than in science. Ordinary people may not welcome a future spent swimming in an unending flood of information. A darker view of the information-dominated universe was described in a famous story, “The Library of Babel,” by Jorge Luis Borges in 1941.³ Borges imagined his library, with an infinite array of books and shelves and mirrors, as a metaphor for the universe.

Gleick’s book has an epilogue entitled “The Return of Meaning,” expressing the concerns of people who feel alienated from the prevailing scientific culture. The enormous success of information theory came from Shannon’s decision to separate information from meaning. His central dogma, “Meaning is irrelevant,” declared that information could be handled with greater freedom if it was treated as a mathematical abstraction independent of meaning. The consequence of this freedom is the flood of information in which we are drowning. The immense size of modern databases gives us a feeling of meaninglessness. Information in such quantities reminds us of Borges’s library extending infinitely in all directions. It is our task as humans to bring meaning back into this wasteland. As finite creatures who think and feel, we can create islands of meaning in the sea of information. Gleick ends his book with Borges’s image of the human condition:

We walk the corridors, searching the shelves and rearranging them, looking for lines of meaning amid leagues of cacophony and incoherence, reading the history of the past and of the future, collecting our thoughts and collecting the thoughts of others, and every so often glimpsing mirrors, in which we may recognize creatures of the information."

The Information: A History, a Theory, a Flood
by James Gleick
Pantheon,2011

The Power of Data Visualization

David McCandless turns complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world.

David McCandless draws beautiful conclusions from complex datasets -- thus revealing unexpected insights into our world.

A Brief Introduction to: Information Theory, Excess Entropy and Computational Mechanics

David Feldman, April 1998

This article contains more information than I was interested in as my current interest is in complexity. However, his axiomatic definition of information entropy was interesting and useful to complexity. He list three axioms:

1. Entropy reaches a maximum when the distribution is uniform.
2. Entropy is a continuous function of the probability function.
3. Entropy is the same for every set of probabilities in the probability function

These are my words not his. It’s my interpretation of his mathematical relationships.

The first axiom states that if the probability of any state for a system is the same as any other state then entropy of the system is at its maximum. The second axiom states that any arbitrary small change in the system should lead to a small change in the entropy. And, the third axiom states that any sample from the system should return the same entropy as any other sample. This describes an unstructured complex system.

For a structured complex system applying these axioms yields some interesting insights. A complex system never has a uniform distribution of probabilities, so the entropy of a complex system is never maximized. A structured complex system is often partially or totally nonlinear, and sensitive to initial conditions. Cause and effect are not necessarily relatable. A small change in the system can have a large impact of the system’s entropy. A structured complex system is sensitive to both space and time history. So, almost by definition, a sample cannot be representative of the system’s entropy.

This last point has been concerning me for some time with respect to market research, marketing research and polling. Most of the systems we seek to gain sight about are by definition now structured complex systems. As a result, sampling will yield unreliable results.

A Brief Introduction to: Information Theory, Excess Entropy and Computational Mechanics
David Feldman, April 1998

The Information Revolution

This video explores the changes in the way we find, store, create, critique, and share information. This video was created as a conversation starter, and works especially well when brainstorming with people about the near future and the skills needed in order to harness, evaluate, and create information effectively.

David Pearce Snyder on Information, Creativity and the Future

David Pearce Snyder, Life-Styles Editor of The Futurist magazine, is a data-based forecaster whose thousands of seminars and workshops on strategic thinking have been attended by representatives from most of the Fortune 500 companies, and from local and federal government agencies, educational institutions and trade associations. Before entering private practice as a consulting futurist in 1981, Mr. Snyder was Chief of Information Systems, and later, Senior Planning Officer for the U.S. Internal Revenue Service, where he designed and managed the Service's Strategic Planning System. He was also a consultant to the RAND Corporation, and served as an instructor for the Federal Executive Institute, and for Congressional and White House staff development programs. Mr. Snyder has published hundreds of studies, articles and reports on the specific future of a wide range of U.S. institutions, industries and professions, and on the socio-economic impacts of new technologies. He is the editor/co-author of five books, including Future Forces and a sequel, America in the 1990s, both published by the American Society of Association Executives. He has appeared on Nightline, the Today Show, CNN, MSNBC, and the BBC World Service.

