Economics, at least as it was taught to me, was a non-experimental social science. Like others in this category—sociology, anthropology, or political science—economists could not, it was thought, conduct experiments and test hypotheses like their counterparts in the hard sciences. The chemist, the physicist, or medical researchers can control for all factors other than the one hypothesis he or she wants tested. The economist could do no such thing, but instead had to figure out how an economy already working actually worked. Or, as one common joke has put it, the economist’s job is to explain how something that works in practice works in theory.
Business pretty much worked this way, too, and for many firms it still does. Individuals or entrepreneurs invent stuff and then try to sell it. The farsighted and strong-willed ones are successful. Henry Ford knew what kind of car the masses of Americans would buy, and what his Ford Motor company would make: a simple black Model T. If consumers didn’t like it, they could go elsewhere. Likewise, Steve Jobs was famous for knowing what electronic devices consumers wanted and what they wanted the designs to look like. And he was mostly right. There are countless other examples of other companies and entrepreneurs who behave with such self-confidence and have been rewarded with success.
This chapter is about a very different way of thinking—the use of experiments in both economics and business, that has affected both domains but in parallel fashion. So far, there has been essentially no cross-pollination of lessons learned in the two arenas.
Nonetheless, I devote an entire chapter in this book to experimentation, for multiple reasons. First, experimentalism is the way much, if not most, of the world operates. It is not just scientists who first formulate hypotheses and test them, but also empirically oriented economists, which is most economists these days, who go about their business in the same fashion, although not in precisely the way that scientists do. Increasingly, many businesses are also borrowing scientific testing principles before and during the introduction of new products and services, as well as refining those they already are selling.
Second, experimental techniques are on the cutting edge of both economics and the business world and for that reason alone they deserve attention.
Third, my idealistic hope is that practitioners from each domain will begin to learn more from each other and, in particular, that some of those reading this book will not only draw that conclusion but actually apply it in their daily endeavors.
In what follows, I distinguish between two types of experiments. In economics, I first speak of laboratory experiments, which have their analogue in focus groups in the business world, since each type of experiment is conducted outside of the real world in an effort to improve the accuracy of predicting how those who live and work in that world will behave or react. I then turn my attention to field experiments, or those conducted with real-world subjects: randomized controlled treatments (RCTs) in economics (borrowed from pharmaceutical testing), and A/B testing and variations thereof in the business world. I close the chapter by discussing the importance of experimentation in innovation and entrepreneurship, which drives economic growth and thus, in a sense, blends the two separate worlds of academe and business I discuss in the chapter.
The notion that economists could learn something from a lab-like setting was so heretical that it took an iconoclastic economist from my hometown, Wichita, Kansas, to begin changing the way economists think and the way at least some economics research is now done.
That individual, Vernon Smith, did what came naturally not only to hard physical scientists, but to many businesspeople every day: He began to experiment, initially with students in his classrooms at the various universities where he has taught, and later in more controlled settings with students or other young people outside the classroom.
Unlike most other economists, who we know about only through their own writings or in some cases through essays or biographies written about them by others, we know about Smith both through his professional work and his remarkably candid autobiography.1 I draw heavily on that work in summarizing Smith and his ideas here. One other note: Unbeknownst to me as I was drafting this part of the book, Bloomberg View columnist Megan McCardle was finishing up her own terrific book, The Upside of Down, which also discusses Smith’s work in detail. I recommend her book to you for a lot of reasons, but if you want to know more about Smith and his experiments, you’ll find it there.2
Smith devoted much of his professional life to experimental economics by accident, mostly through his teaching, where he quickly became unsatisfied with the conventional material that was then and still is found in most economics courses. He credits in his autobiography the university that first hired him after graduate school, Purdue, and the chairman of its economics department in the 1950s and 1960s, Em Weiler, with nurturing his interest in experiments as a way of demonstrating to students how Smith believed economies, and more importantly the actors within them, really behaved. He refined his notions about experimental economics at numerous other universities, but mostly at the University of Arizona.
Drawing on the pioneering work of Harvard economist Edward Chamberlin, who used mock auctions to demonstrate how supply and demand curves work, Smith greatly expanded the use of experiments to confirm basic economic propositions. Like Chamberlin, Smith used students in classroom settings to make bids and offers, illustrating in the process how prices and quantities of a hypothetical commodity converge to their theoretical competitive equilibrium. He found in the course of running these experiments that it doesn’t take a large number of competitors to generate the competitive result found in the supply and demand graphs that populate introductory economics textbooks.
