This article was very influential in my early thinking about the spreadsheet and was cited in my PhD dissertation. It was published as Chapter 10 in Tom Forester’s (ed) Computers in the Human Context: Information Technology, Productivity and People. Basil Blackwell. 108 Cowley Road, Oxford OX4 1JF, UK. Steven Levy gave me permission to put it on my original New York University (NYU) website as part of a classroom project, but as they are closing down those files, I transferred it here.

10 PEOPLE AND COMPUTERS IN COMMERCE
A Spreadsheet Way of Knowledge
_______________________________________
Steven Levy

This classic account of the origins and development of computer spreadsheets suggests that they represent a whole new world view – or “reality by numbers.” Although they may be superficially attractive. the author warns that their use can be obsessive. They are also prone to errors and manipulation. Levy is author of Hackers: Heroes of the Computer Revolution (Doubleday, New York, 1985) and this piece first appeared in Harpers, November 1984.

As Dan Bricklin remembers it, the idea first came to him in the spring of 1978 while he was sitting in a classroom at the Harvard Business School. It was the kind of idea- so obvious, so right- that made him immediately wonder why no one else had thought of it. And yet it was no accident that this breakthrough should have been his.

Bricklin had graduated from MIT, where- and this is crucial to the idea he would have that afternoon in 1978- he had worked intimately with computers. Before deciding to go to graduate school he had worked for two major computer companies- first for Wang, then for the Digital Equipment Corporation, for whom he helped design a word-processing program. Like most Harvard MBA candidates, he wanted to be a businessman; but more often than not, his thoughts strayed to the technological.

The question Bricklin was pondering that day in 1978 concerned how he might use what he knew about computers to help him in his finance course. This was the assignment: he and several other students had been asked to project the complicated financial implications- the shift in numbers and dollars, and the shifts resulting from these shifts- of one company’s acquisition of another.

Bricklin and his classmates would need ledger sheets, often called spreadsheets. Only by painstakingly filling in the pale green grids of the spreadsheets would they get an accurate picture of the merger and its consequences. A row on the ledger might represent an expense of a category of revenue; a column might represent a specific period of time – a day, a month, a year. Run your finger across, say, a row of figures representing mortgage payments for a certain property, and the number in each “cell” of the horizontal row would be the figure paid in the time period represented by that particular vertical column. Somewhere on the sheet the columns and rows would be tallied, and that information would be entered on even larger sheets.

The problem with ledger sheets was that if one monthly expense went up or down, everything – everything – had to be recalculated. It was a tedious task, and few people who earned their MBAs at Harvard expected to work with spreadsheets very much. Making spreadsheets, however necessary, was a dull chore best left to accountants, junior analysts, or secretaries. As for sophisticated “modeling” tasks – which, among other things, enable executives to project costs for their companies – these tasks could be done only on big mainframe computers by the data-processing people who worked for the companies Harvard MBAs managed.

Bricklin knew all this, but he also knew that spreadsheets were needed for the exercise; he wanted an easier way to do them. It occurred to him: why not create the spreadsheets on a microcomputer? Why not design a program that would produce on a computer screen a green, glowing ledger, so that the calculations, as well as the final tabulations, would be visible to the person “crunching” the numbers? Why not make an electronic spreadsheet, a word processor for figures?

Bricklin’s teachers at Harvard thought he was wasting his time: why would a manager want to do a spreadsheet on one of those “toy” computers? What were secretaries and accountants and the people down in DP for? But Bricklin could not be dissuaded. With a computer programmer friend from MIT named Bob Frankston, he set to work developing the first electronic spreadsheet program. It would be contained on a floppy disk and run on the then brand-new Apple personal computer. Bricklin and Frankson released VisiCalc (the name was derived from Visible Calculation) in late 1979.

Today, VisiCalc and its newer rivals – most notably, a more powerful spreadsheet program designed by the Lotus Development Corporation called 1-2-3 – are making fundamental changes in the way American businesses work. For the first time, businessmen have at their fingertips sophisticated and flexible means to chart all the variables – from interest rates to warehouse space – that make (and break) businesses. The biggest firms, the most diversified corporations, can be neatly translated into spreadsheet “models” – each box of the grid a window on to once-overlooked facts or relationships. These models can be used not only to keep track of transactions but also to analyze the nature of a business itself. They allow businessmen to calculate the effects of sudden changes in the corporate environment (a decrease in the prime rate) and to experiment with scenarios (anything from the expansion of a product line to a merger) – all with an ease inconceivable five years ago.

