Stay Ahead Through Rapid Innovation

James Burke

In terms of our ability to compete in this increasingly cutthroat, competitive world of outsourcing and job loss, we seem to have arrived at a tipping point. Given the rapid spread of information and communications technology to the so-called “threat” economies (China, India, Brazil, and others), it is unlikely to be long before sectors of those economies are able to do what up to now only the so-called developed economies can. Given this likelihood, there is probably only one way for any company or any industry to stay ahead in the globalized marketplace: innovate faster than the rest.

For several centuries, our industrial and scientific thinking has been (for good historical reasons) limited by the technological shortfall with which, so far, we have been obliged to work—in a culture of information scarcity where only a small percentage of the population had access to the data and tools with which to innovate. In this sense, the entire high-tech modern world is the product of less than 1% of the brains available at any point in history.

Innovative thinking up to the present also has worked in ways that hampered quick and easy social adaptation to new products and processes. There are several reasons for this. One is that we have for centuries been tied to institutions and institutional ways of thinking that originated in the past, with the technology of the past, designed to solve problems of the past (we still run representative democracies as they were designed in an 18th-century world with no telecommunications). These institutions and thought processes encourage us to look backward.

Another reason for this tendency is the specialist-discipline silo-thinking introduced by 17th-century reductionism (reduce every problem to its simplest component parts) and the scientific method, following Descartes’ reaction to the loss of confidence in the accepted body of knowledge when he introduced methodical doubt and focused specialism—both of which have driven innovation from then on. Soon afterward, the noodler’s mission statement had become what it has been to this day: “Learn more and more about less and less. Make your specialist niche so small that there is room in there only for you. Express yourself only in your own gobbledygook, so that in this way you are incomprehensible and, therefore, irreplaceable.’’

As a result, geeks with their noses assiduously to the work bench have tended not to consider the wider social ramifications of their research: what might happen when their discoveries and products eventually hit the fan.

Unsurprisingly, as a result, the general community often has been taken by surprise, especially when the coming together of ideas in novel ways (the prime trigger for innovation) so often changed the rules and made 1 + 1 = 3. Nineteenth-century German engineer Wilhelm Maybach put together the new antiseptic spray (known only to operating-theater surgeons) and the new petroleum (known only to lighting engineers) to produce the carburetor (known to nobody). This kind of serendipity, combined with silo-thinking research and the unintended social “ripple effect” of new developments (see: refrigerators and ozone layer, typewriters and divorce rate, asbestos and carcinogenics), has tended to make the prediction of innovation extremely difficult. And prediction is the only reason for knowing anything.

Looking ahead from all these effects of our reductionist heritage toward how we might compete in ever-more-competitive world markets buffeted by ever-increasing rates of innovation, it seems we need to do at least two things.

The first: to revive flagging government interest in encouraging pure research, which is where we have previously generated entirely new industries (James Dewar’s work to keep a soap bubble inflated for 3 years led to thin-film research, cling-wrap, and the packaging industry; X-ray diffraction identified protein crystal structures, and helped make possible the discovery of DNA and the development of genetics). The second: to combine knowledge mapping, data mining, and electronic agents so as to develop a predictive “innovation discipline.”

"Innovative thinking up to the present has worked in ways that hampered quick and easy social adaptation to new products and processes."

The knowledge web (k-web.org) that I have been developing with secondary school use in mind, and with the aim of encouraging innovative and cross-disciplinary thinking, uses an active mapping construct that also makes it possible (in real time) to update and correlate all interrelated data about a product, a market, a field of study, a community, a political decision, etc., using a dynamic, interactive map of all relevant elements and (above all) their changing connections with each other.

The great promise of knowledge maps is that they can easily navigate the “unvisited ‘no man’s land’ lying between the disciplines” (mathematician Norbert Weiner), where innovation most often originates and which reductionism tends to shun. Knowledge mapping offers the chance to investigate these “in-between” areas and identify possible new cross-disciplinary endeavors that we need to support if we are to innovate fast enough to stay ahead of the game in the decades to come—in other words, predicting the most likely needs in the months or years ahead and directing effort to satisfy those needs in advance of their emergence.

If at the same time we use knowledge-mapping techniques also to make relational data more easily accessible to the millions of brains available for use, we might tap into a disfranchised pool of talent as a new source of innovative thinking. Eighteenth-century mathematician Pierre Simon Laplace said: “You want me to predict everything? OK. Tell me everything.” We are not far from being able to do something close to that.

The recent International Innovation Initiative Summit in Washington, DC, called for a new educational model to encourage innovative cross-disciplinary thinking. And a recent report identified secondary education as the source of the present disquieting fall in the number of students who are interested in a career in science and engineering. The time to act is now.

JAMES BURKE is an author, lecturer, television producer, and historian, specializing in the public understanding of science and technology. For more than 40 years he has produced, directed, written, and presented award-winning television series on the BBC, U.S. Public Broadcasting Service, Discovery Channel, and The Learning Channel. A best-selling author, Burke’s publications include: Tomorrow’s World, Tomorrow’s World II, Connections, The Day the Universe Changed, Chances, The Axemaker’s Gift (with Robert Ornstein), The Pinball Effect, The Knowledge Web, and Circles. His latest book, Twin Tracks: The Unexpected Origins of the Modern World, focuses on the surprising connections among the seemingly unconnected people, events, and discoveries that have shaped the world. Burke wrote a monthly column for Scientific American for 6 years and is currently a contributor to Time magazine. He was educated at Oxford and holds honorary doctorates for his work in communicating science and technology. Burke is a frequent keynote speaker on the subject of technology and social change. He recently gave the keynote address at the Thermo Informatics World international conference in Prague, which explored how users can take advantage of evolving technologies to drive improvement in laboratories and business, from which this article is adapted.