Smith worked with various colleagues over the years to refine his experiments, and to show they could be applied outside the classroom and in the real world. In his words, Smith confirmed to me that by far the most practical application of his ideas was in the design of bidding procedures for wholesale electric power, which he developed in conjunction with Stephen Rassenti at Arizona. Initially, Smith and Rassenti proposed such a system for the power commission in the state, which rejected the ideas as too impractical. Ironically, they were picked up and implemented in the 1990s in New Zealand and Australia, and also by the electric utility company Ohio Edison.4
It is difficult to overstate the extent to which Smith’s work was long viewed to be out of the mainstream by the rest of the profession, where members spent their time either theorizing or using regression analysis and other statistical techniques (in both cases, using increasingly sophisticated mathematics) to test those theories. The standard view is that economic behavior could only be discerned when people or firms were using their own money in real-world settings. The notion that lessons could be drawn from laboratory settings where individuals were given play (or even small amounts of real) money and then tasked with spending it or using it in some fashion for purposes designed by the experimenters was not only the exception rather than the rule, but looked down on by many mainstream economists––until Smith was awarded the Nobel Prize, of course.
As evidence, consider the fact that fully 8 percent of all the papers published in several leading economics journals in 2011 used experimental methods or fell into the experimental economics category.5 That figure was up from essentially zero in 1973, the first year covered by the study. That same study also showed a sharp upward trend in empirical papers published with the author’s own data set, and downward trends in empirical papers using other data sets and purely theoretical papers.6 The sharp shift toward experimental economic research is no doubt heavily due to the fact that Smith’s influential work legitimized the field.
There is still the nagging question, though, about the extent to which economic experiments, conducted in laboratory settings, can be extrapolated into the real world with people’s own money on the line. Smith and his colleagues have shown that despite the skepticism, many various theoretical economic propositions can be confirmed through such experiments, while the experimental methods they have devised can be used more frequently in business settings.
As I discuss shortly, businesses increasingly have been taking up that challenge, but in a different way than Smith and other experimentalists have gone about their work; that is, by using methods approximating the randomized controlled experiments in the field that are the gold standard for assessing the efficacy and dangers of pharmaceuticals or evaluating various social policy interventions. And businesses appear to have done so without being prodded by economists.
Before I get to that story, however, it is interesting to summarize how some businesses have used a similar laboratory approach to that used by the economic experimentalists. The experimental method to which I refer is the focus group. Movie studios use them to test potential audience reactions to different plots, especially endings. Advertising firms use this technique, along with politicians, to refine their messages, increasingly tailored to very different audiences. Some firms use focus groups to identify products or product areas that consumers might be attracted to. Go to the web and type in “focus groups in business” and among the entries that immediately pop up are articles suggesting that entrepreneurs use focus groups, formal or informal, to test the viability of their ideas before committing much time and a lot of money to new enterprises.
There is a limit, of course, to the effectiveness of focus groups. By construction, they tend to be small, and thus may not be representative of larger populations. Also, what may seem to appeal in a small-group setting may not be readily accepted or welcomed when introduced into the wider marketplace, which is one reason companies may roll out new products or services in certain test geographic areas, getting feedback and introducing refinements before marketing to a much wider audience or market.
At the same time, if they are properly run, focus groups can yield insights in ways that mass experiments, which often call for binary (yes or no) responses, cannot. Focus group participants may volunteer in an unstructured setting ideas or reactions unanticipated by the focus group organizers. This can lead to “aha” moments that change messaging or product designs, or even foster new ideas that firms were not originally planning to pursue.
Economists for years have borrowed techniques from the social sciences, engineering, and mathematics to model or infer individual or collective behaviors. In recent years, a small but growing band of economists, led initially by Michael Kremer of Harvard, and in a much more expansive fashion by Esther Duflo of MIT and Abhibit Banerjee of Harvard, has looked to a favorite technique used in medicine and program evaluation: randomized controlled experiments. Duflo, who earned her PhD and has since taught at MIT, won the Clark Medal in 2010 and a MacArthur genius award in 2009.
