August 27, 2007
The Great Decoupling
Like many people who are intrigued by the digital world, I was floored and deeply influenced by William Gibson‘s science fiction, which I first came across in Omni magazine in the late 1970s, when I was a deeply nerdy pre-teen. His 1984 novel Neuromancer popularized the term ’cyberspace,’ was prescient about how people would be using computers and networks 20 years later, and remains a fantastic read.
Early in the book, which is set in a vaguely specified near future, he tells the reader how to visualize the action in the novel’s Boston-Atlanta Metropolitan Axis:
"Program a map to display frequency of data exchange, every thousand megabytes a single pixel on a very large screen. Manhattan and Atlanta burn solid white. Then they start to pulse, the rate of traffic threatening to overload your simulation. Your map is about to go nova. Cool it down. Up your scale. Each pixel a million megabytes. At a hundred million megabytes per second, you begin to make out certain blocks in midtown Manhattan, outlines of hundred-year-old industrial parks ringing the old core of Atlanta..."
Gibson’s point, of course, is that in a market information flows follow the money. But what about within a hierarchy like a single company? What’s the principle there about where information flows?
Until recently there was also a pretty simple rule of thumb within hierarchies: information flows followed decision rights. A decision right is exactly what it sounds like: the power to make a call, settle on a course of action, arbitrate a dispute, etc. A Gap store manager has decision rights over whom to hire, but not where to open a new location; that decision right resides much higher up in the company.
Information flows have historically followed decision rights for two simple reasons: effective decision-making requires information (often a lot of it), and information has historically been expensive to gather and transmit. As a result, it made sense to be stingy when amassing and sending information, and to only send it where it would be put to best use -- as an aid to decision-making.
As MIT’s Tom Malone has been pointing out for a while now, most recently in his provocative book The Future of Work, one of these two reasons no longer holds. Information is now essentially free to transmit, thanks to the Internet’s pricing structure and to the vast increases in bandwidth brought by the laser and fiber optics. Processing, memory, and storage also continue to decline exponentially in price, making it cheap to store and process information as well. The net result of these increases in computing muscle is that most of us no longer need to be stingy about transmitting, holding, and analyzing information. Instead, we can be profligate.
In addition, it’s also becoming much cheaper to amass information. Enterprise IT collects masses of detailed data about the ongoing activities of a company: its transactions, events, activities, status changes, etc. It can be difficult, of course, to make sense or extract value out of this data, but it’s not difficult to acquire it over time.
Malone draws pictures like the ones below to show what happens over time as information costs go down (I’ll use the broader term ‘information costs’ to emphasize that it’s not just communication costs that decline sharply over time.). Centralization first increases as information collection and transmission become feasible for the first time, then decreases as costs do. Centralization is eventually replaced by lateralization:
But lateralization of what, precisely? The pictures above are probably highly accurate illustrations of how information flows within a hierarchy change over time as information costs plummet. If we could graph current information flows within IBM, Renault, Li & Fung, or The US Army I’d be astonished if they didn’t look like the rightmost picture above. And if we could do the same for the information flows of 10, 20, and 40 years ago I’d be equally astonished if they weren’t much more centralized.
Malone’s theory, however, goes much farther than just outlining how information flows change. It also predicts how decision right allocations will change as a result. His thesis is a simple and powerful one: decision rights will also become more lateralized as information costs plummet, leading to greater power and autonomy at lower levels within a hierarchy -- in short, greater decentralization. As he says in The Future of Work:
"There is ... [a] crucial factor that affects where decisions are made in business, and this factor is changing dramatically almost everywhere...
What is this factor?
It’s the cost of communication...
With new communication technologies… it is now becoming economically feasible -- for the first time in history -- to give huge numbers of workers the information they need to make more choices for themselves."
