Bob Frankston, the programmer who designed VisiCalc with Dan Bricklin, noted that instant hard figures, so recently a luxury, are quickly becoming a necessity. The spreadsheet tool is shaping us. “There’s an increasing demand for quantitative rather than qualitative justification for decisions,” he said. “In the past, before spreadsheets, people would have taken a guess. Now they feel obligated to run the numbers.”

Yet what really has the spreadsheet users charmed is not the hard and fast figures but the “what if” factor: the ability to create scenarios, explore hypothetical developments, try out different options. The spreadsheet, as one executive put it, allows the user to create and then experiment with “a phantom business within the computer.”

“Before the spreadsheet, you barely had enough time to do the totals,” said Archie Barrett, a Capitol Hill staff member who uses an IBM PC-XT to work up spreadsheets for the House Armed Services Committee. “Now you put in a number and see whether you’re above or below the total. You can play what-if games. What if we don’t order as many tanks? What if we order more?”

The what-if factor has changed the way Allen Sneider, a partner in the Boston office of Laventhol & Harwath, a national accounting firm, approaches his job. Sneider bought an Apple in 1978, but he was not able to make it useful in his business until he saw an early copy of VisiCalc and became one of the first professionals to use the program. He explained:

Before, you would suggest a change to a client, get a staff member to calculate it, send it to the typist, to the proofreader, and recalculate it to make sure there weren’t any errors. Now you have a machine right there with the client. Want to see what happens with a different return on investment? Sheltering? Interest rates changing by half of a percent? It’s done in a minute. Before you’d be tempted to say, “Let’s leave it the way it was.” The whole mental attitude toward preparing projections has changed.

The what-if factor has not only changed the nature of jobs such as accounting; it has altered once rigid organizational structures. Junior analysts, without benefit of secretaries or support from data processing departments, can work up 50-page reports, complete with graphs and charts, advocating a complicated course of action for a client. And senior executives who take the time to learn how to use spreadsheets are no longer forced to rely on their subordinates for information.

Theodore Stein is an assistant vice president in data processing at the Connecticut Mutual Life Insurance Company in Hartford. After seeing what VisiCalc and the more powerful Lotus 1–2–3 could do, Stein became a passionate disciple of the spreadsheet. Until recently, Connecticut Mutual, like many large corporations, centralized its computer services in one division – data processing. People out in the field, or even at corporate headquarters, were generally not satisfied with the information they got from DP, Stein said.

DP always has more requests than it can handle. There are two kinds of backlog – the obvious one, of things requested, and a hidden one. People say, “I won’t ask for the information because I won’t get it anyway. When those two guys designed VisiCalc, they opened up a whole new way. We realized that in three or four years, you might as well take your big minicomputer out on a boat and make an anchor out of it. With spreadsheets, a microcomputer gives you more power at a tenth the cost. Now people can do the calculations themselves, and they don’t have to deal with the bureaucracy.

Since it was easy to learn how to use spreadsheets – no programming experience is required – all it takes to get into the game is a $3,000 personal computer and a $500 copy of 1–2–3, or even a copy of VisiCalc or the Micro-Soft Company’s Multiplan, both of which cost less than $200. Stein learned then early in Connecticut Mutual’s spreadsheeting days. The company’s chief financial officer wanted certain information, and his top “experts” had difficulty providing it. So one weekend he brought an Apple computer and a copy of VisiCalc home with him. Monday morning, he called his people in and showed them how he had gotten the information he had been clamoring for. “With one swipe of the diskette, he cut them off at the knees.” Stein said. “He out-teched them. His experts! He’d cut the chain. The following week, they all came down to learn VisiCalc – fast.”

All this powerful scenario-testing machinery right there on the desktop induces some people to experiment with elaborate models. They talk of “playing” with the numbers, “massaging” the model. Computer “hackers” lose themselves in the intricacies of programming; spreadsheet hackers lose themselves in the world of what-if. Some, like Theodore Stein of Connecticut Mutual, admit that their habit goes beyond the point of diminishing returns: “I can’t begin to tell you how many hours I spend at this,” he said. “This is my pet, in a way. Scratching its ears and brushing its code…it’s almost an obsession.”

