Marina Gorbis's Blog, page 1368

Every Content Marketer Needs an Editor

Content marketing is getting a lot of attention as companies strive to capture customer attention in an era in which TV ads get skipped, direct mail goes unopened, and even online ads get blocked. It seems more and more like the best—some would say, only—way to get your message out is for your customers to seek it out as content.

That’s led to an explosion in sponsored reports, videos, slideshares, and just about every other form of content that human beings might voluntarily choose to consume (as opposed to having it foisted upon them as pop-ups and banner ads). Unfortunately, as is widely acknowledged, most of the content in content marketing falls far short of the standard historically set by traditional media outlets: much of it is more marketing than it is content. I’ve lost count of the number of times I’ve made it to the end of a report or blog post, only to find myself still waiting for useful information, fresh insight, or even a coherent argument—rather than a pitch for the author’s book or a link to their consulting practice.

Disappointing readers with content that fails to rise above mediocrity is no way to build brand awareness or drive sales. Sexy headlines and quick quizzes may generate visits or even shared links, but you’re not going to win over the hearts and minds of your potential customers if they abandon your blog posts and reports after a dull or unreadable paragraph or two.  When you consider that 27 million pieces of content are created each day, but that 60 to 70% of website content goes unused, it’s clear that content marketing has emphasized producing a high volume of content at the expense of producing content that people actually want to consume.

Content marketing will only deliver on its promise if it’s good enough to deliver customers–that’s why improving the quality of content marketing is critical to business. But creating the kind of excellent original content that attracts, engages and retains an audience requires a mix of competencies that go well beyond what you find on a typical marketing team. At the top of that list of missing competencies is professional editing.

I’m painfully aware of the role that editors could and should play in the content marketing ecosystem because I’ve experienced many different sides of the content development and content marketing business. I’ve helped to develop and edit the corporate blog here at Vision Critical. I’ve worked with volunteer contributors to online community sites, balancing the need to encourage unpaid contributions with the desire to promote and showcase quality content. I’ve also written for high-profile blogs and publications and in doing so I’ve had both editors who have profoundly advanced my own writing and thinking, and ones who simply post whatever I submit. The impact of quality editing on my own work has made me appreciate the crucial role that editors play in turning information and ideas into compelling content (including right here at HBR).

I’m not talking about simple proofreading or copyediting (though gosh, that would be nice; my inner nitpicker is being driven slowly mad by all those stray apostrophes running loose across corporate blogs). Nor am I talking about overarching editorial direction and content strategy: that’s the part most marketing teams have figured out, albeit imperfectly, simply because understanding an audience (customers, potential customers and perhaps industry influencers) and defining key messages (the benefits your products and services offer, and the expertise you have in the field) are what a marketing team has traditionally needed to do best.

It’s the in-between layer that’s missing: the editor who acts as a proxy for the reader, and ensures your content offers that reader real value in return for their time.  That editor also has the ability to recognize the difference between an idea that’s worth a 140-character tweet, and one that can be developed into a blog post or report—or, for that matter, a three-minute video. They have the ability to work with an author whose ideas may be terrific but who may not be a strong communicator, and develop that author’s ideas into a compelling and engaging piece of content. And yes, the ability transform inelegant or even incoherent prose into a tight, readable argument.

Those competencies make the difference between a site full of content marketing, and a site full of content that actually acts as an effective part of your marketing strategy. Look at the stars of content marketing, and you’ll see that their content isn’t just shiny — it delivers real substance. Like Hubspot, whose widely-shared blog posts offer authoritative insight on everything from the evolution of Google+ to the the psychology of job interviews — topics that go far beyond the company’s specific business of inbound marketing software, but support its claims to expertise. Or Whole Foods, whose Dark Rye magazine holds its own against commercial lifestyle magazines. (A key test for any content marketing: does it read like content people would actually pay for?)  Or IBMblr, IBM’s much-discussed Tumblr, where the company shares a compelling mix of visual and text-based snippets that convey the company’s passion for innovation in a dynamic and charming way.

Companies that want to produce this kind of quality content don’t need more marketing genius; they need more editorial genius. Yet the scramble to build content marketing capacity has not to date translated into a scramble for talented editors. While there is no shortage of opportunities in content marketing, just a handful of these are for editors. Yes, some dispensers of content marketing wisdom include a editor-in-chief in their vision for content marketing teams, but that role is typically described more as a leadership position exerting high-level editorial control than as an in-the-trenches job ensuring high-quality execution.