The strong form of this hypothesis is that companies will become less hierarchical and authoritarian, and more democratic and autonomous. Command-and-control approaches will become archaic. Pyramids will become pancakes. The fleetest, most innovative, and most competitive companies will be those that push decisions downward and empower the people closest to the action. The information gathering and filtering bureaucracies that most large companies have built up will become superfluous, and will be pruned. They’ll be replaced by networks of interdependent yet autonomous units that are given the decision rights necessary to pursue the company’s goals.
This is a powerful argument and there’s clearly a great deal of truth to it. Any of us could point to our favorite examples of technology-enabled decentralization and local empowerment, both across and within companies. Mine include eBay, Innocentive, open source communities, Cambrian House, and Rite Solutions.
But the strong form of the Future of Work hypothesis -- that decentralization of decision rights is a main result of vanishing information costs -- rests on the assumption that decision rights and information flows are inherently coupled. It’s easy to see where this assumption comes from. Because the two have been so tightly coupled up to now it’s reasonable to think that they will they will continue to be, and that big changes in information costs will ‘pull’ decision right along with them.
But the fundamental rule about where decision rights should go has nothing to do with information costs themselves. Instead, it has to do with knowledge. The ground rule is: align decision rights with relevant knowledge. In an economist’s formulation, relevant knowledge is the sum of general knowledge and specific knowledge. General knowledge is just what it sounds like -- knowledge that is widely known and easily transmitted. Specific knowledge is the opposite; it’s knowledge that is confined to one entity (a person, or perhaps a team or a lab) and hard to extract from that entity and send somewhere else.
General knowledge and specific knowledge are close in many ways to a sociologist’s conception of explicit and tacit knowledge, respectively. The reason tacit knowledge stays tacit isn’t just because people don’t want to share, or give away their comparative advantage; it’s because, as the philosopher Michael Polanyi elegantly summarized "We know more than we can tell."
Let’s say that a mortgage company realized that a few of its loan officers were just better at assessing credit risk than all the others. For whatever reasons (intelligence, experience, intuition, etc. ), they just had superior specific knowledge. In that situation, it would make good sense not to decentralize, but instead to centralize that decision right within the company, taking it away from the other loan officers. All the general knowledge (income statements, credit histories, etc.) would be sent to these few people, who would apply their specific knowledge to it and made decisions. In this example low information costs are still important; they allow all the general knowledge to be zipped to the few good officers. But the effect of low information costs isn’t decentralization and greater empowerment. Instead, it’s centralization of an important decision right and reduced autonomy for most loan officers.
Thought experiments like this one indicate to me that the net result of disappearing information costs won’t necessarily be decentralization. It will instead be the decoupling of information flows and decision rights. Organization designers will be able to allocate decision rights without worrying about how costly it will be to get required information to deciders. Leaders will be able to ask "Who should make this decision?" without adding "Keeping in mind that it’s going to be slow, difficult, and expensive to get them the general knowledge they’ll need."
Will this work always, or even usually, lead to more decentralized organizations? I find myself less confident than Malone that this will be the case. I agree with him that we’re at a very interesting point in the history of technology and the economics of information, but I’d label it a great decoupling (of information flow and decision rights) rather than a broad decentralization (as decision rights lateralize along with information flows).
I’m also less confident of a single broad trend toward decentralization because of another fundamental aspect of today’s information technologies: they often serve to change the mix of general and specific knowledge. For example, the mortgage industry has in fact moved to greatly centralize decision rights about whether or not to extend a loan, but in a way that doesn’t quite follow the example given above. Instead of giving this decision to a small group of people, it’s been largely given over to computers.
After a lot of analysis, the formerly somewhat intuitive and qualitative decision about whether to extend a loan has become a quantitative one. For individuals, the single-number FICO score does a pretty good job of capturing the likelihood of defaulting. In this case, the knowledge required to answer the question "Will this person repay their loan?" is no longer specific; it’s become general. Computers and the people who program them have become quite good in several domains at converting specific knowledge into general knowledge. With enough history, data, and intellectual energy many formerly intuitive tasks have been codified to the point that they can be turned over to computers for superior performance. Humans, for example, are probably no longer the world’s best chess players.
