Will Information Technology Really Turn Organizations Upside Down This Time?


Do not read too much into a possible relationship between the development of information technology and the incidence of “upside-down” management. That’s the overwhelming message from responses to the column raising questions about the possible connection between the two.

First, as Greg Waldrip points out, let’s get things in perspective. These are only means to carry out a strategy after goals are determined, all in a supportive management environment. Dennis Crane concurs, adding that “Information technology should only turn businesses upside down when they’ve already determined that there’s some truly fundamental reason to do so.”

Some question whether the “upside down” organization is an idea whose time has come. David Koltermann warns, “The potential revolution to turn management upside down is overstated… In the marketplace of ideas, inhabited by academics and consultants …personal advancement may be better served by being provocative than by being right.”

Others question the importance of the linkage between information technology and the shape of the organization. Allen Roberts suggests that the latter is just one of many potential impacts of information technology, implying that it may not be the most important.

For any of this to have a high degree of relevance, however, depends on other factors in the view of respondents. As John Ladge states, “I know first-hand that it can work, but it really depends on the culture of the organization.” Waldrup puts it more strongly: “Providing more information without creating an atmosphere that allows people to use their judgement will only cause failure.”

Still others pointed out that information technology is most often used in the context of “medium risk, medium gain scenarios like credit card processing, market forecasting, etc.” in Shankar Avsb’s words. He suggests that information technology will play a major part in remolding organizations for only a few, but that “possibly, these would be organizations poised to become the new market leaders.”

Even if many things have to happen before fundamental organizational changes occur, it still leaves us with questions: Is this kind of change worth pursuing? If so, what changes in information technology and policies of disseminating its products will be required? If the process is a long one, is it even practical to begin it in organizations with “continuity-challenged” leadership? Is there any real purpose served by academics in continuing to spread the word about upside down management and preparing potential managers for its possible emergence? What do you think?


Periodically, somebody comes up with the idea of turning the organization upside down, with the customer on top. Those serving customers in the frontline come next, and top management winds up at the bottom. It’s eye-catching and too often grossly out of step with what really happens when organizations employ the concept.

Now we learn that the Army is experimenting with satellite-driven information technology that enables a tank commander to have a full view of the battlefield, including the positions of both friendly and enemy tanks. Armed with this knowledge, the best tank operators can make better, more timely decisions than their superiors—but only under certain conditions. First, frontline tank commanders have to have the intelligence and judgement to sort through a heavy load of information that is changing in real time (not unlike the best video game players). Second, the technology has to operate dependably, a problem in combat. And third and most significant, superiors have to be willing to delegate such decisions to frontliners. As a result, there have been as many spectacular failures as successes in military tests of the technology. In fact, the implementation of information technology generally has been quite disappointing to the “fighting bottom line” in the modern Army to date.

But let’s suppose that all three of these barriers eventually are overcome. What will it mean for the traditional hierarchical military chain of command? Or for business?

For years, W. Edwards Deming, the father of modern continuous quality improvement, had trouble convincing U.S. (as opposed to Japanese) auto manufacturers to implement the keys to improved quality. They include, among other things, improved information, training to improve quality, and delegating authority to frontline production workers to shut down a billion-dollar production line in the interests of quality improvement. More recently, Gary Hamel, in his book Leading the Revolution, has talked of putting such information to use in encouraging people at all levels of an organization to come up with new business ideas and advance them within the company.

If there is a common theme here, it is that information technologies, combined with proper selection, training, and the willingness of managers to rethink their jobs, have the potential for literally turning organizations upside down, changing forever what we have thought of as the role of management, if not leadership. But will it happen, given what the Army has found?

What about the unwillingness of frontliners to employ their information in the service of the organization as a whole, even if their individual performance may be penalized? What about the potential for substituting technology for judgement on the frontline? What about the fact that frontline employees are paid according to their rank rather than their potential impact on performance? And what about management’s ability to change? Is information technology fueling a false hope or are we really entering a new era of upside-down management? What do you think?

Don’t Get Buried in Customer Data—Use It

With the advent of customer relationship management (CRM) in the late 1990s, companies came to believe that by using technology to tailor their offerings to individual consumers’ needs, customer loyalty—and company profits—would skyrocket.