To deliver the kind of content that can truly advance a brand, marketing teams need to hire editors who have the time to really dig into each piece of content they produce, and the mandate to create content that serves the reader as well as the business. That means hiring people with the experience to edit contributions from anywhere in your organization (or outside of it) — even if that means going toe-to-toe with a CEO whose sentences don’t hang together. That means your editors need the authority to make significant changes or even kill selected contributions, but shouldn’t be swamped with managerial duties that crowd out the detailed and intensive revision process — editors need the bandwidth to actually work through each and every piece of branded content you produce so that it is as good as the best unbranded content.

The companies that make this kind of investment in editorial capacity will be most successful in translating their content marketing aspirations into a daily reality of producing excellent content. Content marketing is now a central part of marketing strategy. But it won’t work for readers or for brands unless our content achieves a high and consistent level of quality. It’s time for corporate marketers to recognize what media outlets have long known: if you want quality content, you need quality editors.

Let Algorithms Decide – and Act – for Your Company

In the near future, simply having predictive models that suggest what might be done won’t be enough to stay ahead of the competition. Instead, smart organizations are driving analytics to an even deeper level within business processes—to make real-time operational decisions, on a daily basis. These operational analytics are embedded, prescriptive, automated, and run at scale to directly drive business decisions. They not only predict what the next best action is, but also cause the action to happen without human intervention. That may sound radical at first, but it really isn’t. In fact, it is simply allowing analytics to follow the same evolution that manufacturing went through during the industrial revolution.

Centuries ago everything was manufactured by hand. If you needed a hammer, for example, someone would manually produce one for you. While manually manufacturing every item on demand allows for precise customization, it doesn’t allow for scale or consistency. The industrial revolution enabled the mass production of hammers with consistent quality and lower cost. Certainly, some customization and personal touches were lost. But the advantages of mass production outweigh those losses in most cases. It remains possible to purchase custom made items when the expense is deemed appropriate, but this usually only makes sense in special situations such as when the purchaser desires a one-of-a-kind piece.

The same revolution is happening in analytics. Historically, predictive analytics have been very much an artisanal, customized endeavor. Every model was painstakingly built by an analytics professional like me who put extreme care, precision, and customization into the creation of the model. This led to very powerful, highly-optimized models that were used to predict all sorts of things. However, the cost of such efforts only makes sense for high-value business problems and decisions. What about the myriad lower value decisions that businesses face each day? Is there no way to apply predictive analytics more broadly?

There is.

Operational analytics recognize the need to deploy predictive analytics more broadly, but at a different price point. An assembly line requires giving up customization and beauty in order to achieve an inexpensive, consistent product. So, too, operational analytics require forgoing some analytical power and customization in order to create analytics processes that can increase results in situations where a fully custom predictive model just doesn’t make sense. In these cases, it is better to have a very good model that can actually be deployed to drive value than it is to have no model at all because only an optimal model will be accepted.

Let me illustrate the difference with a common example. One popular use of predictive models is to identify the likelihood that a given customer will buy a specific product or respond to a given offer. An organization might have highly robust, customized models in place for its top 10-20 products or offers. However, it isn’t cost effective to build models in the traditional way for products or offers that are far down the popularity list. By leveraging the learnings from those 10-20 custom models, it is possible to create an automated process that builds a reasonable model for hundreds or thousands of products or offers rather than just the most common ones. This enables predictive analytics to impact the business more deeply.

Operational analytics are already part of our lives today, whether we realize it or not. Banks run automated algorithms to identify potential fraud, websites customize content in real time, and airlines automatically determine how to re-route passengers when weather delays strike while taking into account myriad factors and constraints. All of these analytics happen rapidly and without human intervention. Of course, the analytics processes had to be designed, developed, tested, and deployed by people. But, once they are turned on, the algorithms take control and drive actions. In addition to simply predicting the best move to make or product to suggest, operational analytics processes take it to the next level by actually prescribing what should be done and then causing that action to occur automatically.