They’re still the world’s best radiologists, however. It’s not the case that specific knowledge is headed for extinction. Our brains are powerful and highly specialized computers, and they’re just better at some things than the silicon kind are. In their wonderful book The New Division of Labor: How Computers are Creating the Next Job Market Frank Levy and Richard Murnane explain that we humans excel at pattern recognition, case-based reasoning, and other similar skills that they group together under the label "Expert thinking." Expert thinking results from specific knowledge, and can’t be mimicked with general knowledge alone.
As the examples of chess and mortgage scoring show, today’s expert thinking can become tomorrow’s computer program. Some kinds of expert thinking, in other words, can be codified to a very high degree or substituted for by brute force computational power (As radiology, driving in traffic, and playing the Asian board game Go demonstrate, however, many other human skills appear safe, at least for the time being. ). When this happens, it makes sense to take related decisions out of people’s hands, and give them to computers. This is a type of centralization.
However, just as computer programmers work diligently to convert specific knowledge into general knowledge, the rest of humanity works to do the opposite. We build up our specific knowledge in large part by assimilating lots of information, some of which comes from information technologies. The food service company SYSCO used business intelligence software to help identify which of its current customers were most likely to defect, but it was still the sales rep’s call how to best approach these customers and get them to stay. I find this a very interesting case study: even though the BI software converted some formerly specific knowledge ("What makes a customer likely to defect?" ) to general knowledge, related decision rights did not move away from the sales rep because SYSCO believed that the rep’s specific knowledge about the customer was still critical.
One last point: with all of this information and information technology piling up, it’s sometimes hard to tell where the relevant knowledge lies, and how much of it is specific vs. general. Most large apparel retailers, for example, have highly centralized their sales forecasting activities. Small teams at headquarters determine what’s going to sell 12-24 months in advance. They rely on their intuition, and often on forecasting algorithms that predict demand based on previous sales. The Spanish clothing company Zara, meanwhile, has radically decentralized the work of predicting sales. Zara asks its store managers what garments will sell in their locations over the next couple weeks, then gets those clothes to them in a couple days. Headquarters also regularly asks store managers what trends they’re noticing and designs new clothes throughout the year to capitalize on them. Zara’s leaders believe that for the stylish clothes the company sells the relevant knowledge is almost all specific knowledge, and that it resides in the heads of its store managers around the world. Zara’s recent performance suggests that they’re right about this.
Most of what I’ve seen recently strongly indicates that the sudden near-disappearance of information costs is bringing up a fascinating and consequential set of questions for organization designers and corporate leaders. They now have the freedom to place decision rights where they wish without being hampered by information costs. What are the long-term consequences of this great decoupling? Rather than a steady rise in decentralization, I think we’re going to see an extended period of innovation and experimentation. I think Malone might well be right that the "market share [of centralized management] is likely to decrease," but I also think there will be strong movement in the opposite direction -- toward more centralization of some decision rights—and a lot of very interesting hybrid models, some so interesting that they’ll look like science fiction.
What are you seeing? How are decision rights migrating within your organization, and what role is information technology playing? Is IT central or peripheral to the trends you’re observing?
August 19, 2007
Making Your Company Run Like a Ducati
My previous blog post on the benefits of commercial enterprise systems, which was a response to an article by Cynthia Rettig, generated some interesting comments, both on my blog and elsewhere. The ones that caught my eye argued that companies were digging themselves into a deep, dark, hole of complexity by deploying these technologies:
"Rettig is looking forward and McAfee is taking the historical perspective. In summary, information technology has been good for business to date, but we’re at an impasse where, as the saying goes, past performance is not necessarily indicative of future success." - comment on my blog from Philip Sheldrake
"Also, I think Rettig’s larger point… is that ERP systems… may hinder companies from capitalizing on potentially more flexible and simpler systems going forward." - comment on my blog from Nick Carr
"McAfee’s critique, however, doesn’t address Rettig’s larger point, which concerns the effect of ERP’s complexity on companies’ choices going forward." - from Rough Type, Carr’s blog
When it comes to enterprise IT architectures, everyone agrees that complexity kills. It adds to expense, decreases reliability, and makes system accidents more likely. Everyone also agrees that modern commercial enterprise systems (like those sold by SAP and Oracle) are unbelievably complex pieces of software. So it’s a short and easy logical leap to conclude that companies that buy enterprise IT are killing themselves, or at least mortgaging their futures in a demonstrably counterproductive way.
