The executive’s guide to better listening

Strong listening skills can make a critical difference in the performance of senior executives, but few are able to cultivate them. Here’s how.

A senior executive of a large consumer goods company had spotted a bold partnership opportunity in an important developing market and wanted to pull the trigger quickly to stay ahead of competitors. In meetings on the topic with the leadership team, the CEO noted that this trusted colleague was animated, adamant, and very persuasive about the move’s game-changing potential for the company. The facts behind the deal were solid.
The CEO also observed something troubling, however: his colleague wasn’t listening. During conversations about the pros and cons of the deal and its strategic rationale, for example, the senior executive wasn’t open to avenues of conversation that challenged the move or entertained other possibilities. What’s more, the tenor of these conversations appeared to make some colleagues uncomfortable. The senior executive’s poor listening skills were short-circuiting what should have been a healthy strategic debate.
Eventually, the CEO was able to use a combination of diplomacy, tactful private conversation, and the bureaucratic rigor of the company’s strategic-planning processes to convince the executive of the need to listen more closely to his peers and engage with them more productively about the proposal. The resulting conversations determined that the original deal was sound but that a much better one was available—a partnership in the same country. The new partnership presented slightly less risk to the company than the original deal but had an upside potential exceeding it by a factor of ten.
The situation facing the CEO will be familiar to many senior executives. Listening is the front end of decision making. It’s the surest, most efficient route to informing the judgments we need to make, yet many of us have heard, at one point or other in our careers, that we could be better listeners. Indeed, many executives take listening skills for granted and focus instead on learning how to articulate and present their own views more effectively.
This approach is misguided. Good listening—the active and disciplined activity of probing and challenging the information garnered from others to improve its quality and quantity—is the key to building a base of knowledge that generates fresh insights and ideas. Put more strongly, good listening, in my experience, can often mean the difference between success and failure in business ventures (and hence between a longer career and a shorter one). Listening is a valuable skill that most executives spend little time cultivating. (For more about one executive’s desire to be a better listener, see “Why I’m a listener: Amgen CEO Kevin Sharer,” forthcoming on mckinseyquarterly.com.)
The many great listeners I’ve encountered throughout my career as a surgeon, a corporate executive, and a business consultant have exhibited three kinds of behavior I’ll highlight in this article. By recognizing—and practicing—them, you can begin improving your own listening skills and even those of your organization.

1. Show respect

One of the best listeners I have ever observed was the chief operating officer (COO) of a large medical institution. He once told me that he couldn’t run an operation as complex as a hospital without seeking input from people at all levels of the staff—from the chief of surgery to the custodial crew. Part of what made him so effective, and so appealing as a manager, was that he let everyone around him know he believed each of them had something unique to contribute. The respect he showed them was reciprocated, and it helped fuel an environment where good ideas routinely came from throughout the institution.
The COO recognized something that many executives miss: our conversation partners often have the know-how to develop good solutions, and part of being a good listener is simply helping them to draw out critical information and put it in a new light. To harness the power of those ideas, senior executives must fight the urge to “help” more junior colleagues by providing immediate solutions. Leaders should also respect a colleague’s potential to provide insights in areas far afield from his or her job description.
Here’s an example: I recall a meeting between a group of engineers and the chief marketing officer (CMO) at a large industrial company. She was concerned about a new product introduction that had fallen flat. The engineers were puzzled as well; the company was traditionally dominated by engineers with strong product-development skills, and this group had them too. As the CMO and I discussed the technological aspects of the product with the engineers, I was struck by their passion and genuine excitement about the new device, which did appear to be unique. Although we had to stop them several times to get explanations for various technical terms, they soon conveyed the reasons for their attitude—the product seemed to be not only more efficient than comparable ones on the market but also easier to install, use, and maintain.
After a few minutes, the CMO, who had been listening intently, prompted the engineers with a respectful leading question: “But we haven’t sold as many as you thought we would in the first three months, right?”
“Well, actually, we haven’t sold any!” the team leader said. “We think this product is a game changer, but it hasn’t been selling. And we’re not sure why.”
After a pause to make sure the engineer was finished, the CMO said, “Well, you guys sure seem certain that this is a great product. And you’ve convinced the two of us pretty well. It seems that customers should be tripping over themselves to place orders. So assuming it’s not the product’s quality that’s off, what else are your customers telling you about the product?”
“We haven’t spoken to any customers,” the engineer replied.
The CMO blanched. As the conversation continued, we learned that the product had been developed under close wraps and that the engineers had assumed its virtues would speak for themselves. “But maybe not,” said the team leader. “Maybe we ought to push it a little more. I guess its good traits aren’t so obvious if you don’t know a lot about it.”
That engineer had hit the nail on the head. The device was fine. Customers were wary about switching to something untested, and they hadn’t been convinced by the specs the company’s sales team touted. As soon as the engineers began phoning their counterparts in the customers’ organizations (an idea suggested by the engineers themselves), the company started receiving orders.
Had the CMO looked at the problem by herself, she might have suspected a shortcoming with the product. But after some good listening and targeted follow-up questions, she helped to extract a much better solution from the engineers themselves. She didn’t cut the conversation short by lecturing them on good marketing techniques or belittling their approach; she listened and asked pointed questions in a respectful manner. The product ultimately ended up being a game changer for the company.
Being respectful, it’s important to note, didn’t mean that the CMO avoided asking tough questions—good listeners routinely ask them to uncover the information they need to help make better decisions. The goal is ensuring the free and open flow of information and ideas.
I was amused when John McLaughlin, the former deputy director of the US Central Intelligence Agency, told me that when he had to make tough decisions he often ended his conversations with colleagues by asking, “Is there anything left that you haven’t told me . . . because I don’t want you to leave this room and go down the hall to your buddy’s office and tell him that I just didn’t get it.” With that question, McLaughlin communicated the expectation that his colleagues should be prepared; he demanded that everything come out on the table; and he signaled genuine respect for what his colleagues had to say.

2. Keep quiet

I have developed my own variation on the 80/20 rule as it relates to listening. My guideline is that a conversation partner should be speaking 80 percent of the time, while I speak only 20 percent of the time.¹ Moreover, I seek to make my speaking time count by spending as much of it as possible posing questions rather than trying to have my own say.
 

	Toggle Sidebar
	A field guide to identifying bad listeners

Back to top

That’s easier said than done, of course—most executives are naturally inclined to speak their minds. Still, you can’t really listen if you’re too busy talking. Besides, we’ve all spent time with bad listeners who treat conversations as opportunities to broadcast their own status or ideas, or who spend more time formulating their next response than listening to their conversation partners. Indeed, bad listening habits such as these are ubiquitous (see sidebar, “A field guide to identifying bad listeners”).
I should know because I’ve fallen into these traps myself. One experience in particular made me realize how counterproductive it is to focus on your own ideas during a conversation. It was early in my career as a consultant and I was meeting with an important client whom I was eager to impress. My client was a no-nonsense, granite block of a man from the American heartland, and he scrutinized me over the top of his reading glasses before laying out the problem: “The budget for next year just doesn’t work, and we are asking our employees to make some tough changes.”
All I heard was his concern about the budget. Without missing a beat, I responded to my client and his number-two man, who was seated alongside him: “There are several ways to address your cost problem.” I immediately began reeling off what I thought were excellent suggestions for streamlining his business. My speech gained momentum as I barreled ahead with my ideas. The executive listened silently—and attentively, or so it seemed. Yet he didn’t even move, except to cock his head from time to time. When he reached for a pen, I kept up my oration but watched with some annoyance as he wrote on a small notepad, tore off the sheet of paper, and handed it to his associate. A smile flitted almost imperceptibly across that man’s face as he read the note.
I was already becoming a bit peeved that the executive had displayed no reaction to my ideas, but this little note, passed as though between two schoolboys, was too much. I stopped talking and asked what was written on the paper.
The executive nodded to his associate. “Show him.”
The man leaned across the table and handed me the note. My client had written, “What the hell is this guy talking about?”
Fortunately, I was able to see the humor in the situation and to recognize that I had been a fool. My ego had gotten in the way of listening. Had I paid closer attention and probed more deeply, I would have learned that the executive’s real concern was finding ways to keep his staff motivated while his company was shrinking. I had failed to listen and compounded the error by failing to keep quiet. Luckily for me, I was able to get a second meeting with him.
It’s not easy to stifle your impulse to speak, but with patience and practice you can learn to control the urge and improve the quality and effectiveness of your conversations by weighing in at the right time. Some people can intuitively grasp where to draw the line between input and interruption, but the rest of us have to work at it. John McLaughlin advises managers to think consciously about when to interrupt and to be as neutral and emotionless as possible when listening, always delaying the rebuttal and withholding the interruption. Still, he acknowledges that interrupting with a question can be necessary from time to time to speed up or redirect the conversation. He advises managers not to be in a hurry, though—if a matter gets to your level, he says, it is probably worth spending some of your time on it.
As you improve your ability to stay quiet, you’ll probably begin to use silence more effectively. The CEO of an industrial company, for example, used thoughtful moments of silence during a meeting with his sales team as an invitation for its junior members to speak up and talk through details of a new incentive program that the team’s leader was proposing. As the junior teammates filled in these moments with new information, the ensuing rich discussion helped the group (including the team leader) to realize that the program needed significant retooling. The CEO’s silence encouraged a more meritocratic—and ultimately superior—solution.
When we remain silent, we also improve the odds that we’ll spot nonverbal cues we might have missed otherwise. The medical institution’s COO, who was such a respectful listener, had a particular knack for this. I remember watching him in a conversation with a nurse manager, who was normally articulate but on this occasion kept doubling back and repeating herself. The COO realized from these cues that something unusual was going on. During a pause, he surprised her by asking gently, “You don’t quite agree with me on this one, do you? Why is that?” She sighed in relief and explained what had actually been bugging her.

