Move technology to invisibility.

As technology becomes ubiquitous it also becomes invisible. The more chips proliferate, the less we will notice them. The more networking succeeds, the less we’ll be aware of it.

In the early 1900s, at the heroic stage of the industrial economy, motors were changing the world. Big, heavy motors ran factories and trains and the gears of automation. If big motors changed work, they were sure to change the home, too. So the 1918 edition of the Sears, Roebuck catalog featured the Home Motor–a five-pound electrical beast that would “lighten the burden of the home.” This single Home Motor would supply all the power needs of a modern family. Also for sale were plug-ins that attached to the central Home Motor: an egg beater device, a fan, a mixer, a grinder, a buffer. Any job that needed doing, the handy Home Motor could do. Marc Weiser, a scientist at Xerox, points out that the electric motor succeeded so well that it became invisible. Eighty years later nobody owns a Home Motor. We have instead dozens of micro-motors everywhere. They are so small, so embedded, and so common that we are unconscious of their presence. We would have a hard time just listing all the motors whirring in our homes today (fans, clocks, water pumps, video players, watches, etc.). We know the industrial revolution succeeded because we can no longer see its soldiers, the motors.

Computer technology is undergoing the same disappearance. If the information revolution succeeds, the standalone desktop computer will eventually vanish. Its chips, its lines of connection, even its visual interfaces will submerge into our environment until we are no longer conscious of their presence (except when they fail). As the network age matures, we’ll know that chips and glass fibers have succeeded only when we forget them. Since the measure of a technology’s success is how invisible it becomes, the best long-term strategy is to develop products and services that can be ignored.



If it is not animated, animate it.

Just as the technology of writing now covers almost everything we make (not just paper), so too the technologies of interaction will soon cover all that we make (not just computers). No artifact will escape the jelly bean chip; everything can be animated. Yet even before chips reach the penny price, objects can be integrated into a system as if they are animated. Imagine you had a million disposable chips. What would you do with them? It’s a good bet that half of the value of those chips could be captured now, with existing technology, by creating a distributed swarmlike intelligence using such dumb power.



If it is not connected, connect it.

As a first step, every employee of an institution should have intimate, easy, continuous access to the institution’s medium of choice–email, voicemail, radio, whatever. The benefits of communication often don’t kick in until ubiquity is approached; aim for ubiquity. Every step that promotes cheap, rampant, and universal connection is a step in the right direction.



Distribute knowledge.

Use the minimal amount of data to keep all parts of a system aware of one another. If you operate a parts warehouse, for example, your system needs to be knowledgeable of each part’s location every minute. That’s done by barcoding everything. But it needs to go further. Those parts need to be aware of what the system knows. The location of parts in a warehouse should shift depending on how well they sell, what kind of backlog a vendor forecasts, how their substitutes are selling. The fastest-moving items (which will be a dynamic list) may want to be positioned for easier picking and shipping. The items move in response to the outside–if there is a system to spread the info.

Get machines to talk to one another directly. Information should flow laterally and not just into a center, but out and between as well. The question to ask is, “How much do our products/services know about our business?” How much current knowledge flows back into the edges? How well do we inform the perimeter, because the perimeter is the center of action.



If you are not in real time, you’re dead.

Swarms need real-time communication. Living systems don’t have the luxury of waiting overnight to process an incoming signal. If they had to sleep on it, they could die in their sleep. With few exceptions, nature reacts in real time. With few exceptions, business must increasingly react in real time. High transaction costs once prohibited the instantaneous completion of thousands of tiny transactions; they were piled up instead and processed in cost-effective batches. But no longer. Why should a phone company get paid only once a month when you use the phone every day? Instead it will eventually bill for every call as the call happens, in real time. The flow of crackers off grocery shelves will be known by the cracker factory in real time. The weather in California will be instantly felt in the assembly lines of Ohio. Of course, not all information should flow everywhere; only the meaningful should be transmitted. But in the network economy only signals in real time (or close to it) are truly meaningful. Examine the speed of knowledge in your system. How can it be brought closer to real time? If this requires the cooperation of subcontractors, distant partners, and far-flung customers, so much the better.