The flaw in this logic is that it ignores the differences between system (or design) complexity and module complexity. A company’s IT infrastructure is a system made up of many interdependent modules, or discrete applications. These modules interact with each other in many, many ways, but they also do some purely internal work. An SAP ERP application (module A), for example, might receive an order from a Web front end (module B). This order triggers a number of purely internal events within ERP -- decrementing inventory balances, preparing billing paperwork, printing out a pick list in the warehouse, etc. The order also yields a commission payment for a sales rep. Data about this payment is sent to a CRM application (module C), which salespeople check obsessively from their Blackberries.
The key distinction here is that it’s SAP’s responsibility to configure, test, and maintain all the logic and data flows that are purely internal to ERP, while it’s the CIO’s responsibility to do the same for all the activities that flow between systems. And of all the complaints I’ve heard about commercial enterprise applications over the years, I’ve rarely heard that their internal logic was messed up -- that they kept losing orders, double-paying sales reps, and so on. And when I have heard such complaints during an implementation project, it’s almost always turned out that an interface with another system was to blame. Enterprise systems can be terribly difficult to configure, but if and when they are properly configured their internal logic generally works. CIOs who want to minimize complexity can "set ‘em and forget ‘em." A complexity theorist would lump all that internal logic together as a ’hidden module‘ and ignore it, concentrating instead on all the interfaces between modules.
The counterintuitive result is that adding a wildly elaborate and complicated module can significantly decrease system complexity, if it replaces a number of older modules whose interactions required babysitting. If the PC I wrote this on had a motherboard I’d built myself from scratch, I’d have to spend a lot of time troubleshooting it, and making sure that every new peripheral I added didn’t destabilize the whole machine. I’d be smart to just replace the whole thing with a ready-made and pre-tested motherboard. If I tried to build a motorcycle engine from scratch and put it in my bike I’m sure I’d spend no time riding and all my time fixing. Even though my Ducati’s desmodromic engine is complicated even in comparison to its peers, it gives me no headaches and I never think about it (except to feel cool ‘cause my bike has a desmodromic engine). Some very talented people in Bologna dealt with its complexity, so I don’t have to.
Companies that go through the hard work of deploying enterprise IT and shutting off some of their pre-existing legacy systems are reducing their complexity, not increasing it. They might be mortgaging their future in other ways with this IT architecture choice (although I doubt it, which is a topic for another blog post) but they’re not setting themselves up to be overwhelmed by complexity somewhere down the road. Instead, they’re reducing the number of modules in their system.
August 14, 2007
Are Enterprise Systems Part of the Problem or the Solution?
On August 8, the website of MIT Sloan Management Review (one of my favorite journals) published an article by Cynthia Rettig called "The Trouble With Enterprise Software." Rettig writes that
"Software promises evolutions, revolutions and even transformations in how companies do business. The triumphant vision many buy into is that enterprise software in large organizations is fully integrated and intelligently controls infinitely complex business processes while remaining flexible enough to adapt to changing business needs."
then spends most of the article advancing the argument that most companies are nowhere close to that vision, and that the new technologies they’ve been buying in recent years have been making things worse instead of better. The heart of her argument is that most companies IT infrastructures have become both too complex and too rigid to deliver on the vision, and that installing new systems serves primarily to increase complexity and hence worsen the problem.
Rettig makes some insightful points about the perils of software complexity, and I share her deep skepticism about Service-Oriented Architecture (SOA) as a solution to the challenge of high and increasing complexity.