But in today’s crowded marketplace, customer loyalty is more elusive than ever. A recent McKinsey study reveals that the annual churn in the wireless industry increased from 17 percent in 1995 to 32 percent in 2000. This trend holds true even in industries less susceptible to turnover. In core retail categories such as department stores, for instance, the top players’ market share declined more than 10 percent.

Not surprisingly, many executives’ faith in CRM has waned. In a 2001 Bain & Co. survey of the 25 most popular management tools, CRM was ranked near the bottom. In a follow-up study, 20 percent of the 451 senior executives polled said that their companies’ CRM initiatives had failed to deliver profitable growth and had damaged long-term customer relationships.

Tempting as it may be to point the finger at your CRM technology, that won’t help you reverse these worrisome trends. It’s quite possible that the problem isn’t with your CRM technology at all but with the way you are collecting and using your data, experts say. Although getting your CRM program in order is an essential component of achieving customer loyalty, there’s much more that you need to do.

“Marketers need a good, thoughtful architecture to base their decisions on,” says Harvard Business School marketing professor Gerald Zaltman. A more strategic approach to data mining can provide the foundation for that decision-making architecture. Below, advice on how to use information about the individual customer and the average customer in concert, and how to probe beneath customer preferences and behaviors to uncover the attitudes that provide a more solid understanding of customer loyalty.


One-to-one marketing, a term coined by Don Peppers and Martha Rogers in their influential 1993 book, The One to One Future (Currency/Doubleday), focuses on share of customer: Using the insights about what makes your most loyal customers different to maximize the value of those relationships. By the end of the decade, many marketers had come to believe that the combination of mass customization techniques, sophisticated database software, and the Internet would enable them to actually deliver on the promise of customized offerings to each individual customer.

But that hasn’t happened to the extent it should have, says Cleveland-based consultant James H. Gilmore, coauthor with B. Joseph Pine II of The Experience Economy (Harvard Business School Press, 1999), because “most practitioners have taken the concept of one-to-one marketing and bastardized it into CRM. They’re using CRM tools to design better processes for a nonexistent ‘average’ customer, instead of customizing for individual customers.”

He cites the example of a major hotel chain that asks guests to complete a multiple-question satisfaction survey via their room’s TV set during their stay. When one guest answered “extremely dissatisfied” to all the questions, he was not treated any differently when he checked out. Why? Because his answers went straight to a central repository where they were aggregated with other customers’ responses and used to measure overall market—not customer—satisfaction. A more effective approach would be to feed his answers directly to someone at the front desk who could respond immediately to his needs and create a better experience for him.

“A company’s goal should be to learn more about what each customer needs so that it can close the customer sacrifice gap, which is the difference between what individual customers settle for and what each wants exactly,” says Gilmore. Steve Cunningham, director of customer listening at Cisco, agrees that it’s vital to listen and respond to individual customer needs and preferences. But he believes you must also pay attention to the aggregate data—customer averages based on individual surveys.


“Let’s say that based on the customer survey averages, you realize that your hotel is taking too long to check guests out,” he says. “So you launch initiatives designed to reduce checkout time and prime your personnel to be sensitive to that issue. Despite these efforts, something goes wrong, and one morning the front desk manager sees a long line of guests queued up to check out. Because the survey averages have helped sensitize him to the importance of this issue, he knows he has to do something—for example, pull staff members off other jobs so they can help check people out, or offer free coffee to everyone who’s standing in line.”

Familiarity with the aggregated survey data, in other words, helps the manager tailor his response to individual customers.

Cisco relies on three layers of customer data to inform its efforts to improve customer satisfaction: The overall satisfaction survey that customers fill out annually; interviews with targeted customer segments, follow-on surveys, and sessions with corporate advisory boards that seek to identify an initiative that will address a problem hinted at in the overall relationship survey (“this is the ‘digging and understanding’ layer,” says Cunningham); and, at the most granular level, records of each individual transaction that the company’s technical support group has with a customer.