The experiments Stein and those like him carry out are far-flung attempts to formulate the ultimate model, the spreadsheet that behaves just like an actual business. Allerton J. Cushman of Morgan Stanley has been a connoisseur of these models since discovering that computer spreadsheets could make forecasts of the property-casualty insurance industry. Cushman wrote a pamphlet about his projections entitled “Confessions of an Apple Byter”, which offered the observation that with VisiCalc, getting your arms around the future seems a trifle easier. Cushman’s office, high above midtown Manhattan, is dominated by IBM-compatible computers and printers, and when I visited him there he explained his fascination with modeling this way: “People like to build elegant models, whether of balsa wood or numbers.”

Spreadsheet models have become a form of expression, and the very act of creating them seem to yield a pleasure unrelated to their utility. Unusual models are duplicated and passed around; these templates are sometimes used by other modelers and sometimes only admired for their elegance.

Sterin, Cushman, and others so-called gurus lost themselves in the more esthetic possibilities of spreadsheeting: the perfect model is an end in itself. Power users learn from gurus, but have other ends in mind they can use sophisticated models to gain significant professional advantages. When a guru is not available, there are courses to take, self-help books to study, and magazine articles to examine, like the one in the July 1984 issue of Personal Computing entitled “Power Spreadsheeting,” which warns of “arrested spreadsheet development” and urges users to “think like a spreadsheet”.

Mastery is important, not for art’s sake but to win. A brilliant model is not only beautiful, it yields insights impossible to attain by any other method.

Dick York, a private real estate investor in Sausalito,changed his entire business to revolve around his Lotus 1–2–3. “I’ve used it to reduce everything in my operation to cash flow,” he said. “The spreadsheets give me constant updates, and I’m able to pinpoint property that isn’t bringing in money — I dump those properties immediately. This is information I’d always tried to get manually, but couldn’t.” York told me about the time he negotiated a commercial lease that included both a monthly rental and a percentage of the profit of his operation. In the course of making the spreadsheet model, he discovered there was a point at which going along with a raise in his rent would actually decrease the amount he’d pay the landlord. (The landlord did not have his own spreadsheet to divine this fact.)

Allen Sneider of Lowenthol & Horwath once worked a spreadsheet masterpiece. A client representing a finance company wanted to know whether it would be a good idea to pay $12 million for a factory that made artificial turf. Sneider and the client made a model that was sensitive to all sorts of variables. It would let you know the consequences of any change you might want to make in the business. Add a new production line, decrease production, increase inventory, widen the collateral base, change the mortgage rate, increase hourly wages…it was all there, calculated according to highly refined formulas. What happened? Sneider’s client did not buy the factory (the factory employees bought it). Instead, he started his own business — buying and selling spreadsheet templates.

Because spreadsheets can do so many important things, those who use them tend to lose sight of the crucial fact that the imaginary business that they create on their computers are just that-imaginary. You can’t really duplicate a business inside a computer, just aspects of a business. And since numbers are the strength of spreadsheets. The aspects that get emphasized are the ones easily embodied by numbers. Intangible factors aren’t so easily quantified. Jim McNitt, in The Art of Computer Management, tells the story of a restaurant owner named Maxwell who was trying to decide whether to undertake a costly renovation. He ran fifteen different scenarios on his computer, including one in which he took the money set aside for renovation and invested it elsewhere. What Maxwell found was startling: Not only would renovation be foolhardy, but “even the ‘best case’ showed I’d get nearly as good a rate of a return on my investment in a money market fund as staying in the restaurant business.” Get out of the restaurant business! the spreadsheet said. What the spreadsheet left out, of course was the unquantifiable emotional factor — Maxwell loved what he did. He kept the restaurant (though scuttled the renovation).

Maxwell was his own boss and could follow his instincts. But a corporate executive who ignored such a clear-cut bottom-line conclusion might be risking his professional life. He is more likely to follow the numbers turned out by spreadsheets.