More than a million computer spreadsheet programs worth more than $250 million will be purchased in the United States this year. There are corporate executives, wholesalers, retailers, and small business owners who talk about their business lives in two time periods: before and after the electronic spreadsheet. They cite prodigious gains in productivity. They speak of having a better handle on their businesses, of knowing more and planning better, of approaching their work more imaginatively. A virtual cult of the spreadsheet has formed, complete with gurus and initiates, detailed lore, arcane rituals – and an unshakable belief that the way the world works can be embodied in rows and columns of numbers and formulas.

It is not far-fetched to imagine that the introduction of the electronic spreadsheet will have an effect like that brought about by the development during the Renaissance of double-entry bookkeeping. Like the new spreadsheet, the double-entry ledger, with its separation of debits and credits, gave merchants a more accurate picture of their businesses and let them see – there, on the page – how they might grow by pruning here, investing there. The electronic spreadsheet is to double entry what an oil painting is to a sketch. And just as double-entry changed not only individual businesses but business, so has the electronic spreadsheet.

Already, the spreadsheet has redefined the nature of some jobs; to be an accountant in the age of spreadsheet program is – well, almost sexy. And the spreadsheet has begun to be a forceful agent of decentralization, breaking down hierarchies in large companies and diminishing the power of data processing.

There has been much talk in recent years about an “entrepreneurial renaissance” and a new breed of risk-taker who creates businesses where none previously existed. Entrepreneurs and their venture-capitalist backers are emerging as new culture heroes, settlers of another American frontier. Less well known is that most of these new entrepreneurs depend on their economic spreadsheets as much as movie cowboys depend on their horses.

Mitch Kapor, age 34, a former teacher of Transcendental Meditation, is chairman of the board of the Lotus Development Corporation. In 1983, less than a year after selling its first 1-2-3 package, Lotus went public, a move that brought Kapor’s personal net worth to more than $75 million. “Compare the expansion of business today to the conquering of the continent in the nineteenth century, “Kapor told me recently as he pulled himself away from his IBM-PC. We were talking in his modest office in the old iron-casting factory in Cambridge, Massachusetts, that is now Lotus’s headquarters. “The spreadsheet in that comparison is like the transcontinental railroad. It accelerated the movement, made it possible, and changed the course of the nation.”

Kapor’s comparison is an apt one. The computer spreadsheet, like the transcontinental railroad, is more than a means to an end. The spreadsheet embodies, embraces, that end, and ultimately serves to reinforce it. As Marshall McLuhan observed, “We shape our tools and thereafter our tools shape us.” The spreadsheet is a tool, and it is also a world view – reality by the numbers. If the perceptions of those who play a large part in shaping our world are shaped by spreadsheets, it is important that all of us understand what this tool can and cannot do.

One measure of the spreadsheet’s impact is clear, however, and it is a source of satisfaction to Dan Bricklin: every student in the Harvard Business School is now required to be proficient in using electronic spreadsheets.

Ezra Gottheil, 34 is the senior product-design planner at Lotus. He shows up for work in casual clothes, and his small office is cluttered with piles of manuals and software. When I visited Gottheil he gave me a quick introduction to electronic speadsheeting. Computer programs are said to use different “metaphors” to organize their task; a program might use the metaphor of a Rolodex, or a file cabinet. When you “boot” almost any spreadsheet program into your personal computer, you see little more than some letters running across the top of the display screen and some numbers running down the side. This serves to indicate the grid of a ledger sheet, the metaphor used by Lotus and other best-selling spreadsheets like VisiCalc, Multiplan, and SuperCalc. The “cursor,” a tiny block of light on the screen that acts like a kind of electronic pencil, can be moved (by a touch of the computer keyboard) to any cell on the spreadsheet in order to “input” numbers or formulas. By placing in the cells either figures of formulas that adjust figures according to different variables, it is possible to duplicate the relationships between various aspects of a business and create a “model.” The basic model for a restaurant, for example, world include expenses such as salaries, food and liquor costs, and mortgage or rent payments; revenues might be broken down into “bar” and “food,” perhaps even further by specific dishes. Every week, the figures would be updated, the formulas reworked if necessary (perhaps the price of the olive oil had risen) and the recalculated model provides an accurate snapshot of the business.

