Marina Gorbis's Blog, page 1347

Strategy Lessons From Jean Tirole

Why did Jean Tirole win this year’s economics Nobel?

Here’s one key reason: “Jean has a bit of magical quality of being able to take very complex situations where there are a lot of different moving parts and a lot of institutional details and structuring the essence of it in a relatively simple model,” says Harvard Business School professor Josh Lerner, who has co-authored several recent papers with Tirole. “Obviously models have to simplify reality, but one of the real skills is essentially being able — it’s an art, not a science — to say, ‘What are the key levers here? What are the aspects that distill the situation down to its very essence?’”

In other words, Tirole does what modern academic economists do, only better than almost anyone else. He is the eighth most-influential economist on the planet among his peers, according to the weighted RePEc citations ranking, and three of those above him on the list already have Nobels. Unlike Paul Krugman, another MIT PhD of Tirole’s generation with similar renown as a model builder who has gone on to a second career as a highly visible and controversial public intellectual, Tirole has mainly just kept on building those models — and at a seemingly youthful 61 will presumably just keep building them unless the prize curse gets to him.

The models Tirole builds are mathematical in nature, and start with individuals or firms that are assumed to be rational creatures out to maximize their utility, their profits, or something else along those lines. He then usually brings in the tools of game theory, in which his protagonists have to contend with other rational actors and the moves they might make.

In the “Scientific Background” essay on Tirole’s work provided by the Nobel committee, the focus is on Tirole’s work on industry structure, which has had a big impact on antitrust and other regulation, especially in Europe. The basic story is that early antitrust and regulatory ideas that didn’t have much basis in economic theory were brushed aside in the 1970s and 1980s by the University of Chicago-based “law and economics” movement, which basically taught that competition conquers all, even in pretty concentrated industries. Then a new generation of economists, with Tirole at the lead, showed that a rigorous, orthodox economic approach, if you threw in a little game theory and information asymmetry, actually delivered much more complicated results. Sometimes business regulation improved social welfare, sometimes it didn’t, usually the key was exactly how the regulation was structured.

The implications of this for, say, broadband Internet regulation have been discussed at length elsewhere, so I’ll leave it there. But Tirole’s 1980s work on industrial organization also found its way into thinking about business strategy. The academic study of strategy took a big leap forward in the 1970s when Michael Porter of HBS looked at earlier economic research on industry structure and noticed that market power — which economists wanted to minimize — was the same thing as sustained profitability, which corporate executives wanted to maximize. Porter then used the tools of microeconomics to craft advice for executives on how to get and hold on to that power.

In the early 1980s, the game theory approach to studying industries promised to be the next big wave in strategy. A series of papers (sample title: “The Fat-Cat Effect, the Puppy-Dog Ploy, and the Lean and Hungry Look”) by Tirole and game theorist Drew Fudenberg, who is now at Harvard, seemed to promise firm answers to timeless business questions like, “Should we enter this industry?” “Should we lower our prices?” “Should we increase production?”

“When I was just starting at HBS [as a professor] in 1983, Fudenberg and Tirole were kind of the reigning duo of young theorists,” says Pankaj Ghemawat, who now teaches at NYU’s Stern School and the IESE Business School in Barcelona. “Every single working paper of theirs was eagerly awaited.” For Ghemawat, what followed was a bit of disappointment. Game-theoretic models of industry did indeed often offer wonderfully explicit advice. But it turned out that slight changes in the initial conditions in a model might deliver wildly different advice. And so since the 1980s, he says, “the interest has shifted more to empirical work out of concerns that you can rationalize just about any kind of behavior with a game theoretic model.”

Still, that work has continued to be informed by Tirole. His 1988 book The Theory of Industrial Organization became the standard graduate textbook on the topic. “Many of us who have wound up teaching strategy and doing research in strategy grew up learning game theory from Tirole’s textbook,” says Jan Rivkin, the chair of the strategy unit at HBS. “Game theoretic thinking certainly influenced the strategy field, and Tirole was as influential as anyone in that shift.”

As an example, Rivkin cites the notion of commitment, which Ghemawat wrote a book on. “Game theory models, including some of Tirole’s models, show that a firm can sometimes advance its interests in odd ways,” Rivkin says. “For example, a firm can change its own payoffs and make it attractive to respond aggressively to a rival’s move. If the rival understands those payoffs, the rival might forego the move. Many of us teach such ideas — that one firm’s commitments can change another firm’s actions — in our classes today.”

More recently, Tirole put himself back on the strategy professors’ radar with a 2002 paper, co-authored with Jean-Charles Rochet, now of the University of Zürich, that examined the dynamics of competition in “two-sided markets” that “are characterized by the presence of two distinct sides whose ultimate benefit stems from interacting through a common platform.” This describes lots of modern digital enterprises — think Google and Airbnb — as well as most traditional media companies, and has been discussed a lot already in this week’s coverage. But the significance of the paper seems less in that offers any definitive answers to how to think about the phenomenon than that it kicked off what is a now a rich (if still not exactly conclusive) literature on what are now also called multi-sided platforms. “I don’t know how profound you can say the influence will be,” says Joshua Gans, a professor of strategic management at the University of Toronto’s Rotman School of Business, “but it was at a time where he was a pioneer racing to the fore in terms of thinking about strategy in those sorts of markets.”