RCTs compare treatment and control groups to test whether the tested medicine or policy intervention has had a statistically significant impact.7 Among the interventions the above-mentioned economists have tested are whether putting cameras in school rooms reduces teacher absences (it does), and whether microcredit programs encourage entrepreneurship in poor countries (also a yes).
Kremer, Duflo, and Banerjee are not the only economists who conduct RCTs. Roland Fryer of Harvard uses the method to test the impact of various school interventions, such as paying kids in some manner for their achievements. The late Elinor Ostrom, a political scientist who won the Nobel Prize in Economics for her work (joining several other non-economists), conducted pioneering experiments validating that groups can self-organize to share resources.8 Tyler Cowen even argues in his new, important book Average Is Over that the future of economics, and indeed possibly all social sciences, lies in a merger into a single social science, in which researchers will specialize in the crunching of large bodies of data, some from experiments. The empirical results will drive the theory, not the other way around.9 I have more to say about this projection in Chapter 16.10
One critique of RCT in economics and the social sciences relates to the transferability of the results from the specific experiments being conducted to other contexts. For example, it might be true that installing cameras in schoolrooms in India reduces teacher absences, but that result may be unique to a particular site or to wider region within India if not the entire country. It is not clear whether the same result would be obtained in different countries with different cultural norms and expectations. The same critique can be applied to other RCTs.
Nonetheless, RCTs remain the gold standard not only in medicine but also in the evaluations of programs funded by foundations, schools, hospitals, and other organizations. Even if the results from one experiment in one setting are not generalizable to other organizations in other settings, the findings are likely to be used, and properly so, in the specific contexts where the tests are conducted.
Well before academic economists had discovered the use and power of RCTs, business began using real-world experiments, modeled loosely or closely on RCTs, to fine-tune their products, their marketing strategies, designs of their web pages, and so on. The pioneers on the front lines typically have not been economists, but they have acted like economists in using experimental methods to hone their business strategies and, in some cases, build great companies.
James Manzi, one of the leaders in this field whose efforts I will describe shortly and who is profiled in the accompanying box, has outlined the history of business experimentation.11 In his telling, the true pioneers of the practice were the founders of Capital One, today one of the nation’s largest credit card companies, whose success Manzi attributes to continuous and extensive experimentation.
Capital One was launched by two former Strategic Planning Associates (SPA) consultants, Rich Fairbank and Nigel Morris, who attacked the credit card customer base as if it were one giant laboratory. Do customers respond better to solicitations in blue or white envelopes? Send out solicitations to two groups and see if there is a statistically significant difference. Apply the same approach to virtually everything else the company does, including employee selection, collection policies, cross selling of different financial products, and do as many as 60,000 experiments a year, and that is how Capital One was built. No single experiment was a “home run” but the “singles” from thousands of successful experiments incrementally improved the company so that in 25 years, Capital One grew from nothing into a major Fortune 500 company and one of the largest credit card lenders in the United States.
That is Manzi’s personal experience with how business experiments work: They provide incremental rather than disruptive improvements that over time add up to either major breakthroughs or significant additions to companies’ bottom lines.
The Internet unleashed a huge jump in business experimentation because it became so easy to do. Rather than sending out large batches of different colored envelopes and waiting for sales results, one can change the color or design of websites on a daily or even more frequent basis, and offer the different impressions to different sets of randomly chosen website visitors. If the comparisons are limited to just two sets of customers they now have a name—an A/B test—and we have Google to thank for introducing them.