Count on more being different.

A handful of sand grains will never form an avalanche no matter how hard one tries to do it. Indeed one could study a single grain of sand for a hundred years and never conclude that sand can avalanche. To form avalanches you need millions of grains. In systems, more is different. A network with a million nodes acts significantly different from one with hundreds. The two networks are like separate species–a whale and an ant, or perhaps more accurately, a hive and an ant. Twenty million steel hammers swinging in unison is still 20 million steel hammers. But 20 million computers in a swarm is much, much more than 20 million individual computers.

Do what you can to make “more.” In a network the chicken-and-egg problem can hinder growth at first–there’s no audience because there is no content, and there is no content because there is no audience. Thus, the first efforts at connecting everything to everything sometimes yield thin fruit. At first, smart cards look no different from credit cards–just more inconvenient. But more is different; 20 million smart cards is a vastly different beast than 20 million credit cards.

It’s the small things that change the most in value as they become “more.” A tiny capsule that beeps and displays a number, multiplied by millions: the pager system. What if all the Gameboys or Playstations in the world could talk to one another? What if all the residential electric meters in a city were connected together into a large swarm? If all the outdoor thermometers were connected, we would have a picture of our climate a thousand times better than we have ever had before.

The ants have shown us that there is almost nothing so small in the world that it can’t be made larger by embedding a bit of interaction in many copies of it, and then connecting them all together.

The game in the network economy will be to find the overlooked small and figure out the best way to have them embrace the swarm.



Check for externalities.

The initial stages of exponential growth looks as flat as any new growth. How can you detect significance before momentum? By determining whether embryonic growth is due to network effects rather than to the firm’s direct efforts. Do increasing returns, open systems, n2 members, multiple gateways to multiple networks play a part? Products or companies or technologies that get slightly ahead–even when they are second best–by exploiting the net’s effects are prime candidates for exponential growth.



Coordinate smaller webs.

The fastest way to amp up the worth of your own network is to bring smaller networks together with it so they can act as one larger network and gain the total n2 value. The internet won this way. It was the network of networks, the stuff in between that glued highly diverse existing networks together. Can you take the auto parts supply network and coordinate it with the insurance adjusters network plus the garage repair network? Can you coordinate the intersection of hospital records with standard search engine technology? Do the networks of county property deed databases, U.S. patents, and small-town lawyers have anything useful in common? Three thousand members in one network are far more powerful than one thousand members in three networks.



Create feedback loops.

Networks sprout connections and connections sprout feedback loops. There are two elementary kinds of loops: Self-negating loops such as thermostats and toilet bowl valves, which create feedback loops that regulate themselves, and self-reinforcing loops, which are loops that foster runaway growth such as increasing returns and network effects. Thousands of complicated loops are possible using combinations of these two forces. When internet providers first started up, most charged users steeper fees to log on via high-speed modem; the providers feared speedier modems would mean fewer hours of billable online time. The higher fees formed a feedback loop that subsidized the provider’s purchase of better modems, but discouraged users from buying them. But one provider charged less for high speed. This maverick created a loop that rewarded users to buy high-speed modems; they got more per hour and so stayed longer. Although it initially had to sink much more capital into its own modem purchases, the maverick created a huge network of high-speed freaks who not only bought their own deluxe modems but had few alternative places to go at high speed. The maverick provider prospered. As a new economy business concept, understanding feedback is as important as return-on-investment.



Protect long incubations.

Because the network economy favors the nimble and quick, anything requiring patience and slowness is handicapped. Yet many projects, companies, and technologies grow best gradually, slowly accumulating complexity and richness. During their gestation period they will not be able to compete with the early birds, and later, because of the law of increasing returns, they may find it difficult to compete as well. Latecomers have to follow Drucker’s Rule–they must be ten times better than what they hope to displace. Delayed participation often makes sense when the new offering can increase the ways to participate. A late entry into the digital camera field, for instance, which offered compatibility with cable TV as well as PCs, could make the wait worthwhile.


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This is a blog version of a book of mine first published in 1998. I am re-issuing it (two posts per week) unaltered on its 10th anniversary. Comments welcomed. More details here.
-- KK