Gans thinks Tirole’s most remarkable accomplishment might be his graduate-level textbooks. The Theory of Industrial Organization was just the first. Together with Fudenberg, Tirole wrote Game Theory in 1991. In 1993 it was A Theory of Incentives in Procurement and Regulation with Jean-Jacques Laffont, the late founder of the Industrial Economy Institute at the University of Toulouse, where Tirole has taught for almost two decades. Then, in 2006, came The Theory of Corporate Finance — not a field Tirole had really been known for. “That appeared out of nowhere,” says Gans. “Corporate finance? Since when? Sheesh, when did he do it?”

Gans wrote right after the Nobel announcement that he has “a whole shelf … and not a decorative shelf” of such books by Tirole and has relied on them throughout his career. “There’s very few people who can really absorb more than one of these. They think Jean Tirole is the IO guy or the corporate finance guy or the game theory guy.”

The aim here clearly hasn’t been making money — for that you need to write introductory textbooks for undergraduates. It’s to teach and to influence Tirole’s fellow economists, both in the academy and in government, mainly in the direction of carefully formalizing their analyses and arguments in mathematical terms. This is of course the direction economics has been headed in for more than half a century — Tirole certainly didn’t start it, and he’s been more careful and less ideological about it than many of his peers. But there is ideological content to the very methods that economists use, which Tirole acknowledges with dry humor near the beginning of his corporate finance textbook.

“Many politicians, managers, consultants, and academics object to the economists’ narrow view of corporate governance as being preoccupied solely with investor returns,” he writes. Then, after promising to revisit that debate a few pages later, he adds, “we should indicate right away that the content of this book reflects the agenda of the narrow and orthodox view.”

In recent years Tirole has taken some steps beyond the narrow and the orthodox, although always with his mathematical-economic toolbox in hand. A 2003 paper with Princeton economist Roland Bénabou starts out by agreeing with psychologists’ and sociologists’ long-standing critique that the use of economic incentives (paying your kid to do homework, for example) often backfires. But Bénabou and Tirole then go on to try to explain that backfiring in purely economic terms. Those are the tools Tirole knows how to wield so brilliantly, after all.

Gender Balance Is Hard, but It’s Not Complicated

Large, established organizations are finally starting to accept that gender imbalances are a business problem. Yes, Microsoft’s CEO Satya Nadella recently lit up the blogosphere with his unfortunate suggestion that women should not ask for pay raises. (He quickly apologised.) But gaffes like his are increasingly out of step with the mainstream. This summer, Google publicized the gender balance of its workforce, and vowed to improve. This led other large tech companies to do the same. Leaders at Harvard Business School have admitted the school has not been hospitable to women, and publicized their efforts to improve in a front-page New York Times story. These and other changes are evidence of a steady and growing recognition that today’s gender imbalance are a business and leadership issue.

We are literally – and collectively — changing our minds. Slowly but surely, the shift from the 20th century view that “gender imbalance is a women’s problem” to the more 21st century “gender imbalance is a leadership challenge” is beginning to take root.

It is now important to design the right response. To maximise this moment, leaders need to proceed strategically:

First, lead the charge. The number one driver of better gender balance in large corporations is leadership. If leaders don’t get it, buy it, and sell it, no one else can make it happen. Leaders must be the change they want to see (not just call for change). This requires a thorough understanding of the issues and how to address them.

The best CEOs publicly commit to high-performance meritocracies that recognise and serve a more gender balanced economy and customer base. Acknowledge publicly that you are not yet there (many of your managers probably assume that you are). A bit of mea culpa is not out of place here – vulnerability is increasingly becoming a leadership competence. After 20 years of companies focusing most of their well-meaning but ineffective efforts on fixing women (think assertiveness training and women’s networking events) it is helpful to acknowledge that you’ll be making a shift in approach. And not just by throwing training at mid-level managers. Many managers are bored or skeptical about gender initiatives, so leaders need to prove that they themselves are convinced. Commit to creating a balanced business. Sell this vision. Enthusiastically. Repeatedly. Repeatedly.

Cisco’s John Chambers is a good example. After meeting with Sheryl Sandberg, he admitted that he hadn’t quite “gotten it,” and communicated this admission widely to his employees. “While I have always considered myself sensitive to and effective on gender issues in the workplace, my eyes were opened in new ways and I feel a renewed sense of urgency to make the progress we haven’t made in the last decade… while I believe I am relatively enlightened, I have not consistently walked the talk … What we have been doing hasn’t worked, and it is time to adjust.”

Unilever’s Paul Polman has simply communicated that the company will never achieve its growth and sustainability targets without getting the gender balance right. “Unless we recognise the critical role that women play and unless we involve women more directly in developing solutions, then we are destined never to fulfil our potential.”

Google was the first Silicon Valley tech company to come clean on the reality of its gender situation, admitting that it was wrong to avoid transparency. “We’ve always been reluctant to publish numbers about the diversity of our workforce at Google. We now realize we were wrong, and that it’s time to be candid about the issues. Put simply, Google is not where we want to be when it comes to diversity, and it’s hard to address these kinds of challenges if you’re not prepared to discuss them openly, and with the facts.”

Whatever the exact language, the CEO and the core of the company has to take responsibility. The problem is that many CEOs delegate the issue to a Head of Diversity, most of whom don’t even report directly into them. It takes courage and years of proactive, public pushing from the top to make gender balance happen. You get what you envision.