The power and impact of embedded, automated, operational analytics is only starting to be realized, as are the challenges that organizations will face as they evolve and implement such processes. For example, operational analytics don’t replace traditional analytics, but rather build upon them. Just as it is still necessary to design, prototype, and test a new product before an assembly line can produce the item at scale, so it is still necessary to design, prototype, and test an analytics process before it can be made operational. Organizations must be proficient with traditional analytics methods before they can evolve to operational analytics. There are no shortcuts.

There are certainly cultural issues to navigate as well. Executives may not be comfortable at first with the prospect of turning over daily decisions to a bunch of algorithms. It will also be necessary to get used to monitoring how an operational analytics process is working by looking at the history of decisions it has made as opposed to approving up front a series of decisions the process is recommending. Pushing through such issues will be a necessary step on the path to success.

The tools, technologies, and methodologies required to build an operational analytics process will also vary somewhat from those used to create traditional batch processes. One driver of these differences is the fact that instead of targeting relatively few (and often strategic) decisions, operational analytics usually target a massive scale of daily, tactical decisions. This makes it necessary to streamline a process so that it can be executed on demand and then take action in the blink of an eye.

Perhaps the hardest part of operational analytics to accept, especially for analytics professionals, is the fact that the goal isn’t to find the best or most powerful predictive model like we’re used to. When it is affordable and the decisions being made are important enough to warrant it, we’ll still put in the effort to find the best model. However, there will be many other cases where using a decent predictive model to improve decision quality is good enough. If an automated process can improve results, then it can be used with confidence. Losing sleep over what additional power could be attained in the process with a lot of customization won’t do any good in situations where it just isn’t possible due to costs and scale to actually pursue that customization.

If your organization hasn’t yet joined the analytics revolution, it is time that it did. Predictive analytics applied in batch to only high value problems will no longer suffice to stay ahead of the competition. It is necessary to evolve to operational analytics processes that are embedded, automated, and prescriptive. Making analytics operational is not optional!

To Sell is Human: The New ABCs of Moving Others

Do you sell the same way you did a decade ago?

In the classic movie Glengarry Glen Ross Alec Baldwin tells a group of salesmen that the key to selling is, “A-B-C. A – Always; B – Be; C – Closing. Always be closing.”

But this steamroller approach is now a relic.

According to bestselling author Dan Pink, sales has changed more in the last 10 years than the previous 100. Today, buyers have as much information as sellers—along with ample choices and the means to push back. Selling effectively requires a new approach.

In this interactive Harvard Business Review webinar, Dan Pink draws on cutting-edge social science and best practices from global organizations to reveal the new ABCs of selling. Pink reveals 5 ways to frame messages to increase clarity and promote action. He also discusses why problem finding is now more important than problem solving, how questioning your abilities before a sales call can actually help, and why the most effective salespeople are not extroverts.

How Microeconomists Made Amazon Possible

With the digital age has come the celebration of “platforms.” The concept is that an enterprise can add value at either of two levels. It can provide a broad foundation upon which others can profitably build, or it can be one of those latter efforts, taking advantage of an existing platform and offering solutions that more narrowly target specific opportunities.

When people talk of valuable platforms, they are typically thinking of things like the operating systems for personal computers, tablet computers, and smartphones, all of which allow and indeed encourage software developers to invent “apps”; or the Amazon selling system which provides a layer of basic logistical functions for independent retailers. But platforms have a longer lineage than these. In an earlier age, “general purpose technologies” such as electricity and communications networks were recognized by economists as their own category because they provided vital inputs for all kinds of businesses, revolutionized the way business was conducted in general, and literally redefined what it meant to live in modern society.

Platforms can also be thought of more broadly than technological systems. Government policies, whether established by legislatures, regulatory agencies, or judicial rulings, constitute legal platforms that also enable commerce. There is an extensive academic literature, for example, on how the “rule of law” — property and contract rights that can be enforced, and disputes peaceably and efficiently resolved by a trusted judicial system — is a precondition for both economic growth and advanced living standards (although some economists argue that the causation runs both ways – that economic growth also supports the rule of law by making more resources available for it, and causing more demand for it).

I’d like to argue that ideas can also qualify as platforms, to the extent that others rely or build on them to make their own marks. Further, I would claim that, in the realm of business, more of these platform ideas have been developed by economists than many entrepreneurs and business leaders imagine. I’ll offer three examples.