Gottheil turned to the keyboard of the IBM-PC on a table beside his desk and booted a spreadsheet. The screen lit up with the familiar grid, and Gottheil’s hands arched over the keys as gracefully as the hands of a pianist. He pressed the keys that make the blinking cursor hopscotch across the cells and as he changed an item in one cell, there was a ripple-like movement in the other cells; the spreadsheet program was recalculating. His eyebrows rose as he saw the result. Then he punched in another variable, and another ripple of figures washed across the screen. He was offering the computer different hypothetical developments, and it was feeding back to him their probable consequences. “It’s a good tool,” Gottheil noted matter-of-factly. In these, the early days of electronic spreadsheeting, it is most frequently seen as a tool for saving time. Don Jackson is a certified public accountant in Cincinnati. He has between 40 and 50 clients, mostly small businesses. Before he bought an Apple three years ago, he painstakingly did his calculations on light green crosshatched ledger sheets. A client would come in to work out a billing procedure, and after Jackson had put the relevant numbers on a sheet – in light pencil, so erasures could be easily made – various questions would come up. For example, if the billing procedure was based on a 15 percent interest rate, what would happen if the rate went up to 18 percent? To find out, the whole sheet would have to be redone. Each figure would have to be punched into a hand calculator and then checked by one of Jackson’s employees. “I would work for twenty hours,” Jackson said. “With a spreadsheet, it takes me 15 minutes.”

Jackson’s story is a common one. In the first days of electronic spreadsheets – that is, two or three years ago – those who used them got things done so quickly that, despite the evidence of finished reports, bosses and co-workers often had trouble believing the tasks had been completed. Gottheil told me of an accountant who got “a rush task, sat down with his micro and his spreadsheet, finished it in an hour or two, and left it on his desk for two days. Then he Fed Ex-ed it to the client and got all sorts of accolades for working overtime.”

But saving time is hardly the only benefit of spreadsheets. They encourage businesses to keep track of things that were previously unquantified or altogether overlooked. Executives no longer have to be satisfied with quarterly updates, for it is now an easy matter to compile monthly, weekly, even daily updates. People use spreadsheets to make daily inventory checks, to find out who has paid their bills, to chart the performance of truck drivers over a period of weeks or months. How-to manuals for spreadsheets often use as an example a performance chart for salespeople – the model breaks down how many items they sell week by week and instantly calculates commissions and even bonuses due. If word comes down that a belt-tightening is in order, a few keystrokes will create a sheet that clearly identifies the worst performers.

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.”

Increasingly, however, businessmen are not telling but letting their spreadsheets do the talking. Because a spreadsheet looks so authoritative – and it was done by a computer, wasn’t it? – the hypothetical models get accepted as gospel. The spreadsheet presentation is becoming both more commonplace and more sophisticated: not only the numbers but the formats of the sheets themselves are designed to make eloquent points. This use of spreadsheets has less to do with productivity or insightful analysis than with the art of persuasion. “People doing negotiations now sit down with spreadsheets,” Bob Frankston said. “When you’re trying to sell a car, the standard technique is to ask for the other person’s objections, and then argue them away. If two people are in front of a spreadsheet, and one says, ‘Well, the numbers say this,’ the other can’t say, ‘Yes, but there’s something I can’t quite point to.’”

As spreadsheets are used more for persuasion and negotiation, people are becoming rather sly about their design. Lotus 1-2-3 can turn figures and formulas into graphs – graphs that spreadsheeters can use to skew and oversimplify reality. “With graphs, things take on greater weight,” Allen Sneider said. Sneider expects spreadsheets to become more persuasive – and the distortion of reality greater – when color printers become more common. “If I wanted to, I could skew the picture by choosing a particular color in a bar graph. Some people think red is very negative. They might think green indicates profitability.” All of this has made some people who work with spreadsheets regularly skeptical of what they see. “I know of one venture capital firm that assumes people manipulate spreadsheets,” Kapor said. “So they have this other model to put against the first one, to factor the stuff out.”

