Complexity and Emergence : The Connected Economy : Beyond the Information Age

Christopher Meyer was the director of the Cap Gemini Ernst & Young Center for Business Innovation in Boston. The Center was charged with identifying the issues that will be challenging business in the future, and defining responses to them. His own current research interests include the development of a New Theory of the Firm, the implications for management of new discoveries in complexity and self-organizing systems and the development of the "connected economy."

Chris established the BIOS Group, Cap Gemini Ernst & Young"s initiative to develop complexity-based solutions for management. He has more than 20 years of general management and economic consulting experience.  With Stan Davis he co-wrote "BLUR: The Speed of Change in the Connected Economy" ( Addison-Wesley, 1998 ), "Future Wealth" ( Harvard Business School Press, 2000 ), and "It’s Alive: The Coming Convergence of Information, Biology, and Business" ( Crown Business, 2003 ).

Chris can be reached at Chris.Meyer@gotnerve.com.


Computers are incredibly fast, accurate, and stupid; humans are incredibly slow, inaccurate, and brilliant; together they are powerful beyond imagination.
--Albert Einstein

Over the last fifteen years, business has focused on two themes: time and technology. Because information technology can link people and processes ever more quickly and cheaply, we have multiplied the instant connections among individuals, organizations, and information itself. Attention has been focused on the resulting acceleration of business. But connections are doing more than accelerating the economy; they are changing the way it works. As the number of connections among the elements of a system grows, the system no longer behaves predictably--the system as a whole begins to exhibit unforeseen, "emergent" properties. [footnote 1] Two famous examples of the unanticipated results of connectivity are the 1965 Northeast Blackout and the 1987 stock market crash.

The Northeast Blackout was the largest in history because of the connections shared by the utilities in the power grid. These connections translated an overload at one point in the system into a cascade of failures throughout the grid. Similarly, the stock market crash of October 1987 was created not by economic fundamentals or trader sentiment, but by the interaction of programmed instructions created by independent trades. These unconnected instructions became linked by the mechanisms of the market, increasing the volatility of the system as a whole and causing the Dow Jones Industrial Average to lose 23% of its value in a day.

Figure 1. Competition is driving business to form connections at an unprecedented rate. This connected economy is having unanticipated consequences which will combine in an even greater transformation-to the adaptive economy.

These examples reveal that connection is not necessarily a matter of information technology, though connections are often enabled by it. Connections are a matter of linked decision-making mechanisms. The electric utilities were not connected by a computer, but by electromechanical control systems. The trading rules were connected by the particulars of their timing and price instructions.[footnote 2]

Does this mean that a more connected economy will be characterized by an increasing frequency of calamitous events ? Perhaps, but explosive growth events will be equally characteristic ( e.g., Microsoft, the World Wide Web, and electronic commerce ). Beyond volatility, however, the connected economy will begin to exhibit some novel, emergent properties. In this article, we argue that connections are growing enormously in number, speed, and type, and that this trend will turn the economy into a "complex adaptive system." Market economies have always been adaptive to a degree. But future rates of adaptation will make capitalistic "gales of creative destruction" everyday weather.

In biology, it would have been impossible to foretell the emergence of mammals, reptiles, and the rest by observing the new cellular forms that arose when two types of bacteria combined to create the first cell with a nucleus.[footnote 3] Similarly, we cannot predict the shape of the economy as the emergent properties of connection begin to appear. We can, however, observe four trends that, like the nucleated cell, have the ability to transform today's landscape:

  • Inter-enterprise Relationships 
  • Increasing Returns Economics 
  • Adaptive Systems Theory 
  • Emotion in the Workplace

Inter-Enterprise Relationships

In the 1980's, Procter & Gamble's Pampers Division entered into a strategic partnership with the Wal-Mart stores that sell so many of its diapers. Wal-Mart agreed to transmit daily Pampers sales data from each of its nearly 2,000 locations to Procter & Gamble. Using this data, P&G restocks Wal-Mart's stores with no action needed by Wal-Mart. The result almost doubled Pampers' inventory turns in the first year, to nearly one hundred. A decade later, the level of inter-company coordination achieved by Procter & Gamble and Wal-Mart still exceeds the level of interdepartmental communication and coordination at most companies.[footnote 4]

Prior to the connected age, little attention was paid to the collaborative relationships possible between enterprises. The industrial economy built self-sufficient institutions focused on mass production. Factories were large and often isolated, and companies developed the ancillary capabilities--from legal departments to whole company towns--needed to support their own activities. The best available means for economically sensitive coordination between departments was hierarchy: sharing a boss.