3. Challenge assumptions

Good listeners seek to understand—and challenge—the assumptions that lie below the surface of every conversation. This point was driven home to me the summer before I went to college, when I had the opportunity to hang out with my best friend at a baseball park. He had landed a job in the clubhouse of the Rochester Red Wings, then a minor-league farm team for the Baltimore Orioles. That meant I got to observe Red Wings manager Earl Weaver, who soon thereafter was promoted to Baltimore, where he enjoyed legendary success, including 15 consecutive winning seasons, four American League championships, and one World Series victory. Weaver was considered fiery and cantankerous, but also a baseball genius. To my 18-year-old eyes, he was nothing short of terrifying—the meanest and most profane man I’d ever met.
Weaver wasn’t really a listener; he seemed more of a screamer in a perpetual state of rage. When a young player made an error, Weaver would take him aside and demand an explanation. “Why did you throw to second base when the runner was on his way to third?” He’d wait to hear the player’s reasoning for the sole purpose of savagely tearing it apart, usually in the foulest language imaginable and at the top of his lungs.
But now and then, Weaver would be brought up short; he’d hear something in the player’s explanation that made him stop and reconsider. “I’ve seen that guy take a big wide turn several times but then come back to the bag. I thought maybe if I got the ball to second really fast, we could catch him.” Weaver knew that the move the player described was the wrong one. But as ornery as he was, he apparently could absorb new information that temporarily upended his assumptions. And, in doing so, the vociferous Weaver became a listener.
Weaver called his autobiography It’s What You Learn After You Know It All That Counts. That Zen-like philosophy may clash with the Weaver people thought they knew. But the title stuck with me because it perfectly states one of the cornerstones of good listening: to get what we need from our conversations, we must be prepared to challenge long-held and cherished assumptions.
Many executives struggle as listeners because they never think to relax their assumptions and open themselves to the possibilities that can be drawn from conversations with others. As we’ve seen, entering conversations with respect for your discussion partner boosts the odds of productive dialogue. But many executives will have to undergo a deeper mind-set shift—toward an embrace of ambiguity and a quest to uncover “what we both need to get from this interaction so that we can come out smarter.” Too many good executives, even exceptional ones who are highly respectful of their colleagues, inadvertently act as if they know it all, or at least what’s most important, and subsequently remain closed to anything that undermines their beliefs.
Such tendencies are, of course, deeply rooted in human behavior.² So it takes real effort for executives to become better listeners by forcing themselves to lay bare their assumptions for scrutiny and to shake up their thinking with an eye to reevaluating what they know, don’t know, and—an important point—can’t know.
Arne Duncan, the US Secretary of Education, is one such listener. He believes that his listening improves when he has strong, tough people around him who will challenge his thinking and question his reasoning. If he’s in a meeting, he makes sure that everyone speaks, and he doesn’t accept silence or complacency from anyone. Arne explained to me that as a leader, he tries to make it clear to his colleagues that they are not trying to reach a common viewpoint. The goal is common action, not common thinking, and he expects the people on his team to stand up to him whenever they disagree with his ideas.
Duncan uses a technique I find helpful in certain situations: he will deliberately alter a single fact or assumption to see how that changes his team’s approach to a problem. This technique can help senior executives of all stripes step back and refresh their thinking. In a planning session, for example, you might ask, “We’re assuming a 10 percent attrition rate in our customer base. What if that rate was 20 percent? How would our strategy change? What if it was 50 percent?” Once it’s understood that the discussion has moved into the realm of the hypothetical, where people can challenge any underlying assumptions without risk, the creative juices really begin to flow.
This technique proved useful during discussions with executives at a company that was planning to ramp up its M&A activity. The company had a lot of cash on hand and no shortage of opportunities to spend it, but its M&A capabilities appeared to have gone rusty (it had not done any deals in quite some time). During a meeting with the M&A team and the head of business development, I asked, “Listen, I know this is going to be a little bit shocking to the system, but let’s entertain the idea that your team doesn’t exist. What kind of M&A function would we build for this corporation now? What would be the skills and the strategy?”
The question shook up the team a bit initially. You have to be respectful of the emotions you can trigger with this kind of speculation. Nonetheless, the experiment started a discussion that ultimately produced notable results. They included the addition of talented new team members who could provide additional skills that the group would need as it went on to complete a set of multibillion-dollar deals over the ensuing year.
Throughout my career, I’ve observed that good listeners tend to make better decisions, based on better-informed judgments, than ordinary or poor listeners do—and hence tend to be better leaders. By showing respect to our conversation partners, remaining quiet so they can speak, and actively opening ourselves up to facts that undermine our beliefs, we can all better cultivate this valuable skill.

 

The second economy

In 1850, a decade before the Civil War, the United States’ economy was small—it wasn’t much bigger than Italy’s. Forty years later, it was the largest economy in the world. What happened in-between was the railroads. They linked the east of the country to the west, and the interior to both. They gave access to the east’s industrial goods; they made possible economies of scale; they stimulated steel and manufacturing—and the economy was never the same.
Deep changes like this are not unusual. Every so often—every 60 years or so—a body of technology comes along and over several decades, quietly, almost unnoticeably, transforms the economy: it brings new social classes to the fore and creates a different world for business. Can such a transformation—deep and slow and silent—be happening today?
We could look for one in the genetic technologies, or in nanotech, but their time hasn’t fully come. But I want to argue that something deep is going on with information technology, something that goes well beyond the use of computers, social media, and commerce on the Internet. Business processes that once took place among human beings are now being executed electronically. They are taking place in an unseen domain that is strictly digital. On the surface, this shift doesn’t seem particularly consequential—it’s almost something we take for granted. But I believe it is causing a revolution no less important and dramatic than that of the railroads. It is quietly creating a second economy, a digital one.
Let me begin with two examples. Twenty years ago, if you went into an airport you would walk up to a counter and present paper tickets to a human being. That person would register you on a computer, notify the flight you’d arrived, and check your luggage in. All this was done by humans. Today, you walk into an airport and look for a machine. You put in a frequent-flier card or credit card, and it takes just three or four seconds to get back a boarding pass, receipt, and luggage tag. What interests me is what happens in those three or four seconds. The moment the card goes in, you are starting a huge conversation conducted entirely among machines. Once your name is recognized, computers are checking your flight status with the airlines, your past travel history, your name with the TSA¹ (and possibly also with the National Security Agency). They are checking your seat choice, your frequent-flier status, and your access to lounges. This unseen, underground conversation is happening among multiple servers talking to other servers, talking to satellites that are talking to computers (possibly in London, where you’re going), and checking with passport control, with foreign immigration, with ongoing connecting flights. And to make sure the aircraft’s weight distribution is fine, the machines are also starting to adjust the passenger count and seating according to whether the fuselage is loaded more heavily at the front or back.
These large and fairly complicated conversations that you’ve triggered occur entirely among things remotely talking to other things: servers, switches, routers, and other Internet and telecommunications devices, updating and shuttling information back and forth. All of this occurs in the few seconds it takes to get your boarding pass back. And even after that happens, if you could see these conversations as flashing lights, they’d still be flashing all over the country for some time, perhaps talking to the flight controllers—starting to say that the flight’s getting ready for departure and to prepare for that.
Now consider a second example, from supply chain management. Twenty years ago, if you were shipping freight through Rotterdam into the center of Europe, people with clipboards would be registering arrival, checking manifests, filling out paperwork, and telephoning forward destinations to let other people know. Now such shipments go through an RFID² portal where they are scanned, digitally captured, and automatically dispatched. The RFID portal is in conversation digitally with the originating shipper, other depots, other suppliers, and destinations along the route, all keeping track, keeping control, and reconfiguring routing if necessary to optimize things along the way. What used to be done by humans is now executed as a series of conversations among remotely located servers.
In both these examples, and all across economies in the developed world, processes in the physical economy are being entered into the digital economy, where they are “speaking to” other processes in the digital economy, in a constant conversation among multiple servers and multiple semi-intelligent nodes that are updating things, querying things, checking things off, readjusting things, and eventually connecting back with processes and humans in the physical economy.
So we can say that another economy—a second economy—of all of these digitized business processes conversing, executing, and triggering further actions is silently forming alongside the physical economy.