Google has been conducting just these kinds of experiments for more than a decade, making small tweaks here and there to its website results and other aspects of its business. The company does all this with a growing army of statisticians picking, in each case, whether the A or the B design prompts the best reaction from website visitors, or clicks of ads, or so on. Indeed, Google runs so many A/B tests simultaneously that almost everyone who visits the site is probably being tested whether they know it or not. Put another way, there is no single Google website, but many different ones being tested at the same time. Other companies actively using A/B tests include Amazon, Netflix, and eBay.12
A semi-science has since grown up around the proper construction and administration of A/B tests, given that many other firms, whether Internet-based or still grounded in the physical world but with an Internet presence, use them. One well-known company providing a free tool for anyone or any firm that wants to conduct its own A/B test is Optimizely, founded by two ex-Google employees, Dan Siroker and Pete Koomen, who honed the testing technique for the Obama presidential campaign in 2012. An entrepreneur and writer, Eric Ries, has written the bible for A/B testing by tech startups, The Lean Startup. Ries and his book have even encouraged a whole lean-startup movement.13
Not all A/B-type tests are run on the Internet, because most commerce, after all, is still conducted in bricks-and-mortar facilities. One of the leading companies facilitating experiments in that context is Applied Prediction Technologies, founded by James Manzi (see the following box). Since its founding in 1999, APT has grown to the point where, according to Manzi, 30 to 40 percent of the largest U.S. retailers, hotels, restaurant chains, and retail banks in the United States had used or were using APT’s experimentation platform as of 2012.14
There is one other connection between experimentation and economics I cannot resist closing this chapter with, and it relates to entrepreneurs, many of whom are experimenters by nature, and whose importance to the economy I believe cannot be overstated. With the exception of a few economists like the great Joseph Schumpeter, Israel Kirzner, and a famous economist I am about to reveal, this was not generally well recognized among mainstream economists (and still isn’t in some quarters) until relatively recently. So this is a case where business has been out in front of economics, but economists are catching up and have begun to provide practical research that even the most skeptical entrepreneurs will find useful.
The reason I can make these claims is that I spent nearly a decade of my life on the periphery of entrepreneurship, but at the center of entrepreneurship research when I directed research for the Kauffman Foundation, the world’s largest foundation devoted primarily to advancing entrepreneurship. During the near decade I was there (2003 to 2012), Kauffman greatly expanded its support of mainstream economists to study various aspects of entrepreneurship, and in particular, its connection to innovation and economic growth. The list is long, but a sample of the notable economists who were funded included William Baumol of NYU (profiled in Chapter 4), Edmund Phelps of Columbia University (profiled below), Amar Bhidé of Tufts University (who had already made his mark in the field with a landmark study of innovative entrepreneurs),16 Josh Lerner of Harvard Business School, Steven Kaplan of the University of Chicago, and Alicia Robb, formerly of the Fed staff and at this writing a senior fellow at Kauffman itself.
I benefited greatly from frequent interactions with these remarkable individuals and many others, as well as from reading their research when writing two books on entrepreneurship and economic growth, one with an economist profiled earlier in this book (William Baumol) and the president of the Kauffman Foundation, Carl Schramm,17 and the sequel which Schramm and I coauthored.18 I learned more from writing these books, all the while enjoying the process, than from any other books I had previously written (until this one!). Although the books are very different (and of course I encourage readers of this book to read them), they have a common theme: Entrepreneurs, defined as those who commercialize new products, services, or ways of producing or delivering them, are among the most important, and arguably the most important, drivers of innovation and growth in average living standards.
There are many ways to classify such innovative entrepreneurs. The distinction I believe to be most relevant to this chapter, and thus this book, is between those who are convinced they know better what consumers eventually will want than consumers themselves and are highly unlikely to change their minds––think Steve Jobs, Larry Page, and Sergey Brin––and those entrepreneurs who start with one idea (typically written in detail in a business plan), but often quickly shift to another after some initial encounters with consumers and the marketplace. The latter category includes the entrepreneurial equivalents of scientists, those who have a hypothesis (the business plan) about how a business can be profitable, and then test it through refinements in the products or services they sell to consumers. These experimental entrepreneurs keep experimenting until they get it right.20
I know of no studies that attempt to determine what portion of successful entrepreneurs are inspirational and those that are experimental, but my own impression is that most fall into the second camp or, at the very least, have both elements as part of their nature. As a matter of logic this stands to reason, since I cannot count how many times I have heard the adage, from economists and businessmen (and women), that what makes an entrepreneur different is that he or she sees opportunity where others see only problems. This is a variation of the advice I have heard many successful entrepreneurs give to aspiring entrepreneurs: Channel your entrepreneurial passions into fixing, for commercial gain, the problems that you personally have found to be highly irritating or frustrating. Successful entrepreneurs who are motivated in this fashion even if they succeed on the first try are combining both inspirational and experimental traits.
My guess is that few entrepreneurs succeed on their first try, and thus need to experiment or, to be blunt, to fail, often repeatedly, before achieving success. The secret economist I mentioned earlier who came to this conclusion much earlier than I did was Albert O. Hirschman, certainly one of the more unusual economists of the twentieth century, as should be evident from his profile in the following box.