In the connected economy, high technology businesses are reshaping inter-enterprise relationships.[footnote 6] Arm's length relationships are giving way to complex, connected webs. Capabilities are being linked together to create value, often for a relatively brief period. Not infrequently, the entities cooperating in one area may compete in another.

Inter-enterprise connections have arisen from necessity. When IBM first marketed the PC in 1981, customers perceived it to be produced entirely by IBM. In reality, IBM's main achievement was putting its brand on a working set of components made by Intel, Microsoft, Quantum, et al. The interchangeability of these "modules" of the PC value chain became apparent over the next decade, as the component brands achieved parity with IBM's. The current array of computer competitors--including Compaq, Dell, IBM, and now Intel itself--features every combination of value chain modules. Each module can be bought separately.

This modularization of value chain components is not limited to high technology. The "third party logistics" industry sells warehousing, rapid response shipping, and tracking services, allowing organizations like pharmaceutical companies to focus on their research. Enterprise software systems from vendors including SAP, Baan, and PeopleSoft provide templates for core processes ranging from manufacturing to human resources management.

This has been called the "hollowing out" of corporations. But it is also the creation of "value webs," highly interdependent enterprises each tightly focused on a narrow set of capabilities. Companies will be unable to maintain capabilities that are not world class, and will rely on richly connected relationships with specialists to create their value webs. It seems likely that these webs will be far more adaptive than the vertically integrated corporation.

Figure 2. Alliances in selected high-technology fields, 1970-1993.
( Source: The Alliance Revolution, Benjamin Gomes-Casseres, Harvard University Press, 1996.
 

The economy will increase its adaptability by affording instant access to well developed capabilities, rather than taking time to grow them for each new enterprise. The ability to rapidly and successfully form intimate and effective inter-organizational connections is becoming a key corporate skill in the connected economy. Eventually, this trend may extend to individual employees who will become entrepreneurs providing specialized services to a value chain.

Increasing Returns Economics

Why has everyone with a modem received a dozen AOL discs ? Why is the hottest software product of the decade--the Web browser--given away free ? Why did Sun Microsystems, Oracle, and seven other companies with an interest in the success of the Java Internet script language recently amass $100 million to create a Java venture capital fund managed by Kleiner, Perkins, Caulfield & Byers ?

The answer is increasing returns economics. Economists have traditionally taught that businesses grow to the point where returns to scale diminish. That is, the benefits of scale are overwhelmed by the disadvantages of size, such as the difficulty of coordination, or the distances between producer and customer. These ideas fit well in the era when communication and transportation were difficult. The connected economy facilitates coordination, and increasingly the "goods" can be delivered over a wire--dramatically increasing the size of the enterprise at which diminishing returns set in. Just as important, the connecting parties must share a standard of communication. Such a standard can establish an economic community of interest.

These factors create increasing returns to scale: under such circumstances, the positive economic feedback that is created drives the market to a single solution rather than several competing ones.

The phenomenon is not new. Clockmakers and timetellers in the middle ages had to decide between what we now call clockwise and counterclockwise motion. Similarly, an increasing returns scenario also arose in the early days of the telephone industry: it was understood that a single network connecting everyone was a superior solution to several competing networks. Economists deemed telephone networks "natural monopolies" and recommended regulation.

The experience curve that has long been recognized as a special case of increasing returns. The positive feedback loop between market share and cost measured by the curve makes market leadership an imperative and drives stable industries toward oligopoly, a process limited only by the threat of antitrust action.

What's different with, say, clocks and other knowledge products is that the positive feedback is between market share and ease of use. To achieve this ease of use, knowledge products rely on the protocols of financial transactions ( Quicken ), the formats of videodiscs ( consumer electronics ), the API's[footnote 7] of operating systems and on the accumulated learning of their customers. A new Bill Gates can no longer propose a radically new operating system, because the industry is "locked-in"[footnote 8] to the hardware, software, and ( most important ) the learning investment in the existing product.

As connections grow, we will enter a period where companies fight to achieve increasing returns in ever-larger segments of the economy. Eventually, some of these battles will result in standards we take for granted, like 60 cycle 110 volt current. [footnote 9] But lock-in will be increasingly difficult for a single company to achieve--it will more often occur at the industry level. Just as there are many makers of clockwise clocks, there are many manufacturers of fax machines following the Group III fax standard, and many purveyors of Windows PCs.

Thus, while Windows itself stands ( temporarily ) as a locked-in monopoly, the consortium approach taken by Sun Microsystems et al. to invest in Java startups will be more prevalent in the future. The strategy improves Java's chances for success, reduces each company's risk, and injects the unique investment management skills of Kleiner, Perkins into the value web. Because the economy will become increasingly both intangible and connected, increasing returns will become a strategic imperative. We will see more strategic innovations in the management of increasing returns.