Aspen root systems

If I were to look for adjectives to describe this second economy, I’d say it is vast, silent, connected, unseen, and autonomous (meaning that human beings may design it but are not directly involved in running it). It is remotely executing and global, always on, and endlessly configurable. It is concurrent—a great computer expression—which means that everything happens in parallel. It is self-configuring, meaning it constantly reconfigures itself on the fly, and increasingly it is also self-organizing, self-architecting, and self-healing.
These last descriptors sound biological—and they are. In fact, I’m beginning to think of this second economy, which is under the surface of the physical economy, as a huge interconnected root system, very much like the root system for aspen trees. For every acre of aspen trees above the ground, there’s about ten miles of roots underneath, all interconnected with one another, “communicating” with each other.

The metaphor isn’t perfect: this emerging second-economy root system is more complicated than any aspen system, since it’s also making new connections and new configurations on the fly. But the aspen metaphor is useful for capturing the reality that the observable physical world of aspen trees hides an unseen underground root system just as large or even larger. How large is the unseen second economy? By a rough back-of-the-envelope calculation (see sidebar, “How fast is the second economy growing?”), in about two decades the digital economy will reach the same size as the physical economy. It’s as if there will be another American economy anchored off San Francisco (or, more in keeping with my metaphor, slipped in underneath the original economy) and growing all the while.
Now this second, digital economy isn’t producing anything tangible. It’s not making my bed in a hotel, or bringing me orange juice in the morning. But it is running an awful lot of the economy. It’s helping architects design buildings, it’s tracking sales and inventory, getting goods from here to there, executing trades and banking operations, controlling manufacturing equipment, making design calculations, billing clients, navigating aircraft, helping diagnose patients, and guiding laparoscopic surgeries. Such operations grow slowly and take time to form. In any deep transformation, industries do not so much adopt the new body of technology as encounter it, and as they do so they create new ways to profit from its possibilities.
The deep transformation I am describing is happening not just in the United States but in all advanced economies, especially in Europe and Japan. And its revolutionary scale can only be grasped if we go beyond my aspen metaphor to another analogy.

A neural system for the economy

Recall that in the digital conversations I was describing, something that occurs in the physical economy is sensed by the second economy—which then gives back an appropriate response. A truck passes its load through an RFID sensor or you check in at the airport, a lot of recomputation takes place, and appropriate physical actions are triggered.
There’s a parallel in this with how biologists think of intelligence. I’m not talking about human intelligence or anything that would qualify as conscious intelligence. Biologists tell us that an organism is intelligent if it senses something, changes its internal state, and reacts appropriately. If you put an E. coli bacterium into an uneven concentration of glucose, it does the appropriate thing by swimming toward where the glucose is more concentrated. Biologists would call this intelligent behavior. The bacterium senses something, “computes” something (although we may not know exactly how), and returns an appropriate response.
No brain need be involved. A primitive jellyfish doesn’t have a central nervous system or brain. What it has is a kind of neural layer or nerve net that lets it sense and react appropriately. I’m arguing that all these aspen roots—this vast global digital network that is sensing, “computing,” and reacting appropriately—is starting to constitute a neural layer for the economy. The second economy constitutes a neural layer for the physical economy. Just what sort of change is this qualitatively?
Think of it this way. With the coming of the Industrial Revolution—roughly from the 1760s, when Watt’s steam engine appeared, through around 1850 and beyond—the economy developed a muscular system in the form of machine power. Now it is developing a neural system. This may sound grandiose, but actually I think the metaphor is valid. Around 1990, computers started seriously to talk to each other, and all these connections started to happen. The individual machines—servers—are like neurons, and the axons and synapses are the communication pathways and linkages that enable them to be in conversation with each other and to take appropriate action.
Is this the biggest change since the Industrial Revolution? Well, without sticking my neck out too much, I believe so. In fact, I think it may well be the biggest change ever in the economy. It is a deep qualitative change that is bringing intelligent, automatic response to the economy. There’s no upper limit to this, no place where it has to end. Now, I’m not interested in science fiction, or predicting the singularity, or talking about cyborgs. None of that interests me. What I am saying is that it would be easy to underestimate the degree to which this is going to make a difference.
I think that for the rest of this century, barring wars and pestilence, a lot of the story will be the building out of this second economy, an unseen underground economy that basically is giving us intelligent reactions to what we do above the ground. For example, if I’m driving in Los Angeles in 15 years’ time, likely it’ll be a driverless car in a flow of traffic where my car’s in a conversation with the cars around it that are in conversation with general traffic and with my car. The second economy is creating for us—slowly, quietly, and steadily—a different world.

A downside

Of course, as with most changes, there is a downside. I am concerned that there is an adverse impact on jobs. Productivity increasing, say, at 2.4 percent in a given year means either that the same number of people can produce 2.4 percent more output or that we can get the same output with 2.4 percent fewer people. Both of these are happening. We are getting more output for each person in the economy, but overall output, nationally, requires fewer people to produce it. Nowadays, fewer people are required behind the desk of an airline. Much of the work is still physical—someone still has to take your luggage and put it on the belt—but much has vanished into the digital world of sensing, digital communication, and intelligent response.
Physical jobs are disappearing into the second economy, and I believe this effect is dwarfing the much more publicized effect of jobs disappearing to places like India and China.
There are parallels with what has happened before. In the early 20th century, farm jobs became mechanized and there was less need for farm labor, and some decades later manufacturing jobs became mechanized and there was less need for factory labor. Now business processes—many in the service sector—are becoming “mechanized” and fewer people are needed, and this is exerting systematic downward pressure on jobs. We don’t have paralegals in the numbers we used to. Or draftsmen, telephone operators, typists, or bookkeeping people. A lot of that work is now done digitally. We do have police and teachers and doctors; where there’s a need for human judgment and human interaction, we still have that. But the primary cause of all of the downsizing we’ve had since the mid-1990s is that a lot of human jobs are disappearing into the second economy. Not to reappear.
Seeing things this way, it’s not surprising we are still working our way out of the bad 2008–09 recession with a great deal of joblessness.
There’s a larger lesson to be drawn from this. The second economy will certainly be the engine of growth and the provider of prosperity for the rest of this century and beyond, but it may not provide jobs, so there may be prosperity without full access for many. This suggests to me that the main challenge of the economy is shifting from producing prosperity to distributing prosperity. The second economy will produce wealth no matter what we do; distributing that wealth has become the main problem. For centuries, wealth has traditionally been apportioned in the West through jobs, and jobs have always been forthcoming. When farm jobs disappeared, we still had manufacturing jobs, and when these disappeared we migrated to service jobs. With this digital transformation, this last repository of jobs is shrinking—fewer of us in the future may have white-collar business process jobs—and we face a problem.
The system will adjust of course, though I can’t yet say exactly how. Perhaps some new part of the economy will come forward and generate a whole new set of jobs. Perhaps we will have short workweeks and long vacations so there will be more jobs to go around. Perhaps we will have to subsidize job creation. Perhaps the very idea of a job and of being productive will change over the next two or three decades. The problem is by no means insoluble. The good news is that if we do solve it we may at last have the freedom to invest our energies in creative acts.

Economic possibilities for our grandchildren

In 1930, Keynes wrote a famous essay, “Economic possibilities for our grandchildren.” Reading it now, in the era of those grandchildren, I am surprised just how accurate it is. Keynes predicts that “the standard of life in progressive countries one hundred years hence will be between four and eight times as high as it is to-day.” He rightly warns of “technological unemployment,” but dares to surmise that “the economic problem [of producing enough goods] may be solved.” If we had asked him and his contemporaries how all this might come about, they might have imagined lots of factories with lots of machines, possibly even with robots, with the workers in these factories gradually being replaced by machines and by individual robots.
That is not quite how things have developed. We do have sophisticated machines, but in the place of personal automation (robots) we have a collective automation. Underneath the physical economy, with its physical people and physical tasks, lies a second economy that is automatic and neurally intelligent, with no upper limit to its buildout. The prosperity we enjoy and the difficulties with jobs would not have surprised Keynes, but the means of achieving that prosperity would have.
This second economy that is silently forming—vast, interconnected, and extraordinarily productive—is creating for us a new economic world. How we will fare in this world, how we will adapt to it, how we will profit from it and share its benefits, is very much up to us.

https://www.mckinseyquarterly.com/Strategy/Growth/The_second_economy_2853

What China’s five-year plan means for business

  McKinsey analyzed the potential impact on 33 industries. Two dimensions stood out: the plan’s effect on profit pools and on the competitive landscape.

