New Math for a New Economy

What’s wrong with the 500-year-old way in which all companies keep their books? Just about everything, says Baruch Lev, who has proposed a new method for determining the value of the intangible assets that are at the heart of the new economy.

Accounting is all about accuracy. Accounting is all about hard numbers. Accounting is all about accountability. Accounting is a time-honored tool for making hard decisions about dollars and cents, about profits and losses. Accounting is the land of bean counters, of number crunchers — men and women with green eyeshades and calculators.


Accounting, says Baruch Lev, the Philip Bardes Professor of Accounting and Finance at New York University’s Leonard N. Stern School of Business, is increasingly irrelevant. And, for that reason, it is increasingly essential and interesting to all of us. The problem, says Lev, is that the systems of accounting and financial reporting that are being used today date back more than 500 years. These systems are not only part of the old economy, they’re part of the old, old economy. Luca Pacioli, an Italian mathematician who lived in Venice in the 1400s, developed double-entry bookkeeping in order to offer businesspeople a simple method for keeping track of their transactions — and, even more important, for making sense of the way that they did business. “If you cannot be a good accountant,” Pacioli wrote, “you will grope your way forward like a blind man and may meet great losses.”

Today, argues Lev, being a good accountant doesn’t guarantee good eyesight. The old lens cannot capture the new economy, in which value is created by intangible assets: ideas, brands, ways of working, and franchises.

The disconnect, says Lev, affects more than just financial analysts and corporate financial officers: Employees don’t know how to value their contributions accurately. Managers don’t have good numbers to refer to when deciding whether to back a project, or when assessing a project’s performance. Are knowledge-based companies overvalued on the stock market? Are companies paying too much to acquire knowledge-based assets? These questions, says Lev, and more, cannot be adequately answered with today’s accounting and financial-reporting methods. Accounting, in other words, no longer delivers accountability.


Lev, who is also director of the Vincent C. Ross Institute of Accounting Research and the Project for Research on Intangibles, has become the most articulate, thoughtful, and outspoken critic of old-fashioned accounting, and the most creative advocate of a new, knowledge-based approach to accounting. He has pioneered the development of a Knowledge Capital Scoreboard, which attempts to put hard numbers to intangible assets.

To find out more about what’s wrong with traditional accounting, what is needed to fix it, and why it matters to all of us no matter what our job or industry, Fast Company interviewed Lev in his office in New York City.

Why are you calling for a rethinking of the principles of accounting and finance?


In the past several decades, there has been a dramatic shift, a transformation, in what economists call the production functions of companies — the major assets that create value and growth. Intangibles are fast becoming substitutes for physical assets. At the same time, there has been complete stagnation in our measurement and reporting systems. I’m not talking only about financial reports and Internet investments but also about internal measurements — accounting and reporting inside companies. These systems all date back more than 500 years.

So here’s the situation: We are using a 500-year-old system to make decisions in a complex business environment in which the essential assets that create value have fundamentally changed.

What’s the evidence for this transformation?


Look at the Standard & Poor’s 500 — 500 of the largest companies in the United States, many of which are not in high-tech industries. The market-to-book ratio of these companies — that is, the ratio between the market value of these companies and the net-asset value of the company (the number that appears on the balance sheet) — is now greater than six. What this means is that the balance-sheet number — which is what traditional accounting measures — represents only 10% to 15% of the value of these companies. Even if the stock market is inflated, even if you chop 50% off the market capitalization, you’re still talking about a huge difference between value as perceived by those who pay for it day-to-day and value as the company accounts for it.

Another example: John Kendrick, a well-known economist who has studied the main drivers of economic growth, reports that there has been a general increase in intangible assets contributing to U.S. economic growth since the early 1900s: In 1929, the ratio of intangible business capital to tangible business capital was 30% to 70%. In 1990, that ratio was 63% to 37%.

So intangible assets are becoming more important. But what are intangible assets?