The common assumption that the Information Revolution will create a new generation of high value/high pay rank-and-file jobs remains an article of faith that is not reflected in current hiring patterns or official long-range employment forecasts. To the contrary, routine workplace activities are increasingly being automated, infomated, and commoditized, reducing the need for skilled labor. Simultaneously, macroeconomists expect that international competition made possible by free trade and our new global infostructure – the Internet – will increasingly drive local labor markets worldwide to pay comparable wages for comparable work. But real revolutions arise from the “bottom up,” and a confluence of spontaneously adopted technical innovations and collegial workplace practices is currently foreshadowing a grassroots reinvention of work itself that can be expected to increase the value- added and the income earned by rank-and-file employees. What is emerging is an absolutely unexpected yet intuitively compelling social invention – “open collaboration” – uniquely capable of mobilizing the creative capacities of workers everywhere to exploit the productive potential of information technology, and to address the growing inventory of social, economic, environmental and bio-medical challenges confronting the future of human enterprise.

The Big Switch: Rewiring the World, from Edison to Google

Nicholas Carr, author of Does IT Matter?, has written a provocative and insightful book about the big switch that we are undergoing with respect to information technology infrastructure. He provides a persuasive historical analogy that computer utilities will replace in house computer facilities.

Carr sums up the basic premise in this way, “Why has computing progressed in such a seemingly dysfunctional way? Why has the personalization of computers been accompanied by such complexity and waste? The reason is fairly simple. It comes down to two laws. The first and most famous was formulated in 1965 by the brilliant Intel engineer Gordon Moore. Moore's Law says that the power of microprocessors doubles every year or two. The second was proposed in the 1990s by Moore's equally distinguished colleague Andy Grove. Grove's Law says that telecommunications bandwidth doubles only every century. Grove intended his "law" more as a criticism of what he considered a moribund telephone industry than as a statement of technological fact, but it nevertheless expresses a basic truth: throughout the history of computing, processing power has expanded far more rapidly than the capacity of communication networks. This discrepancy has meant that a company can only reap the benefits of advanced computers if it installs them in its own offices and hooks them into its own local network. As with electricity in the time of direct-current systems, there's been no practical way to transport computing power efficiently over great distances.”

“’The next sea change is upon us’ Those words appeared in an extraordinary memorandum that Bill Gates sent to Microsoft’s top managers and engineers on October 30, 2005. Bely its bland title, ‘Internet Software Services,’ the memo was intended to sound an alarm, to warn the company that the rise of utility computing threatened to destroy its traditional business.”

Microsoft has dominated the PC desktop. What was emerging was a totally different kind of business – software as a service. Something we now call SaaS. This new way to look at software will be very disruptive.

In 2005, Google began work on its Dalles, OR computing utility facility. “The town's remoteness would make it easier for Google to keep the facility secure-and harder for its employees to be lured away by competitors. More important, the town had ready access to the two resources most critical to the data center's efficient operation: cheap electricity and plentiful bandwidth. Google would be able to power its computers with the electricity produced by the many hydroelectric dams along the Columbia, particularly the nearby The Dalles dam with its 1.8-gigawatt generating station. It would also be able to temper its demand for electricity by tapping the river's icy waters to help cool its machines. As for bandwidth, the town had invested in building a large fiber-optic data network with a direct link to an international Internet hub in nearby Harbour Pointe, Washington. The network provided the rich connection to the Internet that Google needed to deliver its services to the world's Web surfers.” Carr speculates that in the future we may look back on this endeavor much as we now look back on Insull’s early electricity generating plants.

One of the first really successful implementations of SaaS was SalesForce, a CRM application. Marc Benioff, who left Oracle to found SalesForce, proclaimed the end of software as we know it. “As it turned out, the idea of software-as-a-service caught on even more quickly than Benioff expected. In 2002, the firm's sales hit $50 million. Just five years later, they had jumped tenfold, to $500 million. It wasn't just small companies that were buying its service, though they had constituted the bulk of the earliest subscribers. Big companies like SunTrust, Merrill Lynch, Dow Jones, and Perkin-Elmer had also begun to sign up, often abandoning their old in-house systems in the process. Benioff's audacious gamble, like Insull's a century earlier, had panned out. As for the once mighty Siebel Systems, it had gone out of business as a stand-alone company. After suffering a string of deep losses in the early years of the decade, it was bought up in early 2006 by Benioff's old company, Oracle.”

Amazon launched the first utility computing service in March, 2006. They allowed customers to store data on Amazon’s systems for a few cents per gigabyte per month.