The Idea to Break Up AT&T

The internet would not be what it has become without huge private investments in its “backbone” – the fiber optic cables that route packets of zeroes and ones to the network nodes close to the hardware (PCs or smartphones) where they originate and end up. But it is all too easy to forget (or not to know) what encouraged those fiber investments in the first place: the federal government’s successful antitrust lawsuit against the “old AT&T” that once monopolized telecommunications in the United States.

Economists were instrumental in providing the intellectual rationale for the Justice Department’s landmark filing of that lawsuit, and just as important, of the relief the government sought: breakup of “Ma Bell’s” control over both long-distance and local telephony. Breakup was critical to the development of the Internet because as long as AT&T faced no competition in long-distance, the company had no incentive to replace its copper wires with the fiber optic technology that ironically was developed by Bell Labs. Post-breakup, long-distance competitors MCI and Sprint, among others, induced the new AT&T long-distance company (which later was acquired by Southwestern Bell but kept the AT&T name) to lay the fiber optic cables across the country that became the Internet’s backbone.

So, when browsers came along in the 1990s, the web was ready for the explosion in commercial traffic and searching that quickly followed. It is not at all clear that Sergey Brin and Larry Page, founders of Google or Jeff Bezos, the founder of Amazon, would have been interested or able to launch their now-iconic companies had not the internet been ready for them when they had hatched their ideas and were ready to implement them.

The Idea to Deregulate Transportation

While web retailing has made shopping hugely more convenient, none of it would be possible at the scale it has achieved without the retailers’ being able to tap into a highly flexible and efficient transportation system capable of delivering goods promptly to customers. We have that transportation system now, but this was not always the case.

Before 1980, all routes and fares of the airline and trucking industries were regulated by agencies of the federal government, dating from Depression-era statutes. In retrospect, it is clear that this system of “economic regulation” was designed to insulate incumbent carriers from competition; neither air nor truck traffic were natural monopolies requiring price and entry controls.

Many transportation economists had argued for decades that economic regulation of airlines and trucking was inappropriate, mainly serving to jack up prices for the consumers and businesses buying these services. Amazingly, President Carter and Senator Ted Kennedy listened to them, using their arguments to persuade Congress to dismantle price and entry controls in these industries in 1978 (airlines) and 1980 (trucking). Carter also appointed noted economists like Alfred Kahn, Elizabeth (“Betsy”) Bailey, and Darius Gaskins, to key regulatory positions, where they were able to administratively deregulate first, where possible, and also to make the case to Congress that ultimately only legislative repeal would really do the trick.

Deregulation not only lowered shipping prices; it unleashed fierce competition between Federal Express and UPS that eventually produced the efficient and flexible transportation system that turned out to be ideal for internet commerce. So when Jeff Bezos and other web retailers came along in the 1990s and later, they were able to tap into that system, without having to buy trucks and plane fleets of their own, which would have been prohibitive barriers to entry. That they didn’t have to is a tribute to the eventual power of economic ideas and research.

Ideas about Energy Price Control

A huge transformation is underway due to the recent, remarkable surge in domestic oil and natural gas production. The reason is well known: the combination of horizontal drilling technology with hydraulic fracturing (“fracking”) has enabled energy producers to locate and bring to the surface oil and gas in “tight” rock formations. The unforeseen energy turnaround has been a boon to U.S. manufacturers, inducing some to rethink their location decisions.

What many don’t fully realize, however, is the unsung role that economists have played in this story. I am old enough to remember the dark days after the Arab oil embargo in 1973-74, which triggered a quadrupling of world oil prices at a time when monetary policy makers and elsewhere were already struggling to contain inflation. Even Republicans in the White House (Nixon and then Ford) were not comfortable with the political implications of the higher gasoline prices this jump in crude prices entailed, and so they implemented a complicated system of controlling the price of “old oil” (that discovered before the price jump) and new oil, alongside a preexisting and even more complicated system of controlling different vintages of natural gas. The results were prices to consumers that were below market clearing levels, which any economist could have predicted would result in shortages: long lines at gas stations for motorists and rationing of natural gas for heating homes.

Economists in both the Ford and Carter Administration were instrumental in decisions dismantling energy price controls, which were gone by the early 1980s. This took some guts, especially by President Carter (again), who agreed to decontrol oil prices toward the end of his term by which time crude oil prices again had soared (Carter and a Democratically controlled Congress did enact a time-limited windfall profits tax on energy producers, however).

