The best way to have a good idea is to have a lot of ideas. — Linus Pauling
—What lingers after this line?
Pauling’s Provocation
Linus Pauling’s maxim overturns the romantic myth of singular inspiration. Rather than waiting for a perfect lightning bolt, he implies a practical truth: good ideas are the rare peaks in a landscape explored by many attempts. This reframes failure from stigma to strategy, signaling that discarded notions are not waste but waypoints. By normalizing volume, Pauling invites us to treat creativity as a process that rewards persistent exploration, not just talent or timing. From this standpoint, the central question shifts from “How do I find one brilliant idea?” to “How do I create the conditions for many?”
Variation and Selection, Not Epiphany
Building on that, creativity behaves like evolution: generate variation, then select. Dean Keith Simonton’s “equal-odds rule” suggests that the chance any one idea is a hit is roughly constant, so producing more ideas statistically increases the odds of excellence (Simonton, 1997). In this view, ideation resembles a portfolio strategy where risk is spread across many bets. Crucially, selection—through critique, testing, or market feedback—does the refining. Just as natural selection filters mutations, constraints and audience response prune possibilities. Hence, the path to quality is not the avoidance of error but its prolific production and systematic culling.
What Histories of Genius Reveal
Historical patterns reinforce this logic. Beethoven’s sketchbooks show relentless drafting and revision; masterpieces emerged from swarms of fragments, not immaculate conception (Nottebohm, 1863; Simonton, 1994). Similarly, prolific creators tend to have more landmark works precisely because they have more works, period—again echoing the equal-odds rule (Simonton, 1997). Science shows the same rhythm: productive periods are punctuated by breakthroughs, yet the surrounding corpus—papers, failed experiments, marginal notes—creates the scaffolding for success. Thus, the biographies we idolize often conceal the real engine of achievement: disciplined, voluminous trial.
Prototyping as a Numbers Game
In practice, invention is iteration. James Dyson famously built 5,127 prototypes before arriving at his bagless vacuum, making quantity the price of a single leap (Dyson, 2003). At 3M, a weak adhesive devised by Spencer Silver (1968) became Post-it Notes only after Art Fry reframed its use years later, illustrating how multiple tries and contexts unlock value. These stories show that many attempts are not redundant; they are informational. Each prototype narrows uncertainty, exposes constraints, and suggests new combinations. Consequently, the fastest route to a good solution is often the shortest cycle time between many imperfect ones.
Divergent First, Convergent Later
Psychology clarifies why sequencing matters. J. P. Guilford distinguished divergent thinking—producing many, varied ideas—from convergent thinking—selecting and refining (Guilford, 1956). Graham Wallas’s classic model similarly moves from preparation and incubation to illumination and verification (Wallas, 1926). When we collapse these modes, we muzzle originality: early criticism truncates exploration. Therefore, effective creators separate phases—first push for unexpected volume, then switch to rigorous evaluation. Incubation, including deliberate breaks, also helps weaker concepts recombine into stronger ones, turning today’s outtakes into tomorrow’s insights.
Group Methods That Multiply Ideas
At the team level, process design matters. Classic brainstorming often underperforms because of production blocking and evaluation apprehension; studies show “nominal” groups—individuals ideating separately—outproduce interactive groups (Diehl & Stroebe, 1987). As a remedy, techniques like brainwriting, 6-3-5, and anonymous digital boards boost idea volume before discussion. Pixar’s Braintrust offers a second lesson: candid, high-safety critique improves selection without stifling generation (Catmull, Creativity, Inc., 2014). This aligns with Amy Edmondson’s research on psychological safety (1999): when people can speak up without fear, both the number and candor of ideas rise, improving the pool from which quality can be drawn.
Turning Volume Into Value
Finally, quantity needs a funnel. Set explicit quotas (e.g., 20 ideas per brief), timebox sprints, and postpone judgment until a review gate. Then apply clear criteria—impact, feasibility, differentiation—using quick tests like mockups, A/B trials, or paper prototypes to eliminate weak options cheaply. Maintain an “idea graveyard” so discarded notions remain searchable for future recombination. Pre-mortems and kill-switch thresholds prevent sunk-cost attachment, while short feedback loops accelerate learning. In the end, Pauling’s advice is both liberating and exacting: make many things, learn quickly, and keep only what survives scrutiny.
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