China’s recently announced 12th five-year plan aims to transform the world’s second-largest economy from an investment-driven dynamo into a global powerhouse with a steadier and more stable trajectory. The plan affects domestic and foreign companies in all industries. To help senior managers decode and understand its provisions, we analyzed the potential impact on 33 industries. Two dimensions stood out: the effect on their profit pools and competitive landscapes. (For a detailed look at this analysis, see the interactive exhibit, “The economic impact of China’s 12th five-year plan.”)
The plan’s likely impact on profit pools was categorized as either favorable (for example, sensitive to an increase in domestic demand or specifically targeted for special treatment), unfavorable (subject to restrictive policies), or neutral. For the effect on the competitive landscape, we looked at the intensity of regulation.
Five groups emerged from the analysis. New strategic industries are singled out for global leadership. Domestic-consumption engines drive consumer growth in the homeland. Restructurers are under government mandate to change. Reinventors are mature industries that must innovate and reinvest to close the gap with global leaders. Social utilities are large state-owned enterprises managing significant components of the national infrastructure.

New strategic industries

The plan characterizes a handful of industries as emerging battlegrounds where countries will be competing for technological leadership during the next wave of development. These industries, including new energy sources and biotechnology, are distinguished by their high profit growth potential and moderate state oversight. In these areas, the government has dedicated itself to incubating national and global champions by helping them gain leading technologies and expanding their commercial capabilities.
China’s government aspires to increase the share of GDP these industries contribute from about 1 percent today to 8 percent by 2015 and to 15 percent by 2020, presenting a huge market potential for domestic and foreign businesses alike. Although significant uncertainties remain in such young markets, companies that compete in them should focus on building core competitiveness in technological and commercial capabilities, as well as on gaining recognition as local innovators. Domestic players should concentrate on acquiring leading technologies and building relationships with local governments. Foreign companies must bring advanced technology and be seen as trusted partners for local innovation.
Competition, its texture defined largely by regulatory decisions, will be fierce. The central government could further shape the competitive landscape by specifically identifying technology paths, industry standards, market entry criteria, and partnership models. Given the fragmented markets that developed around early favorites such as wind and solar power, the government will become increasingly selective in its policies, looking for avenues to expedite consolidation and to identify national champions quickly.

Domestic-consumption engines

The industries that will benefit most from the government’s efforts to retool the Chinese economy and to boost domestic consumption are consumer-facing ones such as airlines, fast-moving consumer goods, food, pharmaceuticals, shipping, and tourism. These domestic-consumption engines, which have a favorable environment for profit growth and reasonably free markets, also benefit from the government’s attention to social harmony and “green” development.
To capture the greatest growth opportunities, companies must increase their market penetration and offer tailored products for core customer segments. They should also closely monitor the development of specific consumption-enhancing government policies, such as encouraging urbanization, optimizing the investment structure, strengthening the social safety net, increasing household income, and developing the retail infrastructure. Opportunities in newly urbanized areas and the countryside should be explored vigorously. In addition, the government’s push to assure higher product safety and quality and to encourage environmentally friendly consumption habits will present further openings for quick movers.
While government efforts to increase household incomes and wages will help spur private spending, they also present companies with the challenge of keeping expenses at bay amid rising labor costs. The plan targets a 13 percent increase in minimum wages each year, along with a more modest annual increase in household income (about 7 percent). Construction, consumer electronics, logistics, retailing, and other industries will feel the pinch. Further, costs will probably increase as a result of new policies for pricing energy, raw materials, and water; tighter environmental regulations; and enhanced consumer protection. Intense concern over inflation means that the government is unlikely to favor moves fully passing these cost increases on to consumers.
The government is also shaping the competitive environment in other ways. Industries such as education, financial services, health care, and logistics are being deregulated, further opening the market to foreign companies. Increased attention to food and drug safety and to quality gives companies with a solid reputation for high standards an opportunity.

Restructurers

Real estate and commercial banking, two industries fundamental to the country’s economic and social well-being, face significant structural risks and follow shaky business models. The government has given these structural reformists a clear mandate to clean up their act.
China’s real-estate industry has enjoyed rapid growth during the past five years, contributing strongly to overall GDP and local-government budgets. But the overheated market has raised fears of speculative bubbles and social instability linked to rising housing costs. In the plan, the government sets a target of 36 million affordable living units and promises strict oversight of housing loans and the residential market.
For fundamental reform, however, the industry must create a profitable and sustainable business model—for instance, in real estate for retailing or affordable-housing projects. Meantime, the central government must find new income sources for municipalities that have used the proceeds from lucrative property sales to finance local-industry development projects, as well as establish alternative investment channels.
Commercial banks also expanded rapidly in the wake of the surging real-estate market, primarily by lending to developers, and face their own obligation to reform. To maintain profit growth rates, banks must identify the plan’s new revenue streams—for example, in support for small- and medium-sized businesses, digital banking, and wealth management—and build capabilities in managing risk and talent and in other value-added roles. They must also become adept at interpreting and balancing contradictory government policies, such as the drive to control inflation while at the same time financing small- and medium-sized enterprises and stimulating private consumption.
After much-needed reform, Chinese banks would be free to offer more sophisticated and diversified services, and the broader industry may enter a new era of competition. These developments will require know-how, talent, well-structured processes, and management. At present, Chinese banks suffer from a capability gap, opening opportunities for leading foreign institutions. Of course, the size of the opportunity depends on the direction and depth of reform. Foreign banks might also be able to give regulators assistance in defining that direction.

Reinventors

Many mature manufacturers lag behind their global competitors in technology and suffer from overcapacity, low efficiency, and high pollution. These companies account for most of the reinventors. The government aims to transform their industries through innovation and upgrades.
This group generally benefits from the drive to stimulate domestic demand. The plan reserves the best opportunities for producers that use advanced technology, add greater value, boast higher energy efficiency, and offer more protection for the environment. Fiscal and tax policies, as well capacity and export regulations, collectively encourage these players to improve their businesses and consolidate. The plan encourages local innovation to develop domestic brand equity and intellectual property.
China’s mature industries are particularly vulnerable to the new focus on green development: that policy will probably drive up costs related to environmental protection, energy conservation, reduced pollution, and even raw materials, in addition to pressures linked to rising labor costs. Energy efficiency and carbon dioxide–emission targets, for example, will add to the demands on industries such as nonferrous metals, power, and steel. Success will rest on a company’s ability to maintain a healthy margin while accumulating green equity.
For this group, the government is taking a direct approach to shaping industry landscapes. In a drive to create national champions, it has set clear guidelines encouraging accelerated industry consolidation, especially in automotive, industrial machinery (such as construction equipment), nonferrous metals, and steel. Prominent domestic players can use the plan’s support for M&A to acquire high-quality assets, strengthen leadership positions, and build credentials as national champions. Foreign companies can also take advantage of this drive by completing strategic mergers and acquisitions and becoming more competitive in the local market. Domestic and foreign players alike must watch developments on policies to push innovation, which will probably further define the country’s aspirations in technology, product portfolios, and partnership models.

Social utilities

State-owned enterprises that manage national infrastructure networks—including the power grid, railways, and telecommunications—will grow steadily thanks to urbanization and strong support from the government. With no real competition, the main responsibility of these social utilities will be to use their scale and procurement power to deliver successful planned domestic projects at global standards of quality and cost.
Improved infrastructure is critical to the country’s urban-development program, and the central government has laid out clear plans for expanding the penetration and capacity of China’s rail, power, and communications networks. These expansion plans will enjoy significant government investment, ensuring that state-owned enterprises and their suppliers (in industries such as construction, equipment, and steel) have secure revenue streams.
However, China’s natural monopolies must work to contain rising construction and operational costs stemming from new energy and environmental regulations and from rising wages. State-owned enterprises will also feel pressure to innovate with and improve their business models for the sake of profitability and high quality. Because these companies have enormous procurement power, they can expect to receive help in their efforts from global technology leaders and, ultimately, to set worldwide industry standards. Foreign companies are quite interested in selling to the national infrastructure networks, which clearly offer big opportunities as their expansion continues.
China’s ambitious 12th five-year plan builds on decades of unprecedented economic growth. It seeks to transform the economy from an investment-led powerhouse focused exclusively on GDP growth to a sustainable model that balances growth with social harmony, and innovation with environmental protection. Whether or not the full slate of aspirations can be achieved, the direction in which China’s leaders hope to move the country is clear. Domestic and foreign companies need to understand the plan’s implications for their industries so they can identify the opportunities and risks ahead.
https://www.mckinseyquarterly.com/Economic_Studies/Productivity_Performance/What_Chinas_five-year_plan_means_for_business_2832

How the best labs manage talent

Of the $1.2 trillion spent globally each year on R&D across corporations and academia, 40 percent—much the largest share—pays for people. Our team interviewed and surveyed world-class researchers in academia and a range of industries to understand what drives research productivity in labs. We found that the best ones, regardless of specialty or industry, share a pattern of behavior across six key practices: talent, strategies and roles, collaboration, problem solving, portfolio and project management, and alignment with the needs of the business and the market. To understand what characterizes the best labs, we then studied 4,500 researchers in 260 laboratories in academia and research-based industries, including automotive, basic materials, high tech, and pharmaceuticals.
Our conclusion was that talent management, more than anything else, is what the best R&D operations consistently get right (Exhibit 1). While all the practices we looked at are clearly correlated with high performance in labs, talent is the most important driver of their productivity and shows the highest level of correlation. Interestingly, talent management is also the practice that has the highest opportunity for improvement. That makes this a tremendously powerful lever to improve R&D productivity, regardless of its current level (Exhibit 2). Strategy is the second most correlated practice, but here the respondents saw the least opportunity for improvement.