To illustrate how Cisco uses these three layers, Cunningham cites a hypothetical example. Assume that for a given year, the average score for product reliability has slipped a bit. Drilling down to the bottom two layers of data, Cisco discovers a problem with the power supply for its routers. It launches an initiative to solve this problem and identifies the number of spare power supply parts it sends out weekly as the measure it will use to track the progress. The transactional measure—the number of spare parts shipped weekly—may start to come down fairly soon after the initiative has been launched, but it may take a while before the change shows up on the annual relationship survey.

“You need both the aggregate and the transactional information,” says Cunningham. “The survey data tells you about the overall health of your relationships with customers; it tells you which way the wind is blowing. It also helps prevent you from running after individual problems that may not be significant in the aggregate. The transactional data gives the detail behind the relationship.” It helps you pinpoint specific issues that need to be addressed to boost overall customer satisfaction.


To boost customer satisfaction and, ultimately, customer loyalty, you have to do more than listen simultaneously to customer averages and to individual customers. You also have to look for what lies beneath the externals of customers’ behavior (what they buy, how they buy, and when they buy). “Without capturing what is going on inside customers’ minds and hearts, and integrating that information with the factual external experiences, the picture is incomplete,” says Doug Grisaffe, chief research methodologist for Indianapolis-based Walker Information.

“CRM tools enable you to collect a lot of rich data about a customer’s frequency and time of purchase, the size of her orders, and what she thinks of your company,” says Harvard’s Zaltman. That’s necessary but not sufficient data: It doesn’t tell you anything about “why customers do what they do, think what they think, and why they like or don’t like your products. Getting that level of insight requires more intensive interactions with customers than CRM tools permit.” It requires that you develop a “poetic insight into customers—a deep knowledge that enables you to intuit their answers to questions you haven’t even asked them.”

In one-on-one interviews with customers, Zaltman uses a process he describes as metaphor elicitation to get at the beliefs, emotions, intentions, and often unconscious attitudes that people have about a product or brand. As he explains in his recent book, How Customers Think: Essential Insights into the Mind of the Market (Harvard Business School Press, 2003), the information gleaned from these interviews as well as from surveys and observation is used to create a consensus map—an illustration of the particular bundles of constructs that customers have developed based on their experience and emotional connection with a product or brand.


A consensus map that Zaltman developed for General Motors reveals the richness of the metaphor elicitation approach. As expected, customers associated GM products with quality and competitive price. But there was more: Customers also linked GM with patriotic feelings. By buying GM cars, they saw themselves as not simply helping Americans keep their jobs, but as fulfilling a larger obligation that they felt toward their country.

Once you understand these often surprising bundles of associations, you can reinforce and sometimes alter them with the messages your company sends to consumers.

Based on the consensus map Zaltman produced, GM’s domestic managers redesigned the customer experience at dealerships and added subtle cues in their advertising to make the idea of patriotism more salient. For GM’s overseas managers, the task was more difficult but no less valuable for that. Realizing that GM products also produced patriotic associations among foreign purchasers, the overseas managers “found cues that underscored patriotic associations with the local country without pressing the American button,” says Zaltman.

Reams of customer data are no guarantee that you’ll be able to increase your most profitable customers’ loyalty—you have to be sure that you’re collecting the most relevant information. Listening for the attitudes that inform customers’ behaviors and preferences, Zaltman maintains, gives you “a more solid basis on which to craft and implement strategies that will improve customer loyalty.”

Why IT Does Matter

Harvard Business Review editor-at-large, Nicholas G. Carr, ignited a firestorm in the opinion piece “Why IT Doesn’t Matter” published in the May 2003 issue of HBR.

Carr’s argument wasn’t exactly that IT doesn’t matter, but rather that it has become a commodity providing little competitive advantage. As a result, he said, companies should rethink how much they pay for IT given this reduced return on investment.

HBR received a large number of positive and critical responses to Carr’s piece including a letter we offer here from two professors at Harvard Business School. —Ed.

In no other area is it more important to have a sense of what you don’t know than it is in IT management. The most dangerous advice to CEOs has come from people who either had no idea of what they did not know, or from those who pretended to know what they didn’t. Couple not knowing that you don’t know with fuzzy logic, and you have the makings of Nicholas Carr’s article.