Second, explain why it matters. Many people think the business case for gender balance is now so obvious that it doesn’t require repetition. In my experience, this is the crux of the challenge. Most managers simply don’t understand the complexity of the issue, and even those who do are not usually ready to preach it to others. Each company needs its own, fact-based explanation of how this relates to the bottom line. Leaders need to make the link to their own businesses, in a convinced and convincing way. You need to make the case and explain why gender balance is an urgent global business imperative – just as explaining “why” is important for any key business initiative. Then get all your leaders to repeat the same, aligned message with their teams.

When Marijn Dekkers became CEO of Bayer — and the first non-German CEO of a DAX 30 company — he knew he’d have to explain why an extremely successful, 150-year-old company might want to change. And he did, over and over, in a variety of media, making it very clear that diversity was a priority.

“One of our most important current innovations,” he wrote, “may not be technological. It may be our skill in managing new talent and market realities. The better we can understand and connect with customers (and potential customers) the stronger we will be… Evolving the balance of nationalities and genders in BAYER’s management is not a management fad. Nor is it the result of German government quotas. It’s simply good business. We want to look like, sound like and anticipate our customers’ needs.”

Beware of purely ethical arguments around diversity and fairness. While this works for many managers, many others will argue that the lack of gender balance is simply due to women’s choices, and has nothing to do with fairness. In our experience (although ethicists struggle with this) a business-driven reason for balance is essential to garner more broadly-based support. This is especially true in countries that are still culturally attached to highly differentiated gender roles.

Finally, build skills. Working across genders, like working across cultures, is a management skill. It requires education, awareness, and the ability to differentiate between real differences and unconscious biases. Help managers understand the current situation in their organizations. What’s the current gender balance among customers? Among employees? At different levels and across different functions?

Most companies also need to spend time educating managers to understand the different behaviors, preferences and concerns of men and women – as customers and as employees. They need to see both the impact of those differences – and how to leverage them to create value. Make a distinction between actual differences and stereotypes. Managers need to understand why both genders get judged negatively for behaving outside of traditional gender roles – and why both genders unconsciously associate leadership with masculine traits. We need to stop fixing the women, but we should also avoid starting to fix the men.

When done constructively, men and women enjoy building skills that immediately unlock opportunities with customers, employees, and stakeholders. Inviting people to courses on “bias” or “stereotyping” is not the best way to prime them for working well together — so seek to be eye-opening and positive, putting your focus on generating opportunities that blind spots may once have concealed.

This does not need to take years; it does not take a global cultural change initiative for any manager to balance their own team. What it does take is changes to business systems (career management, leadership criteria, product and service design and delivery).

Many companies want to simply jump in with skill building – often framed as bias training — without having leadership take a strong stance, and without explaining why this matters to the overall health of the business. But unconscious bias isn’t always the problem. Entrenched business systems often are. And unless leaders decide on the change they want – and explain why it matters—those systems won’t budge.

The risk of investing in training before steps 1 and 2 are in place is that people feel they have done a huge amount (and invested time and money) and it just doesn’t work. That creates a whole new layer of gender fatigue for the future.

Leadership, language, and skill are extraordinarily important in developing effective (and accountable) agents of change. Most managers are very willing to change if you equip and empower them in the right way. And of course, if you then celebrate and promote the ones that are walking the talk — there is no clearer incentive to change than promoting the people who have built balanced teams and unlocked new business opportunities.

Again, this does not require a huge culture shift. It requires the momentum that comes from a strategic push towards a clear vision, backed by strong leadership and skilled managers.

How to (Gradually) Become a Different Company

A number of recent headline-grabbing announcements of divestments and split-ups by companies such as HP (spinning off its PC and printer businesses), GE (the sale of its appliances business to Electrolux), Bayer (the flotation of its MaterialScience chemicals business), and Royal Philips (its separation into two autonomous companies, Lighting and HealthTech) are putting the spotlight again on the phenomenon of “core shifting”: how a company, through a sustained process of acquiring and divesting assets, changes the mix of its business portfolio and thus purposefully shifts the core of its activities.

PPG (originally “Pittsburgh Plate Glass”) is a splendid example of such a transformation. The US-based company used to be a diversified industrial group, with activities in all types of glass, chemicals, paints, optical materials, and biomedical systems. Through a raft of acquisitions and divestments since the early 1990s, it has transformed into a focused world-leading coatings manufacturer with $15 billion in sales. Since 1995, when glass and coatings each accounted for about 40% of sales, the split has evolved to 93% coatings and 7% glass today.

What makes such a transformation successful? From our analysis of a number of core shifts and conversations with the CEOs who have undertaken them, we have drawn five keys to success:

1. Allow time and persevere. Pulling off a core shift takes many years, if not a decade, as PPG and other companies have shown. For example, it took Umicore, a global materials technology group, five years (2002–2007) to lay the basis for its transformation from a commodity supplier of base metals into a premium provider of emission control catalysts, rechargeable battery materials and other value-added solutions. It initially lost about half of its revenues by divesting its copper and zinc smelting business, but by 2010 it had quadrupled its revenues to €2 billion through a combination of acquisitions and organic growth.