Top-quartile academic labs are five times more productive than bottom-quartile ones. Similar differences exist among industrial labs. Yet many research institutions don’t understand how well they are doing, because the people who work there wildly overestimate their own performance: in our survey, 12 percent of them suppose that their own lab is in the top 1 percent, and 70 percent think it is at least in the top 25 percent. Most researchers don’t know how productive great labs are or how they become great. In fact, most labs can assess how well they do only by basic output measures. A halo effect further distorts perceptions: researchers who think that their lab performs well assume that its talent-management practices are also strong.

What top labs get right

Talent management isn’t simply about hiring the best; not everyone can. It’s about managing talent appropriately through selection, recruitment, development, and rewards. Just about any lab can do so, yet many don’t. We looked at each of these areas, and while all are correlated with performance, some matter more than others (Exhibit 3).

Recruiting for potential

Managing talent appropriately starts with recruiting appropriate talent. The head of a top-ranking academic lab told us that “the most important intrinsic we look for is scientific curiosity.” Great labs such as this one evaluate the potential of researchers by appraising their basic intellectual ability, general problem-solving skills, and enthusiasm. They also test a candidate’s cultural fit, important to support teamwork and collaboration, which in turn drive productivity. Candidates may, for example, spend an afternoon devising answers to a specific question or working in the lab with the team. This approach helps labs assess a candidate’s social compatibility as well. Before making a decision on recruitment, the best labs also solicit the views of team members about each candidate.
Average labs typically look mostly for specific technical proficiencies—say, the ability to use a piece of equipment or to run certain tests. Specific technical capabilities are sometimes required, but even when hiring for them, top labs want people who can adapt to new roles as the research evolves. Those new roles, especially in industrial settings, should include project management and business experience—something many labs overlook.

Nurturing people

Talent management doesn’t stop once researchers are hired. As an R&D executive told us, “Many of our research leaders don’t have the capabilities they need to succeed in senior positions in the organization. We are trying to give people more experience across the business to round out their future leadership potential.” A top lab, unlike a weaker one, actively supports its researchers’ development throughout their careers. Senior team members, for example, spend significant time in solo sessions with new researchers and mentor them continually. Year-end reviews appraise these activities. The most productive labs also require all researchers to develop annual personal-development plans.

Recognizing success

Many researchers crave recognition, and labs have a number of ways to provide it: public acknowledgement in meetings, awards, opportunities to present at conferences or to attend symposiums. Even more recognition comes from giving high performers active opportunities, such as larger research budgets, leadership of bigger efforts, and part-time professorships. These incentives, our work shows, often inspire researchers more effectively than money does. They cut turnover significantly and almost always cost far less than financial compensation.
Although public recognition is important, it isn’t everything: we found that researchers also want financial rewards for performance. In the best labs, such incentives are linked transparently to achievements or outcomes—great research, publication in a leading journal, the attainment of a milestone, or successful patent applications. One lab gives small cash bonuses to researchers chosen by peers for exceptional helpfulness. Another offers stock options for killing projects early, to avoid wasting money on futile or low-value efforts. Many academic labs, however, must rely more on nonfinancial motivators.
Not everyone succeeds in the laboratory. Obviously, failure should have consequences, but often it doesn’t: in one research unit, the weakest performers were moved to another lab rather than counseled to leave. The best labs don’t tolerate poor performance for long. If foundering researchers don’t improve, they are asked to depart, which carries the added advantage of importing fresh talent and ideas.

Building diversity

Another driver of high performance is a diverse team of people with different backgrounds, specialties, and forms of expertise to help solve problems. The most important aspect of building such a team is encouraging turnover, not only by weeding out underperformers, but also by encouraging rotation to adjacent research areas, other geographies, different roles, or, for an industry lab, to the business side of the company. To help researchers better understand the needs of business and to create a greater appetite for career opportunities outside R&D, one commercial lab organizes regular presentations by former group members who have rotated into business positions.

Room for improvement

Of the six critical practices that influence a lab’s productivity, the researchers we surveyed told us that talent is the one most in need of improvement. Even the best labs can raise their game in this area, and their research productivity can improve significantly even if executives are happy with its current level.
Given the importance of research for many (if not most) companies, these are clearly matters for the C-suite, not just research managers. Top executives should start by focusing on practical, tactical measures: inquiring about the research unit’s diversity in background, experience, and capabilities; the ability of its culture to support innovation; the support researchers get for personal development; and the alignment between incentives and performance.
Once research leaders accept the value of initiatives to improve talent management, they are easy to implement and have high impact. What’s more, their incremental cost is much lower than that of many other ways of making labs more productive—for example, reorganizing them or investing in new facilities.
Six key practices drive successful research organizations. Among these six, talent management is the one most correlated with high performance yet has the highest opportunity for improvement. No lab should neglect its people.

McKinsey on Finance on iPad

https://www.mckinseyquarterly.com/Organization/Talent/How_the_best_labs_manage_talent_2811

Mckinsey on Finance on iPad

If you follow my blog, you may realize that I am a fan of Mckinsey. I used to wish to have McKinsey on my iPad/iPhone in order for me to read its material whenever I travel. Yesterday, I found it on app store. I would like to share it with you as well.

McKinsey on Finance on iPad

It is very cheap, only $0.99. It is a collection of all articles in Mckinsey on Finance, you can buy your convenience at a penny. I don't still understand how can the developer can earn a profit on this app. Developer of this app is Epsilon Mobile Pte Ltd.

The app is not so fancy, but it is fine. You can read documents with flipping, pinching and note taking. I used a number of other similar apps such as CloudReader, Goodreader, StudentPad (also Epsilon's app), iBook...but none of them have the same features.

I think the app will be more attractive if it has search, download on the go (don't let user download 10M+ app, I am reluctant to any 10M+ app) and an iPhone version.

Is your emerging-market strategy local enough?

The diversity and dynamism of China, India, and Brazil defy any one-size-fits-all approach. But by targeting city clusters within them, companies can seize growth opportunities.

Creating a powerful emerging-market strategy has moved to the top of the growth agendas of many multinational companies, and for good reason: in 15 years’ time, 57 percent of the nearly one billion households with earnings greater than $20,000¹ a year will live in the developing world. Seven emerging economies—China, India, Brazil, Mexico, Russia, Turkey, and Indonesia—are expected to contribute about 45 percent of global GDP growth in the coming decade. Emerging markets will represent an even larger share of the growth in product categories, such as automobiles, that are highly mature in developed economies.
Figures like these create a real sense of urgency among many multinationals, which recognize that they aren’t currently tapping into those growth opportunities with sufficient speed or scale. Even China, forecast to create over half of all GDP growth in those seven developing economies, remains a relatively small market for most multinational corporations—5 to 10 percent of global sales; often less in profits.
To accelerate growth in China, India, Brazil, and other large emerging markets, it isn’t enough, as many multinationals do, to develop a country-level strategy. Opportunities in these markets are also rapidly moving beyond the largest cities, often the focus of many of these companies. For sure, the top cities are important: by 2030, Mumbai’s economy, for example, is expected to be larger than Malaysia’s is today. Even so, Mumbai would in that year represent only 5 percent of India’s economy and the country’s 14 largest cities, 24 percent. China has roughly 150 cities with at least one million inhabitants. Their population and income characteristics are so different and changing so rapidly that our forecasts for their consumption of a given product category, over the next five to ten years, can range from a drop in sales to growth five times the national average.
Understanding such variability can help companies invest more shrewdly and ahead of the competition rather than following others into the fiercest battlefields. Consider Brazil’s São Paulo state, where the economy is larger than all of Argentina’s, competitive intensity is high, and retail prices are lower than elsewhere in the country. By contrast, in Brazil’s northeast—the populous but historically poorest part of the country—the economy is growing much faster, competition is lighter, and prices are higher. Multinationals short on granular insights and capabilities tended to flock to São Paulo and to miss the opportunities in the northeast. It’s only recently that they’ve started investing heavily there—trying to catch up with regional companies in what is often described as Brazil’s “new growth frontier.”
As developing economies become increasingly diverse and competitive, multinationals will need strategic approaches to understand such variance within countries and to concentrate resources on the most promising submarkets—perhaps 20, 30, or 40 different ones within a country. Of course, most leading corporations have learned to address different markets in Europe and the United States. But in the emerging world, there is a compelling case for learning the ropes much faster than most companies feel comfortable doing.
The appropriate strategic approach will depend on the characteristics of a national market (including its stage of urbanization), as well as a company’s size, position, and aspirations in it. In this article, we explore in detail a “city cluster” approach, which targets groups of relatively homogenous, fast-growing cities in China. In India, where widespread urbanization is still gaining steam, we briefly look at similar ways of gaining substantial market coverage in a cost-effective way. Finally, in Brazil we quickly describe how growth is becoming more geographically dispersed and what that means for growth strategies.