Obviously, not all the millions of people who use spreadsheets (VisiCalc alone has sold over 700,000 copies) are accountants, financial analysts, or middle managers. VisiCalc’s co-designer Bob Frankston attributes some of his program’s popularity to these other users: “It turns out there are a number of people who are running their own businesses or doing financial management. The ‘own business’ might be something like renting an apartment. If you’’ve got to project costs for a year, it makes sense to do it with a spreadsheet.” More than 10 million people filed Schedule C “self-employment” reports with the IRS last year: we are becoming a nation of businesspeople. Moreover, we are becoming a society of businesspeople. We speak in a jargon derived from the business world (“What’s the bottom line on this?”). We read columns on “personal money management” that urge us to speculate in markets once reserved for the very few. We have accepted the venture capitalist as a role model. The buzz word these days in computer software firms looking to expand their markets is “personal productivity,” as if the home itself – maybe life itself – were best viewed as a business.

Spreadsheets are at the heart of this movement. Using electronic spreadsheets, everyone can run his or her own business. Thousands of Americans are attending classes to learn about the spreadsheet way of knowledge. Some will lose themselves in the rows of columns, the grids becoming their windows on the world. They will spend their evenings in front of their computers, the dark dimly lit by the glow of green phosphorescent numbers, fiddling with scenarios, trying to make the profit line perfect.

There is no doubt that the electronic spreadsheet saves time and provides insight; there is no doubt that even greater benefits will one day be derived from these grids. Yet all these benefits will be meaningless if the spreadsheet metaphor is taken too much to heart. After all, it is only a metaphor. Fortunately, few would argue that all relations between people can be quantified and manipulated by formulas. Of human behavior, no faultless assumptions – and so no perfect model – can be made.

_________
This article was published as Chapter 10 in Tom Forester’s (ed) Computers in the Human Context: Information Technology, Productivity and People. Basil Blackwell. 108 Cowley Road, Oxford OX4 1JF, UK.

© Copyright Steven Levy

The transcription was done by Anthony J. Pennings and the participants in his New York University course, Introduction to Business Computing: Barbara Head, Bryan de la Roza, Candice Kaup, Dee Dhanraj, Gary Johnston, Janine Bustamante, Karen Headley, Max Ryan, Michael Siatsis, Roxanne Gordon

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Anthony J. Pennings, PhD is the Professor of Global Media at Hannam University in South Korea. Previously, he taught at St. Edwards University in Austin, Texas and was on the faculty of New York University from 2002-2012. He also taught at Victoria University in Wellington, New Zealand and was a Fellow at the East-West Center in Hawaii in the 1990s.

Category: digital spreadsheets, enterprise systems, financial technology
Tags: Bob Frankston > Bricklin > Ezra Gottheil > Mitch Kapor > Multiplan > spreadsheet capitalism > Steven Levy > SuperCalc > VisiCalc

Lotus Spreadsheets – Part 3 – Identifying the Components of a Transformative Tool

Posted on | November 29, 2014 | No Comments

As mentioned in Part 1 and Part 2 of this series, the electronic spreadsheet emerged as an extraordinary meaning-making technology that not only began to be used to produce constructive information, but was complicit in a new organization of global capitalism and arguably, a new rationality shaping the future of our modern civilization.

Spreadsheet applications are a foundational technology for the financial machinations of a global system based on monetary representation, calculation, and manipulation. They incorporate several types of media into a new technology able to represent, compute, and formulate new types of knowledge. It is not my intention to be apologetic for the current global economic system or even argue for a technologically determinist role for the spreadsheet, but rather to investigate the disciplinary, interactive and transformative capabilities that emerged with the diffusion of the spreadsheet innovation throughout modern society.