One of the things that I really like the way Carr writes is that he mixes so many different perspectives and insights. “In the early decades of the twentieth century, as punch-card tabulators and other computing machines gained sophistication, mathematicians and businessmen began to realize that, in the words of one historian, ‘information is a commodity that can be processed by a machine.’ Although it now sounds obvious, it was a revolutionary insight, one that fueled the growth and set the course of the entire computer industry, particularly the software end of it, and that is now transforming many other industries and reshaping much of the world's economy. As the price of computing and bandwidth has plunged, it has become economical to transform more and more physical objects into purely digital goods, processing them with computers and transporting and trading them over networks.”

And, later, “Until recently, most information goods were also subject to diminishing returns because they had to be distributed in physical form. Words had to be printed on paper, moving pictures had to be captured on film, software code had to be etched onto disks. But because the Internet frees information goods from their physical form, turning them into entirely intangible strings of ones and zeroes, it also frees them from the law of diminishing returns. A digital good can be replicated endlessly for essentially no cost-its producer does not have to increase its purchases of inputs as its business expands. Moreover, through a phenomenon called the network effect, digital goods often become more valuable as more people use them. Every new member that signs up for Skype, puts an ad on Craigslist, or posts a profile on PlentyOfFish increases the value of the service to every other member. Returns keep growing as sales or use expands-without limit.”

One of the big factors that is contributing to the rising productivity of computers is social production (the social web and collaboration). “Whereas industrialization in general and electrification in particular created many new office jobs even as they made factories more efficient, computerization is not creating a broad new class of jobs to take the place of those it destroys. As Autor, Levy, and Murnane write, computerization ‘marks an important reversal. Previous generations of high technology capital sharply increased demand for human input of routine information-processing tasks, as seen in the rapid rise of the clerking occupation in the nineteenth century. Like these technologies, computerization augments demand for clerical and information-processing tasks. But in contrast to [its] predecessors, it permits these tasks to be automated.’ Computerization creates new work, but it's work that can be done by machines. People aren't necessary.

That doesn't mean that computers can take over all the jobs traditionally done by white-collar workers. As the scholars note, ‘Tasks demanding flexibility, creativity, generalized problem-solving and complex communications-what we call nonroutine cognitive tasks-do not (yet) lend themselves to computerization.’ That parenthetical ‘yet,’ though, should give us pause. As the power and usefulness of networked computers have advanced during the few years since they wrote their paper, we've seen not only the expansion of software's capabilities but the flowering of a new phenomenon that is further reducing companies' need for workers. Commonly termed ‘social production,’ the phenomenon is reshaping the economics of the media, entertainment, and software industries, among others. In essence, it allows many of those ‘nonroutine cognitive tasks’ that require ‘flexibility, creativity, generalized problem-solving and complex communications’ to be carried out for free-not by computers on the network but by people on the network.”

An example familiar to everyone is YouTube. All the users provide the content, catalogue and rate is value. Wikipedia is another example.

Why do people contribute? Carr lists several reasons:

* They contribute without knowing it (i.e. search engines)
* Self interest (i.e. tools they use to help them for free and results are shared like del.cio.us)
* Competitive or status seeking (i.e. Wikipedia)
* Enjoyment

And, I would add, altruism.

Ubiquitous inexpensive computing and communications with a constant flow of new software applications are fueling this phenomena. “In his book The Wealth of Networks, Yale law professor Yochai Benkler traces the recent explosion in social production to three technological advances. ‘First, the physical machinery necessary to participate in information and cultural production is almost universally distributed in the population of the advanced economies,’ he writes. ‘Second, the primary raw materials in the information economy, unlike the physical economy, are [freely available] public goods-existing information, knowledge, and culture.’ Finally, the Internet provides a platform for distributed, modular production that ‘allows many diversely motivated people to act for a wide range of reasons that, in combination, cohere into new useful information, knowledge, and cultural goods.’”

One of the reasons all of this works is the connection between people and the community it creates. “Richard Barbrook, of the University of Westminster in London, expressed this view well in his 1998 essay 'The Hi-Tech Gift Economy.' He wrote of Internet users:

‘Unrestricted by physical distance, they collaborate with each other without the direct mediation of money or politics. Unconcerned about copyright, they give and receive information without thought of payment. In the absence of states or markets to mediate social bonds, network communities are instead formed through the mutual obligations created by gifts of time and ideas.’"

This a book to be read and discussed.

The Big Switch: Rewiring the World, from Edison to Google
Nicholas Carr
WW Norton & Company, NY, 2008, 278 pp