Rettig, however, also paints commercial enterprise systems such as those sold by SAP and Oracle as part of the problem. She writes that "The concept of a single monolithic system failed for many companies… In the end, ERP systems became just another subset of the legacy systems they were supposed to replace… Try as they might to measure the productivity gains of ERP implementations or IT in general, researchers have yet to arrive at any coherent or consistent conclusions."
It is certainly true that enterprise systems have failed in many companies, and it’s also true that, as she points out, many others have not been able to shut off legacy systems to the extent they expected after ERP went live. But it is simply not the case that researchers have been unable to draw any coherent conclusions about these technologies.
"ERP doesn’t help" is a testable hypothesis, and some colleagues of mine have tested it. NYU’s Sinan Aral, Georgia Tech’s D.J. Wu, and my friend and coauthor Erik Brynjolfsson at MIT recently published a wonderful paper, titled "Which Came First, IT or Productivity? Virtuous Cycle of Investment and Use in Enterprise Systems." I’ll quote from the paper’s abstract:
"While it is now well established that IT intensive firms are more productive, a critical question remains: Does IT cause productivity or are productive firms simply willing to spend more on IT? We address this question by examining the productivity and performance effects of enterprise systems investments in a uniquely detailed and comprehensive data set of 623 large, public U.S firms. The data represent all U.S. customers of a large vendor during 1998–2005 and include the vendor’s three main enterprise system suites: Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM). A particular benefit of our data is that they distinguish the purchase of enterprise systems from their installation and use. Since enterprise systems often take years to implement, firm performance at the time of purchase often differs markedly from performance after the systems go live. Specifically, in our ERP data, we find that purchase events are uncorrelated with performance while go-live events are positively correlated. This indicates that the use of ERP systems actually causes performance gains rather than strong performance driving the purchase of ERP. In contrast, for SCM and CRM, we find that performance is correlated with both purchase and go-live events. Because SCM and CRM are installed after ERP, these results imply that firms that experience performance gains from ERP go on to purchase SCM and CRM… These results provide an explanation of simultaneity in IT value research that fits with rational economic decision-making: Firms that successfully implement IT, react by investing in more IT..."
The paper is well worth downloading and reading in its entirety; it’s a great example of rigorously conducted research aimed at an important open question (the same kind of research Erik and I, along with Michael Sorell and Feng Zhu, have been striving for as we test the hypothesis that "IT Doesn’t Matter" in competitive battles. Our results suggest strongly that it does—see these papers and these blog posts).
The sober and understated language of this paper’s abstract contains a vital insight for people who question the overall value delivered to companies by their information technologies: if IT were not delivering value, rational decision makers would not keep investing in it. Rettig’s argument falls into a long line of pessimistic writing about the value of corporate IT. Much of this writing takes the implicit, and at times explicit, view that the executives who make technology decisions are dupes, perennially falling for a "triumphant vision" of software. These executives are presumably swayed by vendors’ sales pitches and the consistent message from IT’s ‘helper industries’—an ecosystem of analysts, journalists, consultants, and (yes) academics—that everything’s different now, so investments must be made.
There is plenty of anecdotal evidence to support this pessimistic view, and it even seems that US companies have collectively lost their senses for a bit when presented with a particularly appealing IT-based vision (remember how B2B exchanges like Chemdex were going to change everything?). But to believe that corporate executives have been sold technological snake oil for the entire history of the IT industry is to believe that these executives are essentially idiots. This belief underlies a lot of funny Dilbert cartoons and episodes of The Office, but it is at odds with any realistic and logical view of corporate decision making.
Managers would not be spending more than 20% of their capital budgets each year on IT if they didn’t perceive substantial benefits. And their companies wouldn’t stay in business very long if this perception was hugely inaccurate. The only way I can see for the IT pessimists to be right is if the delusion about IT’s benefits is both persistent and virtually universal. And I don’t buy that, if for no other reason than because we don’t have any other examples of such a delusion -- of massive and longstanding economy-wide misallocation of resources within a capitalist system (Some might point out that our continued reliance on fossil fuels is just such a misallocation, but the companies and individuals burning these fuels are not in the short term feeling the effects of global warming; they’re not, in other words, bearing the full costs of their actions. This is clearly not the case with IT.).