It’s extremely difficult to come up with a comprehensive definition of intangible assets. I’ve tried to group them into four categories. First are assets that are associated with product innovation, such as those that come from a company’s R&D efforts. Second are assets that are associated with a company’s brand, which let a company sell its products or services at a higher price than its competitors. Third are structural assets — not flashy innovations or new inventions but better, smarter, different ways of doing business that can set a company apart from its competitors. And fourth are monopolies: companies that enjoy a franchise, or have substantial sunk costs that a competitor would have to match, or have a barrier to entry that it can use to its advantage.

What is it about intangible assets that creates value — value that is more significant than that of tangible assets?

The best way to answer that question is to use another example — and here I’m intentionally steering away from the Web-based and high-tech companies that people usually point to, such as Cisco Systems and Let’s look at American Airlines, or, more accurately, its parent company, AMR Corp.


In October 1996, AMR Corp. sold 18% of its computer-reservations system, called SABRE, to the public. It held on to the remaining 82%. That one transaction provides a beautiful way of evaluating tangible and intangible assets. When I recently checked the market, SABRE constituted 50% of AMR’s value. This is mind-boggling! You have one of the largest airlines in the world, with roughly 700 jets in its fleet, nearly 100,000 employees, and exclusive and valuable landing rights in the world’s most heavily trafficked airports. On the other hand, you have a computer-reservation system. It’s a good system that’s used by a lot of people, but it’s just a computer system nonetheless. And this system is valued as much as the entire airline. Now, what makes this asset — the computer system — so valuable?

One big difference is that when you’re dealing with tangible assets, your ability to leverage them — to get additional business or value out of them — is limited. You can’t use the same airplane on five different routes at the same time. You can’t put the same crew on five different routes at the same time. And the same goes for the financial investment that you’ve made in the airplane.

But there’s no limit to the number of people who can use AMR Corp.’s SABRE system at once: It works as well with 5 million people as it does with 1 million people. The only limit to your ability to leverage a knowledge asset is the size of the market.


Economists call physical assets “rival assets” — meaning that users act as rivals for the specific use of an asset. With an airplane, you’ve got to decide which route it’s going to take. But knowledge assets aren’t rivals. Choosing isn’t necessary. You can apply them in more than one place at the same time. In fact, with many knowledge assets, the more places in which you apply them, the larger the return. With many knowledge assets, you get what economists call “increasing returns to scale.” That’s one key to intangible assets: The larger the network of users, the greater the benefit to everyone.

So that’s how intangible assets can create extraordinary value. But is there a downside to knowledge assets?

As my former teacher and colleague Milton Friedman used to say, “There’s no such thing as a free lunch.” Knowledge assets are very expensive both to acquire and to develop. And they’re extremely difficult to manage.


Look at the extremely high prices that high-tech companies are paying to acquire smaller companies, as they look for knowledge assets that they can leverage. On November 1, 1999, Cisco announced that it had acquired Cerent Corp. for $6.9 billion. For the first six months of 1999, Cerent’s sales totaled roughly $10 million. That’s what it can cost to acquire a knowledge asset. Or look at the high cost of developing a knowledge asset: In the world of pharmaceuticals, it costs close to $500 million to develop a new drug. One last example is America Online, which spent nearly $1.5 billion on customer acquisition when it was creating its franchise. That’s what it can cost to create a high barrier to entry.

There’s another downside of knowledge assets: Property rights are fuzzy. When it comes to a tangible asset, such as an airplane, American Airlines doesn’t have much to worry about. No one is going to steal an airplane. But American Airlines definitely has to worry about someone stealing its software. The proliferation of thousands upon thousands of very costly patent-infringement lawsuits attests to the difficulty of defining and keeping property rights when you’re dealing with knowledge.

And while the benefits that come with knowledge assets can be enormous, they are much more uncertain than the benefits of tangible assets. When you invest in a tangible asset, such as an office building, you always get some kind of return — even during a recession. And when boom times come, your property really pays off. But when you’re building a knowledge asset, you could quite possibly end up with nothing.