Though he was perhaps best known for his classic Exit, Voice, and Loyalty—which finds a role for each noun in any economy—Hirschman also makes some highly useful insights about entrepreneurs and their economic importance.22 In my paraphrasing of his description, the typical entrepreneur is not the swashbuckling risk-taker, but someone who embarks on a path that is so obvious to him or her that it would crazy to not do it, and thus is more accurately characterized as a “prudent” risk-taker. We know, by the way, from much modern research that for many, if not most, entrepreneurs, this is true—an insight that was drilled into me during many encounters I had with entrepreneurship researchers while I was at Kauffman.
But in Hirschman’s telling, here is where experimentation enters the picture. After launching his or her venture, the typical entrepreneur encounters any number of unexpected obstacles: Manufacturing the product is more difficult than expected, or consumers are not as enthusiastic about the initial version of the product or service as the entrepreneur anticipated. The successful entrepreneur is one who finds ways to overcome these obstacles, many times completely changing course again and again before hitting on what it is that consumers really want. The resulting success is often due more to accident than design, although the perseverance, and even madness (to outsiders), of the entrepreneur also play a critical role.
Hirschman describes this sequence of events in one of his essays, which Malcolm Gladwell recounts in his excellent review of Adelman’s biography of Hirschman.23 This essay describes Hirschman’s studies of large paper mills that were constructed in Pakistan with the intention of being supplied by bamboo forests from China. After those forests unexpectedly died, the mill’s operators improvised by building alternative supply chains, which ultimately made the mills more profitable than they would have been otherwise. Hirschman generalized from this experience by claiming what in my own experience rings true: Entrepreneurs typically start on a path they do not see as risky at all, then something happens that upsets their expectations and, being too far into their projects to turn back, they are forced to improvise. Those who get over this hump, or mountain, of unexpected trouble are the surviving entrepreneurial successes.
Hirschman’s account of entrepreneurship is similar in spirit to the much more recent description offered by Scott Adams, the creator of the Dilbert cartoon series. Adams has penned a thoughtful and highly readable account of both his life and how repeated failures ultimately help lead to success in almost any endeavor, including the founding and growth of a new firm.24
So much for economic descriptions and analysis about entrepreneurship and its role in economic advances, which are of interest to economists and to policy makers. But what have economists to say that can benefit entrepreneurs?
Here progress has been slower, in large part because producing this impact has not been high on many researchers’ agendas, and because reaching would-be and actual entrepreneurs is difficult. For one thing, whether entrepreneurs are inspirational or experimental, they are the type of people who do things for themselves, not the kind who consult books and articles, even though it is easier to do than ever before in the age of the Internet. For another, if they do read materials related to their chosen paths in life, entrepreneurs understandably are likely to be partial to things written by other entrepreneurs based on their own real-world experiences rather than by academics or journalists. Who can blame them?
There are limitations, however, with many of the entrepreneurial advice books one sees in bookstores or online. Too many are too general to be of much practical use, while others draw on personal anecdotes that do not often translate to the problems faced by particular entrepreneurs in their specific businesses. From an academic perspective, the advice books tend to be far from scientific because entrepreneurs (or consultants) turned authors are not trained to assemble large data sets and analyze them to draw general conclusions.
Even with these caveats, I can still safely recommend one popular book, coauthored by a successful entrepreneur, that I believe is the best practical guide for entrepreneurs ever written: Previously titled The Knack, its most current edition is entitled Street Smarts.25 The authors are Norm Brodsky, who has moonlighted for years as a columnist for Inc. (in my view, the best of the popular magazines for entrepreneurs) and his Inc. editor and coauthor Bo Burlingame, who has written widely about entrepreneurship for years.
As for the economists, they are slowly catching up, using the analytical and empirical tools of their trade to elicit insights from different data sets collected about entrepreneurs. One the best of this genre is the classic The Origin and Evolution of New Business by Amar Bhidé, now an economics professor at Tufts.26 Bhidé interviewed the founders or top executives of 100 companies no more than eight years old that had made the Inc. 500 in 1989, a list published each year by Inc. magazine of the fastest growing privately held companies over the previous four years. He supplemented this sample with another 200 case studies of successful entrepreneurs compiled by his students (when he taught at Harvard Business School), which he found to broadly corroborate the findings from his more formal sample.