In this post, I begin a formal analysis of the digital spreadsheet by identifying some of its component parts, a type of Cartesian reductionism, but with the intent of showing also how they all work together to create a powerful organizational and productivity tool. Spreadsheets combine a number of technologically enhanced cognition features to create, manipulate and visualize what Jean Baudrillard called “hyperrealities.”[1] These are “the maps that precede the territory”, the diagrammatic rationalities that engender or create the territory. In other words, spreadsheets not only appraise aspects of reality, but are constitutive technologies that can shape perceptions and empower control over the lived experiences of people and the resources that support them.

My interest is not just in the pedantic issues of extracting more efficiency from labor, or empowering a corporate raider, but rather to investigate spreadsheet technology as both a disciplinary and a transformative tool. Furthermore, I see the analysis of the spreadsheet as illuminating major characteristics of the modern world order of recently globalized networks of technocratic finance. Ultimately, an analysis of spreadsheet applications should reveal and help restructure complex social, corporate and institutional arrangements.

So to move into the next stage of my analysis, I will examine how the PC-based spreadsheet combined five rudimentary components together to create a new system for inputting, organizing, processing and presenting information. This structure allows the user to create new aggregates of numerical data, new classifications and connections between disparate resources and new simulated scenarios of alternative possibilities. They are:

1. written symbols;
2. lists;
3. tables;
4. cells and;
5. formulas.

PC-based spreadsheet applications like Lotus 1-2-3 and later Microsoft Excel combined these components in ways that structure and process data to produce new forms of meaning and utility. Information is entered and organized into columns and rows of vertical and horizontal lists. Each row has a numbered address while the columns are identified by letters. The combination of rows and columns enables a multifaceted table that intersects at numerous points called cells.

Numerical, alphabetical, and (later) Unicode-enabled representations such as the ideographic Chinese characters populate the cells and provide the basic intelligibility. The place-holding function of zero and modern arithmatic capabilities are especially important in the success of the spreadsheet application. Information arranged throughout the tables can be operated on systematically by formulas designed to produce specific types of output values. The formal analysis of the electronic spreadsheet will connect these various constituent elements with the meanings that can be created and acted on according to their respective institutional contexts.

In summary, Part 1 of this “spreadsheet saga” introduced the “microcomputer” spreadsheet application starting with VisiCalc and Lotus 1-2-3 and how they diffused rapidly throughout the corporate world in the 1980s. Part 2 presented some of the historical background that led up to the 1980s and why the corporate environment was ripe for a tool like the PC-based spreadsheet, particularly its use in modeling complex mergers and acquisition strategies. Above, I identify the key components that were combined to create the spreadsheet as a dramatically powerful tool to itemize and organize financial and material resources. In my next few posts on this topic, I will examine the components in detail, starting with writing, numbers, and especially the power of zero.

Notes

[1] Baudrillard received some notoriety when the character Neo in the movie Matrix (1999) reveals his stash of money and data storage disks in a hollow version of one of his books, Simulation and Simulacra, It also uses his term “Desert of the Real” as a way of saying power is in the map not the territory.
[2] A lot of good work is being done on the spreadsheet in terms of risks, Ray Panko for example, has done excellent work identifying mistakes that can occur.

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Anthony J. Pennings, PhD is a professor of global media at Hannam University in South Korea. Previously, he taught at St. Edwards University in Austin, Texas and was on the faculty of New York University from 2002-2012. His first faculty position was at Victoria University in Wellington, New Zealand.

Category: data analytics and meaning, democratic political economies, digital spreadsheets, electric money, enterprise systems, financial technology, geopolitical risk, meaning makers, technologies of meaning
Tags: #apennings > #spreadsheetsaga > Baudrillard > digital spreadsheet > hyper-reality > Lotus 1-2-3 > meaning-making technology > Microsoft Excel > spreadsheet capitalism

IBM’s Watson AI Targets Healthcare

Posted on | November 11, 2014 | No Comments

Soon after I moved to Austin, Texas, in late 2012, I attended a talk by Manoj Saxena, who was then General Manager of Watson Solutions, part of IBM’s Software Group. Named after IBM’s first CEO, Thomas J. Watson, the Watson system gained widespread recognition in 2011 when it competed against and defeated human champions on the popular American TV quiz show “Jeopardy!” They now focus on bringing to market the artificial intelligence (AI) computer system that beat the contestants on the game show. IBM is betting that its Watson “cognitive system,” based on Big Blue’s expertise in software and storage combined with new developments in natural language processing will change modern organizations, professional services, and entire industries, including finance, medicine and transportation.