Why is this history important? Because when oil prices again rose in the 2000s, politicians had learned their lesson and did not rush to impose price controls. Higher prices did what economists predicted they would do, but admittedly even more successfully than many probably thought: they provided the economic impetus for energy companies to combine horizontal drilling and fracking, a coupling that has produced remarkable results. So score several points for the technologists and the risk-taking oil and gas production companies, but score at least one point (maybe two) for the economists in the background.

*  *  *  *  *

Is it proper to cast these ideas as “platforms”? Based on what has been built since, it seems fair to say yes. The first two examples were hugely influential in enabling the Internet economy; the third benefited all energy-using industries. The people behind them all belong in the club I call the Trillion Dollar Economists.

So perhaps the so-called dismal science of economics should be celebrated a bit more. Mention the word “economist” and most people conjure up mental images of macro forecasters, making pronouncements about, or in the case of the Fed, actually influencing measures of the overall economy: GDP growth, inflation, and unemployment. We should shine more light on the other, “micro” economists – the ones studying individual firms and markets. Among these are the thinkers who are even now hatching new platforms. Years from now, we’ll see the new companies that were enabled, and the existing businesses whose growth was accelerated, by their most powerful, policy-bending ideas.

How Apple Pushes Entire Industries Forward

Yesterday, hardware stole the show at the Apple unveiling. But Apple’s most impressive achievement on display at yesterday’s announcement was not a technological feat — although the technology on display was certainly impressive.

Apple’s great feat was the use of their scale to swiftly get the world lined up behind a new model for payments. Apple Pay will be more secure, it will be easier, and it will probably be more profitable for the payments industry as a whole by shifting people away from cash (at least for the time being). But putting it into practice required an entire ecosystem to move in unison — merchants, consumers, credit card companies, and banks. Something that only a company with the massive reach of Apple could do.

Big companies’ struggles with innovation have been well documented — including by me. But there are some things you need to be big in order to achieve.

What Apple demonstrated yesterday was its power as an “impatient convener.”

The term was coined by the first CTO of the US Government, Aneesh Chopra. Chopra, and his successor Todd Park, have thoughtfully used the unique position of the White House to bring together disparate leaders to drive innovation through mutually beneficial agreements. Their thesis, which Chopra describes elegantly in his book Innovative State, is that the White House has the pull to sit people down at the table. When the President calls, you answer. When the President says, you need to come to Washington to discuss something like rolling out a smart-grid technologies nationally, you come. And if you are there and the proposal makes sense, you may actually opt in as well – even if there are no demands or formal requests from on high.

Yesterday, Tim Cook demonstrated the benefits to driving innovation as a massive, mature company. Apple used its power as an impatient convener to move an industry. Yesterday, Tim Cook showed that, like the White House, when Apple calls, you answer.

Fixing payments isn’t a novel concept. Years ago, the team at Paypal set out to change the payments industry and free us from crushing payment fees by enabling ACH based payments. More recently, Square decided that archaic payment hardware needed to be refreshed for a world where people carried a supercomputer in their pockets. And Google perennially updates their offering with Google Wallet.

But despite all of these efforts, each of us still carries stuffed wallets and heavy purses around wherever we go. Why? Mobile payment systems need ubiquity before we can replace our old systems. And if we aren’t going to stop carrying our wallets around – why change anything at all? Sure, we’ll swipe when someone has a Square reader. We’ll send a friend cash with Paypal if we don’t have it in our pocket. And we might pay with Google Wallet if there is a big enough coupon to justify re-installing the app. But nothing foundational has really changed.

Consider: last year Square was rumored to process around ~$30B in sales. In the same year, the Federal Reserve suggested Americans swiped credit cards ~30 billion times (and debit cards about 50 billion more times). With the average credit card swipe at somewhere between 80 and 100 dollars, that gives Square a tiny fraction of the processing pie. And Square still relies on the swipe of a plastic card.

On the other hand, on launch date, the Apple Pay will be accepted by terminals across the globe who process hundreds of billions of dollars of payments. Major retailers from Walgreens to Walt Disney will let you pay with Apple’s secure payment technology. And now, according to Jack Dorsey, so will millions of Square merchants around the world.