Targeting the right city clusters in China

By segmenting Chinese cities according to such factors as industry structure, demographics, scale, geographic proximity, and consumer characteristics, we identified 22 city clusters, each homogenous enough to be considered one market for strategic decision making (Exhibit 1). Prioritizing several clusters or sequencing the order in which they are targeted can help a company boost the effectiveness of its distribution networks, supply chains, sales forces, and media and marketing strategies.

For additional detail from the authors about this exhibit, see “A Better Approach to China’s Markets,” from the March 2010 issue of the Harvard Business Review.
More specifically, this approach can help companies to address opportunities in attractive smaller cities cost effectively and to spot opportunities for, among other things, expanding within rather than across clusters (Exhibit 2)—a strategy that requires a less complex supply chain and fewer partners. Companies that nonetheless want to expand across clusters may find it easier to target 50 to 100 similar cities within four or five big clusters than cities that theoretically offer the same market opportunity but are dispersed widely across the country.

Another major benefit of concentrating resources on certain clusters is the opportunity to exploit scale and network effects that stimulate faster, more profitable growth. Because most brands still have a relatively short history in China, for example, word of mouth plays a much greater role there than it does in developed economies. By focusing on attaining substantial market share in a cluster, a brand can unleash a virtuous cycle: once it reaches a tipping point there—usually at least a 10 to 15 percent market share—its reputation is quickly boosted by word of mouth from additional users, helping it to win yet more market share without necessarily spending more on marketing.
Here are four important tips to keep in mind when designing a city cluster strategy for China.

Focus on cluster size, not city size

It’s easy to be dazzled by the size of the biggest cities, but trying to cover all of them is less effective for the simple reason that they can be very far from one another. Although Chengdu, Xi’an, and Wuhan, for example, are among the ten largest cities in China, each of them is about 1,000 kilometers away from any of the others. In Shandong province, the biggest city is Jinan, which is barely in the top 20. Yet Shandong has 21 cities among China’s 150 largest, which makes the area one of the five most attractive city clusters. Its GDP is about four times bigger than that of the cluster of cities around and including Xi’an, as well as three times bigger than the cluster of cities surrounding Chengdu.

Look beyond historical growth rates

The growth of incomes and product categories is another variable that must be treated in granular fashion. Extrapolating future trends from historical patterns is particularly suspect—however detailed that history may be—because consumer spending habits change so rapidly once wealth rises.
In some clusters, many people are starting to buy their first low-end domestic cars; in others, they are upgrading to imports or even to luxury brands. We expect sales of SUVs to increase at a 20 percent compound annual growth rate nationwide in the next four years, for example, but to grow as quickly as 50 percent in several cities and, potentially, even to decline in some where penetration is already deep. Similar or even sharper variance held true in almost every service or product category we analyzed, from face moisturizers to chicken burgers to flat-screen TVs. Yogurt sales in some cities are growing eight times faster than the national average.
The Shenzhen cluster has the highest share (90 percent) of middle class households—those earning over $9,000 a year. In other clusters, such as Nanchang and Changchun–Harbin, more than half of all households are still poor. As a result, people in the Shenzhen cluster are already active consumers of many categories, and the potential for growth is fairly limited. In the poorer clusters, many categories are just emerging, as larger numbers of people pass the threshold at which more goods become affordable. From a strategic viewpoint, the richer cluster could still be a major growth market for premiumgoods but not for most mass-market ones.

Don’t be fooled by generalities

Talking about Chinese consumers and how they shop is a bit like talking about European consumers. While some generalizations may be fair, certain very strong differences, even within regions, go well beyond the already significant economic variance. Guangzhou and Shenzhen, for example, are both tier-one cities, located in the same province and just two hours apart. But Guangzhou’s people mainly speak Cantonese, are mostly locally born, and like to spend time at home with family and friends. In contrast, more than 80 percent of Shenzhen’s residents are young migrants, from all across the country, who mainly speak Mandarin and spend most of their time away from their homes. To be effective, marketers will probably have to differentiate their campaigns and emphasize different channels when reaching out to the people in these two cities. That’s why we suggest managing them in different clusters, despite their proximity.
The need to localize marketing activities also results from the limited reach of national media. China has over 3,000 TV channels, but just a few are available across the country. In some areas, only around 5 percent of consumers watch national television. Other media, such as newspapers and radio (and of course billboards), are even more local.
Very few companies can craft their entire strategy at the level of a cluster—those that do are usually its regional champions. But with differences such as the following common, some tailoring is critical:

• Every second consumer in Shandong believes that well-known brands are always of higher quality, and 30 percent are willing to stretch their budgets to pay a premium for the better product. In south Jiangsu, only a quarter of consumers preferred the well-known brands, and only 16 percent were willing to pay a premium for them.
• In the Shenzhen cluster, 38 percent of food and beverage shoppers found suggestions from in-store promoters to be a credible source of information, compared with only 12 percent in Nanjing.
• In Shanghai, 58 percent of residents shop for apparel in department stores, compared with only 27 percent of Beijing residents.

With such diversity common, even merely fine-tuning the marketing mix and channel focus by cluster can pay enormous dividends.

Allow your clusters to be flexible

Some companies may want to merge or divide clusters for strategic-management purposes. A company could, for instance, merge geographically nearby clusters, such as Guangzhou and Shenzhen or Chengdu and Chongqing, if its supply chain was well positioned to manage these proximate clusters as one. Other companies, highly driven by the media market, would find it sensible to split the Shanghai cluster into subclusters, because some markets within it are still quite different in their TV habits and other choices. By contrast, people in certain clusters, such as Chengdu or Guangzhou, watch similar TV shows across the entire cluster, so intracluster expansion allows companies to make more effective use of the media spending needed to attract consumers in the big cities.
The actual number of submarkets a company opts for will depend in practice on its needs. That number should be manageable—most likely, 20 to 40. Fewer wouldn’t be likely to produce the required degree of granularity, though a company might have logistical reasons for taking this approach. More would probably be too many to run effectively.

Cost-effective market coverage in India

Often, the challenges of accessing consumption growth cost effectively are even greater in India than in China because India is less urbanized and at an earlier stage of its economic development. Companies would need to reach up to 3,500 towns and 334,000 villages, for example, to pursue opportunities in the 10 (of 28) Indian states that by 2030 will account for 73 percent of the country’s GDP and 62 percent of the urban population.
To allocate financial and human resources smartly and make things more manageable, companies need to walk away from averages and adopt more granular approaches. Some companies will be well served by focusing on 12 clusters around India’s 14 largest cities. Those clusters will provide access to as much as 60 percent of the country’s urban GDP by 2030, when the 14 largest cities are likely to account for 24 percent of GDP.
True, India’s major clusters won’t cover as much of the economy as those in China, where they will encompass 92 percent of urban GDP by 2015. Yet a hub-and-spoke approach in India should provide similar opportunities to optimize supply chains, as well as sales and marketing networks. An established technology player formerly operated in 120 cities all over India, for example. Recently, it shifted to focusing on eight clusters with a total of 67 cities, which still gave it access to 70 percent of its potential market. One benefit: customer service costs fell from a rapidly growing 9 to 10 percent of sales to a more acceptable 5 percent (Exhibit 3).

 

Alternatively, a company might improve the economics of its Indian business by focusing on a handful of states, an approach recently adopted by a retailer that had previously been pursuing a national footprint. Another company, this one in the consumer goods sector, recently decided to pursue opportunities in eight cities where consumers earn over $2,500 a year—more than twice the average for India—and the retail infrastructure suits its products nicely. Without this more granular analysis, the multinational would have stayed on the sidelines in the mistaken belief that Indian consumers weren’t ready for its products. It would therefore have missed the opportunity to challenge a competitor rapidly gaining the lead in those markets.