Carr’s examples of railroads and electric power played out over eighty years, (not forty, as he suggests), turning society, business organizations, and lifestyles inside out. The deeper societal impacts came during the second forty years, as society’s insights on how to use the technology changed. It is worth noting that although these technologies mutated significantly (for trains, it meant moving from fifteen miles an hour to eighty miles an hour), the mutation was on a totally different and much smaller scale than IT’s.

The cost performance of IT technologies over the first forty years changed by roughly 107, and for the foreseeable future will continue to evolve at the same rate. That is in sharp contrast to a train, which after eighty years moved six times faster than it had in the earlier period. This is impressive, but not nearly as dramatic as a computer produced in 2000, which runs 10 million times faster than a 1960s’ computer.

Carr’s graph on information technology stands as a subject lesson for Darrell Huff’s well-known book How to Lie with Statistics. Carr’s chart would look very different if he had tracked the number of MIPS or CPU cycles on the network from 1990 to 2002. Even using a log scale on the vertical axis would be barely enough to tilt a vertical straight line enough to create something resembling the curves of the other two schematics in Carr’s article. With this explosion of cost effectiveness has come the ability to do things truly differently. American Hospital Supply’s distribution software and American Airlines’ SABRE reservation system are examples of victories in past technologies. The firms were the first in their industries to see technology’s transforming potential, they had the courage to invest in its performance, and they used it to gain a significant competitive edge. It is naive to assume that other sharply discontinuous technologies will not offer similar transformation opportunities in the future.

In our view, the most important thing that the CEO and senior management should understand about IT is its associated economics. Driven by Moore’s Law, those evolving economics have enabled every industry’s transaction costs to decrease continually, resulting in new economics for the firm and creating the feasibility of products and services not possible in the past. The economics of financial transactions have continually dropped from dollars to cents. New entrants have joined many industries and have focused on taking strategic advantage of IT’s associated economics. Company boundaries have become permeable, organic, and global in scope through IT networks and the Internet.


As the pace of doing business increases, the CEO and senior management team must be aware of how IT can change rules and assumptions about competition. The economics of conducting business will likewise continue to improve—providing opportunities for businesses to expand the customer value proposition by providing more intangible information-based services. For example, the automobile value proposition continues to expand with technology that continuously senses road conditions and applies the appropriate wheel traction and suspension system pressures.

CEO and senior management must understand that historical constraints of every kind continue to be knocked off IT because it is a “universal information-processing machine.” Before e-mail and the Internet, the cost of communications was seen as limiting IT’s wider use. Packet switching was invented as a way to digitize voice, data, and video in a matter that enabled digital computers (and its associated economics) to communicate, and the cost of communication sharply and suddenly dropped. Similar situations have transpired with the advent of digitized photography, use of radio frequencies for various handheld IT appliances, and the development of such products as elevators that call in to the service center or to a computer that automatically dispatches collective software or people when a part or system is about to fail. Often, only the senior management team’s imagination limits new IT-based opportunities.

Our research suggests the following:

New technologies will continue to give companies the chance to differentiate themselves by service, product feature, and cost structure for some time to come. The first mover takes a risk and gains a temporary advantage (longer if there are follow-on possibilities). The fast follower is up against less risk but also has to recover lost ground. Charles Schwab versus Merrill Lynch and Walgreens versus CVS are examples of this playing out over the past decade. Our advice to the CEO is to look at IT use through several different lenses. One lens should be focused on improving cost savings and efficiencies. Another should be focused on the incremental improvement of organizational structure, products, and services. Still another should be focused on the creation of strategic advantage through extending competitive scope, partnerships (customers and other parties), the changing of the rules of competition, and the provision of new IT-based services to extend the customer value proposition.

Unless nurtured and evolved, IT-enabled competitive applications, like many competitive advantages, don’t endure. Even historic strategic systems like American Hospital Supply’s (after a decade of financial malnourishment) may wind up turning into a strategic liability. Others, however, like American Airlines’ SABRE have shown extraordinary robustness and have permitted the survival of otherwise doomed organizations.