Sure, the security features Apple is prepared to offer resonate with us in a time where our identities and financial information are constantly at risk of being stolen. Obviously, the backwards compatibility with all our existing cards is compelling. And the fact that Apple already has our card on file makes it pretty easy. But the real brilliance of Apple’s offer is much simpler: it’s scale.

Apple Pay is impressive, it’s groundbreaking, and it may just unleash a wave of innovation. To do what Apple just did requires deep industry collaboration. It must have taken months of careful negotiations, a lot of trust, and a real threat to inaction. The companies who would have been happy to sit back on their laurels probably felt that failure to engage would result in large losses. It harkens back to the negotiations that must have occurred with record labels before Apple launched the iTunes store. It foreshadows the type of collaboration that Tesla may require in order to retrofit an ecosystem of fuel stations for EV charging. It’s an expert use of product design, network effects, and game theory all wrapped up in one move.

And it also makes me think. How can each of us use the power of impatient convening to our advantage? If Apple is audacious enough to use its power to transform a 50-year old industry, how could you use your company’s reach to create meaningful change?

Power Cues: New Science on Influencing Others

How leaders communicate has a tremendous impact on their ability to lead and influence others, and on their personal success. Yet unknown by many is that most communication is unconscious.

Nick Morgan, communications expert and author of Power Cues: The Subtle Science of Leading Groups, Persuading Others, and Maximizing Your Personal Impact, has looked at recent brain and behavioral science revelations about how humans communicate, and how effective communicators use subtle gestures, visual cues, sounds, and signals that elicit emotion.

In this interactive Harvard Business Review webinar, Morgan shares insights from science on new ways to prompt unconscious responses to connect with people powerfully and persuasively. By leveraging these communications insights—these “power cues”—leaders can maximize their personal impact, enhance their leadership skills, and improve their ability to influence others.

Making Good on Your Organization’s Intentions

Why do teams and organizations often fail to achieve their goals and fall short of delivering on their good intentions?

Leaders often focus on securing commitment and buy-in, yet commitment is rarely the problem. Also, the issue isn’t just understanding the goal and knowing what needs to be done. Teams and individuals often understand and know, yet aren’t successful at doing (the “knowing-doing” gap).

In this interactive Harvard Business Review webinar, motivational expert Heidi Halvorson helps individuals and teams improve the attainment of their goals. Halvorson explains why people and organizations often don’t do what they intend, shares insights from neuroscience, describes the two key pitfalls of execution, and describes what if-then planning is and why it significantly increases the odds of executional success.

Coaching Your Employees

When you’re swamped with your own work, how can you make time to coach your employees—and do it well?

It’s a common problem. But if you don’t build your people’s own skills and capabilities, they’ll come to you for answers instead of finding their own solutions. Hand-holding kills productivity and creativity, and you can’t sustain it. In the long run, it eats up a lot more time and energy than investing in people’s development.

So you really must coach to be an effective manager. You’ll need to work with each person to agree on their goals for growth, motivate them to achieve their goals, support their efforts, and measure their progress.

In this interactive Harvard Business Review webinar, Ed Batista, experienced executive coach and co-author of the HBR Guide to Coaching Your Employees, shares insights from this Guide and from his extensive coaching experience. Batista describes how you can improve your coaching skills, create realistic and inspiring plans for people’s growth, customize your approach, and provide employees the support they need to achieve peak performance.

Capitalism’s Future Is Already Here

On September 13, 1970, The New York Times published an article by Milton Friedman castigating any managers of businesses who were “spending someone else’s money for a general social interest” – in other words, requiring customers to pay more, employees to be paid less, or owners to accept smaller profits so that the firm could exhibit some amount of social responsibility beyond the requirements of the law. Already, in his 1962 book Capitalism and Freedom Friedman had declared that “there is one and only one social responsibility of business–to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game, which is to say, engages in open and free competition without deception or fraud.” Choices about whether and how to use money to remedy social problems should be left to individuals, he argued, who would be in better position to provide it if they were not being in effect taxed by corporate managers who thought they had better ideas for how to spend it.

The article shocked the sensibilities of many who worried about rising corporate power in the world, but for many executives struggling to chart courses through the chaos of newly globalized and deregulated markets, it offered an irresistible clarity: one need only focus on owners’ interests. In 1976, Professors Meckling and Jensen put a finer point on things with their economic rationale for maximizing shareholder value. Ronald Reagan and Margaret Thatcher gave the idea political cover. Very quickly, shareholder value became the gospel of capitalism.