To compete in an increasing returns market, a business must rapidly establish its product as the standard. The goal is to quickly lock in the investment of users and of providers of complementary goods, whether it be in equipment or in knowledge. Once you've installed and learned to use the software AOL sent to you, GENIE's disc will likely be ignored.

Increasing returns suggests that new solutions will diffuse--and disappear--much more rapidly, a second mechanism of increased adaptivity. But the economy won't adapt the way economists predict--in a smooth approach to the "optimum." It will proceed by leaps, in a path-dependent evolution. To understand such behavior, we will turn to the sciences of adaptation.

Adaptive Systems Theory

Farm equipment manufacturer John Deere offers automated planters for sowing every kind of seed in every imaginable farming condition: over 1.6 million configurations in all. Due to the huge number of options, none of the usual array of optimization tools such as dynamic programming were able to efficiently schedule the company's planter factory. After Deere began using genetic algorithms to optimize scheduling, the company's order cancellation rate plummeted from hundreds to 5 or 6 over a six-month period. Overtime went down drastically, too. [footnote 10]

Genetic algorithms are just one of a growing number of tools and ideas germinated in the as yet arcane world of adaptive systems theory--also known as complexity science--that are finding profitable applications in the business world. The most exciting possibilities, however, remain in the research stage: better models of business and the economy.

Traditional economic theory has explored "very thoroughly the domain of problems that are tractable by static equilibrium analysis," says Brian Arthur, the scientist who pioneered the concept of increasing returns. [footnote 11] "But it ... virtually ignored the problems of process, evolution and pattern formation--problems where things were not at equilibrium, where there's a lot of happenstance, where history matters a great deal, where adaptation and evolution might go on forever," he explains. As investigators seek the laws by which systems of all kinds grow and adapt, economists are beginning to tackle these "non-equilibrium" problems. [footnote 12]

Adaptive systems theories hold the potential to amplify our understanding of the evolution of the enterprise and the economy. As the connected economy emerges, enterprises are recognizing that the interactions among economic actors have become at least as important as the efficient functioning of each agent.

Complexity science focuses on the behavior of such systems, called complex adaptive systems ( CAS ).

A CAS consists of independent "agents," each capable of making decisions using a few rules. Agents can be people, circuit breakers, trading instructions, or DNA--any entity whose decisions can be defined by rules. The actions of one agent affect the choices of another, so they are connected. Simulations with large numbers of interacting agents show that they behave in ways that are often unpredictable; the properties of such systems are said to "emerge" from the behavior of the connected individuals. Often these emergent properties are "non-linear"--unpredictable and volatile, like the stock market and the power grid.

These ideas afford a new way of looking at business: an economy is an adaptive system of agents ( firms and individuals ) interacting. Under certain environmental conditions ( a legal system, capital availability ), properties such as growth, cyclicality, and distribution of income emerge. Likewise, a company can be reframed not as a machine in equilibrium, but as an adaptive system of individuals. Success, however measured, is an emergent outcome, not the product of a machine. In the connected economy, the organizations providing the infrastructure upon which agents can most effectively and productively organize themselves will attract the greatest talent. [footnote 13]

The development of complexity theory will help us understand the behavior of the economy as its adaptivity grows.

Emotion in the Workplace

A book on Trust [footnote 14] is currently a common subject of business meeting conversations. Improvisational acting troupes appear at executive conferences. "Casual day" is prevalent enough to spur new retailing ventures. The art of "constructive confrontation" is a required course for new Intel employees. New York's Morgan Hotel has redecorated, replacing its hard-edged Eurostyle with soft colors, comfy armchairs, and a philosophy of comforting people--rather than providing the arena for their power lunches.

Though some of these trends may prove fads, they point to a tendency of more enduring significance. Human emotion will become a more important factor in organizational life over the next twenty years, for several reasons:

  1. The Battle for Attention. As monitoring and control functions become automated, management will increasingly be making choices about what to pay attention to. Since managers will be ever more bombarded by demands for attention, the battle will escalate. Advertising and entertainment professionals have long known the answer: appeal to emotion. The techniques used in television and other media to engage our emotions will be increasingly employed in business situations.
     
  2. High-Affect Technology. The reduced cost to present sound, color, and motion will help "arm" this battle for attention. These media engage parts of the brain wired for emotion, as black and white text does not. [footnote 15] Business relationships will employ new tools already used by the advertising and entertainment industries to capture attention. Stan Davis believes smell may become the next medium. The tools will be chosen based on their ability to elicit emotion.
     