A core shift takes time for several reasons. First, such transformations consume resources, both financial and human. A company needs the financial firepower to make the required acquisitions on top of the capital investments in its ongoing business. Even more important, it takes management time to align all teams, including those of the acquired businesses, to the transformation initiative. Second, finding value-creating acquisition and divestment opportunities requires patience. Third, some stakeholder groups may want to see confirmation of the positive impact of a given move before consenting to continue on the chosen path.

2. Be clear about the destination, yet flexible about the path. To keep all stakeholders aligned over the course of the transformation, the company’s executive team should be clear and unrelenting about the vision of its future and the rationale thereof. Consider Eaton, which used to be a manufacturer of vehicle components such as axles and transmissions. During the past two decades it has transformed into a provider of electrical, hydraulic, and mechanical power management solutions. Throughout this period it has been communicating regularly about its leitmotif of becoming a diversified company with more consistent earnings. Accordingly, it has systematically published figures about the evolution of its business portfolio in terms of sales by segment (e.g., vehicles decreasing from 40% of total in 2000 to 17% in 2013), by destination (e.g., the U.S. from 80% in 2000 to 50% in 2013), and by exposure to the economic cycle.

While the overall desired direction of the transformation should be clear, the actual path to get there is unpredictable. The executive team should not commit to specific moves, as factors outside of their control might require a change of plan. For example, the company may have identified the perfect acquisition target, but be outbid by a rival. Or the economic cycle may suddenly turn and thus make it impossible to divest an activity as planned at a fair price. What is important is to create options and exercise them as the right opportunities arise.

3. Go for the occasional mega-acquisition. Acquisitions are part and parcel of a transformation. While the number may vary from one year to the next, companies such as PPG and Eaton have been acquiring on average one company every quarter for the last two decades. Having said that, what really gives traction to a core shift is the occasional mega-acquisition that is emblematic of the vision and that catapults the company forward. For example, Umicore’s 2003 acquisition of PMG increased its revenues by 50%. Eaton’s acquisitions of Westinghouse’s distribution & control business (1994), Aeroquip-Vickers (1999), and Cooper (2012), increased revenues by roughly one-third with each addition.

Of course, it takes time to digest such acquisitions and restore the company’s financial firepower, which often results in a transformation pattern in which a period of consolidation follows a period of acceleration.

4. Communicate consistently and transparently. Clearly communicating about the vision and its rationale is crucial to keeping everyone committed, whether they’re employees or external analysts. Particularly important are the managers and staff of businesses that have been earmarked for divestment. Clear, open, and up-front communication about the company’s intention and the rationale thereof is essential to keep them motivated and prevent value destruction. Their business should not be labeled a “cash cow” or a “problem,” and their staff must not feel second-class. The message is that the divestment should be beneficial to the business concerned, as its future owner normally will see greater opportunities to create value than its current owner does. The best way to demonstrate the veracity of that message is to continue to do business as if the divestment decision had not been taken, i.e., continue to recruit, invest, and even acquire smaller entities that strengthen the value of the business to prospective buyers.

5. Safeguard the short-term performance of the ongoing business. While M&A transactions absorb much of senior management’s attention and attract great interest from financial analysts and the business press, the company’s operational performance will ultimately make or break the transformation. If short-term performance slips, pressure will mount and stakeholders will question, rightly or wrongly, the pertinence and/or viability of the long-term transformation.

The experience of Chiquita Brands International provides a case in point. Some 10 years ago, the company embarked on a transformation that was meant to reduce the exposure to the volatility and asset intensity of the legacy banana business by shedding ships and farms on one hand, and by acquiring and developing branded healthy snacks on the other hand. However, a significant decrease in profitability and free cash flow over time led the company to change course in 2012 and return to the former core of branded commodity produce, under the leadership of a new CEO.

As is always the case with tips, use them wisely, as fits best. They may not all be applicable in the same way and to the same extent at every company. But when it comes to shifting your business’s core, it usually pays to be tenacious, visionary, bold, transparent, and results-oriented.

Whatever It Is, You’ll Get Over It

Despite wars, famine, economic collapse, and personal tragedies, a majority of human beings feel happy a majority of the time, extensive studies have demonstrated over the past two decades. In fact, people seem to have “happiness set-points” to which they return after even the most extreme perturbations, says a team of researchers led by Ed Diener of the Gallup Organization. The reason for our baseline happiness may have to with evolutionary advantage: A good mood leads to greater creativity, sociality, and, ultimately, reproductive success, the researchers say.

The Dark Side of Efficient Markets

It is generally accepted that efficiency represents the optimal, aspirational state for any market. Efficient markets, which feature many buyers and sellers and perfect information flowing between them, determine the “right price” and hence allocate society’s resources optimally.

Those are indeed positive features. But every good thing is like a face caressed by the sun. The rays that light and warm the face automatically cast a dark shadow behind it. The shadow of an efficient market is increased price volatility — quite the opposite of what we expect from efficient markets.

Think about how markets evolve. We’ll take the market for corn as an example. Farmers used to grow corn, take it to the local market, and sell it to families who use it to bake and cook. Primitive markets like this have two classic features. First, buyers and sellers have to be near to each other so it is a narrow and shallow market, restricted to relatively few people. Second, the value in the exchange is determined by immediate use. The buyer plans to consume the corn relatively promptly, not hold it as an investment or resell it.

As markets such as these evolve and the density of buyers and sellers increases, another actor inevitably arrives: the market maker who facilitates trading between sellers and buyers. They are useful. They help sellers find buyers and vice versa. With their participation, the market in question becomes more efficient. Suppliers can better find the buyers who want their good or service most and buyers can find all the suppliers of the item that they want. These are all good things.