The tight focus on generating returns drove many gains. It hurried along the formation of global supply chains with ever greater efficiency and economies of scale. As more firms became multinationals, fewer showed loyalty to particular communities or any hesitation to migrate their operations to wherever costs were lowest. Employees were viewed more as fungible inputs to operations, and customers viewed more as targets within more and less lucrative segments.

Yet it also began to be evident that, even if the goal was to serve the interests of a single stakeholder, the pursuit could not be so single-minded. Incentives to maximize shareholder value pushed managers toward decisions that paid off in the short term but were devastating to the long term viability of firms. As I’ve explored elsewhere, pervasive short-termism hampered the United States’ capacity to compete in international markets; encouraged a massive trend of offshoring that destroyed major segments of the US economy; generated “bad profits” that undermined customer loyalty; “financialized” the economy, making it vulnerable to increasingly severe financial crashes; undermined economic recoveries; and drastically reduced rates of return on assets and on invested capital of US firms.

These problems hardly arose overnight; they began brewing early. However, it was after the advent of the internet that the challenges to the shareholder value maximization became forceful. This is because the internet …

Shifted power in the marketplace from seller to buyer. Customers, who had access to reliable information about the available choices and a capacity to interact with other customers, were suddenly in charge.
Raised customers’ expectations. As “better, cheaper, faster, smaller, more convenient, and more personalized” became the new norm, the ability to innovate with committed employees and agile processes became critical.
Shredded vertical supply chains. Customers could buy a wider array of stuff online cheaper, and often quicker, than in a physical store. First books and music, then almost anything.
Spawned vast new horizontal value chains, in which millions of people began creating their own virtual meeting places and marketplaces with their own lateral economies of scale. First computer code, then ideas, then music, photos, and videos – and finally, physical things.
Enabled firms to create huge ecosystems of suppliers and customers that could achieve enormous scale without the sclerosis of big hierarchical bureaucracy.

As a result, a new era is emerging. Harking back to Peter Drucker’s insistence in 1973 that “there is only one valid definition of business purpose: to create a customer,” Roger Martin has declared that we are finally entering “the age of customer capitalism.”  If firms serve customers well, Martin asserts, benefits for shareholders and the community follow. Customers as stakeholders become the new center of the capitalist universe and its new gospel.

The shift in goal entails a transformation in management practices from those of hierarchical bureaucracy, including a shift from controlling individuals to enabling teams, networks, and ecosystems; a shift in the way work is coordinated from rules, plans, and reports to agile processes and dynamic linking; a shift from the values of efficiency and predictability to those of continuous improvement and transparency; and a shift from one-way, top-down communications to interactive conversations. These shifts are not just a grab-bag of unconnected management gadgets. They constitute a coherent constellation of leadership and management practices, as described by more than a score of books.

The confusing reality of the moment, however, is that there are (at least) two different systems, operating simultaneously, at different speeds and on different trajectories.

One—the Traditional Economy—is the economy that we inherited from the 20th Century. It’s a world of command and control, focused on making money through economies of scale and comprising big hierarchical bureaucracies that push out products and services and get customers to buy them with sales campaigns and advertising. This is still the larger of the two economies. It’s been in steady decline for a number of decades. It doesn’t generate net new jobs. It’s not very agile. It’s becoming steadily more efficient. But it’s not good at innovation. It’s less and less able to capture the gains of its efficiencies. It’s still a big part of what’s going on in the world. But it doesn’t have much of a future.

The other economy—the Creative Economy—is an economy of continuous innovation and transformation. This is the economy of firms and entrepreneurs that are delivering to customers what they are coming to expect, namely, “better, faster, cheaper, smaller, lighter, more convenient, and more personalized.” The Creative Economy is still relatively small but it is growing rapidly and, when implemented well, is highly profitable. It is the economy of the future. It doesn’t have to be invented: it’s already under way. Its practices represent a paradigm shift in the strict sense laid down by Thomas Kuhn: it’s a different way of thinking, speaking, and acting in the world.