I agree that it’s important not to naively accept anyone’s triumphant vision of corporate IT. But it’s also important not to make claims in the other direction that are too sweeping. Perhaps most fundamentally, it’s critical at some point to stop floating hypotheses about IT’s impact (or lack thereof), and to start testing them. We have enough history and enough data to permit more excellent studies like the one conducted by Aral, Brynjolffson, and Wu. Designing and executing research that is both rigorous and relevant is difficult, at times dismayingly so, but as these three show it’s well worth the effort.
August 03, 2007
And Now for Something Completely Different
Wikipedia’s article on Enterprise 2.0 has been heavily edited by the administrator Jreferee since July 26. I just read through the most recent version, which consists largely of a history of the term. According to this version,
"Enterprise 2.0 is a term used at least since 2001 to describe a second-generation approach to online knowledge within a business (enterprise)...
The term Enterprise 2.0 was coined in 2001 by Participate Systems, Inc. CEO Alan Warms[5] and grew through its use in business and in industry conferences...
By April 2001, both the Web 2.0 source term "Internet 2.0" and the term "Enterprise 2.0" were being used in the sense of second-generation online, collaborative general and business communities, respectively. Today, the term Enterprise 2.0 largely derives popular meaning from its use in business and the collaborative technologies conference of the same name...
Five months after BrainGem sought to trademark "Internet 2.0," Participate Systems, Inc. of Chicago Illinois used "Participant Enterprise 2.0" in April 2001 connection with software used to create online collaborative communities.[5] With $33 million in venture capital backing and a series of series of co-authored whitepapers, Participate Systems CEO Alan Warms sought to trademark "Participant Enterprise 2.0" in November 2001 in connection with software to build and manage online business communities using employee, customer and partner knowledge.[24][26] However, the U.S. Trademark Office saw Enterprise 2.0 as being descriptive rather than distinctive and Participate Systems disclaimed "Enterprise 2.0" from being part of its Participant Enterprise 2.0 trademark in February 2002.[26] Nonetheless, Warms pioneering efforts in this area were rewarded by being selected as one of the World Economic Forum‘s 100 Technology Pioneers of 2001.[27]...
Although Alan Warms coined the term "Enterprise 2.0" in 2001, it took until 2004 before enough business implemented collaboration technologies to support a conference.[28] The "Inaugural 2004 Collaboration in Financial Services Conference" was the first-of-its kind conference to address collaboration technologies in institutional financial services.[28] This September 2004 conference focused on creating an industry roadmap to help financial enterprises address the then-emerging collaboration space.[28]...
MediaLive International held Enterprise 2.0 2006 in June 2006 in Boston, Massachusetts and Enterprise 2.0 2007 in Boston, Massachusetts in June 2007.[31]."
My spring 2006 Sloan Management Review article "Enterprise 2.0: The Dawn of Emergent Collaboration" is cited in a footnote, for which I suppose I should be grateful.
Intrigued by this version of events, I did a quick Google search of the joint terms "Alan Warms" and "Enterprise 2.0." It returned three results. The first two were different views of the current Wikipedia article. The third was evidently an amalgam of two blog posts; one about Enterprise 2.0, and one in which Warms posts a comment.
As I was writing my Sloan Management Article, I did some online searching to see if the term "Enterprise 2.0" was already used to describe anything like the use of Web 2.0 tools and approaches behind the firewall. As I wrote here:
"I thought I coined the phrase ‘Enterprise 2.0’ but tag searching on Technorati shows me that the UK Internet consultant Stuart Eccles posted about ‘Enterprise2.0’ on February 20, 2006. My first post on Enterprise 2.0 appeared on March 24, 2006."