And so it is that spreadsheets help in the drive for paper profits, and are a prime tool of takeover architects. An executive in a acquisition-hungry company might spend his time spreadsheeting in order to find a company ripe for takeover. If his spreadsheet projections were to produce a likely candidate- if the numbers looked good- he would naturally recommend making a takeover bid. Even a hostile takeover seems cut and dried, perfectly logical, in the world of spreadsheets. The spreadsheet user has no way of quantifying a corporate tradition or the misery of stockholders or whether the headaches of a drawn out takeover bid will ultimately harm the corporate climates of the firms involved.

The flexibility of spreadsheets can encourage other heartless moves from headquarters. It is no great drain on an executive’s time to experiment with all sorts of odd, even insidious. He might ask “What if we dropped our pension plan?” Then he might run his idea through a spreadsheet and find a huge gain in capital- and there would be an unthinkable, in hard figures.

Spreadsheets have no way of dealing with hunches, either, no formulas for telling their users when lightning will strike- when a product will be not merely a product but a trend-setting blockbuster.

There were no formulas in Lotus’s spreadsheet projections that did justice to the fantastic consumer acceptance of 1–2–3.”Our own projections were violated on a daily basis,” said Ezra Gottheil. “It was beyond our wildest assumptions.”

People tend to forget that even the most elegantly crafted spreadsheet is a house of cards, ready to collapse at the first erroneous assumption. The spreadsheet that looks good but turns makers themselves pay the price. In August 1984, the Wall Street Journal reported that a Texas-based oil and gas company had fired several executives after the firm lost millions of dollars in an acquisition deal because of “errors traced to a faulty financial analysis spread sheet model.”

An often-repeated truism about computers is “Garbage in, Garbage Out.” Any computer program, no matter how costly, sophisticated, or popular, will yield worthless results if the data fed into it is faulty. With spreadsheets, the danger is not so much that incorrect figures can be fed into them as that “garbage” can be embedded in the models themselves. The accuracy of a spreadsheet model is dependent on the accuracy of the formulas that govern the relationships between various figures. These formulas are based on assumptions made by the model maker. An assumption might be an educated guess about a complicated cause-and-effect relationship. It might also be a wild guess, or a dishonestly optimistic view.

For instance, a 5 percent increase in the cost of raw materials used to make widgets might lead to 10 percent increase in the retail price, according to an established cost-price ratio. Anyone projecting a budget for a widget company could confidently integrate that formula into his model. But to determine the effect of a 10 percent price increase on the number of widgets actually sold, he would have to take into account all sorts of market factors, as well as how people tend to behave in certain situations. Perhaps the spreadsheeter has access to a study that definitively shows that a 5 percent increase in widget prices results in a 6 percent decrease in sales. But maybe no study exists. Or maybe the spreadsheeter knows that the widget company plans to use the projection to seek new financing and therefore doesn’t want to reveal the company’s vulnerability to fluctuations in the price of raw materials. So he might make the ludicrously optimistic assumption that a 5 percent price increase would result in only a 1 percent decrease in sales.

A notorious example of this kind of fiddling occurred when David Stockman, Director of the Office of Management and Budget, was drawing up the budget for Ronald Reagan’s first presidential term. According to William Greider’s book The Education of David Stockman and Other Americans, a mainframe computer had been programmed with an elaborate model of the nation’s economic behavior. When Stockman used the model to project the effects of Reagan’s plan to reduce income taxes and increase defense spending, the computer calculated that the plan would lead to unprecedented federal deficits. Did Stockman warn his president that they were on a dangerous course? No. “He changed the economic assumptions fed into computer model,” writes Greider. “[He] assumed a swift decline in prices and interest rates. …The new model was based on a dramatic surge in the nation’s productivity.” So Stockman was able to fortify the Administration with figures — generated by a computer — showing that the deficit would not be problem.

Stockman’s sleight of hand was fairly easy to discern. In 1981, electronic spreadsheets were just coming into their own, and the kind of sophisticated modeling Stockman did was still done chiefly on mainframe computers. The output he was working with wasn’t in the now-familiar spreadsheet format; instead, the formulas appeared in one place and the results in another. You could see what you were getting. That cannot be said of electronic spreadsheets, which don’t display the formulas that govern their calculations.

As Mitch Kapor explained, with electronic spreadsheets, “You can just randomly make formulas, all of which depend on each other. And when you look at the final results, you have no way of knowing what the rules are, unless somebody tells you.”