I was particularly struck by one of their main pilot projects, using Watson in the healthcare industry. One of the tasks I took on at New York University was to shepherd a proposal for a Master of Science degree in Healthcare IT through the NYS Department of Education approval process. Others designed the program, so I can’t take credit for its content, but as the head of the Department of Management and Information Technology, it fell on my shoulders to push it through.

Soon, the challenges and objectives of the program captured my imagination and raised several questions for me, particularly regarding the roles of artificial intelligence (AI), big data, neural network algorithms, and Natural Language Processing (NLP).

Neither AI nor NLP held much of my interest in the past, as we’ve seen it in SF since the sixties with the computer in the Star Trek television series and, of course, HAL in Stanley Kubrick’s classic 2001: A Space Odyssey (1968). The mouse and drop-down menus pioneered by Xerox and Apple proved to be more efficient than voice and, the more recent touch user interfaces developed by Apple for the iPad and iPhone are extraordinarily “handy” as well.

However, developments such as Apple’s Siri and the Android voice recognition system have made AI sufficiently intriguing. Granted, NLP is much more than just the interface. It is a whole system of machine intelligence with capabilities to process language questions and requests, conduct extensive searches, and analyze structured and increasingly unstructured data. The video above shows Watson’s language capabilities at play in the game show Jeopardy.

The role of information technologies in U.S. healthcare expanded dramatically after the Health Information Technology for Economic and Clinical Health Act (HITECH) was signed into law on February 17, 2009, as part of the American Recovery and Reinvestment Act of 2009 (ARRA). While the discussions about Obamacare linger, the regulations and structural reforms outlined in HITECH have transformed the healthcare industry.

Electronic Health Records (EHR), their “meaningful use”, and the regulations associated with them, such as HIPAA and its provisions for protected health information (PHI,) are becoming core components of the healthcare landscape. But for doctors who universally only have a few scant minutes to review these records before seeing each patient, they further add to the mounds of data they need to ingest and understand to keep on top of their profession and provide the best care. IBM sees Watson as a tool to help medical professionals make decisions about diagnoses and treatments by conducting data-intensive analysis and providing treatment options.

IBM has been working with medical research facilities at the Memorial Sloan-Kettering Cancer Center, Cleveland Clinic, and medical insurer WellPoint to enhance their healthcare capabilities. More than two million pages of text from medical journals and 1.5 million patient records were given to Watson by Memorial Sloan-Kettering to help it answer natural language questions about cancer treatments. IBM has also been working with healthcare insurer WellPoint to use Watson to help doctors make diagnoses based on less testing and more big data analysis to save money and improve diagnostic accuracy.

Wellpoint is the largest insurer in the U.S. and plans to use its Watson deployment for medical personnel who review complex treatment requests from doctors. Watson is programmed to sift through giant pools of medical literature to “form probabilistic logic chains” to support their recommendations. Wellpoint plans to roll out Watson for a few oncology practices, allowing doctors to work with it through their own computer systems or tablets to improve the quality of care and lower costs.

Probably the biggest question is not whether a “cognitive system” like Watson will change entire industries such as finance and healthcare but will Big Blue make any money off this venture into artificial intelligence. Saxena has moved on to Silicon Valley’s The Entrepreneurs Fund, where he still works on funding AI enterprises related to IBM Watson, but from a venture capitalist perspective. My guess is that artificial intelligence is a potentially disruptive technology that is quietly diffusing through modern life under pseudonyms like “cognitive systems,” “neural networks,” and “natural processing languages.” AI will likely have major repercussions over the next few years, but it will be interesting to see if IBM can continue leading the way.

In summary, IBM’s Watson represents a significant leap forward in AI, with its ability to process and analyze vast amounts of data in a contextually relevant manner. Its applications across various industries focus on the potential of cognitive computing to revolutionize how we make decisions, interact with technology, and solve complex problems.

