Sustaining a Shared Reality: How Past Technology Waves Have Impacted Strategy | by Whitney Zimmerman | May, 2026 | MediumSitemapOpen in appSign up<br>Sign in

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Sustaining a Shared Reality: How Past Technology Waves Have Impacted Strategy

Whitney Zimmerman

11 min read·<br>May 27, 2026

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John Ruskin, Doge’s Palace, Venice: 36th Capital (1849–1852), The Ruskin Library, Lancaster UniversityIn 1972, a thirty-year-old McKinsey partner named Lou Gerstner published an article in Business Horizons titled “Can Strategic Planning Pay Off?“ It was a reaction to a great wave of information technology in business — the mainframe data-processing revolution of the 1950s and 1960s — and the effect it had on how companies approached strategy. That wave had taken American business from roughly 240 installed computers in 1955 to about 50,000 worldwide a decade later, anchored by IBM’s System/360, which became the back-office platform of the modern corporation, running payroll, billing, accounting, and inventory for a generation. Two decades later, Gerstner encountered the consequences of a subsequent wave firsthand, when he arrived at IBM as CEO in 1993 and found a company drowning in analysis but, in his words, “paralyzed, unable to act on any predictions.”<br>Major advances in information technology have more than once made it dramatically easier to produce raw material for strategy. And each time, some companies have misused that potential — more analysis, not better decisions. Generative AI is another, powerful wave of change. Understanding past waves is one of the most useful things strategists can do to make the most of the latest. It is, in Francis Gavin’s terms, thinking historically about the present moment.<br>Gerstner’s recurring experiences<br>To write his 1972 article, Gerstner surveyed chief executives about the new discipline of strategic planning that had swept through corporate America, fueled in part by the data-processing capabilities of the previous decade. He recorded their candid reactions. One called it “basically just a plaything of staff.” Another compared it to “a Chinese dinner: I feel full when I get it, but after a little while I wonder whether I’ve eaten at all.” A third was blunter: “A staggering waste of time and money.”<br>In Gerstner’s view, the problem was the disconnection of analysis from decision-making, and that analytical machinery had given companies a false sense of reality. He drew an explicit analogy to the data-processing investments that had enabled the planning boom in the first place: “Following the widespread introduction of data processing in the 1950s, many companies sooner or later were obliged to recognize that the promise of this great management tool was stubbornly refusing to materialize. Real, tangible return on investment was low or nonexistent.” His prescription: the work must be integrated with the real decisions, every project must pass the “so what?” test, and the CEO must be personally involved. Without those, the technology’s promise would remain unrealized, and companies would strategically struggle.<br>Even in 1972, Gerstner saw the limits of automation in strategy. Strategic planning, he wrote, “is fundamentally a creative process. It cannot be programmed or systematized. To structure meaningful, practical action programs requires insight, wisdom, and perspective.” The hardest part of strategy — the judgment, the willingness to take a personal stand on a controversial issue — could not be outsourced.<br>Two decades later, Gerstner experienced the dynamic first-hand. A subsequent IT revolution began in 1979 with two products that shipped that year: VisiCalc, the first electronic spreadsheet, and Oracle, the first commercial SQL relational database. By the mid-1990s, those trends — a spreadsheet on every analyst’s desk and a relational database under every large company’s transactions — together with the PC, enterprise software like SAP R/3, and a growing ecosystem of business intelligence tools, were transforming corporate analytics. IBM was one of the companies that had built the infrastructure that made it possible. IBM had sold the tools and used them itself.<br>What Gerstner found when he arrived at IBM in 1993, as he describes in his memoir Who Says Elephants Can’t Dance?, was a company that had mastered the production of analysis and lost the capacity to act on it. The apparatus had become elaborate, expensive, and in important places systematically misleading. The clearest example was customer satisfaction data: 339 separate surveys, administered by the sales force, which naturally selected its happiest customers — what Gerstner called “asking the innkeeper how good the inn is.”<br>His response was to rebuild IBM’s view of the world, with leaders firmly in the loop. He believed “good strategies start with massive amounts of quantitative analysis — hard, difficult...