But there is an unintended consequence. Actors in the system typically start to speculate. A market grows for those who imagine what consumers might find the good to be worth in the future. In due course, that corn gets traded not in the local market but on the Chicago Board of Trade (CBOT). In the very earliest days, real users of commodities were important players at the CBOT. They made contracts with sellers using the CBOT and actually took delivery of the corn they bought.

But that all changed over time. In the modern era, only a minuscule proportion of CBOT trades are intended for delivery. The vast majority are trades made on expectations of future value, not current use. Buyers don’t want to take delivery on the corn, soybeans, or pork bellies. They are simply trading based on their beliefs about the future value to hypothetical future users of the product in question.

In the natural evolution of markets, as markets become more efficient, they turn from being use-driven to expectations-driven — like equities, real estate, or derivatives based on both.

For this reason, the unintended consequence of efficiency is price volatility. In a use-driven market, the value of a good or service rarely changes dramatically in a short period of time. The value of a peck of corn to a family who needs to eat won’t change much from week to week — because the use is immediate and human habits don’t change quickly. Indeed, if the weather in the growing season starts to deteriorate, then prices will migrate higher over the growing season as buyers and sellers both see that supply will be tight following the poor growing season.

To be sure, dramatic events can cause use to swing very quickly. When a hurricane approaches the Florida coast, the price of plywood can spike because everybody suddenly knows they need to board up their windows. After the hurricane, prices drop back to normal. But this is the exception, not the rule, in use-dominated markets.

Efficient, expectations-driven markets shift quickly for two reasons. First, expectations, unlike uses, have no bounds. They are the product of human imagination, which is ruled alternatively by fear and euphoria. There is simply no limit to how far and how fast expectations can shift. Every bubble and crash reinforces this. Dot-com companies weren’t worth anything close to what their expectations suggested in 1999-2000, nor probably as little as their adjusted expectations implied after the bust. The same held for packages of securitized mortgages in the summer of 2008 and for Dow Jones 30 stocks in March 2009.

Second, expectations extend deep into the imagined future. Rising rents for a piece of real estate may be expected to rise forever. Profit growth of a company may be expected to continue ad infinitum, or losses until bankruptcy. Thus when expectations change, the change is implicitly projected far into the future and discounted back to the present, resulting in a much amplified change in value. One bad quarter can trigger a run on your stock and one good quarter can prompt a feeding frenzy.

So efficiency doesn’t inherently produce smoothness and stability in prices; it produces spikiness, the dark side of efficiency and expectations.

That dark side has not gone unnoticed. It has spurred the growth of an entire industry that exists only to exploit volatility: the hedge fund business. Thanks to the fact that their compensation is dominated by their carried-interest (the 20% in the famous 2&20 formula), their returns are driven by volatility — the more the better. And if more is better, why simply wait for volatility to happen? Why not band together to purposely exacerbate and profit from volatility?

Meanwhile, there are all sorts of good folks operating in use-driven markets, producing goods and services that we use on a daily basis. Most are organized as public companies with stock prices that are jerked around by the volatility aficionados. So while they are working on something that we all want — more and better products and services — they have to deal with the a huge group of influential wielders of capital who exist only to exploit whatever level of volatility they can create.

This is the dark side of efficient markets: systematically high volatility and an entire industry that exists to exploit and exacerbate it.

 

This post is part of a series leading up to the annual Global Drucker Forum, taking place November 13-14 2014 in Vienna, Austria. Read the rest of the series here.

The Condensed November 2014 Issue

Amy Bernstein, editor of HBR, offers executive summaries of the major features. For more, see the November 2014 issue of HBR.

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Zumba’s Success Arose from Long-Term Trends

How do some brands manage to resonate so strongly with the public that they seem to get woven into the fibers of culture? How do their taglines become rallying cries for change (“Where’s the beef?”), their brand names become verbs (“to google” stands for “to search online”), and their products create completely new lifestyles (Apple iPad)?

These brands create their own cultural movements or advance emerging ones in ways that position themselves as the arbiters of popular culture. That’s why they outlast fads like cronuts, Silly Bandz, and Angry Birds. They establish meaningful, lasting connections between their products, people, and the world around them. They decipher where society is going in the long term and figure out how their brand adds value to that direction.

Zumba, the fitness dance movement, has achieved this level of cultural significance. Founded a little over a decade ago, the organization reports more than 15 million weekly participants in over 200,000 locations across more than 180 countries, and its social networks enjoy a combined following of 7.5 million. As the company releases a constant stream of videos, conferences, apparel, equipment, and music, the brand has become a phenomenon.

When Zumba launched, the concept tapped into several emerging trends that together created the right conditions for it: increasing Latin influence on mainstream American culture, emerging social networks, and growing awareness of physical activity’s importance to health. Instead of following a single trend, the brand thrived on several complementary developments and so was able to lead its own movement.

It started with a bold vision. “Our purpose at Zumba is to change lives through health, wellness, and overall happiness,” said Zumba CEO, CMO, and cofounder Alberto Perlman. This sweeping vision echoes the essence of Zumba culture: “FEJ,” which is pronounced “fedge” and stands for Freeing, Electrifying Joy. Like other brands that manage to elevate their perceived value above the merely commercial exchange of goods or services for money, Zumba believes it is on a mission. Its leaders are not satisfied simply to make the headlines – they want a place in history books. Being driven by a higher purpose serves as the foundation for breakthrough brands.