  3. The Impact on Productivity. All attention is not of equal quality: Mihaly Csikszentmihalyi's book Flow: The Psychology of Optimal Experience describes in detail the familiar state of intense concentration, high performance, and controlled excitement that occurs when individuals are emotionally engaged in work. He asserts that individuals in flow are much more productive, [footnote 16] and they associate the state with feelings of pleasure, power, and accomplishment. It is thus in the interest of business to create an environment where people spend a greater proportion of their time in this fully engaged flow state. Since individuals take greater pleasure from their work in such a state, the workplace that encourages this state will attract the most talented labor.
     
  4. The Blurring of Personal Workspace. Telecommunications options will create choices for finding an ideal flow-state workspace. It is harder to retain the traditional "manager-as-economic-man" stance when working at home, in the midst of family and personal environment.
     
  5. The Waning of the Machine Metaphor. As biological ideas take hold in business, the idea of the employee as a part of a mechanical process will lose its power, and it will become less defensible to suppress emotion at work.

How this focus on emotional connection may change adaptiveness is unclear. Perhaps the non-linear aspects of the economy will be better understood and reconciled as a result. But for all the above reasons, managers in the future--or whatever managers will become--will have to have a far greater facility for eliciting, channeling, and modulating emotions than today. Organizations that can hire and develop this capability will achieve higher organizational performance.

The Adaptive Advantage

In the primeval soup from which we all descended, atoms connected with other atoms to form molecules. These reacted to form organic chemicals, which eventually--through millions of years and billions of chance opportunities--created bacteria and higher organisms. This property of "self-organization," as adaptive systems theorist Stuart Kauffman calls it, is a general characteristic of systems whose components can interact with one another ( i.e., connect ). And, in such systems, connections grow ever richer over time.

The new density of connections is now evolving the four new features of economic life discussed in this article. Perhaps these features are like the adaptations--lungs ? legs ? wings ? vocal chords ?--that helped mammals evolve. If the growing density of connections in the economy parallels the development of new cell types in the biosphere, what will be the outcome ?

We can no more predict the range of future enterprises from today's innovations than we can envision an elephant by considering the properties of the bacteria from which it evolved. The implication for us as managers is that we won't know what is right--the companies that will thrive in the new economy might have trunks and tusks, but they also might have wings and feathers. As managers, how do we cope ?

Biology has been working on this problem for about four billion years. What does it teach us ? The answers are far from complete, but on the frontier of adaptive systems theory is a set of ideas about adaptiveness itself. The adaptive system, it appears, balances control against disorder, efficiency against experimentation, and standardization against diversity. This balance gives it the best chance both to thrive when the environment is stable and to re-adapt when the situation changes radically.

We are in the beginning of learning how to use the laws of the biosphere for the econosphere: how to find the balance between stability and innovation. Given our recent mechanistic bent, our overarching answer for the present is to favor adaptivity. The answer is not to fight the adaptiveness, but to go with it--you can't fight emergence. Learn the "Lessons from Adaptive Systems Theory" listed on page 71.

It will be painful, threatening, and dangerous to abandon the structures, systems, and dicta that brought us to where we are now. But if they prevent us from adapting to the connected future, they must be left behind.

It's the best possible time to be alive, when almost everything you thought you knew is wrong.

-Tom Stoppard, Arcadia
Act I, Scene Four

The Evolution of Connection

The power of a computer is proportional to the square of the number of computers it is connected to.

-Robert Metcalf, the inventor of Ethernet

In the 1980's, early work in activity based costing revealed that time was a primary driver of cost in the industrial corporation. Studies of "time based competition" showed that more than 80% of the cycle time in many production processes was spent in "non-value added activities" such as waiting in queues and inventories. [footnote 5] Eliminating these delays and their attendant costs was a primary focus of "just-in-time" manufacturing and logistics and, more broadly, of "reengineering."

At the same time, technologies such as 800 numbers, overnight package delivery ( based on bar coding ), and customer databases changed the economics of customized, remote service. Consequently, "anytime, anyplace" delivery became the customer's expectation, and seven-day, 24-hour service the provider's obligation.

These cost-saving opportunities and escalating customer expectations, combined with falling cost of telecommunications, strengthened the push for connection. Innovative businesses quickly capitalized on the advantages such connection could convey. The Italian clothier Benetton, for example, substituted information for inventory by collecting daily sales data from around the world. This allowed the company to make manufacturing decisions based on purchases, rather than relying on stock made months in advance. This new system created a direct feedback loop from the customer to the maker, circumventing the delays of information transfer through the retailer and wholesaler. In addition to cutting inventory, carrying costs, and retail markdown expense, the new connection provided better input on customer design preferences.