Eccles is not mentioned in the current version of the Wikipedia article.
Does anyone have a good explanation for why this particular Wikipedia article seems to remain in great flux instead of converging, despite the pretty clear record? Because I honestly don’t.
One bit of encouraging news as we head into the weekend: the phrase "Enterprise 2.0" is now popular enough on the Internet to appear in Google Trends!
August 02, 2007
Grandes Entreprises 2.0
In Paris, les grands projets have usually been buildings, from Louis XIV’s Invalides to Napoleon’s Arc de Triomphe to Mitterand’s Louvre Pyramid and Grande Arche in La Defense. These edifices are all closely associated with French central government and its leader and exemplify the country’s tendency toward dirigisme, which can be summed up as the state telling its citizenry how, when, and where something important is going to play out. Most of these projects arouse strong emotions when they’re announced. Some, like I.M Pei’s Louvre Pyramid, come to be widely admired. Others, like the arch at La Defense, seem to have sturdy careers ahead of them as critical and popular laughingstocks. As a group, les grands projects have immensely influenced the character of the city that so many of us love.
I just came back from Paris, where I think I saw the city in the early stages of being changed by a very different sort of project. On July 15 Paris started the Vélib program, a networked bicycle rental service modeled on successful programs already in place in Lyon, Stockholm, Barcelona, and a few other cities. Vélib at present consists of about 10,600 bikes kept at 750 stations around the city (both of these numbers are expected to double by the end of this year), a self-service rental kiosk at each station, and an information system that ties the whole system together (this Newsday article describes the system nicely).
Anyone with a credit card can walk up to the kiosk, buy a daily, weekly, or annual membership, then immediately rent a bike. ‘Rent’ is not exactly the right word because if the bike is returned within a half hour, to any station, there’s no charge. Keeping the bike longer than that costs 1 Euro for the first additional half hour, then substantially more after that. This pricing is designed to encourage short rentals (for one-way trips, for example), and it appears to work. In Lyon, the average bike is used more than 7 times a day. If you don’t return the bike within 24 hours your credit card is charged the replacement cost.
I’ll vouch that there appear to be bikes and stations everywhere, and that people are taking advantage of them. My untrained eye and opportunistic observations indicated that both Parisians and tourists are using Vélib at all hours, and in many different neighborhoods. It appears poised to become a big success.
I bring up Vélib because it illustrates two points I try to stress when talking about IT’s impact. First, information technology lets you do new things. Vélib was simply not possible prior to the era of modern computing. Its pricing structure leads to the desired behaviors, and the pricing scheme depends on being able to track how long bikes were used no matter where they were picked up or dropped off. This immediately implies a citywide network that’s not expensive to run. Thanks to the Internet, we have one of these. The era of densely internetworked computing we’ve been in since the middle of the 1990s isn’t just the continuation or acceleration of previous trends in IT. It’s a departure from them, and a time of greatly expanded possibilities.
The second point I underscore is some of these possibilities, and the ones I find most intriguing at present, involve using IT to get out of the business of dirigisme. Vélib required a good bit of up front work to get the initial conditions right, but once it’s up and running it’s egalitarian, centerless (to its users), and actually quite difficult to direct over the short term -- its managers couldn’t, for example, order Parisians to stop taking bikes to the eastern part of the city for an afternoon. It looks, in other words, a lot like many of the Enterprise 2.0 efforts I’ve been studying and writing about for a while, which is probably why I was so taken with it.
Innovators of all kinds, from government officials to entrepreneurs to enlightened managers, are increasingly going to look around at the computing resources available to them at very low prices and say, essentially, "Hey, wait a minute— we actually have all the ingredients we need to address this need / seize this opportunity / solve this problem. This will actually work!" And in many cases the solutions they put in place will not attempt to dictate how their constituencies will interact. Their solutions will instead provide an environment in which users can act and interact fluidly as circumstances demand. I imagine that this new, explicitly non-dirigiste style of interaction will over time alter the character of many institutions.