Seizing new regional opportunities in Brazil

In contrast to China and India, Brazil has been open to multinationals for decades. But during much of that time, most large companies in sectors such as consumer packaged goods focused on the southern (and most affluent) parts of the country. With just over half of the national population, this region includes São Paulo city and state, Brazil’s financial and industrial center.
As economic growth accelerated in recent years, many consumers started upgrading to more sophisticated products. But growth has also been moving beyond the south and a few large cities, becoming more geographically dispersed. In the populous northeast, for example, income per capita is only half of its level in São Paulo, but the economy is growing faster than it is elsewhere in Brazil. Succeeding in new regions like the northeast requires a fresh approach for many companies. Consider the following:

• Many global companies still make the mistake of doing their consumer research in São Paulo when they are designing new products or national marketing campaigns for Brazil. They don’t realize that cosmopolitan São Paulo probably has more in common culturally with New York than with any other city in Brazil.
• Modern-format stores account for 70 percent of retailing in Brazil overall, but for only 55 percent in the northeast. To reach thousands of small (and often capital-constrained) outlets spread all over the region, packaged-goods companies must develop third-party networks specializing in frequent deliveries of goods and small drop sizes. What’s more, in Brazil as a whole, many consumer goods companies found that they had focused too much on hypermarkets when designing assortments and promotions. One company, for example, discovered that Brazil’s expanding drugstore chains were the fastest-growing channel for personal-care and beauty products. Some leading consumer goods companies have now created specialized organizations that execute distinct channel strategies in different regions and categories, with tailored product portfolios and displays.
• Many packaged-goods companies see detergent powders as a developed category in Brazil. But relatively affluent consumers there are upgrading to larger and more sophisticated washing machines, and many consumers in the northeast are buying their first fully automated machines. New detergent formulas therefore have enormous potential—annual consumption in the northeast is less than half of what it is in the south. Seizing this opportunity requires an understanding of the regional consumer, however, particularly pack size preferences (Exhibit 4). Consumers in the northeast also want a strong perfume and great quantities of foam but care less about whitening power.

Brazil is distinct from China and India in many respects. But as these examples suggest, there too identifying growth opportunities increasingly requires a detailed understanding of vast regional variations in competition levels, income, product growth rates, consumer preferences, and retail channels.
There is no one-size-fits-all strategy for capturing consumer growth in emerging markets. What’s clear, though, is that traditional country strategies and other aggregated approaches will miss the mark because they can’t account for the variability and rapid change in these markets. As the battle for the wallet of the emerging-market consumer shifts into higher gear, companies that think about growth opportunities at a more granular level have a better chance of winning.

McKinsey on Finance on iPad
https://www.mckinseyquarterly.com/Is_your_emerging_market_strategy_local_enough_2790

Remaking market making

There are some who believe that the rise of new, low-cost electronic securities trading should have killed market making and brokerage—the obscure tasks of executing securities trades for customers and matching buy and sell orders, whether on the floor of the New York Stock Exchange or on some trader’s desk deep inside an investment bank. Indeed, commissions have been slashed and bid-ask spreads have fallen; revenue from trading activities has been volatile. Furthermore, the industry has been tarred by trading scandals that have ranged from price-fixing among NASDAQ market makers to the rogue trader who brought down the 232-year-old Barings Bank.
The conventional wisdom is thus that investment banks and securities firms should abandon securities trading and stick to more attractive activities, such as managing assets and originating securities. Investors have hopped on this bandwagon, penalizing banks that earn substantial trading revenue with low price-to-earnings ratios (Exhibit 1).

But is market making and brokerage really such a bad business? Our analysis shows that, despite the gloom-and-doom prognosis, its economics are healthy. The old business model, which relied on manual, ticket-based trading and on fat commissions and spreads, will no longer work. But market making can still be attractive for players that use technology to automate the trading process and gain scale. All banks, whether they choose to compete fully or not, should decide how to position themselves.

Market making revisited

Despite all the bad press, the economics of market making and brokerage compare well with those of other core banking activities, such as underwriting securities and managing assets. Over the past 20 years, trading revenue has grown just as fast as other sources of bank income and been only a bit more volatile (Exhibit 2). And despite declining margins, trading revenue has grown even faster in recent years because of the global boom in securities trading. From 1995 to 1999, market making and brokerage revenue grew at an 18 percent clip annually, slightly faster than the overall average revenue for the whole securities industry. At the same time, the trading of securities accounted for more than half of the total revenue growth for some of the largest securities firms (Exhibit 3).

On the whole, margins in market making and brokerage can be just as attractive as margins in other banking activities. Some banks are realizing a return on equity of well over 20 percent from making markets for traditional cash equities, while margins for more innovative products (such as derivatives) or for the provision of trade-related services can top 40 percent. Compare this with the 10 to 30 percent earned in underwriting and asset management.
Historically, trading volumes surged every time the structure and efficiency of markets improved—for example, the 1986 "Big Bang" reforms at the London Stock Exchange and the 1997 order-handling rules in the United States. So the prospects are good: forthcoming regulatory changes—such as the introduction of single stock futures in both the United Kingdom and the United States—will stimulate the trading of securities by increasing the market’s efficiency and give market makers more flexibility, thereby improving their margins.
In the United States, NASDAQ’s SuperMontage will increase the market’s transparency by introducing a quasi-central limit order book in over-the-counter (OTC) stocks. (The SuperMontage will display three levels of orders or quotes on individual stocks rather than just the best bid and offer, so participants will be able to get a better sense of the depth of prices of and interest in a particular security.) The repeal of the NYSE’s Rule 390 will authorize the off-exchange trading of all listed stocks, thus boosting the market’s efficiency and allowing market makers to match orders internally and to capture both sides of the spread. Decimalization, which was recently introduced on the NYSE and is now being launched in OTC stocks, should also stimulate demand because spreads will narrow, thereby reducing the cost to trade.
In Europe, the changes will be even more far-reaching. The existence of more than 20 separate International Settlement Depositories makes clearing and settlement for intra-European trades three times more costly than they are for US ones. The implementation of a proposal to establish two main clearinghouses would eventually reduce much of that cost and stimulate cross-border trading, but even without this change, the trading of securities is booming among retail and institutional investors alike. European retail investors are diversifying their portfolios of bonds and local equities, taking advantage of new higher-yielding securities and cross-border opportunities. Institutional investors, overly concentrated in local securities, are also diversifying. As a result, from 1996 to 1999 the compound annual growth rate for the trading of European equities (31 percent) outstripped that of the United States (25 percent). We expect this trend to continue.
Meanwhile, the businesses that were supposed to save investment banks—M&A and equity origination—are becoming less attractive. They enjoyed record years in 1999 and 2000, but the sharp devaluation of technology stocks, the downturn in global equities markets, and the slowdown of many economies will all have their effect. In the United States, the telecom and technology sectors accounted for nearly 60 percent of investment-banking activity last year; this level is already falling off as investors question the growth trajectories of these businesses and as companies restructure their balance sheets.

A factory, not a fashion show

Far from killing the business of market making and brokerage, technology will actually save it

If market making and brokerage is an attractive business, why do so many industry players disparage it? The main reason is confusion about the role of technology. Far from killing the business, technology will actually save it. Sure, commissions and spreads are falling, and this trend won’t be reversed. The old people-intensive business model, for the most part, no longer holds. Huge parts of the business—trading in bonds, cash equities, and standardized derivatives—are becoming commoditized. Winning in this environment will require banks to reach unprecedented scale, and a handful of them will take the lion’s share of the profits. But emerging technologies will make competing in this new environment profitable for the eventual winners, allowing them to increase—dramatically—the volume of trades they can process while lowering their costs and increasing their profitability. The leading players will recognize that technology is an advantage, not a threat.
New systems can automate everything from front-end order capture to back-office clearing and settlement. At the front end, new services now enable both institutional and retail investors to enter their trades directly into their brokers’ systems or electronic communications networks (also known as alternative trading systems). Firms process far more trades, and both costs and errors are lower. Bloomberg, Bridge Information Systems, ITG, and Reuters offer such services, and most investors now have electronic-data-interchange links to their brokers.
Technology is also revolutionizing the post-trade process, reducing per-ticket clearing and settlement expenses. Cross-border European trades cost an estimated €28 ($24.90) to settle, compared with only €1 or €2 for settlements executed with more highly automated systems. To automate the back office, financial institutions should look at custodian and clearing banks. State Street, for example, has invested $250 million to $300 million annually in technology for the past five years and can now offer inexpensive back-office services to other firms. Financial institutions must keep an eye on these players, since they are now creeping into the execution of trades.