Citation APA (7th Edition)

Pennings, A.J. (2014, Nov 11). IBM’s Watson AI Targets Healthcare. apennings.com https://apennings.com/data-analytics-and-meaning/ibms-watson-ai-targets-healthcare/

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Anthony J. Pennings, PhD is a professor at the State University of New York, Korea. Previously, he taught at St. Edwards University in Austin, Texas and was on the faculty of New York University from 2002-2012. He first taught at Victoria University in Wellington, New Zealand and was a Fellow at the East-West Center in Hawaii for many years.

Category: data analytics and meaning, health IT
Tags: AI > ARRA > cancer treatments > cognitive systems > Electronic Health Records (EHR) > Healthcare IT > IBM Watson > Manoj Saxena > Memorial Sloan-Kettering Cancer Center > natural language processing > NLP > Siri > The Entrepreneurs Fund > The Health Information Technology for Economic and Clinical Health Act > Wellpoint

Lotus Spreadsheets – The Killer App of the Reagan Revolution – Part 2 – Spreadsheet Capitalism Emerges

Posted on | November 9, 2014 | No Comments

In order to understand the widespread adoption of the spreadsheet during the “Reagan Revolution” and its political-economic implications, it is important to understand the context in which it emerged. In Part 1, I identified a number of characteristics of the Reagan Revolution that allowed the electronic spreadsheet to flourish. This included wide-scale deregulation and other actions that radically transformed the economy and restored finance-centered capitalism to its pre-New Deal dominance.[1] In this post I examine the transformation of the 1980s corporate landscape facilitated by PC-based spreadsheet-modeled mergers and acquisitions (M&A) activities.

The pertinent events go back to the stock market of the 1960s and a time when corporations were quickly merging and absorbing other companies, only to find their stock depressed by the economic conditions of the 1970s. By the time Ronald Reagan became president, they found themselves top-heavy, immobile, and ripe for takeover by new corporate raiders armed with computer spreadsheets, junk bonds, and several new strategies including the leveraged buyout (LBO). While the Vietnam War was heating up and NASA was testing technology for the trip to moon, many companies such as Beatrice, ITT, as well as Gulf and Western were busy buying up other corporations. The strategy was to elevate their revenues and create financial stability through diversification.

The formation of these “conglomerates” was generally met with eager approval on Wall Street and led to a rise in stock prices as a series of mergers combined different types of companies into mega-corporations. The top “Nifty Fifty” of the 1960s included such companies as Proctor & Gamble, Bristol-Myers, Xerox, Pepsico, and GE. They were considered ceaseless growth stocks and guaranteed long term investments. Companies like ITT, which got its start buying up Caribbean and South American telephone companies, followed the pack and also became conglomerates. Despite Nixon’s gold deregulation and signs of impending economic trouble, the DJIA finally surpassed the 1,000 mark in November 1972.

Economic conditions caused a major economic decline in the mid-1970s driving the stock prices of the conglomerates down as well. By 1974, the DJIA sank from its high of over 1,000 to nearly 600 and stock prices continued to stagnate throughout the decade. The fall was precipitated by the currency and oil crises as well as the newly created international eurocurrency markets that siphoned capital off to countries in need of dollar-denominated cash to pay for their rising energy costs. This combination of the global currency crisis, the rapid elevation of oil prices, and the movement of capital into the euromarkets for recirculation to developing nations around the world worked to drive down stock prices. By the late 1970s, As euromoney slipped back into the US, it created soaring inflation. The result was to drive the country into a recession with concurrent inflation a unique combination of economic stagnation with increasing price inflation was occurring that became known as “stagflation”. In response, the Federal Reserve followed a monetary policy that increased interest rates to reduce inflation.

Capital began to return to the US in the early 1980s, and it became available for mergers and acquisitions. High interest rates and a soaring government debt sent new money, especially from Japan, into the US. With investment confidence in the Third and Second Worlds badly shaken, the capital markets turned back to the American corporate sector. This was encouraged by the tax cuts of the Reagan administration as well as a lax attitude towards corporate mergers by its Justice Department. Although expensive, more capital became available for the stock market and the tide began to turn. During the period 1979 to 1984, corporations spent nearly half a trillion dollars to merge or acquire other corporations sparking the stock market and sending investor confidence soaring. The Dow-Jones Industrial average went from 800 to over 1200. Aided by a massive increase in military spending and deregulation in the airline, banking and telecommunications sectors, electronic money switched from syndicated lending for third world countries to bonds and securities to support corporate takeovers and high tech startups.