Given the nature of knowledge assets, what is the conflict between these new assets and the old laws of accounting?

One problem is that you end up with accounting practices that are virtually antithetical to the business practices that they’re trying to measure. Let me give you an example. In 1994 and 1995, America Online capitalized some of its customer-acquisition costs — which means that it considered part of those costs assets. In other words, AOL was saying that, in acquiring new customers, it was creating a unique asset — one that would help the company become even more profitable in the future. Financial analysts called that cheating! It was a new industry, competition was fierce, and analysts thought that AOL was trying to manipulate its earnings. Finally, in October 1996, AOL gave up and completely expensed its $385 million in customer-acquisition costs.

Today, AOL has a market value of roughly $140 billion. Compare that with the $385 million that it tried to capitalize, and it’s almost humorous! And yet only five or six years ago, financial analysts were proclaiming that AOL was a cheat.


Or take, for example, what happened when IBM acquired Lotus in 1995. As an accounting requirement, IBM had to estimate the fair-market value of the assets that it had acquired. IBM estimated that the portion of Lotus’s R&D that was in process — R&D for which there was not yet a product — was worth $1.84 billion. That’s 53% of the entire $3.5 billion acquisition price. IBM expensed the entire thing — because those are the rules of accounting: Once you estimate that something is in-process R&D, you have to expense it. As a result, no trace of an asset remains.

This kind of mindless writing-off of all investments in knowledge assets means that there is no accountability — and no ability to measure the performance of an investment or to learn from it. And the problem is only getting worse: Over the past 20 years, as the actual value of companies’ intangible assets has been going up, that value, as it is represented in financial reports, has appeared to be consistently going down.

How do you account for this failure of accounting?


Accounting is based on the matching principle. To determine your earnings, you match your revenues against your expenses. It’s that simple — that’s what an accounting system does. And if the matching is good, you get a reliable income number.

Now here’s the problem: With knowledge assets, you get a complete mismatch, and the system breaks down completely. Take the AOL example. During its period of tremendous growth, AOL immediately expensed all of its customer-acquisition costs. So for that period, the company was showing those costs as big losses. Then, once the customers were acquired, the company realized large benefits — which then increased its income without any associated costs! So both periods are misstated in financial reports. Companies that are on a steep growth curve — for example, Internet and biotech companies — are most likely understating their results. And older companies that have plateaued are most likely overstating their results. The outcome is a disconnect with the market, which is supposed to reflect reality.

There’s another disconnect between the world of accounting and the world of knowledge assets: Accounting records transactions, but much of value creation or value destruction precedes any transaction. Look at regional telephone companies. In the late 1980s, deregulation started to hit the regional phone system. The old system was based on a guarantee of a reasonable rate of return for phone companies. The companies had an assured monopoly and assured profits. The new system was more open and competitive.


Investors immediately understood the implications of moving from a secure monopoly to a competitive system: higher risks, lower returns. But the accounting system didn’t reflect any change at all — because deregulation is not a transaction! Five or six years after deregulation began, the Baby Bells finally said that their assets must be much lower than before, and wrote off $27.6 billion of assets. But in the preceding five years, there was an almost total disconnect between what the company was actually worth, what the accounting system showed, and what the markets understood.

Remember: This system was invented hundreds of years ago. Luca Pacioli, the monk who created it, was a genius. He developed a system that is still working 500 years later. But Pacioli’s system is frail. After all, it relies on transactions. But when you’re working with knowledge assets, value is created or destroyed without making any transaction at all.

When a drug passes its clinical tests, huge value is created — but there’s no transaction. Nothing changes hands. Nobody buys anything, and nobody sells anything. When software passes a beta-test, it suddenly becomes valuable — but there’s no transaction. Or think about how value is destroyed: When a big, old company is late in figuring out how to enter the world of e-commerce, huge value is destroyed — but there’s no transaction.