The shift from the Traditional Economy to the Creative Economy isn’t just a technical wrangle about economics or management theory. It’s a shift in what society demands of the managers of its most powerful institutions: from narrow definitions of their owners and decisions that serve their short-term interests, to broad acceptance of the responsibility that comes with power and leadership concerned with what is best for society. In the shift, we are learning that an argument about the proper activities of managers can be logical, can be strongly argued, can influence decades of practice in the world’s largest corporations – and can still be plain, flat, dead wrong.

 

This post is part of a series of perspectives by leading thinkers participating in the Sixth Annual Global Drucker Forum, November 13-14 in Vienna. For more information, see the  conference homepage .

Will Tim Cook Ever Escape Steve Jobs’s Shadow?

Being the successor of a successful leader is one of the toughest challenges. How can you do more? There’s a lot to lose and few chances to win. Should you replicate the winning leadership style of your predecessor? The chances are that you will likely do worse. Should you change and build a new style? You risk destroying a well-tuned machine that works perfectly.

Three years ago Tim Cook accepted such a challenge. After a transient of three years without significant innovative product launches, yesterday he unveiled his first move into a new product category: smartwatches. He announced the Apple Watch with the well-known sentence that Steve Jobs used at the end of his speeches: “One more thing…” Regardless of what you thought of the latest smartwatch, those words are a cause for concern.

Like others’ initial reactions to the Apple Watch, mine are mixed. It has an excellent design. Apple also obviously worked intensively on the user experience. And it provides some delightful features, such as the digital touch that allow a new type of social interactions among people who wear the watch and are next to each other (e.g. by sending your heartbeat to the watch of your lucky friend).

But is the new smartwatch another example of Apple entering an emerging product category late and proposing a new interpretation that offers a more meaningful user experience? I’m not totally convinced. This time Apple seems less bold. It does not really reinvent the category; its differences from other smartwatches already on the market (e.g., Motorola’s Moto, Sony’s SmartWatch, and Samsung’s Gear) are not striking. Some commentators likened this lack of breakthrough features to other Apple copycat moves (e.g., the new iPhone 6’s bigger screens, which follows Samsung’s lead). According to some, this is a sign that Apple has lost its magical touch.

That said, the Apple Watch could be a winner. Customers (and app developers) will ultimately determine its success.

I’m more concerned about the tone of yesterday’s event and what it reveals about Apple’s leadership. The event came across like a replay of a movie I had already seen: the same format used by Steve Jobs — the same staging, colors, lighting, pace, and agenda; (almost) the same faces and voices, with the same magnifying adjectives celebrating the products features; the same “one more thing,” and the same band (U2) closing the event. In some moments, the thin silhouette of Tim Cook even reminded me of Jobs.

Apple loves art. So let me use an art-based analogy to describe my feelings. Yesterday’s extravaganza looked as if Apple’s leadership had entered a Mannerism period: In the 16th century, after the radical changes introduced by Renaissance masters like Leonardo, Raphael, and Michelangelo, many artists found it difficult to blaze a new path and instead copied and exaggerated their predecessors’ styles. It was a more sophisticated but also more artificial way of painting that lost the harmonious and natural dynamics of the Renaissance. In other words, yesterday’s extravaganza came across to me like an exaggerated celebration of Jobs’s style.

For Apple, the risk is Cook is applying a leadership recipe that has run its course. Every organization needs rituals, self-celebration, and stability, of course. But it also needs renewal. Not only because markets and competition change, but also because people in an organization — especially the youngest and freshest members of it — need new causes. They need new rituals and “manners” that they have helped create. This gives them a sense of ownership of the future and fuels new energies. As several innovation and strategy studies show, the most pernicious competitor of a successful organization is not out there in the market; it’s inside. Perhaps the strongest competitor of today’s Apple is Jobs’s Apple.

For Cook, as a leader and as a person, the risk is that by staying on the same path, he will never be “as good as Steve.” The risk is that one day, looking back to these years, he will have a feeling of having been good but never good enough. For sure, Cook’s leadership style has been forged by his closeness to Jobs. And for sure, there is a sense of emotional attachment, a sense of gratitude. But no one is the same. Perhaps Cook’s own style would be good for Apple and allow it to achieve greater heights; perhaps not. But at least he should give his organization and himself a chance to do so.

My hope is now that Tim has proven he can lead Steve’s way, he will feel free to move on and lead Tim’s way.