Evaluating these opportunities as well as thinking through their implications and timing, is vitally important, nonboring work. The new technologies will allow new things to be transformed in nonlinear ways. Radio-frequency identification devices for grocery stores, smart cards, and automated ordering systems for hospital physicians are all examples of new process targets that technologies will soon address. In the more distant future we will see the improved creation of drugs and treatments through the ability to rapidly and more deeply analyze huge databases. Understanding the potential and then deciding when the time is right to seize these transformative applications will be neither routine nor boring for the CEO or CIO.

Grid computing, standardization of components, and open systems, far from stifling differentiation, provide a stable platform to build on and offer new ways of differentiating, either by cost, structure, product, or service. Just as literacy stimulated innovation, so do open systems and grids. Outsourcing the commodity infrastructure is a great way to control costs, build competence, and free up resources, which can be used to combine data bits in creative ways to add value. Relatively bulletproof operational reliability will be a key part of the price of success. Back-office or server farms, help desks, and network operations will be outsourced to specialists to attain this reliability (at rock-bottom costs). Packages like SAP further help remove commodity maintenance activities and allow firms to better analyze customer information and provide service at the sharp end. The package of skills needed inside an organization is changing very fast for competition in the information age.

The jobs of the CTO and CIO are and will be of unparalleled importance in the decades ahead. Max Hopper of American Airlines and Paul Strassmann of Kraft and NASA are not the last of a dying breed of dinosaurs, but prototypes of the leadership skills needed for survival.

If you take 1955 (with the IBM 701) as the start date and use eighty years as a technology cycle, 2035 may not be far off the mark for playing much of this out. Even then, the special recombinant nature of this technology makes us uncomfortable calling an end date. We wish Carr were right, because everyone’s golf handicap could then improve. Unfortunately, the evidence is all to the contrary.

How IT Shapes Top-Down and Bottom-Up Decision Making

What determines whether decisions happen on the bottom, middle, or top rung of the corporate ladder? New research from professor Raffaella Sadun from Harvard Business School finds that the answer often lies in the technology that a company deploys. Key concepts include:

  • Enterprise Resource Planning software is a decentralizing technology: It provides information that enables lower-level managers to make more decisions without consulting their superiors.
  • By the same token, Computer-Assisted Design and Computer-Assisted Manufacturing software creates a situation in which the plant worker needs less access to superiors in order to make a decision.
  • The better the data network, the easier it is for workers to lean on superiors and rely on them to make decisions. It’s also easier for executives to micromanage and keep all the decisions in the corporate office.
  • Trust is also a key factor in determining whether decisions are centralized at headquarters or decentralized at the local level. Research finds that the average level of trust of a multinational’s home country tends to influence the level of decentralization in that company.

What determines whether decisions happen on the bottom, middle, or top rung of the corporate ladder? New research offers a surprising conclusion: The answer often lies in the technology that a company uses.

Information-based systems, such as Enterprise Resource Planning (ERP) software, will push decision-making toward the bottom of the corporate ladder. Communication systems, such as e-mail and instant messaging applications, will push the decision-making process toward the top.

And that means developing an IT strategy isn’t all about deploying the best technology, says Raffaella Sadun, an assistant professor of strategy at Harvard Business School.


“The bottom line is that whoever is in charge of the acquisitions and the IT strategy, they obviously cannot just think about the technology side, they also have to think about the organizational side,” she says. “Traditionally, technology is thought of as a tool that enables empowerment, but that’s not always the case.”

Sadun discusses the issue in “The Distinct Effects of Information Technology and Communication Technology on Firm Organization,” a paper she cowrote with Nicholas Bloom of Stanford University and Luis Garicano and John Van Reenen of the Centre for Economic Performance, London School of Economics.

“Technologies that make the acquisition of information easier at the lower level of the hierarchy are associated with a decentralization of the decision-making process,” Sadun says. “On the other hand, we have the communication technologies, which actually do exactly the opposite.”


Companies, however, often fail to consider the disparate roles of their software systems, let alone their effects on organizational behavior. Rather, they lump “information technology” into one amorphous idea—the “IT” department—which encompasses all the technology in the organization.

“Technology tends to be dumped into a single category,” Sadun says. “The reality is that IT is a huge, heterogeneous set of technologies.”

Similarly, when examining issues such as organization and productivity, industry and academic studies historically tend to treat information and communication technologies as “an aggregate homogeneous capital stock,” according to the paper. To that end, Sadun and her fellow researchers set out to show how—and why—managers need to consider the very different organizational effects of communication and information technologies.