Bhidé’s purpose in writing his book was to uncover the keys to entrepreneurial success by identifying factors common among successful entrepreneurs. One of his main findings was that most founders had capital constraints, or limited money to start their ventures, which were generally financed by the founders’ own savings and borrowings (from credit cards and mortgages). Only 5 percent of the sample companies—and these were among the most successful private firms—were funded initially by more formal sources, such as venture capital firms. Subsequent research supported by the Kauffman Foundation over the years has confirmed this result.
Bhidé also confirmed that successful entrepreneurs mostly improvised or experimented as they went along. Few wrote or adhered to business plans, the focus of so much coursework and many entrepreneurial competitions since. The companies did not have seasoned professionals at the top (except for those financed by VCs, who often replace founders with more experienced executives when putting money into new companies), but generally were run by founders who were struggling and adapting as they went along. These findings emerged from both Bhidé’s formal sample and from his students’ case studies. For readers who want to learn more, I strongly urge reading Bhidé’s study, which has stood the test of time, and has been largely reinforced by more recent comprehensive studies of entrepreneurship, such as Noam Wasserman’s sure-to-be-classic The Founder’s Dilemmas, which I discuss shortly.
One drawback of the Bhidé study, however, is that it suffers from survivorship bias, because he looked only at many of the most successful companies. That was his objective, of course, but in doing so he implicitly made no attempt to establish a control group that inevitably would have had many unsuccessful or relatively less successful companies in his sample. Those less successful might also share some of the traits or keys to success Bhidé found among the most successful entrepreneurs, but we will never know.
While I was at Kauffman, the foundation’s largest monetary commitment to entrepreneurship research was the funding of the most comprehensive longitudinal data set of new firms ever assembled about U.S. firms. This Kauffman Firm Survey (KFS) followed 5,000 firms established in 2004 (the year the study was launched) for eight straight years, asking over 100 questions of their founders or top leaders. By doing this, the KFS enables researchers to test numerous hypotheses about the factors driving entrepreneurial success, although it too suffers from a form of survivorship bias, though one not as severe as in the Bhidé study. The reason is that many firms fail or merge, dropping out of the KFS database over time, which means that only the survivors report the most complete data histories. However, unlike the Bhidé study that deliberately chose 100 of the most successful enterprises as the basis for its analysis, the KFS sample includes surviving firms that exhibit various degrees of success. Numerous researchers have made use of the KFS to author papers, including those of one of Kauffman’s own senior fellows, Alicia Robb.
As of this writing, however, by far the best and most recent empirically based study of and guide for potential and actual entrepreneurs in my opinion is The Founder’s Dilemmas, by Noam Wasserman of the Harvard Business School.27 Wasserman’s exhaustive treatment of virtually all aspects of the early stages of launching a new business is based on the experiences of nearly 10,000 founders, almost 20,000 executives, in about 3,600 startups over a 10-year period from 2000 to 2009. The book is chock full of advice, backed by an extensive analysis of the data on a wide variety of topics, including: whether to found companies alone or in teams; the issues that come up in teams that tend to lead to success or failure of the enterprise; the often tension-filled discussions about how to split up equity and compensate founders and their employees; hiring issues; and when to stay with the company (and if so, how to transition toward founder and management succession), or to sell out to a strategic buyer. This brief summary just scratches the surface of an enormously impressive book, which I believe is must-reading for anyone thinking about or in the process of founding a business. The book and its research provides clear evidence that academics can provide practical advice, provided they go out, like Wasserman, and talk to real people doing the things that entrepreneurs care about and that academics want to analyze.
Experiments are a part of everyday life and of many disciplines and pursuits, including both economics and business. Yet the movements toward experimentation in both lines of endeavor have developed, at least up to now, quite independently of one another.
This eventually will change. Both economists and those actively engaged in business now use experiments in laboratory settings and in the field. As this continues, I expect that businesses will call upon economists more frequently for their advice and their research lessons. Likewise, if economists are asked more frequently for their advice, expect to see them produce more business-relevant research.
Of the firms engaged in experimentation, perhaps the most important to the overall economy are new ones (speaking only of the United States), since they drive innovation, especially disruptive innovation, which determines the pace of economic growth. We may not need economists to start new businesses, but the better their research about what accounts for successful entrepreneurship, the larger should be the number of successful entrepreneurs and their companies. Or so we should all hope.