And, importantly, Zumba connects its internal culture, FEJ, to the larger external context, particularly by inspiring many students to become trained as instructors, entrepreneurs who run their own Zumba communities, and evangelists who recruit new students and instructors. As such, Zumba has established authentic relevance and deeper emotional connections with its customers. In fact, the connection between Zumba’s external and internal culture is so strong that the line between the two worlds has become blurred.

The Zumba brand flourishes in this self-reinforcing loop. Recently the company introduced a new mantra to its network of instructors, “Let It Move You,” that it’s now promoting to the public in a TV advertising campaign. The internal-external connection of the brand is evident in Perlman’s explanation of the campaign: “Our number one goal is to support our licensed Zumba instructors and inspire millions to get off the couch and moving in a Zumba class.”

Achieving Zumba’s level of cultural impact is the result of anticipating and advancing cultural movements instead of chasing trends. Great brands like Zumba constantly scan the cultural environment for signs of meaningful, long-lasting change that might affect them. They seek to understand the potential — as well as the existing — role of their brand in people’s lives and in broader culture. They keep abreast of new technology, demographic shifts, consumer tastes, laws, resource prices, and competitive behavior. And they identify possible ways to exploit developments in these fields to give their customers more reasons and more opportunities to engage with them.

Cultural movements represent forces that shape the way people live. Great brands use cultural movements to create futures in which they thrive and grow.

Experiment with Organizational Change Before Going All In

Think about the last time you considered introducing a significant change in your enterprise with the intention of improving organizational effectiveness. Maybe you were contemplating a change in employment policies such as flextime or one in customer-facing processes such as a new billing system. You likely studied the proposed change in detail, discussed it at length with relevant colleagues, came up with a strategy for implementing it, and then introduced it. A crucial step is missing from this process, however: a rigorous way to determine whether the change is accomplishing its intended objectives.

Why do organizations so often introduce such new initiatives without thinking about this step? Behavioral economics, the discipline that combines the fields of psychology, judgment and decision making, and economics, offers an explanation.

When we think that a particular course of action is the correct decision, our human tendency is to interpret any available information as supportive of that course of action. This tendency is known as confirmation bias — our perspective on the world is distorted in a way that tilts toward confirming our currently held views. Furthermore, once we start down a path and invest resources in it, we tend to justify our past investments by continuing down that path even when new information suggests that the path is unwise, a phenomenon known as the escalation of commitment.

Together, confirmation bias and the escalation of commitment lead organizations to refrain from evaluating changes because the key decision makers feel (erroneously) that they already know that the changes are good ones. The unfortunate result is that organizations persist in implementing ineffective policies and fail to even contemplate the possibility of superior alternatives.

That’s where experimental testing comes in. By forcing organizations to clearly articulate their goals and then to rigorously judge their decisions by those metrics, experimental tests can help managers avoid costly mistakes and can open up the consideration of other possible solutions.

When pharmaceutical companies conduct clinical trials to test the safety and efficacy of their drugs as part of the process for obtaining regulatory approval, some patients receive the drug and others some standard existing treatment or a sugar pill (placebo). A comparison of the two sets of results tells us whether the drug improves patients’ symptoms and has side effects. Many potential changes in your organizations can be subjected to a similar experiment: implement the change in some places, but not in others, and compare performance in the two groups to learn whether the change is effective.

Why can’t you sidestep the hassle of an experiment and simply compare the performance before and after a change? In some cases, this approach is valid, but in many cases the results will be misleading. Say you introduce an innovative new customer-relationship-management (CRM) tool for your sales force, and revenue increases by 15%. The change is a success, right? Maybe or maybe not. What you have neglected to ask is what would have happened if you had not introduced the change. Revenue might have increased by 20%. Without some knowledge of what would have taken place in the absence of the change, it’s hard to evaluate your success.

A handful of organizations have already embraced the principles of behavioral economics and the experimental mind-set. One is the Walt Disney Company’s R&D department, where one of us spent a summer. After identifying areas for cost reduction or process streamlining, it would design randomized experiments to test the effectiveness of possible changes.

In one project, the group looked for ways to encourage hotel guests to reuse their towels, an environmentally friendly practice that could also save Disney money. Group members designed an experiment to test whether having guests make a specific commitment to practice sustainable behavior and giving them a pin to symbolize that commitment would lead guests to engage in more eco-friendly behavior. The result: Guests who were randomly chosen to be part of the program were over 25% more likely to reuse their towels compared to guests who were randomly chosen not to be part of the program.

Having an on-site lab may not be feasible for many organizations, but it is still possible to engage in experimental testing without devoting vast resources to the effort. Careful experiments require three key ingredients, which can often be implemented with little incremental cost.

Identify a target outcome. This outcome must be something specific and measurable. “The effectiveness of the customer service call center” is too vague and might be narrowed down to “the percentage of incoming calls successfully routed to the appropriate technician within three minutes of receipt.”

Articulate what exactly your proposed change will involve. Simpler changes are often better, since complex changes with many moving parts make it difficult to identify the component that is driving results.

