Intangible Assets Plus Hard Numbers Equals Soft Finance

The third measure is Macromedia's percentage of the money that each customer spends on Web-design products -- in other words, loyalty, or "share of wallet." "Ultimately, if we can increase customer loyalty, we know we can translate that into more revenue," says Nelson. But how much revenue? The executive team grappled with that question for several months. "What's the value of a customer relationship?" asks Nelson. "You don't have a lot of hard data. You have to draw on a lot of gut in order to come up with the numbers that correspond to the market, the technology, and the ability of the team."

Nelson finally did come up with numbers that reflected cost cuts, increased conversions, increased loyalty, and revenues from new products. In the end, she signed off on a $6 million spending program -- money for new hires, consulting help, and hardware and software. "At the end of the day, it is a venture investment -- high risk, high reward," she says. "One thing that we know is that it's extremely valuable to us to own that customer relationship."

The most powerful lesson that Nelson has learned as a CFO is the importance of developing a soft analysis of hard numbers to measure value in the new economy. Long-term value still rises and falls on cash flow. And cash flow rises and falls on revenue. But revenue comes from a lot of intangibles these days -- in particular, customer and consumer relationships. The challenge is to develop scenarios that, as much as possible, predict which revenue streams will pay.

Counting on Character

Ken Wilcox, 51, is not a textbook banker. If he were, he would lean on the same "5 Cs of credit" that every other banker uses to evaluate loans: character, capacity, capital, collateral, and cash flow. If he were, he would ask the people who work for him to hold on to one simple thought: Only cash flow repays loans. If he were, he would not work for Silicon Valley Bank.

When companies come to him for financing, Wilcox has a way of valuing them that's different from the method that his peers rely on. It's not that he doesn't use the five Cs; he just looks at them from a different angle. Take capacity. Wilcox doesn't look for profit-making records; he looks for the promise of an equity infusion. Or take collateral. He doesn't look for plant and equipment; he looks for salable intangibles -- intellectual property such as patents, or knowledge bases such as customer lists. "We don't have tangible collateral," he says.

Silicon Valley Bank wasn't built on tangible collateral, and that's rare among banks. With $3.5 billion in assets and 575 employees, SVB funds a lot of startups and young companies. It operates nationwide in three sectors: technology (including computers, software, semiconductors, communication, and online services), life sciences (biotech and medical devices), and a hodgepodge of special industries, premium wineries among them. For entrepreneurs, SVB is the blue chip of high-tech lenders.

One reason why Wilcox isn't a textbook banker now is that he has never been one. He has always been faced with special cases, such as software companies that are trying to change the world. One SVB client, Scott Rozic, sells software for "intelligently automating the capture, organization, and discovery of information." Few mainstream banks would touch Rozic's company, Verge Software.

The problem goes to the heart of finance in the new economy: New companies don't have tangible value. They have no history of revenue -- let alone cash flow. They have no physical assets to sell other than rapidly depreciating computer hardware. Mainstream banks, finding no value to lend against, would never make loans to a business like Verge. So why would Wilcox be interested?

Safety without Cash Flow

Wilcox was never one to follow in others' footsteps. He earned a PhD in German studies from Ohio State University and taught at the University of North Carolina at Chapel Hill. But he was smart enough at finance to figure out that rising inflation and his lagging professor's salary meant that he was rapidly losing purchasing power. "I didn't like being poor," he says.

So in 1981, he sold all of his stuff, drove north, and enrolled at Harvard Business School. After Harvard, he went into high-tech lending. At the time, only about 100 people in the entire country even acknowledged that they would lend to high-tech, high-risk companies. In fact, the banking industry was structured to make lending to early-stage technology firms all but impossible. Banks were requiring all clients to hand over financial statements for the previous three to five years, and those statements had to demonstrate at least a couple of years of profitability and positive cash flow, as well as hard assets.