“This difference matters not just for firms’ organization and productivity, but also in the labor market, as information access and communication technology changes can be expected to affect the wage distribution in opposite directions,” their paper states.

The researchers looked at non-production decisions such as capital investment, new hires, and new product plans. Such decisions are either centralized near the top of the corporate ladder or decentralized and delegated to the top of a particular business unit. And the decision makers often depend on ERP software, which facilitates the dissemination of information throughout a large company, enabling detailed coordination among various operating units.

Next, they looked at production decisions, which involve figuring out the tasks necessary to meet the goals and deciding how to pace them. These decisions are generally the bailiwick of either a factory floor worker or a supervisor. For those cases, the researchers studied the role of Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) software in decision-making.

In both instances, the researchers hypothesized that the information software would lead to decentralized decision-making. Because the software eases access to the information necessary to make important choices, both the ERP and CAD systems would increase the likelihood that plant managers and production workers would make decisions and act on them without having to consult an executive at headquarters.

On the other hand, the team hypothesized that a rise in leased lines and corporate intranets would lead to a rise in centralized decision-making at the top of the corporate ladder.


In the past, communication often depended on faxes, overnight delivery services, “snail mail,” or site visits. Even with phone calls, it was difficult for anyone at headquarters to make educated decisions and communicate them to branch offices. In those cases, it was natural to cede control of daily operations to a local manager.

With today’s networking technologies, it’s easier for top executives to keep a constant flow of communication with branch offices. However, the network may actually deter innovation. When technology makes it easier to communicate, erstwhile independent workers may find themselves pestering their bosses with e-mailed questions throughout the day. Micromanaging executives find themselves making all the decisions and constantly sending mandates down the corporate ladder.

“Whenever there is a reduction in the cost of transmitting information, it’s easier for the person down in the hierarchy to communicate with the CEO,” Sadun says. “And the CEO can monitor constantly what this person is doing and just give orders, rather than rely on the judgment of those below.”

The research team evaluated data from some 1,000 manufacturing firms in eight countries, including detailed technology rollout histories and surveys that gauged the relative decisional autonomy of plant managers and floor workers. (In gauging the factors that determine whether a firm adopts any given technology, the researchers considered geographic variables that might affect the cost of acquiring the technology—the firm’s distance from the Walldorf, Germany, headquarters of ERP market leader SAP, for instance, and the fact that telecom industry regulations vary from country to country, which means networking prices vary, too.)

The findings were consistently parallel with the hypotheses: An increase in the penetration of ERP systems led to a substantial increase in plant manager autonomy. A CAD/CAM deployment raised the likelihood of floor worker autonomy. But communication technologies served to lower autonomy, meaning more decisions happened at the corporate level.

“I was reassured and surprised at the same time that these results were holding across countries and industries,” Sadun says.


That said, Sadun notes that technology is hardly the only factor that determines whether a firm allows decision-making both up and down the corporate ladder. Another major factor lies in cultural differences across and within countries. In a separate study, Sadun found that otherwise similar companies showed huge differences in decision-making tactics, according to their geographical location. In the paper “The Organization of Firms across Countries,” coauthored with Bloom and Van Reenen, she documents that firms located in areas with high levels of trust tend to be systematically more decentralized than those in areas with low levels of trust.

Sweden and Portugal, for example, seem to be on opposite ends of the trust spectrum. “There’s huge cross country heterogeneity in the way even apparently similar firms decide how to allocate decision rights within the firm,” Sadun says. “Take Swedish manufacturing companies, for example. You see that they are completely decentralized, and the middle manager is basically a mini-CEO with loads of decision-making power. And then you take a firm that produces exactly the same good, but instead of in Sweden, it’s in Portugal. And there, the middle manager doesn’t decide anything and is completely dependent on the authority of the CEO.

“In our research,” she continues, “we argue that different levels of trust are a key determinant of these differences. If a CEO can trust his senior managers, he will be more willing to decentralize decision-making. For example, there might be a lower concern about the fact that managers will use their power to pursue their personal interests instead of those of the firm.”