If something as fundamental as the accounting and financial-reporting system doesn’t work in the new economy, why hasn’t there been a more vocal call for change?

There are two major barriers to change. The first is an objective difficulty to this problem: The issue of knowledge assets is inherently uncertain — we’re still struggling to come up with a definition that works. And the issue of intellectual-property rights, for example, continues to be fuzzy. There’s no one solution that will eradicate the problem — and every new solution presents new problems. Given how difficult the material is, it’s easier for people to wait for a better solution to come along.

The second barrier to change is an informal coalition that opposes any change to the current system. Managers love the current system. They don’t want to put anything on the balance sheet that may turn out to be worthless. Accountants share this love of the current system. If they don’t have to value intangible assets, such as AOL’s customer-acquisition costs, their legal liability is reduced. Let’s face it: Valuing things that are inherently difficult to value, and then standing by that valuation when someone sues you, can be very unpleasant.

Institutional investors and financial analysts are also quite happy with the current system because they think that they’ve got inside networks and proprietary information. They have lunch with managers. They visit companies. In doing so, they feel that they’re getting important private information. How would it serve their interests if that information were made public? So there are some awesome forces against change.

If all of these people are against change, then the system must be fine, right? What’s the problem?

The problem is that lots of mistakes are being made. For example, I just finished studying roughly 1,500 companies — all of which have significant R&D investments. About a quarter of these companies are systematically undervalued by their investors. And many of them are computer, biotech, and software companies with substantial R&D but below-average earnings. That means that the cost of capital for these companies is unusually high — and that impedes their growth. The systematic undervaluing of these companies brings serious economic and social costs to the companies, to their shareholders, and to the economy. So the problem is not academic or abstract; it has serious business implications. And although I do not have the data to prove it, my guess is that many internal decisions are also deficient because managers, too, are relying much too heavily on accounting information.

What solutions do you propose to fix that problem?

I think that there are a few remedies — none are complete, but all will help. One is to improve the accounting system. Some people have given up on accounting altogether. They say that the system is dead and that something entirely new is needed. To me, that would be a big mistake. I believe that accounting is still incredibly efficient. So the solution is not to do away with the old system but to improve it.

I don’t expect any breakthroughs but slight amendments that improve on what already exists. One example: satellite accounts. These can be a set of accounts around the regular ones that will provide more information about the real value of assets. The U.S. government, for example, expenses R&D in the same mindless way that companies do. But the government has also set up satellite accounts in which it capitalizes R&D. It’s not a great revolution, but it does provide a way to compare things.

And your more revolutionary proposal?

Another remedy requires going outside of the existing system. I’ve developed a way to measure knowledge assets, intellectual earnings, and knowledge earnings. It’s a computation that starts with what I call “normalized earnings” — a measure that’s based on past and future earnings. When you’re dealing with accounting for knowledge, you simply cannot do it unless you consider the potential for future earnings that knowledge creates. In fact, that’s one of the things that is fundamentally wrong with all of the other ways we have of accounting for earnings, including improvements such as EVA [Economic Value Added]: They are all based purely on history. They are accounting in the past.

My approach looks at the past. But I also look at the consensus forecasts of analysts. Based on those forecasts, I create an average, and I call that average normalized earnings. From those normalized earnings, I then subtract an average return on physical and financial assets, based on the theory that these are substitutable assets. Merck & Co., for instance, has lots of laboratories and manufacturing facilities. The equipment there is not unique. What is unique are the people, the patents, the knowledge that is being developed there. So when I subtract from the total normalized earnings a reasonable return on the physical and financial assets, I define what remains as the knowledge earnings. Those are the earnings that are created by the knowledge assets.

For example, my recent computations show that Microsoft has knowledge assets worth $211 billion — by far the most of any company. Intel has knowledge assets worth $170 billion, and Merck has knowledge assets worth $110 billion. Now, compare those figures with DuPont’s assets. DuPont has more employees than all of those companies combined. And yet, DuPont’s knowledge assets total only $41 billion — there isn’t much extra profitability there.