Introduce the change in some places in the organization (the “treatment group”) but not in others (the “control group”). Take the unit targeted for the change and divide it into two groups. Ideally, you’ll be able to flip of a coin to determine which places are assigned to which group; randomization helps to ensure that the two groups are similar, on average, right before the experimental test begins. Any differences in outcomes between the two groups can then be attributed to the change. When such simple randomization is not feasible due to logistics, ethics, cost, or sample size, more sophisticated analytical techniques can be employed.

Testing workplace practices in this manner is important because our own intuition regarding what will or won’t work is often mistaken. Take the issue of productivity. Most of us believe that if we fall behind on deadlines or commitments at work, we should simply spend more time working. Yet it turns out that people are actually more productive when they work a bit less rather than a bit more.

One of us (Francesca) conducted a field experiment on this topic with Giada DiStefano (of HEC Paris), Brad Staats (of the University of North Carolina’s Kenan-Flagler Business School), and Gary Pisano (of Harvard Business School) at a tech-support call center in Bangalore, India. The research team studied employees in their initial weeks of training to serve a particular customer account.

They were randomly assigned to one of three groups. Each group went through the same technical training with a couple of key differences. On the sixth through the 16th days of training, workers in one group spent the last 15 minutes of each day reflecting (in writing) on the lessons they had learned that day. Employees in another group did the same but then spent an additional five minutes explaining their notes to a fellow trainee. Those assigned to a control group just kept working at the end of the day and did not write down or share any thoughts they might have about the lessons they had learned.

In a test given at the end of the month-long training program, employees in the first and second groups respectively performed 22.8% and 25% better, on average, than the control group. This was in spite of the fact that trainees in the control condition worked 15 minutes longer per day than trainees in the other two groups. Though we focused on performance during training in this study, we found that reflection had a similarly beneficial impact on how people carried out their jobs day in and day out in terms of things such as productivity in entering data, teamwork, and service quality.

Think about the most pressing questions your own organization is facing. Would employees be more productive if they had flexible hours or the ability to work from home? Would your clients be more satisfied with your services if your processes were more transparent? Would your company be more successful in retaining talent if employees had greater decision-making authority? Your intuition may suggest answers, but it may be worth it to put them to the test.

Strategic Humor: Cartoons from the November 2014 Issue

Enjoy these cartoons from the November issue of HBR, and test your management wit in the HBR Cartoon Caption Contest. If we choose your caption as the winner, you will be featured in an upcoming magazine issue and win a free Harvard Business Review Press book.

“I was just looking for a simple yes or no.”

Bill Abbott

“Actually, no, his skill set isn’t evident at this point.”

Elizabeth Westley and Steven Mach

“There isn’t one.”

Crowden Satz

And congratulations to our November caption contest winner, Laren Hagen of Seattle, Washington. Here’s his winning caption:

“Introducing our newest member of the board: the CH2O.”

Cartoonist: John Klossner

NEW CAPTION CONTEST

Enter your caption for this cartoon in the comments below—you could be featured in an upcoming magazine issue and win a free book. To be considered for this month’s contest, please submit your caption by October 29.

Cartoonist: Paula Pratt

How Uber and the Sharing Economy Can Win Over Regulators

Sharing economy firms are disrupting traditional industries across the globe. For proof, look no further than Airbnb which, at $10 billion, can boast a higher valuation than the Hyatt hotel chain. Uber is currently valued at $18.2 billion relative to Hertz at $12.5 billion and Avis at $5.2 billion. Beyond individual firms, there are now more than 1,000 cities across four continents where people can share cars. The global sharing economy market was valued at $26 billion in 2013 and some predict it will grow to become a $110 billion revenue market in the coming years, making it larger than the U.S. chain restaurant industry. The revenue flowing through the sharing economy directly into people’s wallets will surpass $3.5 billion this year, with growth exceeding 25%, according to Forbes. The business model – where peers can offer and purchase goods and services from each other through an online platform – continues to be applied to new industries from car sharing to peer-to-peer fashion, among many others.

These firms bring significant economic, environmental, and entrepreneurial benefits including an increase in employment and a reduction in carbon dioxide emissions (in the case of car sharing services). Shervin Pishevar, a venture capitalist and an investor in Couchsurfing, Getaround, Uber and other startups in this space, believes these services will have a major impact on the economics of cities; “This is a movement as important as when the web browser came out.”

However, rather than rolling out the red carpet, city governments have resisted many of these new entrants issuing subpoenas and cease-and-desist orders. Just in the last month, Pennsylvania’s Public Utility Commission issued a cease-and-desist order on Lyft and Uber operations. The companies face fines of $1,000 per day, and 23 drivers face civil and criminal charges.

Regulation is often the most significant barrier to future growth for sharing economy firms. This is particularly unfortunate since the incentives of city governments and sharing economy firms are often aligned. Given the benefits these types of firms bring to cities and firms’ vested interest in the very consumer protections that city governments are seeking to ensure, one would expect a less rocky start for these new entrants.

The relationship between sharing economy firms and regulators will likely remain uneasy for the foreseeable future. But companies in this space can benefit from being more cooperative with regulators. As a manager in a sharing economy firm, you can increase the growth of your firm, reduce unnecessary delays, avoid conflict with regulators and expand access for consumers, by pursuing the following maxims:

Be offensive (rather than defensive) with regulators: The sharing economy is a new concept and many city regulators are unfamiliar with the business model. As a result they are often skeptical and assume sharing economy firms are trying to make a profit by skirting the regulations ‘traditional’ industries (i.e., taxis) face. It makes far more sense to be proactive and explain your business to regulators rather than wait for them to approach you with a concern. By approaching regulators yourself you can avoid misperceptions. It is likely in your interest to reach out to the regulators to explain your business and work with them early on to classify your business under the city’s existing regulatory infrastructure rather than having them come to you.