Electronic connections continue to shrink the length of time between action and response, thanks to growing prevalence of pagers, cellular phones, voice-mail systems, electronic data interchange, etc. Connection innovations continue to proliferate. Examples of technologies that help make faster, more robust, more reliable connections include: electronic commerce; broadband networks; multi-media; global positioning systems; on-line language translation; effective data-to-voice and voice-to-data interfaces; seamless man-to-machine interfaces; data communications protocols; non-invasive medical monitoring devices; and integrated vehicle-highway systems.

Lessons for the Adaptive Economy

  • Experiment, don't plan. The best-laid plans will be confounded by events to which you are newly connected. In complex systems, it only takes a small deviation to create a huge change ( the flapping of a butterfly's wings in Beijing can cause a hurricane in Hawaii ). In the connected economy, your business is an agent in a massive, complex system.
  • Recombine, don't invent. Nature makes progress by mixing together the "ideas" of evolution--literally, by swapping elements of code. Build on things that work by recombining them in new ways. The connected economy makes these things more accessible faster than before.
  • Innovate, don't perfect. Nature never reaches a maximum--it finds an adaptation that does better than what went before. In the connected economy, someone else will create more value by building on your innovation than you can by continuing to work on it.
  • Act, don't coordinate. Stuart Kauffman has experimented with the way simulated organizations perform when they are controlled in different ways: centrally ( the "Stalinist Limit" ); completely individually ( the "Leftist Italian Limit" ); and various options in between. His results suggest that adaptation occurs most effectively and requires the lowest amount of energy when organizations are broken into "patches" of modest size--six to ten. While these results are derived from "toy world" simulations, their implications ring true to experienced managers.
  • Trust, but verify. The biosphere is full of nasty characters. Wasps lay their eggs in caterpillars, which die to support the wasps. The Ebola virus has little redeeming social value. But both have adapted effectively to their environments. Computer scientist John Holland's research has shown that the "tit for tat" strategy, which may be seen as equivalent to the Golden Rule, can be beaten by more sophisticated players ( actually software programs genetically bred for the purpose ) that first clean out the players who are too "moral" for their own good. The players then revert to the Golden Rule behavior among sophisticated opponents who understand the game. Neither the connected economy nor the adaptive economy that will succeed it are "new age"--both are as red in tooth and ink as ever.

1. Quantitative simulations show that as the number of connections among elements in a system rises above half the number of elements, the probability of cascading events rises dramatically. This represents a "phase change" in the system, resulting in non-linear responses to external inputs. See Stuart Kauffman, At Home in the Universe.
2. Underscoring the point, the SEC installed automatic rules designed to limit similar cascades--and called them "circuit breakers".
3. See Gould, Steven Jay, Wonderful Life: The Burgess Shale and Nature of History ( New York: Norton, 1989 ).
4. See Stan Davis, 2020 Vision ( 1992 ) for an explanation of these ideas.
5. Stalk, George. "Time: The Next Source of Competitive Advantage",Harvard Business Review, July/August 1988
6. See Moore, James, The Death of Competition: Leadership and Strategy in the Age of Business Ecosystems ( New York: Harper Business, 1996 ).
7. Application Program Interface
8. Brian, Arthur, W., "Increasing Returns and the New World of Business", Harvard Business Review, July/August 1996.
9. Note the penalty customers pay for using portable phones and computers--carrying around low voltage PC power supplies ( the "softwindows" of the electrical novice ).
10. Petzinger, Thomas, "At Deere They Know a Mad Scientist May Be a Firm's Biggest Asset", The Wall Street Journal, ( July 14, 1995 ).
11. Waldrop, M. Mitchell, Complexity: The Emerging Science at the Edge of Order and Chaos ( New York: Simon & Schuster, 1992 ), p. 325.
12. In fact, adaptive systems theory presented Arthur with the tools necessary for modeling the theory of increasing returns economics. See also Anderson, Philip W., Kenneth J. Arrow, and David Pines, The Economy as an Evolving Complex System ( Addison Wesley, 1988 ).
13. This, in turn will create an increasing returns feedback loop: the best talent using the best infrastructure creates the most value, which creates the greatest means to improve the infrastructure and attract more talent.
14. Fukuyama, Francis, Trust ( New York, Free Press, 1996 ).
15. DaMasio, Antonio R, Descartes' Error, Emotion, Reason, and the Human Brain ( New York, G.P. Putnam's Sons, 1994 ).
16. Csikszentmihaly; Mihaly, Flow: The Psychology of Optimal Experience ( New York, Harper Collins, 1990 ).


© Copyright Christopher Meyer

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