Take a look at other companies where different kinds of knowledge assets make a big difference: I calculated that Phillip-Morris has knowledge assets worth $160 billion, largely because of its huge brand value. Coca-Cola is also a huge brand, and its knowledge assets are worth $60 billion. I identified another type of knowledge asset — structural capital. Structural capital is a unique way of doing business. In the case of Dell Computer, the company doesn’t produce computers that are better than other companies’ computers, but the way in which it markets its computers is entirely different. Which is why Dell’s knowledge capital totals $86 billion — higher than that of Wal-Mart.

This is my first measure. I call it a top-down approach because it’s an overall measure. According to the calculations that I’ve made, it performs far better than earnings or book value.

Is the top-down approach sufficient?

To complement the knowledge measure, we need to identify the drivers of knowledge. Here’s how I think about it:

Economic theory and research tell us that almost all industries share a similar development pattern. They start out with a large number of companies, and then, usually after some kind of big innovation, there’s a shakeout period that eliminates many of those companies. (At the turn of the century, there were more than 100 American car manufacturers; now there are only 2.) During the shakeout, most of the original companies fall by the wayside — even those that previously were large and successful. General Electric was once a major semiconductor manufacturer, but it had to get out of the industry when the shakeout hit. So the question is, Who can survive the shakeout that invariably hits every industry?

The survivors are those companies that have good technology, because they have the ability to innovate. For me, technology also includes structural capital like that of companies like Dell and Home Depot. I’m in the process of developing a technological-capabilities index: an index based on measures that are quantifiable, publicly available, and linked to value. These aren’t stories — about good customer relations, good public relations, or good service — but measures that can be supported by real research.

Let me give you an example. Some people use patents as an important knowledge attribute, but to me the number of patents that a company has is not very meaningful at all. You can get patents on almost anything, so simply having a large number of patents is absolutely meaningless. But there are ways to measure the attributes of the patents that have real significance. For instance, one powerful measure of the real value of a patent is how many times subsequent patents refer to it. If you have good science, then people will refer to you a lot, and you’ll contribute a lot.

My technological-capabilities index is based on measures of inputs, such as investment in R&D, investment in product development, investment in information systems; on measures of intermediate outputs, such as patents and trademarks; on measures of competitive position, such as the number of people who access a particular Web site; and, of course, on measures based on the ultimate output — commercialization. Commercialization of R&D is a powerful predictor of a company’s success. Recently, a couple of French economists conducted a study using data that French companies are required to publish showing the percentage of their revenue that comes from new products. The results of their study demonstrate how important commercialization of new products is to a company’s success in the marketplace.

These are just a few examples of a whole system of knowledge and innovation drivers — a system that allows managers to benchmark and to focus on those things that work or do not work, both of which indicate a company’s knowledge assets.

Let’s say that I’m not a CFO. How does this accounting disconnect affect me? Why should I care?

This problem affects each of us directly. Both employees and executives are valued by accounting numbers, such as return on investment or earnings growth. Bonuses, for example, are often based on these old-fashioned accounting numbers. We need to be aware of the limitations of accounting, and propose improvements that do a better job of reflecting our efforts and achievements.

There’s another way that accounting problems touch all of us. These days, most of us are also investors, which means that we must analyze corporate reports. We are all making investment decisions based on accounting information that is, at best, limited and, at worst, badly distorted. All of us need better information so that we can make better investment decisions.

But the biggest payoff comes from developing systems that improve accounting and reporting. Last October, for example, Cisco announced that it was in the process of developing an intranet that will provide users with an up-to-the-minute look at its books. Systems that give outsiders real-time access to some of a company’s data will also be big business. In short, technology has created far more data than ever before. But what we all need — and what we all need to work on — is the transformation of this data into valuable information and knowledge.

Alan M. Webber ( is a Fast Company founding editor. You can learn more about Baruch Lev on the Web (