For example, Uber would like to be classified as a communications platform rather than a “transportation network company” and reaching out to local regulators could avoid challenges and conflicts down the road given the nature of the initial classification. Further, given the newness of the business model, regulators may not be aware of how existing regulation may unfairly bias one business model over another, particularly when comparing traditional and sharing economy businesses. For example, rules (currently under consideration in Washington D.C.) that prevent passengers using taxi services from specifying their destination in an effort to avoid discrimination would likely favor Uber and Lyft over Sidecar (which asks for your destination to facilitate true ridesharing). Firms should not hesitate to pro-actively make the case for fair policy to the relevant regulator.

Lastly, many sharing economy firms are true intermediaries, providing a platform for consumers rather than providing services directly, and should be regulated as such. Without explaining the nature of your firm you will likely be regulated as a traditional firm not as an intermediary resulting in higher taxes and requirements.

Be responsive to regulators’ legitimate concerns. Many sharing economy business models do raise legitimate concerns about user safety, privacy and access. Airbnb needs to be sure the apartments they list are safe for renters and Lyft needs to make sure the cars its drivers use are safe for passengers. Where regulators’ concerns are legitimate companies should respond, both because it is the right thing to do and because it will build credibility with the authorities. In making their case, companies should make arguments they would believe if they were regulators.

While it is easy to categorize business as in line with the free market and progressives as anti-market, the reality is far more nuanced. In fact it was a truly bipartisan coalition that drove the de-regulation of the trucking and airline industries in the 1970s. By being focused on consumer interest and responding to regulators legitimate concerns, sharing economy firms will reach a broader audience of advocates than they anticipated and better outcomes.

Use state of the art approaches to reaching out to government. Just as there are best practices in compensation or writing code, there are best practices in influencing public policy. Best practices in approaching government include, forming coalitions and industry associations to represent a shared point of view rather than each company approaching regulators independently and only in times of crisis. Further, sharing economy firms should seek outside validators. As President Lincoln once said about lawyers, “He who represents himself has a fool for a client.” This is even more true in the public relations sphere. Public officials are suspicious of self-interested argumentation and wherever possible it is best to use trusted external validators that can provide a credibility signal that government officials can trust.

Share your data: Data need not be made public in order to share it with government, and can help your case by reducing regulator concerns. Sharing economy entrepreneur, Shelby Clark, Founder of car-sharing service RelayRides, suggested the idea of metrics-based regulations. Under this model a firm such as RelayRides could share accident and insurance claim data that could lead to lower insurance requirements given a track record of infrequent accidents. Regulators, like the California Public Utilities Commission, need data to make sure ridesharing firms, for example, aren’t restricting access for people in particular neighborhoods or for the disabled. Sharing that data will likely ease these concerns for regulators and minimize requirements for firms. Sharing data about the number of users, for example, enables cities to see the benefits your firm is providing to their citizens in terms of increased transportation options.

Make a well-researched case for the value provided by your firm: Rather than relying on maxims about the usefulness of the sharing economy, it helps to have concrete data, especially in the face of skeptical regulators. Airbnb commissioned a study that found that; “Because an Airbnb rental tends to be cheaper than a hotel, people stay longer and spent $1,100 in the city, compared with $840 for hotel guests; 14% of their customers said they would not have visited the city at all without Airbnb.” These positive spillover effects are a compelling case for authorities in cities like San Francisco, the focus of the study. Although such research is inexpensive since much of it is already gathered by sharing economy firms, it is worth noting that supportive research may already exist, such as an analysis from Susan Shaheen, an expert from U.C. Berkeley, that found that, “car sharers report reducing their vehicle miles travelled by 44% (addressing travel congestion). In addition, surveys in Europe show CO2 emissions are being cut by up to 50%”. Firms should marshal such evidence and take it on themselves to publicize the benefits their firms provide.

Find the best regulations out there and share them with the government: City governments are often under-resourced and many existing rules are simply outdated and are not relevant given the business model of sharing economy firms. There’s no reason firms themselves cannot find the best rules out there and propose them to the Mayor’s office. It is a challenge for many cities to develop new regulations, and firms could take the first step to gather input from users and consumers to understand existing obstacles and identify outdated rules that need to be re-written in line with these new models. The California Public Utilities Commission decided that 16-point vehicle inspections were required in addition to background checks for drivers for ridesharing services, but a firm like Getaround could just as easily have proposed such a solution. Certainly city governments will make the final decision and firms should not be writing their own regulations, but if there are good rules out there, let the city know. 

It is easy to blame regulators for business problems and be right. It is more difficult but far more rewarding to avoid regulatory problems and enjoy business success. Since many of these businesses come out of Silicon Valley it is easy to think the largest risk is the underlying technology or competition. However, the major risk to the viability of many sharing economy firms is that a city or state government rules its business model impermissible. Hoping regulators play along is not an option, and antagonizing city governments is ill-advised. Instead, these firms need to find a new way to do business and should start by sharing with regulators.