New systems allow trading firms to match trades internally, thereby capturing the entire spread between the bid and offer price

Paradoxically, technology can also increase margins per trade and improve the ability to manage the execution of block trading. New systems allow trading firms to match trades internally, thus capturing the full spread between the bid and offer price and avoiding exchange fees, though internalization can boost profits only for institutions with enough volume to ensure a high internal matching rate. New order-management software can automatically break up and manage large trades to minimize their impact on market prices, thereby giving the customer a better price and boosting margins in the process. This is particularly useful in portfolio reallocations, which entail the trading of large blocks of many different securities.
Newer technology can also give market makers and brokers a better understanding of their customer base. Banks and securities firms that have always won business by building personal relationships with a few big investors can now use software to determine the profitability and appropriate service levels for a much larger number of accounts. Another new technology will permit trading units to change their service model away from primarily "push" (deluging portfolio managers with the latest research) and more toward "pull," which allows investors to access research selectively and analysts to aggregate and tailor information easily. Multex.com, for example, gives investors access to research from most major institutions. Consortia such as Securities.Hub are making it possible for investors to access, in a single place, the initial-public-offering calendars, research, and other services of leading firms. All of these efforts increase margins per account and may boost trading volumes as well.

Getting to scale

Investing in these new technologies obviously raises the fixed costs of any trading business. Scale, which makes the business more attractive in several other ways, will therefore be needed. Besides lowering the marginal cost per trade, a greater volume of orders cuts volatility and risk. With a larger order flow, an institution can match more of its trades internally, thereby putting up less capital in each transaction and holding a smaller inventory of securities. As a result, there is a clear negative correlation between trading revenue and the value at risk (VAR) relative to trading volume (Exhibit 4).¹ Merrill Lynch and Morgan Stanley Dean Witter, for example, have a much lower VAR relative to their trading revenue than do firms that have smaller order flows. Bigger companies will find trading to be a more stable and profitable business.

In capturing additional order flow, players will also benefit from diversification. Institutional orders from mutual-fund managers, pension funds, and insurance companies are important because of those orders’ size and overall share of the market. But many institutional-investor segments trade infrequently and tend to base their buy and hold activities on fundamental portfolio decisions. Hedge funds are usually more active traders, with average turnover rates that are three or more times the size of their assets, so their order flow can provide valuable real-time information on market conditions. And banks can’t ignore retail customers: smaller trades are easier to execute and more richly priced. Furthermore, small orders (a proxy for retail trades) now represent around 70 percent of all trades executed in OTC stocks, up from 57 percent in 1994. Orders from outside the United States will also be important given the rapid growth of global securities trading.
Increasingly, winning businesses will need to provide services beyond trade execution. Some investment banks, for example, now offer prime brokerage services—all of the back-office and financing services that support a trade—to hedge funds and other players.
A faster way of capturing extra order flow, following the lead of wholesale trading houses in the OTC market such as Knight Trading Group and Spear, Leeds & Kellogg, is to purchase order flow from smaller broker-dealers. Because wholesalers process a large volume of trades, they can often act as the counterparty on both sides of a trade, thus boosting margins. Investment banks have recently bought several of these wholesalers: Goldman Sachs purchased Benjamin Jacobson & Sons and Spear, Leeds & Kellogg, while Merrill Lynch purchased Herzog Heine Geduld. But perhaps this model has been too successful, for few independent wholesalers are now left; Knight is the most important of them.
Acquiring customers in Europe is going to be more difficult for US banks, since European retail investors naturally turn to local institutions, and European bank acquisitions are complicated by large branch networks and strong labor unions. A more promising strategy is to capture order flow through another channel. Morgan Stanley and OM Gruppen, for example, launched Jiway, an exchange where retail investors trade the top European stocks (more than 400 of them at present). Goldman Sachs launched PrimeAccess, a service that provides international-trade execution, research, and some IPO allocations to on-line brokers (mostly in Europe), including Direct Anlage Bank and Banca Popolare di Verona. Merrill Lynch and Credit Suisse First Boston (CSFB) are launching similar services; to this end, CSFB built an alliance with Postbank’s on-line broker, Easytrade, in Germany.

A role for proprietary trading

Many banks abandoned the trading of securities because it has been associated, wrongly, with the scandals of so-called proprietary trading. In the second half of the 1990s, banks often put their own capital at risk to make speculative macroeconomic bets—for example, bets on the direction of interest rates or currency movements. Not surprisingly, the returns were highly volatile, and the shareholders and managers of these banks were sometimes caught off guard.
Such trading has received a huge amount of well-deserved bad press. These activities are essentially no different from what hedge funds do, but while George Soros’s investors are prepared, at least in theory, to stomach huge losses as well as gains, shareholders of blue-chip banks are not.² In recent years such opportunities have been more limited, and the resulting risk of these trades is better left to hedge funds, whose investors can diversify their own portfolios appropriately.
Most major banks have now scaled down these speculative activities, but taking principal positions is a necessary—and potentially lucrative—part of market making. The difference is that such positions are closely related to customer business, not speculative bets. In making markets or executing a large client trade, a bank must often take on some or most of the position for a period and stands to gain (or lose) from price movements during that time. In fixed-income businesses, trading gains (or losses) from this kind of activity can overwhelm spread or commission revenues. Naturally, banks also gain valuable information about market sentiment from market making. They can, and should, exploit this information to manage their inventory of securities efficiently and (if risk limits are observed) to gain from taking principal positions for the bank’s account.³

The sweet spots

Other parts of the trading business will continue to earn higher margins as well. One task that will never be fully automated is block trading, or executing the huge trades that would move prices too much if put into the market all at once. Traditionally, "upstairs" traders break these trades into smaller ones and work them over several days to obtain the best overall price for the customer. Electronic-trading algorithms are replacing some of this activity; trades of 100,000 (or even a million) shares may soon be executed electronically.4
Even so, the average size of block trades is increasing in parallel. Last year, J. P. Morgan executed a $1.9 billion trade; other trades too were reported to involve more than $1 billion. Given this trend, upstairs trading will always be needed. What will change is the definition of a block trade; in other words, the size of trades defined as block trades will increase.
Margins also remain substantial in more complex derivatives and bundled products. There has been tremendous growth, for example, in derivatives that allow would-be IPO millionaires to realize their assets before they exercise their options. Other opportunities exist for structuring intergenerational wealth transfers and for taking short positions on market movements for large investors. In fixed income, demand for credit derivatives is likely to continue growing despite recent hiccups. Bundled products, such as portfolio reallocation, index trading, and arbitrage, are attractive as well.

The low-margin commodity side of market making and brokerage will eventually look quite different from the higher-margin trading side

Over time, the low-margin commodity side of the trading business and the higher-margin areas will look very different. The former will be ruled by programmers developing new trading algorithms; the latter will remain labor-intensive and high touch. For those higher-margin areas, investments in talent will be of critical importance. Still, there will be important synergies between the two sides of the business. Proprietary trading, for instance, will depend on information that is derived from the flow of customer orders. With a strong flow, a trading firm can reduce its inventory and net more trades internally. We therefore expect the leading players to develop strong capabilities in both the automated, volume-driven business and the high-touch areas.

Only a few players will win

With the price of new technologies likely to be several hundred million dollars a year, competing in this new environment will hardly be cheap

With the price of new technologies and talent likely to be several hundred million dollars a year, competing in this new environment certainly will not be cheap. Some players are already investing heavily, and this seems to be paying off: investors report that the biggest spenders on all forms of information technology have lower trading costs than do their more frugal counterparts.
How should banks react? Different, and difficult, choices will have to be made. Institutions with a strong share of trading volume should move full-speed ahead. Given the scale and speed needed to win, Mergers and acquisitions are the most promising way to obtain new technology and order flow quickly; relying on organic growth will be difficult. A global presence is a necessity, since much of the growth will take place outside the United States, and some new technologies—and institutional learning—can be leveraged globally.5
To gain a foothold in other countries, joint ventures may offer an alternative. In Europe, for example, the prevalence of universal banking means that a pure-play acquisition is tough, and an acquisition of a universal bank would bring in several business lines that are much less attractive. At the same time, the biggest players can’t afford to ignore the talent needed for the high-margin parts of the business. Technology, scale, and skills will differentiate the best from the rest.
Yet the game isn’t over for smaller and more regionally oriented institutions. Smaller banks have a good position to make great outsourcing deals with larger players that want to gain order flow. Besides getting paid for order flow, smaller institutions might gain access, for example, to the larger bank’s research and IPO calendar. In Europe, several smaller or more retail-focused players have partnered with large trading houses to offer customers more cheaply executed trades, a broad array of research, and access to European and US securities. In addition, smaller firms can make markets in niche securities for which skill is more important than scale. The regional bank WestLB, for instance, may be able to compete successfully in making markets for some German derivatives.
Trading is being redefined by technology and is creating terrific opportunities for a host of banks. It is clearly time for another look.

About the Authors

Jonathan Davidson is a principal in McKinsey’s Toronto office; Léo Grépin is a consultant in the Montréal office; Charlotte Hogg is a principal in the Washington, DC, office.

McKinsey on Finance on iPad