A new breed of financial analysts emerged, armed with electronic spreadsheets on their Apple or IBM PCs. They evaluated company after company looking for new buying opportunities. Their main strategy was to analyze companies to buy and divest of their pension funds or sell off marketable subsidiaries in a process called a leveraged buyout (LBO). With more money available from banks, corporate raiders used a number of strategies to attack the fat conglomerates whose stock prices had been hit hard since 1974. The basic strategy in raiding a company involved borrowing the money, often at quite high interest rates, buying a majority share in the corporation, and then selling off some of the company’s assets to pay back the loan. This process was portrayed in Oliver Stone’s (1987) Wall Street when the infamous Gordon Gekko attempted to break up the fictional Bluestone Airlines and sell off its airplanes and build condos where the hangars were located. Gekko at one point claims the real profits would come from raiding the company’s “overfunded” pension fund.

Another technique used was called “greenmail”. This strategy involved threatening to take over the corporation enough to scare the management into buying back up huge amounts of stock and in the process raising the price. The raider would initiate a LBO and buy a significant amount of stock. After the stock price rose significantly, the raider would sell their shares for a hefty profit.

These techniques often involved the use of junk bonds championed by Michael Milken of Drexel Burnham Lambert. These were high-yield bonds issued by corporations with low credit ratings. Milken persuaded a number of raiders to use junk bonds in their takeover pursuits. While junk bonds were used to build important information age corporations such as MCI and McCaw Wireless, they were also bought up by newly deregulated Savings and Loans banks that ran into trouble by the late 1980s.

Ultimately Milken was sent to jail in a controversial move, but in the meantime, Wall Street’s DJIA boomed from 800 in 1979 to over 1500 in the December of 1985. This was only the start of the run however, as it reached 2,000 in the first month of 1987 and nearly 2500 the autumn of the infamous “Crash of 1987”.

With the spreadsheet in action, financial activities increased dramatically. While the contribution of financial firms to the US Gross National Product (GDP) was just over US$32 billion in 1950, it grew to $400 billion in 1980 and rocketed to $626 billion in 1985. During this time goods production also grew significantly, largely due to the commercialization of Cold War technologies, but the economic contribution by the financial sector grew twice as fast, particularly during the first five years of the Reagan era when it grew by sixty-four percent. With the spreadsheet, more complex financial calculations could be done by significantly fewer people. But the most important factor was that the electronic spreadsheet made the information more accessible and available faster to the people who could use it. [2]

In the next segment of this analysis of the spreadsheet, I will introduce the more formal analysis of this tool and how it “remediates,” or incorporates other meditated tools.

Notes

[1] I’m repeating this quote from “Lotus Spreadsheets – The Killer App of the Reagan Revolution – Part 1”. It is from Peter Gowan’s (1999) Global Gamble: Washington’s Faustian Bid for World Dominance for emphasis.
[2] See Magdoff, H. and Sweezy, P.M. (1987) Stagnation and the Financial Explosion. New York: Monthly Review Press. For information on the finance vs. goods production see p.23.

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Anthony J. Pennings, PhD is Professor and Associate Chair of the Department of Technology and Society, State University of New York, Korea. Before joining SUNY, he taught at Hannam University in South Korea and from 2002-2012 was on the faculty of New York University. Previously, he taught at St. Edwards University in Austin, Texas, Marist College in New York, and Victoria University in New Zealand. He has also spent time as a Fellow at the East-West Center in Honolulu, Hawaii.

Anthony J. Pennings, PhD is a professor of global media at Hannam University in South Korea. Previously, he taught at St. Edwards University in Austin, Texas and was on the faculty of New York University from 2002-2012. His first faculty position was at Victoria University in Wellington, New Zealand.

Category: digital spreadsheets, dystopian economies, financial technology, geopolitical risk, global communications, meaning makers, technologies of meaning
Tags: #apennings > #spreadsheetsaga > eurodollars > Michael Milken > Reagan Revolution > stagflation

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